ORCID Profile
0000-0001-9705-0079
Current Organisations
Western Sydney University
,
Western Sydney University - Campbelltown Campus
,
CSIRO
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Pattern Recognition and Data Mining | Image Processing | Artificial Intelligence and Image Processing | Psychology | Computer-Human Interaction | Developmental Psychology and Ageing
Diagnostic Methods | Clinical Health (Organs, Diseases and Abnormal Conditions) not elsewhere classified | Expanding Knowledge in the Information and Computing Sciences | Expanding Knowledge in Psychology and Cognitive Sciences | Expanding Knowledge in the Medical and Health Sciences | Expanding Knowledge in Technology |
Publisher: Elsevier BV
Date: 05-2010
DOI: 10.1016/J.JNEUMETH.2010.02.020
Abstract: In magnetic resonance imaging (MRI), accuracy and precision with which brain structures may be quantified are frequently affected by the partial volume (PV) effect. PV is due to the limited spatial resolution of MRI compared to the size of anatomical structures. Accurate classification of mixed voxels and correct estimation of the proportion of each pure tissue (fractional content) may help to increase the precision of cortical thickness estimation in regions where this measure is particularly difficult, such as deep sulci. The contribution of this work is twofold: on the one hand, we propose a new method to label voxels and compute tissue fractional content, integrating a mechanism for detecting sulci with topology preserving operators. On the other hand, we improve the computation of the fractional content of mixed voxels using local estimation of pure tissue intensity means. Accuracy and precision were assessed using simulated and real MR data and comparison with other existing approaches demonstrated the benefits of our method. Significant improvements in gray matter (GM) classification and cortical thickness estimation were brought by the topology correction. The fractional content root mean squared error diminished by 6.3% (p<0.01) on simulated data. The reproducibility error decreased by 8.8% (p<0.001) and the Jaccard similarity measure increased by 3.5% on real data. Furthermore, compared with manually guided expert segmentations, the similarity measure was improved by 12.0% (p<0.001). Thickness estimation with the proposed method showed a higher reproducibility compared with the measure performed after partial volume classification using other methods.
Publisher: Springer International Publishing
Date: 2016
Publisher: Springer Science and Business Media LLC
Date: 09-06-2020
DOI: 10.1186/S13195-020-00634-1
Abstract: Heme and iron homeostasis is perturbed in Alzheimer’s disease (AD) therefore, the aim of the study was to examine the levels and association of heme with iron-binding plasma proteins in cognitively normal (CN), mild cognitive impairment (MCI), and AD in iduals from the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) and Kerr Anglican Retirement Village Initiative in Ageing Health (KARVIAH) cohorts. Non-targeted proteomic analysis by high-resolution mass spectrometry was performed to quantify relative protein abundances in plasma s les from 144 CN in iduals from the AIBL and 94 CN from KARVIAH cohorts and 21 MCI and 25 AD from AIBL cohort. ANCOVA models were utilized to assess the differences in plasma proteins implicated in heme/iron metabolism, while multiple regression modeling (and partial correlation) was performed to examine the association between heme and iron proteins, structural neuroimaging, and cognitive measures. Of the plasma proteins implicated in iron and heme metabolism, hemoglobin subunit β ( p = 0.001) was significantly increased in AD compared to CN in iduals. Multiple regression modeling adjusted for age, sex, APOEε4 genotype, and disease status in the AIBL cohort revealed lower levels of transferrin but higher levels of hemopexin associated with augmented brain amyloid deposition. Meanwhile, transferrin was positively associated with hippoc al volume and MMSE performance, and hemopexin was negatively associated with CDR scores. Partial correlation analysis revealed lack of significant associations between heme/iron proteins in the CN in iduals progressing to cognitive impairment. In conclusion, heme and iron dyshomeostasis appears to be a feature of AD. The causal relationship between heme/iron metabolism and AD warrants further investigation.
Publisher: Springer Science and Business Media LLC
Date: 02-2021
DOI: 10.1038/S41467-021-21057-Y
Abstract: Aging and Alzheimer’s disease (AD) are associated with progressive brain disorganization. Although structural asymmetry is an organizing feature of the cerebral cortex it is unknown whether continuous age- and AD-related cortical degradation alters cortical asymmetry. Here, in multiple longitudinal adult lifespan cohorts we show that higher-order cortical regions exhibiting pronounced asymmetry at age ~20 also show progressive asymmetry-loss across the adult lifespan. Hence, accelerated thinning of the (previously) thicker homotopic hemisphere is a feature of aging. This organizational principle showed high consistency across cohorts in the Lifebrain consortium, and both the topological patterns and temporal dynamics of asymmetry-loss were markedly similar across replicating s les. Asymmetry-change was further accelerated in AD. Results suggest a system-wide dedifferentiation of the adaptive asymmetric organization of heteromodal cortex in aging and AD.
Publisher: Elsevier BV
Date: 03-2012
DOI: 10.1016/J.COMPMEDIMAG.2011.08.004
Abstract: Due to physical limitations inherent in magnetic resonance imaging scanners, three dimensional volumetric scans are often acquired with anisotropic voxel resolution. We investigate several interpolation approaches to reduce the anisotropy and present a novel approach - constrained reverse diffusion for thick slice interpolation. This technique was compared to common methods: linear and cubic B-Spline interpolation and a technique based on non-rigid registration of neighboring slices. The methods were evaluated on artificial MR phantoms and real MR scans of human brain. The constrained reverse diffusion approach delivered promising results and provides an alternative for thick slice interpolation, especially for higher anisotropy factors.
Publisher: IOP Publishing
Date: 10-11-2014
DOI: 10.1088/0031-9155/59/23/7245
Abstract: Accurate segmentation of hip joint cartilage from magnetic resonance (MR) images offers opportunities for quantitative investigations of pathoanatomical conditions such as osteoarthritis. In this paper, we present a fully automatic scheme for the segmentation of the in idual femoral and acetabular cartilage plates in the human hip joint from high-resolution 3D MR images. The developed scheme uses an improved optimal multi-object multi-surface graph search framework with an arc-weighted graph representation that incorporates prior morphological knowledge as a basis for segmentation of the in idual femoral and acetabular cartilage plates despite weak or incomplete boundary interfaces. This automated scheme was validated against manual segmentations from 3D true fast imaging with steady-state precession (TrueFISP) MR examinations of the right hip joints in 52 asymptomatic volunteers. Compared with expert manual segmentations of the combined, femoral and acetabular cartilage volumes, the automatic scheme obtained mean (± standard deviation) Dice's similarity coefficients of 0.81 (± 0.03), 0.79 (± 0.03) and 0.72 (± 0.05). The corresponding mean absolute volume difference errors were 8.44% (± 6.36), 9.44% (± 7.19) and 9.05% (± 8.02). The mean absolute differences between manual and automated measures of cartilage thickness for femoral and acetabular cartilage plates were 0.13 mm (± 0.12) and 0.11 mm (± 0.11), respectively.
Publisher: Elsevier BV
Date: 04-2014
DOI: 10.1016/J.MEDIA.2014.02.002
Abstract: Deformable models incorporating shape priors have proved to be a successful approach in segmenting anatomical regions and specific structures in medical images. This paper introduces weighted shape priors for deformable models in the context of 3D magnetic resonance (MR) image segmentation of the bony elements of the human hip joint. The fully automated approach allows the focusing of the shape model energy to a priori selected anatomical structures or regions of clinical interest by preferentially ordering the shape representation (or eigen-modes) within this type of model to the highly weighted areas. This focused shape model improves accuracy of the shape constraints in those regions compared to standard approaches. The proposed method achieved femoral head and acetabular bone segmentation mean absolute surface distance errors of 0.55±0.18mm and 0.75±0.20mm respectively in 35 3D unilateral MR datasets from 25 subjects acquired at 3T with different limited field of views for in idual bony components of the hip joint.
Publisher: Elsevier BV
Date: 08-2016
DOI: 10.1016/J.RIDD.2016.04.007
Abstract: To investigate the extent of white matter damage in children with unilateral cerebral palsy (UCP) caused by periventricular white matter lesions comparing between unilateral and bilateral lesions and to investigate a relationship between white matter microstructure and hand function. Diffusion MRI images from 46 children with UCP and 18 children with typical development (CTD) were included. Subjects were grouped by side of hemiparesis and unilateral or bilateral lesions. A voxel-wise white matter analysis was performed to identify regions where fractional anisotropy (FA) was significantly different between UCP groups and CTD and where FA correlated with either dominant or impaired hand function (using Jebsen Taylor Hand Function Test). Children with unilateral lesions had reduced FA in the corticospinal tract of the affected hemisphere. Children with bilateral lesions had widespread reduced FA extending into all lobes. In children with left hemiparesis, impaired hand function correlated with FA in the contralateral corticospinal tract. Dominant hand function correlated with FA in the posterior thalamic radiations as well as multiple other regions in both left and right hemiparesis groups. Periventricular white matter lesions consist of focal and diffuse components. Focal lesions may cause direct motor fibre insult resulting in motor impairment. Diffuse white matter injury is heterogeneous, and may contribute to more global dysfunction.
Publisher: IOP Publishing
Date: 27-02-2007
DOI: 10.1088/0031-9155/52/6/005
Abstract: The accurate segmentation of the articular cartilages from magnetic resonance (MR) images of the knee is important for clinical studies and drug trials into conditions like osteoarthritis. Currently, segmentations are obtained using time-consuming manual or semi-automatic algorithms which have high inter- and intra-observer variabilities. This paper presents an important step towards obtaining automatic and accurate segmentations of the cartilages, namely an approach to automatically segment the bones and extract the bone-cartilage interfaces (BCI) in the knee. The segmentation is performed using three-dimensional active shape models, which are initialized using an affine registration to an atlas. The BCI are then extracted using image information and prior knowledge about the likelihood of each point belonging to the interface. The accuracy and robustness of the approach was experimentally validated using an MR database of fat suppressed spoiled gradient recall images. The (femur, tibia, patella) bone segmentation had a median Dice similarity coefficient of (0.96, 0.96, 0.89) and an average point-to-surface error of 0.16 mm on the BCI. The extracted BCI had a median surface overlap of 0.94 with the real interface, demonstrating its usefulness for subsequent cartilage segmentation or quantitative analysis.
Publisher: Elsevier BV
Date: 05-2023
DOI: 10.1016/J.PEDNEO.2022.07.014
Abstract: Acquired Brain Injury (ABI) describes a range of brain injuries occurring after birth, including tumor, traumatic brain injury or stroke. Although MRIs are routinely used for diagnosis, prediction of outcome following brain injury is challenging. Quantitative structural information from brain images may provide an opportunity to predict patient outcomes however, due to the high prevalence of severe pathology in children with ABI, quantitative approaches must be robust to injury severity. In this pilot cross-sectional study, automated quantitative measures were extracted from the MRIs of a cohort of children with ABI (n = 30, 8-16 years, follow up MRI taken 1.8-13.4 years after time of injury) as well as 36 typically developing controls with no brain injury (7-17 years) using a pathology-robust technique. Measures of brain volume, lesion volume and cortical morphology were associated with concurrent motor, behavioral, visual and communicative function using Least Absolute Shrinkage and Selection Operator (LASSO) regression. These regression models were validated on a separate test set (n = 8 of the ABI cohort), which revealed significant correlations between measures of brain structure with motor, cognitive, visual and communicative function (r = 0.65-0.85, all p < 0.01). Furthermore, comparisons of the structural measures to the typically developing cohort revealed overall reductions in global grey matter volume among the ABI cohort, as well as cortical thinning in several cortical areas. These preliminary associations reveal that motor and behavioral function can be estimated from MRI alone, highlighting the potential utility of the proposed pathology-robust MRI quantification tools to provide estimates of long-term clinical prognosis of children with ABI following injury.
Publisher: Wiley
Date: 05-03-2020
DOI: 10.1002/HBM.24978
Publisher: SAGE Publications
Date: 04-2016
Abstract: Quantitative magnetic resonance imaging (MRI) techniques, such as T2 and T2 star (T2*) mapping, have been used to evaluate ligamentous tissue in vitro and to identify significant changes in structural integrity of a healing ligament. These studies lay the foundation for a clinical study that uses quantitative mapping to evaluate ligaments in vivo, particularly the posterior cruciate ligament (PCL). To establish quantitative mapping as a clinical tool for identifying and evaluating chronic or acute PCL injuries, T2 and T2* values first must be determined for an asymptomatic population. To quantify T2 and T2* mapping properties, including texture variables (entropy, variance, contrast, homogeneity), of the PCL in an asymptomatic population. It was hypothesized that biomarker values would be consistent throughout the ligament, as measured across 3 clinically relevant subregions (proximal, middle, and distal thirds) in the asymptomatic cohort. Cross-sectional study Level of evidence, 4. Unilateral knee MRI scans were acquired for 25 asymptomatic subjects with a 3.0-T MRI system using T2 and T2* mapping sequences in the sagittal plane. The PCL was manually segmented and ided into thirds (proximal, middle, and distal). Summary statistics for T2 and T2* values were calculated. Intra- and interrater reliability was assessed across 3 raters to 2 time points. The asymptomatic PCL cohort had mean T2 values of 36.7, 29.2, and 29.6 ms in the distal, middle, and proximal regions, respectively. The distal PCL exhibited significantly higher mean, variance, and contrast and lower homogeneity of T2 values than the middle and proximal subregions ( P .05). T2* results exhibited substantial positive skew and were therefore presented as median and quartile (Q) values. Median T2* values were 7.3 ms (Q1-Q3, 6.8-8.9 ms), 7.3 ms (Q1-Q3, 7.0-8.5 ms), and 7.3 ms (Q1-Q3, 6.4-8.2 ms) in the distal, middle, and proximal subregions, respectively. This is the first study to identify T2 and T2* mapping values, and their texture variables, for the asymptomatic PCL. The distal third of the PCL had significantly greater T2 values than the proximal or middle thirds. T2 and T2* values of the asymptomatic PCL can provide a baseline for comparison with acute and chronic PCL injuries in future studies.
Publisher: Elsevier BV
Date: 08-2017
DOI: 10.1016/J.EJRAD.2017.05.042
Abstract: To examine whether magnetic resonance (MR) imaging can offer a viable alternative to computed tomography (CT) based 3D bone modeling. CT and MR (SPACE, TrueFISP, VIBE) images were acquired from the left knee joint of a fresh-frozen cadaver. The distal femur, proximal tibia, proximal fibula and patella were manually segmented from the MR and CT examinations. The MR bone models obtained from manual segmentations of all three sequences were compared to CT models using a similarity measure based on absolute mesh differences. The average absolute distance between the CT and the various MR-based bone models were all below 1mm across all bones. The VIBE sequence provided the best agreement with the CT model, followed by the SPACE, then the TrueFISP data. The most notable difference was for the proximal tibia (VIBE 0.45mm, SPACE 0.82mm, TrueFISP 0.83mm). The study indicates that 3D MR bone models may offer a feasible alternative to traditional CT-based modeling. A single radiological examination using the MR imaging would allow simultaneous assessment of both bones and soft-tissues, providing anatomically comprehensive joint models for clinical evaluation, without the ionizing radiation of CT imaging.
