ORCID Profile
0000-0002-4745-3635
Current Organisation
University of Nottingham School of Medicine
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Publisher: Wiley
Date: 08-08-2017
DOI: 10.1002/MRM.26837
Abstract: 3T magnetic resonance scanners have boosted clinical application of 1 H‐MR spectroscopy (MRS) by offering an improved signal‐to‐noise ratio and increased spectral resolution, thereby identifying more metabolites and extending the range of metabolic information. Spectroscopic data from clinical 1.5T MR scanners has been shown to discriminate between pediatric brain tumors by applying machine learning techniques to further aid diagnosis. The purpose of this multi‐center study was to investigate the discriminative potential of metabolite profiles obtained from 3T scanners in classifying pediatric brain tumors. A total of 41 pediatric patients with brain tumors (17 medulloblastomas, 20 pilocytic astrocytomas, and 4 ependymomas) were scanned across four different hospitals. Raw spectroscopy data were processed using TARQUIN. Borderline synthetic minority overs ling technique was used to correct for the data skewness. Different classifiers were trained using linear discriminative analysis, support vector machine, and random forest techniques. Support vector machine had the highest balanced accuracy for discriminating the three tumor types. The balanced accuracy achieved was higher than the balanced accuracy previously reported for similar multi‐center dataset from 1.5T magnets with echo time 20 to 32 ms alone. This study showed that 3T MRS can detect key differences in metabolite profiles for the main types of childhood tumors. Magn Reson Med 79:2359–2366, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Publisher: JMIR Publications Inc.
Date: 20-01-2022
DOI: 10.2196/31925
Abstract: Depression is a substantial health and economic burden. In approximately one-third of patients, depression is resistant to first-line treatment therefore, it is essential to find alternative treatments. Transcranial magnetic stimulation (TMS) is a neuromodulatory treatment involving the application of magnetic pulses to the brain that is approved in the United Kingdom and the United States in treatment-resistant depression. This trial aims to compare the clinical effectiveness, cost-effectiveness, and mechanism of action of standard treatment repetitive TMS (rTMS) targeted at the F3 electroencephalogram site with a newer treatment—a type of TMS called theta burst stimulation (TBS) targeted based on measures of functional brain connectivity. This protocol outlines brain imaging acquisition and analysis for the Brain Imaging Guided Transcranial Magnetic Stimulation in Depression (BRIGhTMIND) study trial that is used to create personalized TMS targets and answer the proposed mechanistic hypotheses. The aims of the imaging arm of the BRIGhTMIND study are to identify functional and neurochemical brain signatures indexing the treatment mechanisms of rTMS and connectivity-guided intermittent theta burst TMS and to identify imaging-based markers predicting response to treatment. The study is a randomized double-blind controlled trial with 1:1 allocation to either 20 sessions of TBS or standard rTMS. Multimodal magnetic resonance imaging (MRI) is acquired for each participant at baseline (before TMS treatment) with T1-weighted and task-free functional MRI during rest used to estimate TMS targets. For participants enrolled in the mechanistic substudy, additional diffusion-weighted sequences are acquired at baseline and at posttreatment follow-up 16 weeks after treatment randomization. Core data sets of T1-weighted and task-free functional MRI during rest are acquired for all participants and are used to estimate TMS targets. Additional sequences of arterial spin labeling, magnetic resonance spectroscopy, and diffusion-weighted images are acquired depending on the recruitment site for mechanistic evaluation. Standard rTMS treatment is targeted at the F3 electrode site over the left dorsolateral prefrontal cortex, whereas TBS treatment is guided using the coordinate of peak effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. Both treatment targets benefit from the level of MRI guidance, but only TBS is provided with precision targeting based on functional brain connectivity. Recruitment began in January 2019 and is ongoing. Data collection is expected to continue until January 2023. This trial will determine the impact of precision MRI guidance on rTMS treatment and assess the neural mechanisms underlying this treatment in treatment-resistant depressed patients. ISRCTN Registry ISRCTN19674644 www.isrctn.com/ISRCTN19674644 DERR1-10.2196/31925
Publisher: American Medical Association (AMA)
Date: 09-2020
Publisher: Springer Science and Business Media LLC
Date: 23-09-2021
DOI: 10.1038/S41598-021-96189-8
Abstract: Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of in idual tumor types. 69 children with biopsy-confirmed brain tumors were recruited into this study. All participants had perfusion and diffusion weighted imaging performed at diagnosis. Imaging data were processed using conventional methods, and a Bayesian survival analysis performed. Unsupervised and supervised machine learning were performed with the survival features, to determine novel sub-groups related to survival. Sub-group analysis was undertaken to understand differences in imaging features. Survival analysis showed that a combination of diffusion and perfusion imaging were able to determine two novel sub-groups of brain tumors with different survival characteristics (p 0.01), which were subsequently classified with high accuracy (98%) by a neural network. Analysis of high-grade tumors showed a marked difference in survival (p = 0.029) between the two clusters with high risk and low risk imaging features. This study has developed a novel model of survival for pediatric brain tumors. Tumor perfusion plays a key role in determining survival and should be considered as a high priority for future imaging protocols.