Publisher: BMJ
Date: 09-2019
DOI: 10.1136/BMJOPEN-2019-032194
Abstract: Children with bilateral cerebral palsy often experience difficulties with posture, gross motor function and manual ability, impacting independence in daily life activities, participation and quality of life (QOL). Hand–Arm Bimanual Intensive Training Including Lower Extremity (HABIT-ILE) is a novel intensive motor intervention integrating upper and lower extremity training. This study aimed to compare HABIT-ILE to usual care in a large randomised controlled trial (RCT) in terms of gross motor function, manual ability, goal attainment, walking endurance, mobility, self-care and QOL. A within-trial cost–utility analysis will be conducted to synthesise costs and benefits of HABIT-ILE compared with usual care. 126 children with bilateral cerebral palsy aged 6–16 years will be recruited across three sites in Australia. Children will be stratified by site and Gross Motor Function Classification System and randomised using concealed allocation to either receiving HABIT-ILE immediately or being waitlisted for 26 weeks. HABIT-ILE will be delivered in groups of 8–12 children, for 6.5 hours per day for 10 days (total 65 hours, 2 weeks). Outcomes will be assessed at baseline, immediately following intervention, and then retention of effects will be tested at 26 weeks. Primary outcomes will be the Gross Motor Function Measure and ABILHAND-Kids. Secondary outcomes will be brain structural integrity, walking endurance, bimanual hand performance, self-care, mobility, performance and satisfaction with in idualised goals, and QOL. Analyses will follow standard principles for RCTs using two-group comparisons on all participants on an intention-to-treat basis. Comparisons between groups for primary and secondary outcomes will be conducted using regression models. Ethics approval has been granted by the Medical Research Ethics Committee of Children’s Health Queensland Hospital and the Health Service Human Research Ethics Committee (HREC/17/QRCH/282) of The University of Queensland (2018000017/HREC/17/QRCH/2820), and The Cerebral Palsy Alliance Ethics Committee (2018_04_01/HREC/17/QRCH/282). ACTRN12618000164291.
Publisher: Elsevier BV
Date: 07-2015
DOI: 10.1016/J.MEDIA.2015.04.014
Abstract: CT-MR registration is a critical component of many radiation oncology protocols. In prostate external beam radiation therapy, it allows the propagation of MR-derived contours to reference CT images at the planning stage, and it enables dose mapping during dosimetry studies. The use of carefully registered CT-MR atlases allows the estimation of patient specific electron density maps from MRI scans, enabling MRI-alone radiation therapy planning and treatment adaptation. In all cases, the precision and accuracy achieved by registration influences the quality of the entire process. Most current registration algorithms do not robustly generalize and lack inverse-consistency, increasing the risk of human error and acting as a source of bias in studies where information is propagated in a particular direction, e.g. CT to MR or vice versa. In MRI-based treatment planning where both CT and MR scans serve as spatial references, inverse-consistency is critical, if under-acknowledged. A robust, inverse-consistent, rigid/affine registration algorithm that is well suited to CT-MR alignment in prostate radiation therapy is presented. The presented method is based on a robust block-matching optimization process that utilises a half-way space definition to maintain inverse-consistency. Inverse-consistency substantially reduces the influence of the order of input images, simplifying analysis, and increasing robustness. An open source implementation is available online at aehrc.github.io/Mirorr/. Experimental results on a challenging 35 CT-MR pelvis dataset demonstrate that the proposed method is more accurate than other popular registration packages and is at least as accurate as the state of the art, while being more robust and having an order of magnitude higher inverse-consistency than competing approaches. The presented results demonstrate that the proposed registration algorithm is readily applicable to prostate radiation therapy planning.
Publisher: Elsevier BV
Date: 12-2019
DOI: 10.1016/J.NEUROIMAGE.2019.116206
Abstract: Participant movement can deleteriously affect MR image quality. Further, for the visualization and segmentation of small anatomical structures, there is a need to improve image quality, specifically signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), by acquiring multiple anatomical scans consecutively. We aimed to ameliorate movement artefacts and increase SNR in a high-resolution turbo spin-echo (TSE) sequence acquired thrice using non-linear realignment in order to improve segmentation consistency of the hippoc us subfields. We assessed the method in 29 young healthy participants, 11 Motor Neuron Disease patients, and 11 age matched controls at 7T, and 24 healthy adolescents at 3T. Results show improved image segmentation of the hippoc us subfields when comparing template-based segmentations with in idual segmentations with Dice overlaps N = 75 ps < 0.001 (Friedman's test) and higher sharpness ps < 0.001 in non-linearly realigned scans as compared to linearly, and arithmetically averaged scans.
Publisher: SPIE
Date: 23-02-2012
DOI: 10.1117/12.911752
Publisher: Elsevier BV
Date: 2022
Publisher: SPIE
Date: 23-02-2012
DOI: 10.1117/12.911746
Publisher: Springer Science and Business Media LLC
Date: 03-12-2021
DOI: 10.1038/S41467-021-26703-Z
Abstract: Heterogeneity of brain diseases is a challenge for precision diagnosis rognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical heterogeneity contrasted against normal brain structure, to identify disease subtypes through neuroimaging signatures. When applied to regional volumes derived from T1-weighted MRI (two studies 2,832 participants 8,146 scans) including cognitively normal in iduals and those with cognitive impairment and dementia, Smile-GAN identified four patterns or axes of neurodegeneration. Applying this framework to longitudinal data revealed two distinct progression pathways. Measures of expression of these patterns predicted the pathway and rate of future neurodegeneration. Pattern expression offered complementary performance to amyloid/tau in predicting clinical progression. These deep-learning derived biomarkers offer potential for precision diagnostics and targeted clinical trial recruitment.
Publisher: SPIE
Date: 08-03-2007
DOI: 10.1117/12.711234
Publisher: Springer Science and Business Media LLC
Date: 2012
Publisher: Elsevier BV
Date: 11-2019
DOI: 10.1016/J.MRI.2019.08.010
Abstract: The fluid and white matter suppression sequence (FLAWS) provides two T1-weighted co-registered datasets: a white matter (WM) suppressed contrast (FLAWS1) and a cerebrospinal fluid (CSF) suppressed contrast (FLAWS2). FLAWS has the potential to improve the contrast of the subcortical brain regions that are important for Deep Brain Stimulation surgery planning. However, to date FLAWS has not been optimized for 1.5 T. In this study, the FLAWS sequence was optimized for use at 1.5 T. In addition, the contrast-enhancement properties of FLAWS image combinations were investigated using two voxel-wise FLAWS combined images: the ision (FLAWS- ) and the high contrast (FLAWS-hc) image. FLAWS sequence parameters were optimized for 1.5 T imaging using an approach based on the use of a profit function under constraints for brain tissue signal and contrast maximization. MR experiments were performed on eleven healthy volunteers (age 18-30). Contrast (CN) and contrast to noise ratio (CNR) between brain tissues were measured in each volunteer. Furthermore, a qualitative assessment was performed to ensure that the separation between the internal globus pallidus (GPi) and the external globus pallidus (GPe) is identifiable in FLAWS1. The optimized set of sequence parameters for FLAWS at 1.5 T provided contrasts similar to those obtained in a previous study at 3 T. The separation between the GPi and the GPe was clearly identified in FLAWS1. The CN of FLAWS-hc was higher than that of FLAWS1 and FLAWS2, but was not different from the CN of FLAWS- . The CNR of FLAWS-hc was higher than that of FLAWS- . Both qualitative and quantitative assessments validated the optimization of the FLAWS sequence at 1.5 T. Quantitative assessments also showed that FLAWS-hc provides an enhanced contrast compared to FLAWS1 and FLAWS2, with a higher CNR than FLAWS- .
Publisher: Cold Spring Harbor Laboratory
Date: 14-03-2022
DOI: 10.1101/2022.03.13.22272320
Abstract: In Alzheimer’s disease, plasma Aβ 1-42 and p-tau predict high amyloid status from Aβ-PET, however the extent to which combination of both plasma assays predict remains unknown. Prototype Simoa assays were used to measure plasma s les from cognitively normal (CN) and symptomatic adults in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. The p-tau181/Aβ 1-42 ratio showed the best prediction of Aβ-PET across all participants (AUC=0.905, 95%CI:0.86-0.95) and in CN (AUC=0.873 0.80–0.94), and symptomatic (AUC=0.908 0.82–1.00) adults. Plasma p-tau181/Aβ 1-42 ratio correlated with CSF-p-tau181 (Elecsys®, Spearman’s ρ=0.74, P .0001) and predicted abnormal CSF Aβ (AUC=0.816, 0.74-0.89). The p-tau181/Aβ 1-42 ratio also predicted future rates of cognitive decline assessed by AIBL PACC or CDR-SOB (P .0001). Plasma p-tau181/Aβ 1-42 ratio predicted both Aβ-PET status and cognitive decline, demonstrating potential as both a diagnostic aid and as a screening and prognostic assay for preclinical Alzheimer’s disease trials.
Publisher: Elsevier BV
Date: 03-2019
Publisher: Wiley
Date: 21-09-0002
DOI: 10.1016/J.IJDEVNEU.2015.08.004
Abstract: Cerebral palsy (CP) describes a group of permanent disorders of posture and movement caused by disturbances in the developing brain. Accurate diagnosis and prognosis, in terms of motor type and severity, is difficult to obtain due to the heterogeneous appearance of brain injury and large anatomical distortions commonly observed in children with CP. There is a need to optimise treatment strategies for in idual patients in order to lead to lifelong improvements in function and capabilities. Magnetic resonance imaging (MRI) is critical to non-invasively visualizing brain lesions, and is currently used to assist the diagnosis and qualitative classification in CP patients. Although such qualitative approaches under-utilise available data, the quantification of MRIs is not automated and therefore not widely performed in clinical assessment. Automated brain lesion segmentation techniques are necessary to provide valid and reproducible quantifications of injury. Such techniques have been used to study other neurological disorders, however the technical challenges unique to CP mean that existing algorithms require modification to be sufficiently reliable, and therefore have not been widely applied to MRIs of children with CP. In this paper, we present a review of a subset of available brain injury segmentation approaches that could be applied to CP, including the detection of cortical malformations, white and grey matter lesions and ventricular enlargement. Following a discussion of strengths and weaknesses, we suggest areas of future research in applying segmentation techniques to the MRI of children with CP. Specifically, we identify atlas-based priors to be ineffective in regions of substantial malformations, instead propose relying on adaptive, spatially consistent algorithms, with fast initialisation mechanisms to provide additional robustness to injury. We also identify several cortical shape parameters that could be used to identify cortical injury, and shape modelling approaches to identify anatomical injury. The benefits of automatic segmentation in CP is important as it has the potential to elucidate the underlying relationship between image derived features and patient outcome, enabling better tailoring of therapy to in idual patients.
Publisher: Wiley
Date: 21-09-2021
DOI: 10.1002/HBM.25658
Abstract: Quadrantanopia caused by inadvertent severing of Meyer's Loop of the optic radiation is a well‐recognised complication of temporal lobectomy for conditions such as epilepsy. Dissection studies indicate that the anterior extent of Meyer's Loop varies considerably between in iduals. Quantifying this for in idual patients is thus an important step to improve the safety profile of temporal lobectomies. Previous attempts to delineate Meyer's Loop using diffusion MRI tractography have had difficulty estimating its full anterior extent, required manual ROI placement, and/or relied on advanced diffusion sequences that cannot be acquired routinely in most clinics. Here we present CONSULT: a pipeline that can delineate the optic radiation from raw DICOM data in a completely automated way via a combination of robust pre‐processing, segmentation, and alignment stages, plus simple improvements that bolster the efficiency and reliability of standard tractography. We tested CONSULT on 696 scans of predominantly healthy participants (539 unique brains), including both advanced acquisitions and simpler acquisitions that could be acquired in clinically acceptable timeframes. Delineations completed without error in 99.4% of the scans. The distance between Meyer's Loop and the temporal pole closely matched both averages and ranges reported in dissection studies for all tested sequences. Median scan‐rescan error of this distance was 1 mm. When tested on two participants with considerable pathology, delineations were successful and realistic. Through this, we demonstrate not only how to identify Meyer's Loop with clinically feasible sequences, but also that this can be achieved without fundamental changes to tractography algorithms or complex post‐processing methods.
Publisher: Wiley
Date: 08-11-2023
DOI: 10.1111/ENE.15589
Abstract: Weight loss in patients with amyotrophic lateral sclerosis (ALS) is associated with faster disease progression and shorter survival. Decreased hypothalamic volume is proposed to contribute to weight loss due to loss of appetite and/or hypermetabolism. We aimed to investigate the relationship between hypothalamic volume and body mass index (BMI) in ALS and Alzheimer's disease (AD), and the associations of hypothalamic volume with weight loss, appetite, metabolism and survival in patients with ALS. We compared hypothalamic volumes from magnetic resonance imaging scans with BMI for patients with ALS ( n = 42), patients with AD ( n = 167) and non‐neurodegenerative disease controls ( n = 527). Hypothalamic volumes from patients with ALS were correlated with measures of appetite and metabolism, and change in anthropomorphic measures and disease outcomes. Lower hypothalamic volume was associated with lower and higher BMI in ALS (quadratic association probability of direction = 0.96). This was not observed in AD patients or controls. Hypothalamic volume was not associated with loss of appetite ( p = 0.58) or hypermetabolism ( p = 0.49). Patients with lower BMI and lower hypothalamic volume tended to lose weight ( p = 0.08) and fat mass ( p = 0.06) over the course of their disease, and presented with an increased risk of earlier death (hazard ratio [HR] 3.16, p = 0.03). Lower hypothalamic volume alone trended for greater risk of earlier death (HR 2.61, p = 0.07). These observations suggest that lower hypothalamic volume in ALS contributes to positive and negative energy balance, and is not universally associated with loss of appetite or hypermetabolism. Critically, lower hypothalamic volume with lower BMI was associated with weight loss and earlier death.
Publisher: Cold Spring Harbor Laboratory
Date: 26-09-2019
DOI: 10.1101/784363
Abstract: As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across erse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,232 structural brain MRI scans from participants without known neuropsychiatric disorder from 18 different studies that represent geographic ersity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to in idual cortical and deep structures and derive normative age trends of brain structure through the lifespan (3 to 96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this normative reference of brain development and aging, and to examine deviations from normative ranges, potentially related to disease.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 12-11-2020
DOI: 10.1212/WNL.0000000000011222
Abstract: To determine the effect of Aβ level on progression risk to MCI or dementia and longitudinal cognitive change in cognitively normal (CN) older in iduals. All CN from the Australian Imaging Biomarkers and Lifestyle study (AIBL) with Aβ PET and ≥3 years follow-up were included (n=534 age 72±6 yrs 27% Aβ positive follow-up 5.3±1.7 yrs). Aβ level was ided using the standardised 0-100 Centiloid scale: CL negative, 15-25 CL uncertain, 26-50 CL moderate, 51-100 CL high, CL very high, noting CL approximates a positive scan. Cox proportional hazards analysis and linear mixed effect models were used to assess risk of progression and cognitive decline. Aβ levels in 63% were negative, 10% uncertain, 10% moderate, 14% high and 3% very high. Fifty-seven (11%) progressed to MCI or dementia. Compared to negative Aβ, the hazard ratio for progression for moderate Aβ was 3.2 (95% CI 1.3-7.6 p .05), for high was 7.0 (95% CI 3.7-13.3 p .001) and for very high was 11.4 (95% CI 5.1-25.8 p .001). Decline in cognitive composite score was minimal in the moderate group (-0.02 SD/year, p=0.05) while the high and very high declined substantially (high -0.08 SD/year, p .001 very high -0.35 SD/year p .001). The risk of MCI or dementia over 5 years in older CN is related to Aβ level on PET, 5% if negative vs 25% if positive but ranging from 12% if 26-50 CL to 28% if 51-100 CL and 50% if CL. This information may be useful for dementia risk counselling and aid design of preclinical AD trials.