Publisher: Elsevier BV
Date: 10-2003
Publisher: Cold Spring Harbor Laboratory
Date: 23-09-2021
DOI: 10.1101/2021.09.21.21263298
Abstract: Cerebral microbleeds (CMBs) appear as small, circular, well defined hypointense lesions of a few mm in size on T2*-weighted gradient recalled echo (T2*-GRE) images and appear enhanced on susceptibility weighted images (SWI). Due to their small size, contrast variations and other mimics (e.g. blood vessels), CMBs are highly challenging to detect automatically. In large datasets (e.g. the UK Biobank dataset), exhaustively labelling CMBs manually is difficult and time consuming. Hence it would be useful to preselect candidate CMB subjects in order to focus on those for manual labelling, which is essential for training and testing automated CMB detection tools on these datasets. In this work, we aim to detect CMB candidate subjects from a larger dataset, UK Biobank, using a machine learning-based, computationally light pipeline. For our evaluation, we used 3 different datasets, with different intensity characteristics, acquired with different scanners. They include the UK Biobank dataset and two clinical datasets with different pathological conditions. We developed and evaluated our pipelines on different types of images, consisting of SWI or GRE images. We also used the UK Biobank dataset to compare our approach with alternative CMB preselection methods using non-imaging factors and/or imaging data. Finally, we evaluated the pipeline’s generalisability across datasets. Our method provided subject-level detection accuracy 80% on all the datasets (withindataset results), and showed good generalisability across datasets, providing a consistent accuracy of over 80%, even when evaluated across different modalities.
Publisher: Mary Ann Liebert Inc
Date: 03-2020
Publisher: Radiological Society of North America (RSNA)
Date: 04-2015
Abstract: To identify statistical consensus between published studies for distribution and functional relevance of tract white matter (WM) degradation in multiple sclerosis (MS). By systematically searching online databases, tract-based spatial statistics studies were identified that compared fractional anisotropy (FA a marker for WM integrity) in MS patients to healthy control subjects, correlated FA in MS patients with physical disability, or correlated FA in MS patients with cognitive performance. Voxelwise meta-analysis was performed by using the Signed Differential Mapping method for each comparison. Moderating effects of mean age, mean physical disability score, imager magnet strength, lesion load, and number of diffusion directions were assessed by means of meta-regression. Meta-analysis was performed on data from 495 patients and 253 control subjects across 12 studies. MS diagnosis was significantly associated with widespread lower tract FA (nine studies largest cluster, 4379 voxels z = 7.1 P < .001). Greater physical disability was significantly associated with lower FA in the right posterior cingulum, left callosal splenium, right inferior fronto-occipital fasciculus, and left fornix crus (six studies 323 voxels z = 1.7 P = .001). Impaired cognition was significantly associated with lower FA in the callosal genu, thalamus, right posterior cingulum, and fornix crus (seven studies largest cluster, 980 voxels z = 2.5 P < .001). WM damage is widespread in MS with differential and only minimally overlapping distributions of low FA that relates to physical disability and cognitive impairment. The higher number of clusters of lower FA in relation to cognition and their higher z scores suggest that cerebral WM damage may have a greater relevance to cognitive dysfunction than physical disability in MS, and that low anterior callosal and thalamic FA have specific importance to cognitive status.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 02-2012
DOI: 10.1161/STROKEAHA.111.636449