Publisher: BMJ
Date: 02-2017
Publisher: Wiley
Date: 30-05-2020
DOI: 10.1002/JMRI.26810
Abstract: Arterial spin labeling (ASL) is an emerging MRI technique for noninvasive measurement of cerebral blood flow (CBF) that has been used to show hemodynamic changes in the brains of people with Alzheimer's disease (AD). CBF changes have been measured using positron emission tomography (PET) across the AD spectrum, but ASL showed limited success in measuring CBF variations in the preclinical phase of AD, where amyloid β (Aβ) plaques accumulate in the decades prior to symptom onset. To investigate the relationship between CBF measured by multiphase‐pseudocontinuous‐ASL (MP‐PCASL) and Aβ burden as measured by 11 C‐PiB PET imaging in a study of cognitively normal (CN) subjects age over 65. Cross‐sectional. Forty‐six CN subjects including 33 with low levels of Aβ burden and 13 with high levels of Aβ. 3T/3D MP‐PCASL. The MP‐PCASL method was chosen because it has a high signal‐to‐noise ratio. Furthermore, the data were analyzed using an efficient processing pipeline consisting of motion correction, ASL motion correction imprecision removal, temporal and spatial filtering, and partial volume effect correction. General Linear Model. In CN subjects positive for Aβ burden ( n = 13), we observed a positive correlation between CBF and Aβ burden in the hippoc us, amygdala, caudate ( P 0.01), frontal, temporal, and insula ( P 0.05). To the best of our knowledge, this is the first study using MP‐PCASL in the study of AD, and the results suggest a potential compensatory hemodynamic mechanism that protects against pathology in the early stages of AD. Level of Evidence: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020 :505–513.
Publisher: Cold Spring Harbor Laboratory
Date: 25-08-2021
DOI: 10.1101/2021.08.23.21261848
Abstract: Ongoing research seeks to identify blood-based biomarkers able to predict the onset and progression of Alzheimer’s disease (AD). A potential biomarker is the unfolded conformational variant of p53, previously observed in in iduals in the prodromal and clinical AD stages. In this retrospective study, we compare diagnostic and prognostic performances of measures of the amyloid β load with those of a conformational variant of U-p53 in plasma s les from in iduals participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) cohort. Immunoprecipitation (IP) followed by liquid chromatography (LC) tandem mass spectrometry (MS/MS) and protein sequencing in plasma s les from the AIBL study identified the clinically relevant AZ 284 ® peptide, representing a measure of the U-p53 conformational variant (U-p53 AZ ). Based on U-p53 AZ quantification via IP/LC electrospray ionisation-coupled MS/MS (AlzoSure ® Predict test) on 515 s les from 482 in iduals from the AIBL cohort, the predictive performance of U-p53 AZ was assessed and compared with amyloid load as measured by amyloid β-positron emission tomography (Aβ-PET). Its predictive performance was determined at 36, 54, 72 and 90 months following baseline assessment. U-p53 AZ was able to identify in iduals with AD dementia with an area under the receiver operating characteristic curve (AUC) of 99%. U-p53 AZ outperformed the conventional Aβ-PET measures in predicting the onset of AD dementia both from preclinical (AUC=98%) and prodromal stages (AUC=89%), even 90 months prior to onset (AUC=99%). Additionally, the estimated predictive performance of U-p53 AZ was superior (AUC ≥98%) to other risk factors (i.e., gender, Aβ-PET and APOE ε4 allele status) in identifying in iduals at high risk for progression to AD. These findings support use of U-p53 AZ as blood-based biomarker predicting if in iduals, at both asymptomatic and MCI stages, would progress to AD at least six years prior to the onset of clinical AD dementia.
Publisher: Cold Spring Harbor Laboratory
Date: 08-02-2021
DOI: 10.1101/2021.02.08.430215
Abstract: 1 Magnetic Resonance Imaging (MRI) motion artefacts frequently complicate structural and diffusion MRI analyses. While diffusion imaging is easily ‘scrubbed’ of motion affected volumes, the same is not true for structural images. Structural images are critical to most diffusion-imaging pipelines thus their corruption can lead to disproportionate data loss. To enable diffusion-image processing when structural images have been corrupted, we propose a means by which synthetic structural images can be generated from diffusion MRI. This technique combines multi-tissue constrained spherical deconvolution, which is central to many existing diffusion analyses, with the Bloch equations which allow simulation of MRI intensities given scanner parameters and magnetic resonance (MR) tissue properties. We applied this technique to 32 scans, including those acquired on different scanners, with different protocols and with pathology present. The resulting synthetic T1w and T2w images were visually convincing and exhibited similar tissue contrast to acquired structural images. These were also of sufficient quality to drive a Freesurfer-based tractographic analysis. In this analysis, probabilistic tractography connecting the thalamus to the primary sensorimotor cortex was delineated with Freesurfer, using either real or synthetic structural images. Tractography for real and synthetic conditions was largely identical in terms of both voxels encountered (Dice 0.88 – 0.95) and mean fractional anisotropy (intrasubject absolute difference 0.00 – 0.02). We provide executables for the proposed technique in the hope that these may aid the community in analysing datasets where structural image corruption is common, such as studies of children or cognitively impaired persons. We propose a simple means of synthesizing T1w and T2w images from diffusion data The proposed method worked well for a variety of acquisitions Synthetic images showed tissue contrast akin to acquired images Synthetic images were high enough quality to be used for Freesurfer seeded diffusion tractography This method enables analysis of datasets where motion has corrupted acquired structural MRIs
Publisher: Public Library of Science (PLoS)
Date: 18-02-2022
DOI: 10.1371/JOURNAL.PONE.0247343
Abstract: Magnetic Resonance Imaging (MRI) motion artefacts frequently complicate structural and diffusion MRI analyses. While diffusion imaging is easily ‘scrubbed’ of motion affected volumes, the same is not true for T1w or T2w ‘structural’ images. Structural images are critical to most diffusion-imaging pipelines thus their corruption can lead to disproportionate data loss. To enable diffusion-image processing when structural images are missing or have been corrupted, we propose a means by which synthetic structural images can be generated from diffusion MRI. This technique combines multi-tissue constrained spherical deconvolution, which is central to many existing diffusion analyses, with the Bloch equations that allow simulation of MRI intensities for given scanner parameters and magnetic resonance (MR) tissue properties. We applied this technique to 32 scans, including those acquired on different scanners, with different protocols and with pathology present. The resulting synthetic T1w and T2w images were visually convincing and exhibited similar tissue contrast to acquired structural images. These were also of sufficient quality to drive a Freesurfer-based tractographic analysis. In this analysis, probabilistic tractography connecting the thalamus to the primary sensorimotor cortex was delineated with Freesurfer, using either real or synthetic structural images. Tractography for real and synthetic conditions was largely identical in terms of both voxels encountered (Dice 0.88–0.95) and mean fractional anisotropy (intrasubject absolute difference 0.00–0.02). We provide executables for the proposed technique in the hope that these may aid the community in analysing datasets where structural image corruption is common, such as studies of children or cognitively impaired persons.
Publisher: American Medical Association (AMA)
Date: 07-2013
Publisher: Elsevier BV
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2010
Publisher: IOP Publishing
Date: 25-10-2016
DOI: 10.1088/0031-9155/61/22/8070
Abstract: Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice's similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.
Publisher: IOP Publishing
Date: 30-11-2012
DOI: 10.1088/0031-9155/57/24/8357
Abstract: Recent advances in high resolution magnetic resonance (MR) imaging of the spine provide a basis for the automated assessment of intervertebral disc (IVD) and vertebral body (VB) anatomy. High resolution three-dimensional (3D) morphological information contained in these images may be useful for early detection and monitoring of common spine disorders, such as disc degeneration. This work proposes an automated approach to extract the 3D segmentations of lumbar and thoracic IVDs and VBs from MR images using statistical shape analysis and registration of grey level intensity profiles. The algorithm was validated on a dataset of volumetric scans of the thoracolumbar spine of asymptomatic volunteers obtained on a 3T scanner using the relatively new 3D T2-weighted SPACE pulse sequence. Manual segmentations and expert radiological findings of early signs of disc degeneration were used in the validation. There was good agreement between manual and automated segmentation of the IVD and VB volumes with the mean Dice scores of 0.89 ± 0.04 and 0.91 ± 0.02 and mean absolute surface distances of 0.55 ± 0.18 mm and 0.67 ± 0.17 mm respectively. The method compares favourably to existing 3D MR segmentation techniques for VBs. This is the first time IVDs have been automatically segmented from 3D volumetric scans and shape parameters obtained were used in preliminary analyses to accurately classify (100% sensitivity, 98.3% specificity) disc abnormalities associated with early degenerative changes.
Publisher: American Society of Neuroradiology (ASNR)
Date: 23-11-2017
DOI: 10.3174/AJNR.A5478
Publisher: Wiley
Date: 25-11-2019
DOI: 10.1002/HBM.24870
Publisher: Elsevier BV
Date: 05-2012
Publisher: Wiley
Date: 30-01-2015
DOI: 10.1002/MRM.25598
Abstract: To validate a fully automated scheme to extract biochemical information from the hip joint cartilages using MR T2 mapping images incorporating segmentation of co-registered three-dimensional Fast-Spin-Echo (3D-SPACE) images. Manual analyses of unilateral hip (3 Tesla) MR images of 24 asymptomatic volunteers were used to validate a 3D deformable model method for automated cartilage segmentation of SPACE scans, partitioning of the in idual femoral and acetabular cartilage plates into clinically defined sub-regions and propagating these results to T2 maps to calculate region-wise T2 value statistics. Analyses were completed on a desktop computer (∼ 10 min per case). The mean voxel overlap between automated A and manual M segmentations of the cartilage volumes in the (clinically based) SPACE images was 73% (100 × 2|A∩M|/[|A|+|M|]). The automated and manual analyses demonstrated a relative difference error <10% in the median "T2 average signal" for each cartilage plate. The automated and manual analyses showed consistent patterns between significant differences in T2 data across the hip cartilage sub-regions. The good agreement between the manual and automatic analyses of T2 values indicates the use of structural 3D-SPACE MR images with the proposed method provides a promising approach for automated quantitative T2 assessment of hip joint cartilages.
Publisher: Springer International Publishing
Date: 2018
Publisher: Oxford University Press (OUP)
Date: 24-07-2017
DOI: 10.1093/BRAIN/AWX137
Abstract: See Derry and Kent (doi:10.1093/awx167) for a scientific commentary on this article.The large variance in cognitive deterioration in subjects who test positive for amyloid-β by positron emission tomography indicates that convergent pathologies, such as iron accumulation, might combine with amyloid-β to accelerate Alzheimer's disease progression. Here, we applied quantitative susceptibility mapping, a relatively new magnetic resonance imaging method sensitive to tissue iron, to assess the relationship between iron, amyloid-β load, and cognitive decline in 117 subjects who underwent baseline magnetic resonance imaging and amyloid-β positron emission tomography from the Australian Imaging, Biomarkers and Lifestyle study (AIBL). Cognitive function data were collected every 18 months for up to 6 years from 100 volunteers who were either cognitively normal (n = 64) or diagnosed with mild cognitive impairment (n = 17) or Alzheimer's disease (n = 19). Among participants with amyloid pathology (n = 45), higher hippoc al quantitative susceptibility mapping levels predicted accelerated deterioration in composite cognition tests for episodic memory [β(standard error) = -0.169 (0.034), P = 9.2 × 10-7], executive function [β(standard error) = -0.139 (0.048), P = 0.004), and attention [β(standard error) = -0.074 (0.029), P = 0.012]. Deteriorating performance in a composite of language tests was predicted by higher quantitative susceptibility mapping levels in temporal lobe [β(standard error) = -0.104 (0.05), P = 0.036] and frontal lobe [β(standard error) = -0.154 (0.055), P = 0.006]. These findings indicate that brain iron might combine with amyloid-β to accelerate clinical progression and that quantitative susceptibility mapping could be used in combination with amyloid-β positron emission tomography to stratify in iduals at risk of decline.
Publisher: Elsevier BV
Date: 02-2018
DOI: 10.1016/J.EARLHUMDEV.2017.12.014
Abstract: This study aimed to examine associations between structural MRI and concurrent motor, neurological and neurobehavioral measures at 30-32 weeks postmenstrual age (PMA 'Early'), and at term equivalent age ('Term'). In this prospective cohort study, infants underwent Early MRI (n = 119 73 male median 32 weeks 1 day PMA) and Term MRI (n = 102 61 male median 40 weeks 4 days PMA) at 3 T. Structural images were scored generating white matter (WM), cortical gray matter, deep gray matter, cerebellar and global brain abnormality scores. Clinical measures were General Movements Assessment (GMs), Hammersmith Neonatal Neurological Examination (HNNE) and NICU Neonatal Neurobehavioral Scale (NNNS). The Premie-Neuro was administered Early and the Test of Infant Motor Performance (TIMP) and a visual assessment at Term. Early MRI cerebellar scores were strongly associated with neurological components of HNNE (reflexes), NNNS (Hypertonicity), the Premie-Neuro neurological subscale (regression coefficient β = -0.06 95% confidence interval CI = -0.09, -0.04 p < .001) and cr ed-synchronized GMs (β = 1.10 95%CI = 0.57, 1.63 p < .001). Term MRI WM and global scores were strongly associated with the TIMP (WM β = -1.02 95%CI = -1.67, -0.36 p = .002 global β = -1.59 95%CI = -2.62, -0.56 p = .001). Brain structure on Early and Term MRI was associated with concurrent motor, neurological and neurobehavioral function in very preterm infants.
Publisher: Frontiers Media SA
Date: 28-09-2015
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 15-02-2022
DOI: 10.1212/WNL.0000000000200118
Abstract: This prospective study sought to determine the association of modifiable/nonmodifiable components included in the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) risk score with hippoc al volume (HV) loss and episodic memory (EM) decline in cognitively normal (CN) older adults classified as brain β-amyloid (Aβ) negative (Aβ−) or positive (Aβ+). Australian Imaging, Biomarkers and Lifestyle study participants (age 58–91 years) who completed ≥2 neuropsychological assessments and a brain Aβ PET scan (n = 592) were included in this study. We computed the CAIDE risk score (age, sex, APOE ε4 status, education, hypertension, body mass index [BMI], hypercholesterolemia, physical inactivity) and a modifiable CAIDE risk score (CAIDE-MR education, hypertension, BMI, hypercholesterolemia, physical inactivity) for each participant. Aβ+ was classified using Centiloid . Linear mixed models assessed interactions between each CAIDE score, Aβ group, and time on HV loss and EM decline. Age, sex, and APOE ε4 were included as separate predictors in CAIDE-MR models to assess differential associations. Exploratory analyses examined relationships between in idual modifiable risk factors and outcomes in Aβ− cognitively normal (CN) adults. We observed a significant Aβ group × CAIDE × time interaction on HV loss (β [SE] = –0.04 [0.01] p 0.000) but not EM decline (β [SE] = –2.33 [9.96] p = 0.98). Decomposition revealed a significant CAIDE × time interaction in Aβ+ participants only. When modifiable/nonmodifiable CAIDE components were considered separately, we observed a significant Aβ group × CAIDE-MR × time interaction on EM decline only (β [SE] = 3.03 [1.18] p = 0.01). A significant CAIDE-MR score × time interaction was observed in Aβ− participants only. Significant interactions between APOE ε4 and age × time on HV loss and EM decline were observed in both groups. Exploratory analyses in Aβ− CN participants revealed a significant interaction between BMI × time on EM decline (β [SE] = –3.30 [1.43] p = 0.02). These results are consistent with studies showing that increasing age and APOE ε4 are associated with increased rates of HV loss and EM decline. In Aβ− CN adults, lower prevalence of modifiable cardiovascular risk factors was associated with less HV loss and EM decline over ∼10 years, suggesting interventions to reduce modifiable cardiovascular risk factors could be beneficial in this group.