Abstract: Granulocyte-colony stimulating factor (G-CSF) is neuroprotective in experimental stroke and mobilizes CD34 + peripheral blood stem cells into the circulation. We assessed the safety of G-CSF in recent stroke in a phase IIb single-center randomized, controlled trial. G-CSF (10 μg/kg) or placebo (ratio 2:1) was given SC for 5 days to 60 patients 3 to 30 days after ischemic or hemorrhagic stroke. The primary outcome was the frequency of serious adverse events. Peripheral blood counts, CD34 + count, and functional outcome were measured. MRI assessed lesion volume, atrophy, and the presence of iron-labeled CD34 + cells reinjected on day 6. Sixty patients were recruited at mean of 8 days (SD ±5) post ictus, with mean age 71 years (±12 years) and 53% men. The groups were well matched for baseline minimization rognostic factors. There were no significant differences between groups in the number of participants with serious adverse events: G-CSF 15 (37.5%) of 40 versus placebo 7 (35%) of 20, death or dependency (modified Rankin Score: G-CSF 3.3±1.3, placebo 3.0±1.3) at 90 days, or the number of injections received. G-CSF increased CD34 + and total white cell counts of 9.5- and 4.2-fold, respectively. There was a trend toward reduction in MRI ischemic lesion volume with respect to change from baseline in G-CSF–treated patients ( P =0.06). In 1 participant, there was suggestion that labeled CD34 + cells had migrated to the ischemic lesion. This randomized, double-blind, placebo-controlled trial suggests that G-CSF is safe when administered subacutely. It is feasible to label and readminister iron-labeled CD34 + cells in patients with ischemic stroke. URL: www.controlled-trials.com . Unique identifier: ISRCTN63336619.
Publisher: Wiley
Date: 25-10-2019
DOI: 10.1111/ENE.14084
Publisher: JMIR Publications Inc.
Date: 09-07-2021
Abstract: epression is a substantial health and economic burden. In approximately one-third of patients, depression is resistant to first-line treatment therefore, it is essential to find alternative treatments. Transcranial magnetic stimulation (TMS) is a neuromodulatory treatment involving the application of magnetic pulses to the brain that is approved in the United Kingdom and the United States in treatment-resistant depression. This trial aims to compare the clinical effectiveness, cost-effectiveness, and mechanism of action of standard treatment repetitive TMS (rTMS) targeted at the F3 electroencephalogram site with a newer treatment—a type of TMS called theta burst stimulation (TBS) targeted based on measures of functional brain connectivity. This protocol outlines brain imaging acquisition and analysis for the Brain Imaging Guided Transcranial Magnetic Stimulation in Depression (BRIGhTMIND) study trial that is used to create personalized TMS targets and answer the proposed mechanistic hypotheses. he aims of the imaging arm of the BRIGhTMIND study are to identify functional and neurochemical brain signatures indexing the treatment mechanisms of rTMS and connectivity-guided intermittent theta burst TMS and to identify imaging-based markers predicting response to treatment. he study is a randomized double-blind controlled trial with 1:1 allocation to either 20 sessions of TBS or standard rTMS. Multimodal magnetic resonance imaging (MRI) is acquired for each participant at baseline (before TMS treatment) with T1-weighted and task-free functional MRI during rest used to estimate TMS targets. For participants enrolled in the mechanistic substudy, additional diffusion-weighted sequences are acquired at baseline and at posttreatment follow-up 16 weeks after treatment randomization. Core data sets of T1-weighted and task-free functional MRI during rest are acquired for all participants and are used to estimate TMS targets. Additional sequences of arterial spin labeling, magnetic resonance spectroscopy, and diffusion-weighted images are acquired depending on the recruitment site for mechanistic evaluation. Standard rTMS treatment is targeted at the F3 electrode site over the left dorsolateral prefrontal cortex, whereas TBS treatment is guided using the coordinate of peak effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. Both treatment targets benefit from the level of MRI guidance, but only TBS is provided with precision targeting based on functional brain connectivity. ecruitment began in January 2019 and is ongoing. Data collection is expected to continue until January 2023. his trial will determine the impact of precision MRI guidance on rTMS treatment and assess the neural mechanisms underlying this treatment in treatment-resistant depressed patients. SRCTN Registry ISRCTN19674644 www.isrctn.com/ISRCTN19674644 ERR1-10.2196/31925
Publisher: Mary Ann Liebert Inc
Date: 05-2015
Publisher: Elsevier BV
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 04-02-2021
DOI: 10.1038/S41598-021-82214-3
Abstract: To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10 −3 mm 2 s −1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.