Publisher: Elsevier BV
Date: 10-2007
DOI: 10.1016/J.ACRA.2007.06.021
Abstract: The segmentation of textured anatomy from magnetic resonance images (MRI) is a difficult problem. We present an approach that uses features extracted from the magnitude and phase of the MRI signal to segment the bones in the knee. Moreover, we show that by incorporating shape information, more accurate and anatomically valid segmentations are obtained. Eighteen volunteers were scanned in a whole-body 3T clinical scanner using a transmit-receive quadrature extremity coil. A gradient-echo sequence was used to acquire three-dimensional (3D) volumes of raw complex image data consisting of phase and magnitude information. These images were manually segmented and features were extracted using a bank of Gabor filters. The extracted features were then used to train a support vector machine (SVM) classifier. Each image was then automatically segmented using both the SVM classifier and a 3D active shape model (ASM) driven by the classifier. The use of phase and magnitude information from both echoes obtained the most accurate classifier results with an average dice similarity coefficient of 0.907. The use of 3D ASMs further improved the robustness, accuracy and anatomic validity of the segmentations with an overall DSC of 0.922 and an average point to surface error along the bone-cartilage interface of 0.73 mm. Our results demonstrate that the incorporation of phase and multiple echoes improve the results obtained by the classifier. Moreover, we show that 3D ASMs provide a robust and accurate way of using the classifier to obtain anatomically valid segmentation results.
Publisher: IOP Publishing
Date: 21-09-2015
DOI: 10.1088/0031-9155/60/19/7601
Abstract: To develop an automated approach for 3D quantitative assessment and measurement of alpha angles from the femoral head-neck (FHN) junction using bone models derived from magnetic resonance (MR) images of the hip joint.Bilateral MR images of the hip joints were acquired from 30 male volunteers (healthy active in iduals and high-performance athletes, aged 18–49 years) using a water-excited 3D dual echo steady state (DESS) sequence. In a subset of these subjects (18 water-polo players), additional True Fast Imaging with Steady-state Precession (TrueFISP) images were acquired from the right hip joint. For both MR image sets, an active shape model based algorithm was used to generate automated 3D bone reconstructions of the proximal femur. Subsequently, a local coordinate system of the femur was constructed to compute a 2D shape map to project femoral head sphericity for calculation of alpha angles around the FHN junction. To evaluate automated alpha angle measures, manual analyses were performed on anterosuperior and anterior radial MR slices from the FHN junction that were automatically reformatted using the constructed coordinate system.High intra- and inter-rater reliability (intra-class correlation coefficients > 0.95) was found for manual alpha angle measurements from the auto-extracted anterosuperior and anterior radial slices. Strong correlations were observed between manual and automatic measures of alpha angles for anterosuperior (r = 0.84) and anterior (r = 0.92) FHN positions. For matched DESS and TrueFISP images, there were no significant differences between automated alpha angle measures obtained from the upper anterior quadrant of the FHN junction (two-way repeated measures ANOVA, F < 0.01, p = 0.98).Our automatic 3D method analysed MR images of the hip joints to generate alpha angle measures around the FHN junction circumference with very good reliability and reproducibility. This work has the potential to improve analyses of cam-type lesions of the FHN junction for large-scale morphometric and clinical MR investigations of the human hip region.
Publisher: Wiley
Date: 29-09-2020
DOI: 10.1002/MRM.28517
Abstract: To demonstrate that fluid and white matter suppression (FLAWS) imaging can be used for high‐resolution T 1 mapping with low transmitted bias field ( ) sensitivity at 7T. The FLAWS sequence was optimized for 0.8‐mm isotropic resolution imaging. The theoretical accuracy and precision of the FLAWS T 1 mapping was compared with the one of the magnetization‐prepared two rapid gradient echoes (MP2RAGE) sequence optimized for low sensitivity. FLAWS images were acquired at 7T on six healthy volunteers (21 to 48 years old two women). MP2RAGE and saturation‐prepared with two rapid gradient echoes (SA2RAGE) datasets were also acquired to obtain T 1 mapping references and maps. The contrast‐to‐noise ratio (CNR) between brain tissues was measured in the FLAWS‐hco and MP2RAGE‐uni images. The Pearson correlation was measured between the MP2RAGE and FLAWS T 1 maps. The effect of on FLAWS T 1 mapping was assessed using the Pearson correlation. The FLAWS‐hco images were characterized by a higher brain tissue CNR ( , , ) than the MP2RAGE‐uni images ( , , ). The theoretical accuracy and precision of the FLAWS T 1 mapping ( ) were in agreement with those provided by the MP2RAGE T 1 mapping ( ). A good agreement was found between in vivo T 1 values measured with the MP2RAGE and FLAWS sequences ( r = 0.91). A weak correlation was found between the FLAWS T 1 map and the map within cortical gray matter and white matter segmentations ( ). The results from this study suggest that FLAWS is a good candidate for high‐resolution T 1 ‐weighted imaging and T 1 mapping at the field strength of 7T.
Publisher: Wiley
Date: 04-03-2015
DOI: 10.1002/JMRI.24609
Abstract: To propose a robust and automated model-based semantic registration for the multimodal alignment of the knee bone and cartilage from three-dimensional (3D) MR image data. The movement of the knee joint can be semantically interpreted as a combination of movements of each bone. A semantic registration of the knee joint was implemented by separately reconstructing the rigid movements of the three bones. The proposed method was validated by registering 3D morphological MR datasets of 25 subjects into the corresponding T2 map datasets, and was compared with rigid and elastic methods using two criteria: the spatial overlap of the manually segmented cartilage and the distance between the same landmarks in the reference and target datasets. The mean Dice Similarity Coefficient (DSC) of the overlapped cartilage segmentation was increased to 0.68 ± 0.1 (mean ± SD) and the landmark distance was reduced to 1.3 ± 0.3 mm after the proposed registration method. Both metrics were statistically superior to using rigid (DSC: 0.59 ± 0.12 landmark distance: 2.1 ± 0.4 mm) and elastic (DSC: 0.64 ± 0.11 landmark distance: 1.5 ± 0.5 mm) registrations. The proposed method is an efficient and robust approach for the automated registration between morphological knee datasets and T2 MRI relaxation maps.
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.JOCA.2014.06.029
Abstract: To validate an automatic scheme for the segmentation and quantitative analysis of the medial meniscus (MM) and lateral meniscus (LM) in magnetic resonance (MR) images of the knee. We analysed sagittal water-excited double-echo steady-state MR images of the knee from a subset of the Osteoarthritis Initiative (OAI) cohort. The MM and LM were automatically segmented in the MR images based on a deformable model approach. Quantitative parameters including volume, subluxation and tibial-coverage were automatically calculated for comparison (Wilcoxon tests) between knees with variable radiographic osteoarthritis (rOA), medial and lateral joint space narrowing (mJSN, lJSN) and pain. Automatic segmentations and estimated parameters were evaluated for accuracy using manual delineations of the menisci in 88 pathological knee MR examinations at baseline and 12 months time-points. The median (95% confidence-interval (CI)) Dice similarity index (DSI) (2 ∗|Auto ∩ Manual|/(|Auto|+|Manual|)∗ 100) between manual and automated segmentations for the MM and LM volumes were 78.3% (75.0-78.7), 83.9% (82.1-83.9) at baseline and 75.3% (72.8-76.9), 83.0% (81.6-83.5) at 12 months. Pearson coefficients between automatic and manual segmentation parameters ranged from r = 0.70 to r = 0.92. MM in rOA/mJSN knees had significantly greater subluxation and smaller tibial-coverage than no-rOA/no-mJSN knees. LM in rOA knees had significantly greater volumes and tibial-coverage than no-rOA knees. Our automated method successfully segmented the menisci in normal and osteoarthritic knee MR images and detected meaningful morphological differences with respect to rOA and joint space narrowing (JSN). Our approach will facilitate analyses of the menisci in prospective MR cohorts such as the OAI for investigations into pathophysiological changes occurring in early osteoarthritis (OA) development.
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/AN12366
Abstract: The aim of this study was to determine the effect of potassium (K) supplementation on the calcium (Ca) absorption capacity from the rumen and abomasum of sheep. The Ca absorption capacity from the rumen and abomasum of sheep was measured using stable strontium (Sr) as a Ca-analogue tracer method. The sheep, cannulated at either the rumen or abomasum, were randomly allocated to one of two groups (control or K-supplemented) and fed in in idual metabolism pens twice daily with a diet comprising oaten hay, lucerne chaff and barley fortified with or without potassium carbonate (K2CO3). The K content of the diet of the K-supplemented animals was 3.1% of dry matter compared with 1.4% for the control animals. The animals were fed their respective diets for a period of 2 weeks. The fractional absorption capacity (FC) of Ca was estimated before, during and after the treatment period. Supplementation with K decreased the FC of Ca in both the rumen and abomasum during treatment and increased the FC of Ca in the abomasum post-treatment. Supplementation with K also increased the fractional excretion of K in the urine, but decreased the fractional excretion of Ca and magnesium (Mg) (P 0.05), showing that K supplementation significantly affected Ca and Mg metabolism. Results suggest that renal conservation of Ca and Mg is an important mechanism controlling the Ca and Mg pool for vital functions of the body. In times of high demand for these minerals during lactation and pregnancy, high K in the diets may predispose sheep to hypomagnesaemia and hypocalcaemia, which in turn will have a negative impact on productivity and economic returns.
Publisher: The Open Journal
Date: 05-08-2022
DOI: 10.21105/JOSS.04368
Publisher: Wiley
Date: 17-05-2020
DOI: 10.1002/SIM.8568
Publisher: Research Square Platform LLC
Date: 05-04-2022
DOI: 10.21203/RS.3.RS-1503113/V1
Abstract: Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to structural covariance patterns across brain regions and in iduals. We present a mega-analysis of structural covariance with magnetic resonance imaging of 50,699 healthy and diseased in iduals (12 studies, 130 sites, and 12 countries) over their lifespan (ages 5 through 97). Patterns of structural covariance (PSC) were highly heritable (0.05 h2 .78) and significantly associated with 1610 independent significant variants after Bonferroni correction (10.3 -log10[p-value] 8.8): 1245 previously unreported, and 69% of them independently replicated (-log10[p-value] = 4.5). Associations revealed an imaging phenotypic landscape between 2003 PSCs and 49 clinical and cognitive traits at multiple scales. We constructed machine learning-derived in idualized imaging signatures for various disease diagnoses using PSC features at multiple scales, suggesting that disease effects on the brain were better manifested in a multi-scale continuum than on any single scale. Experimental results were integrated into the Multi-scale Structural Imaging Covariance (MuSIC) atlas and made publicly accessible through the BRIDGEPORT web portal (ridgeport/). Our results reveal strong associations between brain structural covariance, genetics, and clinical phenotypes, supporting that PSCs can serve as an endophenotypic anatomic dictionary in future research.
Publisher: Cold Spring Harbor Laboratory
Date: 18-07-2020
DOI: 10.1101/2020.07.16.20155598
Abstract: 1 Quadrantanopia caused by inadvertent severing of Meyer’s Loop of the optic radiation is a well-recognised complication of temporal lobectomy for conditions such as epilepsy. Dissection studies indicate that the anterior extent of Meyer’s Loop varies considerably between in iduals. Quantifying this for in idual patients is thus an important step to improve the safety profile of temporal lobectomies. Previous attempts to delineate Meyer’s Loop using diffusion MRI tractography have had difficulty estimating its full anterior extent, required manual ROI placement, and/or relied on advanced diffusion sequences that cannot be acquired routinely in most clinics. Here we present CONSULT – a pipeline that can delineate the optic radiation from raw DICOM data in a completely automated way via a combination of robust preprocessing, segmentation, and alignment stages, plus simple improvements that bolster the efficiency and reliability of standard tractography. We tested CONSULT on 694 scans of predominantly healthy participants (538 unique brains), including both advanced acquisitions and simpler acquisitions that could be acquired in clinically acceptable timeframes. Delineations completed without error in 99.4% of the scans. The distance between Meyer’s Loop and the temporal pole closely matched both averages and ranges reported in dissection studies for all tested sequences. Median scan-rescan error of this distance was 1mm. When tested on two participants with considerable pathology, delineations were successful and realistic. Through this, we demonstrate not only how to identify Meyer’s Loop with clinically accessible sequences, but also that this can be achieved without fundamental changes to tractography algorithms or complex post-processing methods. We propose a fully automated means of delineating the optic radiation using diffusion MRI from DICOM data Anatomical measurements from tractography of over 500 brains align well with previous dissection studies The proposed pipeline works well with clinically accessible and advanced acquisitions Median scan-rescan error was 1mm Plausible tractography was generated when pathology was present
Publisher: Springer Science and Business Media LLC
Date: 27-08-2016
Publisher: Public Library of Science (PLoS)
Date: 12-07-2018
Publisher: Elsevier BV
Date: 2021
Publisher: Springer Science and Business Media LLC
Date: 22-10-2020
DOI: 10.1186/S40359-020-00476-4
Abstract: The aim of this metasynthesis was to explore adult anorexia nervosa (AN) treatment experiences, including facilitators and barriers to treatment engagement and ways that questions of identity and personal agency were negotiated in treatment contexts. From 14 qualitative studies that met the search criteria, this thematic synthesis analyzed the sensitized concept of identity in the participants’ experiences of AN treatments, including their sense of personal agency, and implications for their recovery. The study was registered with Prospero (ID: CRD42018089259) and is reported according to PRISMA guidelines. Three meta-themes were generated with the following key findings: grappling with identity, where collaborative and tailored interventions were positively experienced the quality of the therapeutic relationship, which existed in a recursive relationship and, rebuilding identity that included therapists standing with the person in recovering a sense of identity outside the anorexic identity. Importantly, interventions that failed to be negotiated with the person were experienced as disempowering however, where a two-way trust existed in the therapeutic relationship, it critically empowered and shaped participants’ sense of identity, and broadened the perception that they were valuable as a person. There was consensus across the range of treatment contexts that in iduals with a lived AN experience preferred treatments where they experienced (1) a sense of personal agency through tailored interventions and (2) therapists who treated them as a person who, in the face of their struggles, had skills and capacities in the processes of recovering and rebuilding sustainable and preferred identities outside the AN identity.
Publisher: Springer Science and Business Media LLC
Date: 10-12-2021
DOI: 10.1038/S41598-021-02827-6
Abstract: To improve understanding of Alzheimer’s disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p 0.001) for clinical classification to measured data in the other dataset. Further, the increased power of the overall harmonised dataset was demonstrated by observing a significant association between CVLT-II test scores (imputed for ADNI) with PET Amyloid-β in MCI APOE -ε4 homozygotes in the imputed data (N = 65) but not for the original AIBL dataset (N = 11). These results suggest that MissForest can provide a practical solution for data harmonization using imputation across studies to improve power for more nuanced analyses.
Publisher: Wiley
Date: 20-12-2016
Abstract: Patients presenting with clinically isolated syndrome (CIS) may proceed to clinically definite multiple sclerosis (CDMS). Midsagittal corpus callosum area (CCA) is a surrogate marker for callosal atrophy, and can be obtained from a standard MRI study. This study explores the relationship between CCA measured at CIS presentation (baseline) and at 5 years post presentation, with conversion from CIS to CDMS. The association between CCA and markers of disability progression is explored. Corpus callosum area was measured on MRI scans at presentation and 5-year review following diagnosis of a first demyelinating event, or evidence of progressive MS, in 143 participants in the Ausimmune/AusLong Study. Relationships between CCA (at baseline and follow-up) and clinical outcomes were assessed. Mean CCA at baseline study was 6.63 cm Baseline CCA obtained from standard MRI protocols may be compared with subsequent MRI examinations as a surrogate for neurodegeneration and cerebral atrophy in patients with MS. This study demonstrates an association between CCA and disability in in iduals presenting with CIS who convert to MS.
Publisher: Elsevier BV
Date: 10-2018
DOI: 10.1016/J.CMPB.2018.07.011
Abstract: Biomedical imaging analysis typically comprises a variety of complex tasks requiring sophisticated algorithms and visualising high dimensional data. The successful integration and deployment of the enabling software to clinical (research) partners, for rigorous evaluation and testing, is a crucial step to facilitate adoption of research innovations within medical settings. In this paper, we introduce the Simple Medical Imaging Library Interface (SMILI), an object oriented open-source framework with a compact suite of objects geared for rapid biomedical imaging (cross-platform) application development and deployment. SMILI supports the development of both command-line (shell and Python scripting) and graphical applications utilising the same set of processing algorithms. It provides a substantial subset of features when compared to more complex packages, yet it is small enough to ship with clinical applications with limited overhead and has a license suitable for commercial use. After describing where SMILI fits within the existing biomedical imaging software ecosystem, by comparing it to other state-of-the-art offerings, we demonstrate its capabilities in creating a clinical application for manual measurement of cam-type lesions of the femoral head-neck region for the investigation of femoro-acetabular impingement (FAI) from three dimensional (3D) magnetic resonance (MR) images of the hip. This application for the investigation of FAI proved to be convenient for radiological analyses and resulted in high intra (ICC=0.97) and inter-observer (ICC=0.95) reliabilities for measurement of α-angles of the femoral head-neck region. We believe that SMILI is particularly well suited for prototyping biomedical imaging applications requiring user interaction and/or visualisation of 3D mesh, scalar, vector or tensor data.
Publisher: BMJ
Date: 05-2020
DOI: 10.1136/BMJOPEN-2019-036480
Abstract: Infants born very preterm are at risk of adverse neurodevelopmental outcomes, including cognitive deficits, motor impairments and cerebral palsy. Earlier identification enables targeted early interventions to be implemented with the aim of improving outcomes. Protocol for 6-year follow-up of two cohorts of infants born weeks gestational age (PPREMO: Prediction of Preterm Motor Outcomes PREBO: Prediction of Preterm Brain Outcomes) and a small term-born reference s le in Brisbane, Australia. Both preterm cohorts underwent very early MRI and concurrent clinical assessment at 32 and 40 weeks postmenstrual age (PMA) and were followed up at 3, 12 and 24 months corrected age (CA). This study will perform MRI and electroencephalography (EEG). Primary outcomes include the Movement Assessment Battery for Children second edition and Full-Scale IQ score from the Wechsler Intelligence Scale for Children fifth edition (WISC-V). Secondary outcomes include the Gross Motor Function Classification System for children with cerebral palsy executive function (Behavior Rating Inventory of Executive Function second edition, WISC-V Digit Span and Picture Span, Wisconsin Card Sorting Test 64 Card Version) attention (Test of Everyday Attention for Children second edition) language (Clinical Evaluation of Language Fundamentals fifth edition), academic achievement (Woodcock Johnson IV Tests of Achievement) mental health and quality of life (Development and Well-Being Assessment, Autism Spectrum Quotient-10 Items Child version and Child Health Utility-9D). Examine the ability of early neonatal MRI, EEG and concurrent clinical measures at 32 weeks PMA to predict motor, cognitive, language, academic achievement and mental health outcomes at 6 years CA. Determine if early brain abnormalities persist and are evident on brain MRI at 6 years CA and the relationship to EEG and concurrent motor, cognitive, language, academic achievement and mental health outcomes. Ethical approval has been obtained from Human Research Ethics Committees at Children’s Health Queensland (HREC/19/QCHQ/49800) and The University of Queensland (2019000426). Study findings will be presented at national and international conferences and published in peer-reviewed journals. ACTRN12619000155190p. www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12619000155190p
Publisher: Wiley
Date: 06-09-2016
DOI: 10.1118/1.4961011
Abstract: Magnetic resonance (MR) imaging plays a key role in investigating early degenerative disorders and traumatic injuries of the glenohumeral cartilages. Subtle morphometric and biochemical changes of potential relevance to clinical diagnosis, treatment planning, and evaluation can be assessed from measurements derived from in vivo MR segmentation of the cartilages. However, segmentation of the glenohumeral cartilages, using approaches spanning manual to automated methods, is technically challenging, due to their thin, curved structure and overlapping intensities of surrounding tissues. Automatic segmentation of the glenohumeral cartilages from MR imaging is not at the same level compared to the weight-bearing knee and hip joint cartilages despite the potential applications with respect to clinical investigation of shoulder disorders. In this work, the authors present a fully automated segmentation method for the glenohumeral cartilages using MR images of healthy shoulders. The method involves automated segmentation of the humerus and scapula bones using 3D active shape models, the extraction of the expected bone-cartilage interface, and cartilage segmentation using a graph-based method. The cartilage segmentation uses localization, patient specific tissue estimation, and a model of the cartilage thickness variation. The accuracy of this method was experimentally validated using a leave-one-out scheme on a database of MR images acquired from 44 asymptomatic subjects with a true fast imaging with steady state precession sequence on a 3 T scanner (Siemens Trio) using a dedicated shoulder coil. The automated results were compared to manual segmentations from two experts (an experienced radiographer and an experienced musculoskeletal anatomist) using the Dice similarity coefficient (DSC) and mean absolute surface distance (MASD) metrics. Accurate and precise bone segmentations were achieved with mean DSC of 0.98 and 0.93 for the humeral head and glenoid fossa, respectively. Mean DSC scores of 0.74 and 0.72 were obtained for the humeral and glenoid cartilage volumes, respectively. The manual interobserver reliability evaluated by DSC was 0.80 ± 0.03 and 0.76 ± 0.04 for the two cartilages, implying that the automated results were within an acceptable 10% difference. The MASD between the automatic and the corresponding manual cartilage segmentations was less than 0.4 mm (previous studies reported mean cartilage thickness of 1.3 mm). This work shows the feasibility of volumetric segmentation and separation of the glenohumeral cartilages from MR images. To their knowledge, this is the first fully automated algorithm for volumetric segmentation of the in idual glenohumeral cartilages from MR images. The approach was validated against manual segmentations from experienced analysts. In future work, the approach will be validated on imaging datasets acquired with various MR contrasts in patients.
Publisher: Elsevier BV
Date: 2015
DOI: 10.1016/J.NEUROBIOLAGING.2014.04.033
Abstract: (11)C-Pittsburgh compound B (PiB) is a positron emission tomography (PET) tracer designed to bind to amyloid-β (Aβ) plaques, one of the hallmarks of Alzheimer's disease (AD). The potential of PiB as an early marker of AD led to the increasing use of PiB in clinical research studies and development of several F-18-labeled Aβ radiotracers. Automatic quantification of PiB images requires an accurate parcellation of the brain's gray matter (GM). Typically, this relies on a coregistered magnetic resonance imaging (MRI) to extract the cerebellar GM, compute the standardized uptake value ratio (SUVR), and provide parcellation and segmentation for quantification of regional and global SUVR. However, not all subjects can undergo MRI, in which case, an MR-less method is desirable. In this study, we assess 3 PET-only quantification methods: a mean atlas, an adaptive atlas, and a multi-atlas approaches on a database of 237 subjects having been imaged with both PiB PET and MRI. The PET-only methods were compared against MR-based SUVR quantification and evaluated in terms of correlation, average error, and performance in classifying subjects with low and high Aβ deposition. The mean atlas method suffered from a significant bias between the estimated neocortical SUVR and the PiB status, resulting in an overall error of 5.6% (R(2) = 0.98), compared with the adaptive and multi-atlas approaches that had errors of 3.06% and 2.74%, respectively (R(2) = 0.98), and no significant bias. In classifying PiB-negative from PiB-positive subjects, the mean atlas had 10 misclassified subjects compared with 0 for the adaptive and 1 for the multi-atlas approach. Overall, the adaptive and the multi-atlas approaches performed similarly well against the MR-based quantification and would be a suitable replacements for PiB quantification when no MRI is available.
Publisher: Cold Spring Harbor Laboratory
Date: 16-05-2023
DOI: 10.1101/2023.05.15.23289982
Abstract: Increasing physical activity (PA) is an effective strategy to slow reductions in cortical volume and maintain cognitive function in older adulthood. However, PA does not exist in isolation, but coexists with sleep and sedentary behaviour to make up the 24-hour day. We investigated how the balance of all three behaviours (24-hour time-use composition) is associated with grey matter volume in healthy older adults, and whether grey matter volume influences the relationship between 24-hour time-use composition and cognitive function. This cross-sectional study included 378 older adults (65.6 ± 3.0 years old, 123 male) from the ACTIVate study across two Australian sites (Adelaide and Newcastle). Time-use composition was captured using 7-day accelerometry, and T1-weighted magnetic resonance imaging was used to measure grey matter volume both globally and across regions of interest (ROI: frontal lobe, temporal lobe, hippoc i, and lateral ventricles). Pairwise correlations were used to explore univariate associations between time-use variables, grey matter volumes and cognitive outcomes. Compositional data analysis linear regression models were used to quantify associations between ROI volumes and time-use composition, and explore potential associations between the interaction between ROI volumes and time-use composition with cognitive outcomes. After adjusting for covariates (age, sex, education), there were no significant associations between time-use composition and any volumetric outcomes. There were significant interactions between time-use composition and frontal lobe volume for long-term memory (p=0.018) and executive function (p=0.018), and between time-use composition and total grey matter volume for executive function (p=0.028). Spending more time in moderate-vigorous PA was associated with better long-term memory scores, but only for those with smaller frontal lobe volume (below the s le mean). Conversely, spending more time in sleep and less time in sedentary behaviour was associated with better executive function in those with smaller total grey matter volume. Although 24-hour time use was not associated with total or regional grey matter independently, total grey matter and frontal lobe grey matter volume mediated the relationship between time-use composition and several cognitive outcomes. Future studies should investigate these relationships longitudinally to assess whether changes in time-use composition correspond to changes in grey matter volume and cognition.
Publisher: Elsevier BV
Date: 11-2014
DOI: 10.1016/J.SPINEE.2014.05.023
Abstract: Magnetic resonance (MR) examinations of morphologic characteristics of intervertebral discs (IVDs) have been used extensively for biomechanical studies and clinical investigations of the lumbar spine. Traditionally, the morphologic measurements have been performed using time- and expertise-intensive manual segmentation techniques not well suited for analyses of large-scale studies.. The purpose of this study is to introduce and validate a semiautomated method for measuring IVD height and mean sagittal area (and volume) from MR images to determine if it can replace the manual assessment and enable analyses of large MR cohorts. This study compares semiautomated and manual measurements and assesses their reliability and agreement using data from repeated MR examinations. Seven healthy asymptomatic males underwent 1.5-T MR examinations of the lumbar spine involving sagittal T2-weighted fast spin-echo images obtained at baseline, pre-exercise, and postexercise conditions. Measures of the mean height and the mean sagittal area of lumbar IVDs (L1-L2 to L4-L5) were compared for two segmentation approaches: a conventional manual method (10-15 minutes to process one IVD) and a specifically developed semiautomated method (requiring only a few mouse clicks to process each subject). Both methods showed strong test-retest reproducibility evaluated on baseline and pre-exercise examinations with strong intraclass correlations for the semiautomated and manual methods for mean IVD height (intraclass correlation coefficient [ICC]=0.99, 0.98) and mean IVD area (ICC=0.98, 0.99), respectively. A bias (average deviation) of 0.38 mm (4.1%, 95% confidence interval 0.18-0.59 mm) was observed between the manual and semiautomated methods for the IVD height, whereas there was no statistically significant difference for the mean IVD area (0.1%±3.5%). The semiautomated and manual methods both detected significant exercise-induced changes in IVD height (0.20 and 0.28 mm) and mean IVD area (5.7 and 8.3 mm(2)), respectively. The presented semiautomated method provides an alternative to time- and expertise-intensive manual procedures for analysis of larger, cross-sectional, interventional, and longitudinal MR studies for morphometric analyses of lumbar IVDs.
Publisher: Elsevier BV
Date: 10-2014
Publisher: Elsevier BV
Date: 07-2020
Publisher: Oxford University Press (OUP)
Date: 11-2013
Publisher: Springer International Publishing
Date: 2016
Publisher: Wiley
Date: 2022
DOI: 10.1002/DAD2.12307
Abstract: We evaluated a new Simoa plasma assay for phosphorylated tau (P‐tau) at aa217 enhanced by additional p‐tau sites (p217+tau). Plasma p217+tau levels were compared to 18 F‐NAV4694 amyloid beta (Aβ) positron emission tomography (PET) and 18 F‐MK6240 tau PET in 174 cognitively impaired (CI) and 223 cognitively unimpaired (CU) participants. Compared to Aβ− CU, the plasma levels of p217+tau increased 2‐fold in Aβ+ CU and 3.5‐fold in Aβ+ CI. In Aβ− the p217+tau levels did not differ significantly between CU and CI. P217+tau correlated with Aβ centiloids P = .67 (CI, P = .64 CU, P = .45) and tau SUVR MT P = .63 (CI, P = .69 CU, P = .34). Area under curve (AUC) for Alzheimer's disease (AD) dementia versus Aβ− CU was 0.94, for AD dementia versus other dementia was 0.93, for Aβ+ versus Aβ− PET was 0.89, and for tau+ versus tau− PET was 0.89. Plasma p217+tau levels elevate early in the AD continuum and correlate well with Aβ and tau PET.
Publisher: Elsevier BV
Date: 10-2009
Publisher: Oxford University Press (OUP)
Date: 11-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: Springer Science and Business Media LLC
Date: 24-02-2021
DOI: 10.1038/S41390-021-01399-5
Abstract: This study aimed to identify which MRI and clinical assessments, alone or in combination, from (i) early (32 weeks postmenstrual age, PMA), (ii) term equivalent age (TEA) and (iii) 3 months corrected age (CA) are associated with motor or cognitive outcomes at 2 years CA in infants born <31 weeks gestation. Prospective cohort study of 98 infants who underwent early and TEA MRI (n = 59 males median birth gestational age 28 + 5 weeks). Hammersmith Neonatal Neurological Examination (HNNE), NICU Neonatal Neurobehavioural Scale and General Movements Assessment (GMs) were performed early and at TEA. Premie-Neuro was performed early and GMs, Test of Infant Motor Performance and visual assessment were performed at TEA and 3 months CA. Neurodevelopmental outcomes were determined using Bayley Scales of Infant and Toddler Development 3rd edition. The best combined motor outcome model included 3-month GMs (β = -11.41 95% CI = -17.34, -5.49), TEA MRI deep grey matter score (β = -6.23 95% CI = -9.47, -2.99) and early HNNE reflexes (β = 3.51 95% CI = 0.86, 6.16). Combined cognitive model included 3-month GMs (β = -10.01 95% CI = -15.90, -4.12) and TEA HNNE score (β = 1.33 95% CI = 0.57, 2.08). Early neonatal neurological assessment improves associations with motor outcomes when combined with term MRI and 3-month GMs. Term neurological assessment combined with 3-month GMs improves associations with cognitive outcomes. We present associations between 32- and 40-week MRI, comprehensive clinical assessments and later 2-year motor and cognitive outcomes for children born <31 weeks gestation. MRI and clinical assessment of motor, neurological and neurobehavioural function earlier than term equivalent age in very preterm infants is safe and becoming more available in clinical settings. Most of these children are discharged from hospital before term age and so completing assessments prior to discharge can assist with follow up. MRI and neurological assessment prior to term equivalent age while the child is still in hospital can provide earlier identification of children at highest risk of adverse outcomes and guide follow-up screening and intervention services.