Publisher: BMJ
Date: 07-2020
DOI: 10.1136/BMJOPEN-2020-038430
Abstract: The BRIGhTMIND study aims to determine the clinical effectiveness, cost-effectiveness and mechanism of action of connectivity guided intermittent theta burst stimulation (cgiTBS) versus standard repetitive transcranial magnetic stimulation (rTMS) in adults with moderate to severe treatment resistant depression. The study is a randomised double-blind controlled trial with 1:1 allocation to either 20 sessions of (1) cgiTBS or (2) neuronavigated rTMS not using connectivity guidance. A total of 368 eligible participants with a diagnosis of current unipolar major depressive disorder that is both treatment resistant (defined as scoring 2 or more on the Massachusetts General Hospital Staging Score) and moderate to severe (scoring 16 on the 17-item Hamilton Depression Rating Scale (HDRS-17)), will be recruited from primary and secondary care settings at four treatment centres in the UK. The primary outcome is depression response at 16 weeks (50% or greater reduction in HDRS-17 score from baseline). Secondary outcomes include assessments of self-rated depression, anxiety, psychosocial functioning, cognition and quality of life at 8, 16 and 26 weeks postrandomisation. Cost-effectiveness, patient acceptability, safety, mechanism of action and predictors of response will also be examined. Ethical approval was granted by East Midlands Leicester Central Research Ethics Committee (ref: 18/EM/0232) on 30 August 2018. The results of the study will be published in relevant peer-reviewed journals, and then through professional and public conferences and media. Further publications will explore patient experience, moderators and mediators of outcome and mechanism of action. ISRCTN19674644
Publisher: Cold Spring Harbor Laboratory
Date: 09-07-2023
DOI: 10.1101/2023.07.08.23292404
Abstract: Impaired attention performance is a significant burden to people with multiple sclerosis (MS). Brain connectivity fluctuates with transitions between cognitive states, so measurement of network dynamics during these conditions may help to understand MS-related attention impairment. In people with MS and healthy controls, attention was measured using the Attention Network Test. 3T MRI was used to measure structural connectivity and both static and dynamic functional connectivity in the attention-related fronto-parietal network (FPN) at rest and during an attentionally-demanding task. Groups were compared on connectivity of the FPN during rest and task performance. Relationships between network connectivity and attention performance were tested using linear regression. The s le comprised 37 people with MS and 23 matched controls. At rest, people with MS had significantly lower structural connectivity (R 2 =0.13, p=0.004), lower static functional connectivity (R 2 =0.07, p=0.032) and higher dynamic functional connectivity (R 2 =0.08, p=0.026) of the FPN. Higher dynamic connectivity was significantly associated with poorer attention performance in people with MS (R 2 =0.20, p=0.008). During attention-task performance, static functional connectivity was greater in people with MS than controls (R 2 =0.10, p=0.008). The task-induced reduction in static connectivity (relative to rest) was directly related to attention performance (R 2 =0.23, p .001). Increased dynamic functional connectivity of the FPN at rest may be a useful indicator of deficits in sustained attention in people with MS. The transition from rest to active-attentive state is accompanied by an increase in dynamic connectivity, and decrease in static connectivity which may be helpful in understanding aetiology and treatment of attention impairment.
Location: Germany
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2006
End Date: 2009
Funder: Medical Research Council
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