Publisher: Elsevier BV
Date: 12-2015
Publisher: Oxford University Press (OUP)
Date: 27-06-2020
Abstract: Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In particular, MRI-derived brain age has been used as a comprehensive biomarker of brain health that can identify both advanced and resilient ageing in iduals via deviations from typical brain ageing. Imaging signatures of various brain diseases, including schizophrenia and Alzheimer’s disease, have also been identified using machine learning. Prior efforts to derive these indices have been h ered by the need for sophisticated and not easily reproducible processing steps, by insufficiently powered or ersified s les from which typical brain ageing trajectories were derived, and by limited reproducibility across populations and MRI scanners. Herein, we develop and test a sophisticated deep brain network (DeepBrainNet) using a large (n = 11 729) set of MRI scans from a highly ersified cohort spanning different studies, scanners, ages and geographic locations around the world. Tests using both cross-validation and a separate replication cohort of 2739 in iduals indicate that DeepBrainNet obtains robust brain-age estimates from these erse datasets without the need for specialized image data preparation and processing. Furthermore, we show evidence that moderately fit brain ageing models may provide brain age estimates that are most discriminant of in iduals with pathologies. This is not unexpected as tightly-fitting brain age models naturally produce brain-age estimates that offer little information beyond age, and loosely fitting models may contain a lot of noise. Our results offer some experimental evidence against commonly pursued tightly-fitting models. We show that the moderately fitting brain age models obtain significantly higher differentiation compared to tightly-fitting models in two of the four disease groups tested. Critically, we demonstrate that leveraging DeepBrainNet, along with transfer learning, allows us to construct more accurate classifiers of several brain diseases, compared to directly training classifiers on patient versus healthy control datasets or using common imaging databases such as ImageNet. We, therefore, derive a domain-specific deep network likely to reduce the need for application-specific adaptation and tuning of generic deep learning networks. We made the DeepBrainNet model freely available to the community for MRI-based evaluation of brain health in the general population and over the lifespan.
Publisher: Elsevier BV
Date: 02-2020
Publisher: Elsevier BV
Date: 02-2012
DOI: 10.1016/J.NEUROIMAGE.2011.10.014
Abstract: The hippoc us is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippoc us. The hippoc al shape variations among a population can be usually described using statistical shape models (SSMs). Conventional SSMs model the modes of variations among the population via principal component analysis (PCA). Although these modes are representative of variations within the training data, they are not necessarily discriminative on labeled data or relevant to the differences between the subpopulations. We use the shape descriptors from SSM as features to classify AD from normal control (NC) cases. In this study, a Hotelling's T2 test is performed to select a subset of landmarks which are used in PCA. The resulting variation modes are used as predictors of AD from NC. The discrimination ability of these predictors is evaluated in terms of their classification performances with bagged support vector machines (SVMs). Restricting the model to landmarks with better separation between AD and NC increases the discrimination power of SSM. The predictors extracted on the subregions also showed stronger correlation with the memory-related measurements such as Logical Memory, Auditory Verbal Learning Test (AVLT) and the memory subscores of Alzheimer Disease Assessment Scale (ADAS).
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 04-09-2020
DOI: 10.1212/WNL.0000000000010728
Abstract: To determine the extent to which deficits in learning over 6 days are associated with β-amyloid–positive (Aβ+) and hippoc al volume in cognitively normal (CN) adults. Eighty CN older adults who had undergone PET neuroimaging to determine Aβ status (n = 42 Aβ− and 38 Aβ+), MRI to determine hippoc al and ventricular volume, and repeated assessment of memory were recruited from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Participants completed the Online Repeatable Cognitive Assessment–Language Learning Test (ORCA-LLT), which required they learn associations between 50 Chinese characters and their English language equivalents over 6 days. ORCA-LLT assessments were supervised on the first day and were completed remotely online for all remaining days. Learning curves in the Aβ+ CN participants were significantly worse than those in matched Aβ− CN participants, with the magnitude of this difference very large ( d [95% confidence interval (CI)] 2.22 [1.64–2.75], p 0.001), and greater than differences between these groups for memory decline since their enrollment in AIBL ( d [95% CI] 0.52 [0.07–0.96], p = 0.021), or memory impairment at their most recent visit. In Aβ+ CN adults, slower rates of learning were associated with smaller hippoc al and larger ventricular volumes. These results suggest that in CN participants, Aβ+ is associated more strongly with a deficit in learning than any aspect of memory dysfunction. Slower rates of learning in Aβ+ CN participants were associated with hippoc al volume loss. Considered together, these data suggest that the primary cognitive consequence of Aβ+ is a failure to benefit from experience when exposed to novel stimuli, even over very short periods.
Publisher: Elsevier BV
Date: 08-2007
DOI: 10.1016/J.MEDIA.2007.03.003
Abstract: Magnetic resonance (MR) imaging is a widely available and well accepted non invasive imaging technique. Development of automatic and semi-automatic techniques to analyse MR images has been the focus of much research and numerous publications. However, most of this research only uses the magnitude of the acquired complex MR signal, discarding the phase information. In MR, the phase relates to the magnetic properties of tissues, information which is not found in the magnitude signal. As a result, phase is a complement to the magnitude signal and can improve the segmentation and analysis of MR images. In this paper, we consider the automatic classification of textured tissues in 3D MRI. Specifically, we include features extracted from the phase of the MR signal to improve texture discrimination in the bone segmentation. Our approach does not require phase unwrapping, with the MR signal processed in its complex form. The extra information extracted from the phase provides better segmentation, compared to only using magnitude features. The segmentation approach is integrated within a novel multiscale scheme, designed to improve the speed of pixel based classification algorithms, such as support vector machines. An order of magnitude increase is obtained, by reducing the number of pixels that need to be classified.
Publisher: Wiley
Date: 17-05-2011
DOI: 10.1002/JMRI.22188
Abstract: To compare automated segmentation of the quadratus lumborum (QL) based on statistical shape modeling (SSM) with conventional manual processing of magnetic resonance (MR) images for segmentation of this paraspinal muscle. The automated SSM scheme for QL segmentation was developed using an MR database of 7 mm axial images of the lumbar region from 20 subjects (cricket fast bowlers and athletic controls). Specifically, a hierarchical 3D-SSM scheme for segmentation of the QL, and surrounding psoas major (PS) and erector spinae+multifidus (ES+MT) musculature, was implemented after image preprocessing (bias field correction, partial volume interpolation) followed by image registration procedures to develop average and probabilistic MR atlases for initializing and constraining the SSM segmentation of the QL. The automated and manual QL segmentations were compared using spatial overlap and average surface distance metrics. The spatial overlap between the automated SSM and manual segmentations had a median Dice similarity metric of 0.87 (mean = 0.86, SD = 0.08) and mean average surface distance of 1.26 mm (SD = 0.61) and 1.32 mm (SD = 0.60) for the right and left QL muscles, respectively. The current SSM scheme represents a promising approach for future automated morphometric analyses of the QL and other paraspinal muscles from MR images.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2014
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 04-2016
DOI: 10.1016/J.NEUROIMAGE.2016.01.056
Abstract: Identifying diffuse axonal injury (DAI) in patients with traumatic brain injury (TBI) presenting with normal appearing radiological MRI presents a significant challenge. Neuroimaging methods such as diffusion MRI and probabilistic tractography, which probe the connectivity of neural networks, show significant promise. We present a machine learning approach to classify TBI participants primarily with mild traumatic brain injury (mTBI) based on altered structural connectivity patterns derived through the network based statistical analysis of structural connectomes generated from TBI and age-matched control groups. In this approach, higher order diffusion models were used to map white matter connections between 116 cortical and subcortical regions. Tracts between these regions were generated using probabilistic tracking and mean fractional anisotropy (FA) measures along these connections were encoded in the connectivity matrices. Network-based statistical analysis of the connectivity matrices was performed to identify the network differences between a representative subset of the two groups. The affected network connections provided the feature vectors for principal component analysis and subsequent classification by random forest. The validity of the approach was tested using data acquired from a total of 179 TBI patients and 146 controls participants. The analysis revealed altered connectivity within a number of intra- and inter-hemispheric white matter pathways associated with DAI, in consensus with existing literature. A mean classification accuracy of 68.16%±1.81% and mean sensitivity of 80.0%±2.36% were achieved in correctly classifying the TBI patients evaluated on the subset of the participants that was not used for the statistical analysis, in a 10-fold cross-validation framework. These results highlight the potential for statistical machine learning approaches applied to structural connectomes to identify patients with diffusive axonal injury.
Publisher: Cold Spring Harbor Laboratory
Date: 21-12-2021
DOI: 10.1101/2021.12.18.473283
Abstract: The Fluid And White matter Suppression (FLAWS) MRI sequence allows for the acquisition of multiple T1-weighted contrasts in a single sequence acquisition. However, its acquisition time is prohibitive for use in clinical practice when the k-space is linearly downs led and reconstructed using the Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) technique. This study proposes a FLAWS sequence optimization tailored to allow for the acquisition of FLAWS images with a Cartesian phyllotaxis k-space unders ling and compressed sensing (CS) reconstruction at 3T. The CS FLAWS sequence parameters were determined using a method previously employed to optimize FLAWS imaging at 1.5T and 7T. In-vivo experiments show that the proposed CS FLAWS optimization allows to reduce the FLAWS sequence acquisition time from 8 mins to 6 mins without decreasing the FLAWS image quality. In addition, this study demonstrates for the first time that T1-weighted imaging with low B1 sensitivity and T1 mapping can be performed with the FLAWS sequence at 3T for both GRAPPA and CS reconstructions. The FLAWS T1 mapping was validated using in-silico, in-vitro and in-vivo experiments with comparison against the inversion recovery turbo spin echo and MP2RAGE T1 mappings. These new results suggest that the recent advances in FLAWS imaging allow to combine the MP2RAGE imaging benefits (T1-weigthed imaging with low B1 sensitivity and T1 mapping) and with the previous version of FLAWS imaging benefits (multi T1-weighted contrast imaging) in a single 6 mins sequence acquisition.
Publisher: American Society of Neuroradiology (ASNR)
Date: 18-05-2017
DOI: 10.3174/AJNR.A5191
Publisher: IOP Publishing
Date: 27-09-2013
DOI: 10.1088/0031-9155/58/20/7375
Abstract: Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.
Publisher: Springer Science and Business Media LLC
Date: 21-04-2022
DOI: 10.1007/S11357-022-00558-8
Abstract: The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippoc al volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippoc al volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippoc al volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive in iduals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippoc al volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.
Publisher: Informa UK Limited
Date: 08-08-2023
Publisher: Wiley
Date: 06-04-2016
DOI: 10.1118/1.4944871
Abstract: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering "similar" gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework) similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.
Publisher: Springer International Publishing
Date: 2018
Publisher: Elsevier BV
Date: 11-2019
DOI: 10.1016/J.NEUROIMAGE.2019.116018
Abstract: The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently h ered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.
Publisher: Wiley
Date: 02-10-2023
DOI: 10.1002/ACR.25245
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 10-2021
Publisher: American Psychological Association (APA)
Date: 11-2020
DOI: 10.1037/NEU0000690
Publisher: Elsevier BV
Date: 12-2015
DOI: 10.1016/J.COMPMEDIMAG.2015.05.002
Abstract: Many medical image processing techniques rely on accurate shape modeling of anatomical features. The presence of shape abnormalities challenges traditional processing algorithms based on strong morphological priors. In this work, a sparse shape reconstruction from a statistical shape model is presented. It combines the advantages of traditional statistical shape models (defining a 'normal' shape space) and previously presented sparse shape composition (providing localized descriptors of anomalies). The algorithm was incorporated into our image segmentation and classification software. Evaluation was performed on simulated and clinical MRI data from 22 sciatica patients with intervertebral disc herniation, containing 35 herniated and 97 normal discs. Moderate to high correlation (R=0.73) was achieved between simulated and detected herniations. The sparse reconstruction provided novel quantitative features describing the herniation morphology and MRI signal appearance in three dimensions (3D). The proposed descriptors of local disc morphology resulted to the 3D segmentation accuracy of 1.07±1.00mm (mean absolute vertex-to-vertex mesh distance over the posterior disc region), and improved the intervertebral disc classification from 0.888 to 0.931 (area under receiver operating curve). The results show that the sparse shape reconstruction may improve computer-aided diagnosis of pathological conditions presenting local morphological alterations, as seen in intervertebral disc herniation.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2019
Publisher: Cold Spring Harbor Laboratory
Date: 19-02-2022
DOI: 10.1101/2022.02.16.22271024
Abstract: We evaluated a new Simoa plasma assay for phosphorylated tau at aa217 enhanced by additional ptau sites (p217+tau). Plasma p217+tau levels were compared to 18 F-NAV4694 amyloid-beta (Aβ) PET and 18 F-MK6240 tau PET in 174 cognitively impaired (CI) and 223 cognitively unimpaired (CU) participants. Compared to Aβ-CU, the plasma levels of p217+tau increased two-fold in Aβ+ CU and 3.5-fold in Aβ+ CI. In Aβ-the p217+tau levels did not significantly differ between CU, MCI or dementia. P217+tau correlated with Aβ centiloids ρ=0.67 (CI 0.64 CU 0.45) and tau SUVR MT ρ=0.63 (CI 0.69 CU 0.34). Area under curve (AUC) for AD vs Aβ-CU was 0.94, for AD vs other dementia was 0.93, for Aβ+ vs Aβ– PET was 0.89 and for tau+ vs tau-PET was 0.89. Plasma p217+tau levels elevate early in the AD continuum and correlate well with Aβ and tau PET. Systematic review: The authors reviewed the literature using PubMed, meeting abstracts and presentations. Plasma phospho-tau measures compare well to PET and post-mortem across the continuum of AD but accuracy varies across ptau target sites and assay methods. There are no reports comparing PET to plasma assays targeting multiple sites of tau phosphorylation as typically found in AD. The p217+tau assay targets p217 with binding enhanced by phosphorylation at additional sites such as aa212. Interpretation: Plasma p217+tau elevates early and correlates with both Aβ and tau as measured by PET indicating that tau phosphorylation is an early event in AD and occurs with Aβ deposition. Plasma p217+tau measurement should assist both selection for trials and diagnosis of AD. Future directions: Further validation studies, head-to-head comparison to other assays, assessing the influence of co-morbidities and the ability to measure change in brain Aβ and tau levels are required.
Publisher: Wiley
Date: 30-08-2018
DOI: 10.1016/J.IJDEVNEU.2018.08.010
Abstract: Autism Spectrum Disorder (ASD) affects approximately 1% of the population and leads to impairments in social interaction, communication and restricted, repetitive behaviours. Establishing robust neuroimaging biomarkers of ASD using structural magnetic resonance imaging (MRI) is an important step for diagnosing and tailoring treatment, particularly early in life when interventions can have the greatest effect. However currently, there is mixed findings on the structural brain changes associated with autism. Therefore in this systematic review, recent (post-2007), high-resolution (3 T) MRI studies investigating brain morphology associated with ASD have been collated to identify robust neuroimaging biomarkers of ASD. A systematic search was conducted on three databases PubMed, Web of Science and Scopus, resulting in 123 reviewed articles. Patients with ASD were observed to have increased whole brain volume, particularly under 6 years of age. Other consistent changes observed in ASD patients include increased volume in the frontal and temporal lobes, increased cortical thickness in the frontal lobe, increased surface area and cortical gyrification, and increased cerebrospinal fluid volume, as well as reduced cerebellum volume and reduced corpus callosum volume, compared to typically developing controls. Findings were inconsistent regarding the developmental trajectory of brain volume and cortical thinning with age in ASD, as well as potential volume differences in the white matter, hippoc us, amygdala, thalamus and basal ganglia. To elucidate these inconsistencies, future studies should look towards aggregating MRI data from multiple sites or available repositories to avoid underpowered studies, as well as utilising methods which quantify larger-scale image features to reduce the number of statistical tests performed, and hence risk of false positive findings. Additionally, studies should look to perform a thorough validation strategy, to ensure generalisability of study findings, as well as look to leverage the improved image resolution of 3 T scanning to identify subtle brain changes related to ASD.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2020
Publisher: Wiley
Date: 25-09-2021
DOI: 10.1002/JMRI.27908
Abstract: In the medical imaging domain, deep learning‐based methods have yet to see widespread clinical adoption, in part due to limited generalization performance across different imaging devices and acquisition protocols. The deviation between estimated brain age and biological age is an established biomarker of brain health and such models may benefit from increased cross‐site generalizability. To develop and evaluate a deep learning‐based image harmonization method to improve cross‐site generalizability of deep learning age prediction. Retrospective. Eight thousand eight hundred and seventy‐six subjects from six sites. Harmonization models were trained using all subjects. Age prediction models were trained using 2739 subjects from a single site and tested using the remaining 6137 subjects from various other sites. Brain imaging with magnetization prepared rapid acquisition with gradient echo or spoiled gradient echo sequences at 1.5 T and 3 T. StarGAN v2, was used to perform a canonical mapping from erse datasets to a reference domain to reduce site‐based variation while preserving semantic information. Generalization performance of deep learning age prediction was evaluated using harmonized, histogram matched, and unharmonized data. Mean absolute error (MAE) and Pearson correlation between estimated age and biological age quantified the performance of the age prediction model. Our results indicated a substantial improvement in age prediction in out‐of‐s le data, with the overall MAE improving from 15.81 (±0.21) years to 11.86 (±0.11) with histogram matching to 7.21 (±0.22) years with generative adversarial network (GAN)‐based harmonization. In the multisite case, across the 5 out‐of‐s le sites, MAE improved from 9.78 (±6.69) years to 7.74 (±3.03) years with histogram normalization to 5.32 (±4.07) years with GAN‐based harmonization. While further research is needed, GAN‐based medical image harmonization appears to be a promising tool for improving cross‐site deep learning generalization. 4 Stage 1
Publisher: IOP Publishing
Date: 22-01-2015
DOI: 10.1088/0031-9155/60/4/1441
Abstract: We present a statistical shape model approach for automated segmentation of the proximal humerus and scapula with subsequent bone-cartilage interface (BCI) extraction from 3D magnetic resonance (MR) images of the shoulder region. Manual and automated bone segmentations from shoulder MR examinations from 25 healthy subjects acquired using steady-state free precession sequences were compared with the Dice similarity coefficient (DSC). The mean DSC scores between the manual and automated segmentations of the humerus and scapula bone volumes surrounding the BCI region were 0.926 ± 0.050 and 0.837 ± 0.059, respectively. The mean DSC values obtained for BCI extraction were 0.806 ± 0.133 for the humerus and 0.795 ± 0.117 for the scapula. The current model-based approach successfully provided automated bone segmentation and BCI extraction from MR images of the shoulder. In future work, this framework appears to provide a promising avenue for automated segmentation and quantitative analysis of cartilage in the glenohumeral joint.
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 09-2014
DOI: 10.1016/J.NEUROIMAGE.2014.04.056
Abstract: Understanding structure-function relationships in the brain after stroke is reliant not only on the accurate anatomical delineation of the focal ischemic lesion, but also on previous infarcts, remote changes and the presence of white matter hyperintensities. The robust definition of primary stroke boundaries and secondary brain lesions will have significant impact on investigation of brain-behavior relationships and lesion volume correlations with clinical measures after stroke. Here we present an automated approach to identify chronic ischemic infarcts in addition to other white matter pathologies, that may be used to aid the development of post-stroke management strategies. Our approach uses Bayesian-Markov Random Field (MRF) classification to segment probable lesion volumes present on fluid attenuated inversion recovery (FLAIR) MRI. Thereafter, a random forest classification of the information from multimodal (T1-weighted, T2-weighted, FLAIR, and apparent diffusion coefficient (ADC)) MRI images and other context-aware features (within the probable lesion areas) was used to extract areas with high likelihood of being classified as lesions. The final segmentation of the lesion was obtained by thresholding the random forest probabilistic maps. The accuracy of the automated lesion delineation method was assessed in a total of 36 patients (24 male, 12 female, mean age: 64.57±14.23yrs) at 3months after stroke onset and compared with manually segmented lesion volumes by an expert. Accuracy assessment of the automated lesion identification method was performed using the commonly used evaluation metrics. The mean sensitivity of segmentation was measured to be 0.53±0.13 with a mean positive predictive value of 0.75±0.18. The mean lesion volume difference was observed to be 32.32%±21.643% with a high Pearson's correlation of r=0.76 (p<0.0001). The lesion overlap accuracy was measured in terms of Dice similarity coefficient with a mean of 0.60±0.12, while the contour accuracy was observed with a mean surface distance of 3.06mm±3.17mm. The results signify that our method was successful in identifying most of the lesion areas in FLAIR with a low false positive rate.
Publisher: Wiley
Date: 14-05-2019
DOI: 10.1016/J.JALZ.2019.02.005
Abstract: Data from eighty-eight subjects (52 male subjects, aged 79.8 ± 10.6 years) who underwent antemortem Against combined Bielschowsky silver staining and immunohistochemistry histopathological scores, statistical parametric mapping had 96% sensitivity, 96% specificity, and 95% accuracy, whereas magnetic resonance-less CapAIBL standardized uptake value ratio Quantification of
Publisher: Wiley
Date: 15-08-2020
DOI: 10.1002/MP.14421
Publisher: Wiley
Date: 25-01-2022
DOI: 10.1002/ALZ.12538
Abstract: The apolipoprotein E ( APOE ) genotype is the strongest genetic risk factor for late‐onset Alzheimer's disease. However, its effect on lipid metabolic pathways, and their mediating effect on disease risk, is poorly understood. We performed lipidomic analysis on three independent cohorts (the Australian Imaging, Biomarkers and Lifestyle [AIBL] flagship study, n = 1087 the Alzheimer's Disease Neuroimaging Initiative [ADNI] 1 study, n = 819 and the Busselton Health Study [BHS], n = 4384), and we defined associations between APOE ε2 and ε4 and 569 plasma/serum lipid species. Mediation analysis defined the proportion of the treatment effect of the APOE genotype mediated by plasma/serum lipid species. A total of 237 and 104 lipid species were associated with APOE ε2 and ε4, respectively. Of these 68 (ε2) and 24 (ε4) were associated with prevalent Alzheimer's disease. In idual lipid species or lipidomic models of APOE genotypes mediated up to 30% and 10% of APOE ε2 and ε4 treatment effect, respectively. Plasma lipid species mediate the treatment effect of APOE genotypes on Alzheimer's disease and as such represent a potential therapeutic target.
Publisher: American Association for Cancer Research (AACR)
Date: 03-04-2023
DOI: 10.1158/2159-8290.22540513
Abstract: Supplementary Figure 7
Publisher: Cold Spring Harbor Laboratory
Date: 15-02-2022
DOI: 10.1101/2022.02.13.22270894
Abstract: Tau deposition plays a critical role over cognition and neurodegeneration in Alzheimer’s disease (AD). Recent generation tracers have high target to background ratios giving a wide dynamic range that may improve sensitivity for detection of low levels of tau (Pascoal, Shin et al. 2018). Building on previous evidence, this study aims to characterize the effects of tau deposition as assessed by 18 F-MK6240, in a large cohort of patients across the AD disease spectrum. A total of 464 participants, enrolled in the AIBL-ADNeT study, underwent 18 F-MK6240 tau PET, 18 F-NAV4964 Aβ PET, 3D structural MRI (hippoc al and whole-brain cortical volumes) and extensive neuropsychological evaluation. Participants included 266 cognitively unimpaired controls (CU), 112 patients with mild cognitive impairment (MCI), and 86 patients with probable AD dementia. Evaluation included the characterization of the pattern and degree of 18 F-MK6240 tracer retention in each clinical group as well as assessment of the relationship between 18 F-MK6240 and age, Aβ imaging, brain volumetrics and cognition in each of the clinical groups. Standard uptake value ratios (SUVR) were estimated in four predefined composite regions of interest (ROIs), reflecting the stereotypical progression of tau pathology in the brain: 1. Mesial-temporal (Me), 2. Temporoparietal (Te), 3. Remainder of neocortex (R), 4. A temporal meta-region termed metaT+. 18 F-MK6240 retention was higher in AD patients compared with all other diagnostic groups, with 18 F-MK6240 distinguishing patients with AD from CU in iduals, with the highest effect size obtained in the amygdala (Cohen’s d : 2.07), and Me (Cohen’s d : 1.99). When considering Aβ status, 18 F-MK6240 not only was able to distinguish between Aβ+ AD patients and Aβ- CU (Cohen’s d : 2.23), but also between Aβ+ and Aβ- CU (Cohen’s d : 1.32). In Aβ- CU, 18 F-MK6240 retention in Me showed a slow age-related increase, while 18 F-MK6240 retention was higher in younger elderly Aβ+ AD patients compared to their older counterparts. There was a sigmoidal relationship between subthreshold tau and Aβ, providing evidence for a very slow but steady increase in subthreshold tau prior to a fast increase in cortical Aβ. Moreover, a non-linear relationship between Aβ and tau suggest that detectable cortical Aβ precedes detectable cortical tau. While age was the main predictor of cognitive decline in CU, and Aβ and hippoc al volume in MCI, the main predictor of cognitive decline in the AD group was tau. High tau was associated with faster cognitive decline and clinical progression in the CU and MCI groups. This large study provides further evidence that 18 F-MK6240 discriminates CU from AD and, most importantly, Aβ+ from Aβ- CU in iduals with high effect sizes, suggesting that 18 F- MK6240 can detect lower tau levels than earlier tau tracers, crucial for early detection of tau deposition as well as tracking small tau changes over time. In conclusion, identification of regional cortical tau deposition has critical diagnostic and prognostic implications and should become a standard tool to identify in iduals at risk, as well as outcome measure, in both anti- Aβ and anti-tau trials.
Publisher: Oxford University Press (OUP)
Date: 2020
DOI: 10.1093/BRAINCOMMS/FCAA041
Abstract: Plasma amyloid-β peptide concentration has recently been shown to have high accuracy to predict amyloid-β plaque burden in the brain. These amyloid-β plasma markers will allow wider screening of the population and simplify and reduce screening costs for therapeutic trials in Alzheimer’s disease. The aim of this study was to determine how longitudinal changes in blood amyloid-β track with changes in brain amyloid-β. Australian Imaging, Biomarker and Lifestyle study participants with a minimum of two assessments were evaluated (111 cognitively normal, 7 mild cognitively impaired, 15 participants with Alzheimer’s disease). Amyloid-β burden in the brain was evaluated through PET and was expressed in Centiloids. Total protein amyloid-β 42/40 plasma ratios were determined using ABtest® assays. We applied our method for obtaining natural history trajectories from short term data to measures of total protein amyloid-β 42/40 plasma ratios and PET amyloid-β. The natural history trajectory of total protein amyloid-β 42/40 plasma ratios appears to approximately mirror that of PET amyloid-β, with both spanning decades. Rates of change of 7.9% and 8.8%, were observed for total protein amyloid-β 42/40 plasma ratios and PET amyloid-β, respectively. The trajectory of plasma amyloid-β preceded that of brain amyloid-β by a median value of 6 years (significant at 88% confidence interval). These findings, showing the tight association between changes in plasma and brain amyloid-β, support the use of plasma total protein amyloid-β 42/40 plasma ratios as a surrogate marker of brain amyloid-β. Also, that plasma total protein amyloid-β 42/40 plasma ratios has potential utility in monitoring trial participants, and as an outcome measure.
Publisher: Frontiers Media SA
Date: 19-11-2021
DOI: 10.3389/FNAGI.2021.744872
Abstract: Background: Worldwide, coffee is one of the most popular beverages consumed. Several studies have suggested a protective role of coffee, including reduced risk of Alzheimer’s disease (AD). However, there is limited longitudinal data from cohorts of older adults reporting associations of coffee intake with cognitive decline, in distinct domains, and investigating the neuropathological mechanisms underpinning any such associations. Methods: The aim of the current study was to investigate the relationship between self-reported habitual coffee intake, and cognitive decline assessed using a comprehensive neuropsychological battery in 227 cognitively normal older adults from the Australian Imaging, Biomarkers, and Lifestyle (AIBL) study, over 126 months. In a subset of in iduals, we also investigated the relationship between habitual coffee intake and cerebral Aβ-amyloid accumulation ( n = 60) and brain volumes ( n = 51) over 126 months. Results: Higher baseline coffee consumption was associated with slower cognitive decline in executive function, attention, and the AIBL Preclinical AD Cognitive Composite (PACC shown reliably to measure the first signs of cognitive decline in at-risk cognitively normal populations), and lower likelihood of transitioning to mild cognitive impairment or AD status, over 126 months. Higher baseline coffee consumption was also associated with slower Aβ-amyloid accumulation over 126 months, and lower risk of progressing to “moderate,” “high,” or “very high” Aβ-amyloid burden status over the same time-period. There were no associations between coffee intake and atrophy in total gray matter, white matter, or hippoc al volume. Discussion: Our results further support the hypothesis that coffee intake may be a protective factor against AD, with increased coffee consumption potentially reducing cognitive decline by slowing cerebral Aβ-amyloid accumulation, and thus attenuating the associated neurotoxicity from Aβ-amyloid-mediated oxidative stress and inflammatory processes. Further investigation is required to evaluate whether coffee intake could be incorporated as a modifiable lifestyle factor aimed at delaying AD onset.
Publisher: Elsevier BV
Date: 12-2015
DOI: 10.1016/J.IJROBP.2015.08.045
Abstract: To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [S ling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1w flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional γ pass rate was 1.00 ± 0.00 (2 mm/2%). The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.
Publisher: Cold Spring Harbor Laboratory
Date: 22-01-2022
DOI: 10.1101/2022.01.20.476706
Abstract: Deficits in memory are seen as a canonical sign of ageing and a prodrome to dementia in older adults. However, the nature of cognitive and brain changes across a wider aperture of adulthood is not well known. We quantify the relationship between cognitive function and brain morphology from mid-life to older adulthood, and the influence of age, sex, amyloid and genetic risk for dementia. We analyzed three observational cohorts (PISA, AIBL, ADNI) with cognitive, genetic and neuroimaging measures comprising a total of 1570 healthy mid-life and older adults (mean age 72, range 49-90 years, 1330 males) and 1365 age- and sex-matched adults with mild cognitive impairment or Alzheimer’s disease. Among healthy adults, we find robust modes of co-variation between regional sulcal width and multidomain cognitive function that change from mid-life to the older age range. The most prominent cortical changes in mid-life are predominantly associated with changes in executive functions, whereas they are most strongly associated with poorer memory function in older age. These cognitive changes are accompanied by an age-dependent pattern of sulcal widening. Amyloid exerts a weak, but significant, influence on cognition, but not on sulcal width. The APOE ɛ4 allele also exerts a weak influence on cognition, but only significantly in the (larger and older) AIBL cohort. These findings provide new insights into brain and cognition in mid-life and older adults, suggesting that cognitive screening in mid-life cohorts should encompass executive functions as well as memory.
Publisher: Springer Science and Business Media LLC
Date: 28-05-2019
Publisher: Elsevier BV
Date: 10-2017
DOI: 10.1016/J.ACRA.2017.03.025
Abstract: This study aimed to evaluate the accuracy of an automated method for segmentation and T2 mapping of the medial meniscus (MM) and lateral meniscus (LM) in clinical magnetic resonance images from patients with acute knee injury. Eighty patients scheduled for surgery of an anterior cruciate ligament or meniscal injury underwent magnetic resonance imaging of the knee (multiplanar two-dimensional [2D] turbo spin echo [TSE] or three-dimensional [3D]-TSE examinations, T2 mapping). Each meniscus was automatically segmented from the 2D-TSE (composite volume) or 3D-TSE images, auto-partitioned into anterior, mid, and posterior regions, and co-registered onto the T2 maps. The Dice similarity index (spatial overlap) was calculated between automated and manual segmentations of 2D-TSE (15 patients), 3D-TSE (16 patients), and corresponding T2 maps (31 patients). Pearson and intraclass correlation coefficients (ICC) were calculated between automated and manual T2 values. T2 values were compared (Wilcoxon rank sum tests) between torn and non-torn menisci for the subset of patients with both manual and automated segmentations to compare statistical outcomes of both methods. The Dice similarity index values for the 2D-TSE, 3D-TSE, and T2 map volumes, respectively, were 76.4%, 84.3%, and 75.2% for the MM and 76.4%, 85.1%, and 76.1% for the LM. There were strong correlations between automated and manual T2 values (r The present automated method offers a promising alternative to manual T2 mapping analyses of the menisci and a considerable advance for integration into clinical workflows.
Publisher: Society of Nuclear Medicine
Date: 27-01-2022
Publisher: Cold Spring Harbor Laboratory
Date: 05-04-2019
DOI: 10.1101/597856
Abstract: Participant movement can deleteriously affect MR image quality. Further, for the visualization and segmentation of small anatomical structures, there is a need to improve image quality, specifically signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), by acquiring multiple anatomical scans consecutively. We aimed to ameliorate movement artefacts and increase SNR in a high-resolution turbo spin-echo (TSE) sequence acquired thrice using non-linear realignment in order to improve segmentation consistency of the hippoc us subfields. We assessed the method in young healthy participants, Motor Neurone Disease patients, and age matched controls. Results show improved image segmentation of the hippoc us subfields when comparing template-based segmentations with in idual segmentations with Dice overlaps N=51 ps 0.001 (Friedman’s test) and higher sharpness ps 0.001 in non-linearly realigned scans as compared to linearly, and arithmetically averaged scans.
Publisher: Wiley
Date: 04-02-2018
DOI: 10.1002/MRM.27109
Publisher: Elsevier BV
Date: 06-2011
DOI: 10.1016/J.NEUROIMAGE.2011.02.014
Abstract: Registration of diffusion-weighted images is an important step in comparing white matter fibre bundles across subjects, or in the same subject at different time points. Using diffusion-weighted imaging, Spherical Deconvolution enables multiple fibre populations within a voxel to be resolved by computing the fibre orientation distribution (FOD). In this paper, we present a novel method that employs FODs for the registration of diffusion-weighted images. Registration was performed by optimising a symmetric diffeomorphic non-linear transformation model, using image metrics based on the mean squared difference, and cross-correlation of the FOD spherical harmonic coefficients. The proposed method was validated by recovering known displacement fields using FODs represented with maximum harmonic degrees (l(max)) of 2, 4 and 6. Results demonstrate a benefit in using FODs at l(max)=4 compared to l(max)=2. However, a decrease in registration accuracy was observed when l(max)=6 was used this was likely caused by noise in higher harmonic degrees. We compared our proposed method to fractional anisotropy driven registration using an identical code base and parameters. FOD registration was observed to perform significantly better than FA in all experiments. The cross-correlation metric performed significantly better than the mean squared difference. Finally, we demonstrated the utility of this method by computing an unbiased group average FOD template that was used for probabilistic fibre tractography. This work suggests that using crossing fibre information aids in the alignment of white matter and could therefore benefit several methods for investigating population differences in white matter, including voxel based analysis, tensor based morphometry, atlas based segmentation and labelling, and group average fibre tractography.
Publisher: SPIE
Date: 04-03-2010
DOI: 10.1117/12.844048
Publisher: Wiley
Date: 12-08-2019
Publisher: Springer Science and Business Media LLC
Date: 16-08-2021
DOI: 10.1186/S12891-021-04576-Z
Abstract: Arthroscopic surgery for femoroacetabular impingement syndrome (FAI) is known to lead to self-reported symptom improvement. In the context of surgical interventions with known contextual effects and no true sham comparator trials, it is important to ascertain outcomes that are less susceptible to placebo effects. The primary aim of this trial was to determine if study participants with FAI who have hip arthroscopy demonstrate greater improvements in delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC) index between baseline and 12 months, compared to participants who undergo physiotherapist-led management. Multi-centre, pragmatic, two-arm superiority randomised controlled trial comparing physiotherapist-led management to hip arthroscopy for FAI. FAI participants were recruited from participating orthopaedic surgeons clinics, and randomly allocated to receive either physiotherapist-led conservative care or surgery. The surgical intervention was arthroscopic FAI surgery. The physiotherapist-led conservative management was an in idualised physiotherapy program, named Personalised Hip Therapy (PHT). The primary outcome measure was change in dGEMRIC score between baseline and 12 months. Secondary outcomes included a range of patient-reported outcomes and structural measures relevant to FAI pathoanatomy and hip osteoarthritis development. Interventions were compared by intention-to-treat analysis. Ninety-nine participants were recruited, of mean age 33 years and 58% male. Primary outcome data were available for 53 participants (27 in surgical group, 26 in PHT). The adjusted group difference in change at 12 months in dGEMRIC was -59 ms (95%CI − 137.9 to - 19.6) ( p = 0.14) favouring PHT. Hip-related quality of life (iHOT-33) showed improvements in both groups with the adjusted between-group difference at 12 months showing a statistically and clinically important improvement in arthroscopy of 14 units (95% CI 5.6 to 23.9) ( p = 0.003). The primary outcome of dGEMRIC showed no statistically significant difference between PHT and arthroscopic hip surgery at 12 months of follow-up. Patients treated with surgery reported greater benefits in symptoms at 12 months compared to PHT, but these benefits are not explained by better hip cartilage metabolism. Australia New Zealand Clinical Trials Registry reference: ACTRN12615001177549 . Trial registered 2/11/2015.
Publisher: Wiley
Date: 30-01-2020
DOI: 10.1002/HBM.24939
Publisher: Wiley
Date: 2021
DOI: 10.1002/DAD2.12136
Abstract: In cognitively normal (CN) adults, increased rates of amyloid beta (Aβ) accumulation can be detected in low Aβ (Aβ–) apolipoprotein E ( APOE ) ε4 carriers. We aimed to determine the effect of ε4 on the ability to benefit from experience (ie, learn) in Aβ– CNs. Aβ– CNs (n = 333) underwent episodic memory assessments every 18 months for 108 months. A subset (n = 48) completed the Online Repeatable Cognitive Assessment‐Language Learning Test (ORCA‐LLT) over 6 days. Aβ– ε4 carriers showed significantly lower rates of improvement on episodic memory over 108 months compared to non‐carriers (d = 0.3). Rates of learning on the ORCA‐LLT were significantly slower in Aβ– ε4 carriers compared to non‐carriers (d = 1.2). In Aβ– CNs, ε4 is associated with a reduced ability to benefit from experience. This manifested as reduced practice effects (small to moderate in magnitude) over 108 months on the episodic memory composite, and a learning deficit (large in magnitude) over 6 days on the ORCA‐LLT. Alzheimer's disease (AD)–related cognitive abnormalities can manifest before preclinical AD thresholds.
Publisher: Elsevier BV
Date: 12-2018
DOI: 10.1016/J.NEUROIMAGE.2018.08.044
Abstract: The centiloid scale was recently proposed to provide a standard framework for the quantification of β-amyloid PET images, so that amyloid burden can be expressed on a standard scale. While the framework prescribes SPM8 as the standard analysis method for PET quantification, non-standard methods can be calibrated to produce centiloid values. We have previously developed a PET-only quantification: CapAIBL. In this study, we show how CapAIBL can be calibrated to the centiloid scale. Calibration images for Using the calibration images, there was a very strong agreement, and very little bias between the centiloid values computed using CapAIBL and those computed using the standard method with R The PET-only quantification method, CapAIBL, can produce reliable centiloid values. The bias observed in the AIBL dataset for 18F-NAV4694 and
Publisher: American Society of Neuroradiology (ASNR)
Date: 19-08-2021
DOI: 10.3174/AJNR.A7230
Publisher: Cold Spring Harbor Laboratory
Date: 13-03-2022
DOI: 10.1101/2022.03.11.22272240
Abstract: Background Tau PET imaging enables prospective longitudinal observation of the rate and location of tau accumulation in Alzheimer's disease (AD). 18 F-MK6240 is a newer, high affinity tracer for the paired helical filaments of tau in AD. It is widely used in clinical trials, despite sparse longitudinal natural history data. We aimed to evaluate the impact of disease stage, and two reference regions on the magnitude and effect size of regional change. Methods One hundred and fifty-eight participants: 83 cognitively unimpaired (CU) Aβ-, 37 CU Aβ+, 19 mild cognitively impaired (MCI) Aβ+ and 19 AD Aβ+ had annual 18 F-MK6240 PET for one or two years (mean 1.6 years). Standardized uptake value ratios (SUVR) were generated for three in-house composite ROI: mesial temporal (Me), temporoparietal (Te), and rest of neocortex (R), and a Free-Surfer derived meta-temporal (MT) ROI. Two reference regions were examined: cerebellar cortex (SUVR Cb ) and eroded subcortical white matter (SUVR WM ). Results Low rates of accumulation were seen in CU Aβ-, predominantly in the mesial temporal lobe (MTL). In CU Aβ+, increase was greatest in the MTL, particularly the amygdala. In MCI Aβ+, a similar increase was seen in MTL, but also globally in the cortex. In AD Aβ+, greatest increase was in temporoparietal and frontal regions, with a decrease in the MTL. In CU and MCI increases were greater using SUVR WM . In AD, the SUVR Cb showed marginally greater increase. Interpolation of the data suggests it takes approximately two decades to accumulate tau to the typical levels found in AD, similar to the rates of accumulation of Aβ plaques. Conclusions The rate of tau accumulation varies according to brain region and baseline disease stage, confirming previous reports. The PET measured change is greater, with fewer outliers, using an eroded white matter reference region, except in AD. While the eroded subcortical white matter reference may be preferred for trials in preclinical AD, the cerebellar cortex would be preferred for trials in symptomatic AD.
Publisher: Springer Science and Business Media LLC
Date: 16-09-2015
Publisher: Springer Science and Business Media LLC
Date: 26-01-2021
DOI: 10.1007/S00259-021-05191-9
Abstract: Previous studies have shown that Aβ-amyloid (Aβ) likely promotes tau to spread beyond the medial temporal lobe. However, the Aβ levels necessary for tau to spread in the neocortex is still unclear. Four hundred sixty-six participants underwent tau imaging with [18F]MK6420 and Aβ imaging with [ 18 F]NAV4694. Aβ scans were quantified on the Centiloid (CL) scale with a cut-off of 25 CL for abnormal levels of Aβ (A+). Tau scans were quantified in three regions of interest (ROI) (mesial temporal (Me) temporoparietal neocortex (Te) and rest of neocortex (R)) and four mesial temporal region (entorhinal cortex, amygdala, hippoc us, and parahippoc us). Regional tau thresholds were established as the 95%ile of the cognitively unimpaired A- subjects. The prevalence of abnormal tau levels (T+) along the Centiloid continuum was determined. The plots of prevalence of T+ show earlier and greater increase along the Centiloid continuum in the medial temporal area compared to neocortex. Prevalence of T+ was low but associated with Aβ level between 10 and 40 CL reaching 23% in Me, 15% in Te, and 11% in R. Between 40 and 70 CL, the prevalence of T+ subjects per CL increased fourfold faster and at 70 CL was 64% in Me, 51% in Te, and 37% in R. In cognitively unimpaired, there were no T+ in R below 50 CL. The highest prevalence of T+ were found in the entorhinal cortex, reaching 40% at 40 CL and 80% at 60 CL. Outside the entorhinal cortex, abnormal levels of cortical tau on PET are rarely found with Aβ below 40 CL. Above 40 CL prevalence of T+ accelerates in all areas. Moderate Aβ levels are required before abnormal neocortical tau becomes detectable.
Publisher: IEEE
Date: 08-2016
Publisher: American Society of Neuroradiology (ASNR)
Date: 19-10-2018
DOI: 10.3174/AJNR.A5448
Publisher: American College of Physicians
Date: 12-2020
DOI: 10.7326/M20-0990
Publisher: Wiley
Date: 23-03-2016
DOI: 10.1002/HBM.23177
Publisher: Elsevier BV
Date: 2017
DOI: 10.1016/J.MEDIA.2016.08.005
Abstract: The evaluation of changes in Intervertebral Discs (IVDs) with 3D Magnetic Resonance (MR) Imaging (MRI) can be of interest for many clinical applications. This paper presents the evaluation of both IVD localization and IVD segmentation methods submitted to the Automatic 3D MRI IVD Localization and Segmentation challenge, held at the 2015 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2015) with an on-site competition. With the construction of a manually annotated reference data set composed of 25 3D T2-weighted MR images acquired from two different studies and the establishment of a standard validation framework, quantitative evaluation was performed to compare the results of methods submitted to the challenge. Experimental results show that overall the best localization method achieves a mean localization distance of 0.8 mm and the best segmentation method achieves a mean Dice of 91.8%, a mean average absolute distance of 1.1 mm and a mean Hausdorff distance of 4.3 mm, respectively. The strengths and drawbacks of each method are discussed, which provides insights into the performance of different IVD localization and segmentation methods.
Publisher: Elsevier BV
Date: 11-2018
DOI: 10.1016/J.COMPMEDIMAG.2018.05.001
Abstract: Accurate quantification of white matter hyperintensities (WMH) from Magnetic Resonance Imaging (MRI) is a valuable tool for the analysis of normal brain ageing or neurodegeneration. Reliable automatic extraction of WMH lesions is challenging due to their heterogeneous spatial occurrence, their small size and their diffuse nature. In this paper, we present an automatic method to segment these lesions based on an ensemble of overcomplete patch-based neural networks. The proposed method successfully provides accurate and regular segmentations due to its overcomplete nature while minimizing the segmentation error by using a boosted ensemble of neural networks. The proposed method compared favourably to state of the art techniques using two different neurodegenerative datasets.
Start Date: 11-2010
End Date: 11-2013
Amount: $540,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 05-2023
End Date: 05-2028
Amount: $4,583,816.00
Funder: Australian Research Council
View Funded ActivityStart Date: 06-2020
End Date: 05-2024
Amount: $396,000.00
Funder: Australian Research Council
View Funded Activity