ORCID Profile
0000-0002-0718-1663
Current Organisation
University of Leeds
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Publisher: Elsevier BV
Date: 08-2004
Publisher: Springer Science and Business Media LLC
Date: 06-01-2015
DOI: 10.1007/S11548-014-1142-5
Abstract: Realistic modelling of soft tissue biomechanics and mechanical interactions between tissues is an important part of biomechanically-informed surgical image-guidance and surgical simulation. This submission details a contact-modelling pipeline suitable for implementation in explicit matrix-free FEM solvers. While these FEM algorithms have been shown to be very suitable for simulation of soft tissue biomechanics and successfully used in a number of image-guidance systems, contact modelling specifically for these solvers is rarely addressed, partly because the typically large number of time steps required with this class of FEM solvers has led to a perception of them being a poor choice for simulations requiring complex contact modelling. The presented algorithm is capable of handling most scenarios typically encountered in image-guidance. The contact forces are computed with an evolution of the Lagrange-multiplier method first used by Taylor and Flanagan in PRONTO 3D extended with spatio-temporal smoothing heuristics for improved stability and edge-edge collision handling, and a new friction model. For contact search, a bounding-volume hierarchy (BVH) is employed, which is capable of identifying self-collisions by means of the surface-normal bounding cone of Volino and Magnenat-Thalmann, in turn computed with a novel formula. The BVH is further optimised for the small time steps by reducing the number of bounding-volume refittings between iterations through identification of regions with mostly rigid motion and negligible deformation. Further optimisation is achieved by integrating the self-collision criterion in the BVH creation and updating algorithms. The effectiveness of the algorithm is demonstrated on a number of artificial test cases and meshes derived from medical image data. It is shown that the proposed algorithm reduces the cost of BVH refitting to the point where it becomes a negligible part of the overall computation time of the simulation. It is also shown that the proposed surface-normal cone computation formula leads to about 40 % fewer BVH subtrees that must be checked for self-collisions compared with the widely used method of Provot. The proposed contact-force formulation and friction model are evaluated on artificial test cases that allow for a comparison with a ground truth. The quality of the proposed contact forces is assessed in terms of trajectories and energy conservation a [Formula: see text]0.4 % drop off in total energy and highly plausible trajectories are found in the experiments. The friction model is evaluated through a benchmark problem with an analytical solution and a maximum displacement error of 8.2 %, and excellent agreement in terms of the stick/slip boundary is found. Finally, we show with realistic image-guidance ex les that the entire contact-modelling pipeline can be executed within a timeframe that is of the same order of magnitude as that required for standard FEM computations.
Publisher: Elsevier BV
Date: 02-2015
DOI: 10.1016/J.JBIOMECH.2015.01.002
Abstract: The personalization of trabecular micro-architecture has been recently shown to be important in patient-specific biomechanical models of the femur. However, high-resolution in vivo imaging of bone micro-architecture using existing modalities is still infeasible in practice due to the associated acquisition times, costs, and X-ray radiation exposure. In this study, we describe a statistical approach for the prediction of the femur micro-architecture based on the more easily extracted subject-specific bone shape and mineral density information. To this end, a training s le of ex vivo micro-CT images is used to learn the existing statistical relationships within the low and high resolution image data. More specifically, optimal bone shape and mineral density features are selected based on their predictive power and used within a partial least square regression model to estimate the unknown trabecular micro-architecture within the anatomical models of new subjects. The experimental results demonstrate the accuracy of the proposed approach, with average errors of 0.07 for both the degree of anisotropy and tensor norms.
Publisher: Springer Science and Business Media LLC
Date: 26-08-2015
DOI: 10.1007/S10439-015-1432-2
Abstract: Low trauma fractures are amongst the most frequently encountered problems in the clinical assessment and treatment of bones, with dramatic health consequences for in iduals and high financial costs for health systems. Consequently, significant research efforts have been dedicated to the development of accurate computational models of bone biomechanics and strength. However, the estimation of the fabric tensors, which describe the microarchitecture of the bone, has proven to be challenging using in vivo imaging. On the other hand, existing research has shown that isotropic models do not produce accurate predictions of stress states within the bone, as the material properties of the trabecular bone are anisotropic. In this paper, we present the first biomechanical study that uses statistically-derived fabric tensors for the estimation of bone strength in order to obtain patient-specific results. We integrate a statistical predictive model of trabecular bone microarchitecture previously constructed from a s le of ex vivo micro-CT datasets within a biomechanical simulation workflow. We assess the accuracy and flexibility of the statistical approach by estimating fracture load for two different databases and bone sites, i.e., for the femur and the T12 vertebra. The results obtained demonstrate good agreement between the statistically-driven and micro-CT-based estimates, with concordance coefficients of 98.6 and 95.5% for the femur and vertebra datasets, respectively.
Publisher: SPIE
Date: 26-02-2009
DOI: 10.1117/12.811588
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2015
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Elsevier BV
Date: 04-2012
DOI: 10.1016/J.MEDIA.2010.11.003
Abstract: A deformable registration method is described that enables automatic alignment of magnetic resonance (MR) and 3D transrectal ultrasound (TRUS) images of the prostate gland. The method employs a novel "model-to-image" registration approach in which a deformable model of the gland surface, derived from an MR image, is registered automatically to a TRUS volume by maximising the likelihood of a particular model shape given a voxel-intensity-based feature that represents an estimate of surface normal vectors at the boundary of the gland. The deformation of the surface model is constrained by a patient-specific statistical model of gland deformation, which is trained using data provided by biomechanical simulations. Each simulation predicts the motion of a volumetric finite element mesh due to the random placement of a TRUS probe in the rectum. The use of biomechanical modelling in this way also allows a dense displacement field to be calculated within the prostate, which is then used to non-rigidly warp the MR image to match the TRUS image. Using data acquired from eight patients, and anatomical landmarks to quantify the registration accuracy, the median final RMS target registration error after performing 100 MR-TRUS registrations for each patient was 2.40 mm.
Publisher: Elsevier BV
Date: 02-2017
DOI: 10.1016/J.MEDIA.2016.10.008
Abstract: Image registration is an essential technique to obtain point correspondences between anatomical structures from different images. Conventional non-rigid registration methods assume a continuous and smooth deformation field throughout the image. However, the deformation field at the interface of different organs is not necessarily continuous, since the organs may slide over or separate from each other. Therefore, imposing continuity and smoothness ubiquitously would lead to artifacts and increased errors near the discontinuity interface. In computational mechanics, the eXtended Finite Element Method (XFEM) was introduced to handle discontinuities without using computational meshes that conform to the discontinuity geometry. Instead, the interpolation bases themselves were enriched with discontinuous functional terms. Borrowing this concept, we propose a multiresolution eXtented Free-Form Deformation (XFFD) framework that seamlessly integrates within and extends the standard Free-Form Deformation (FFD) approach. Discontinuities are incorporated by enriching the B-spline basis functions coupled with extra degrees of freedom, which are only introduced near the discontinuity interface. In contrast with most previous methods, restricted to sliding motion, no ad hoc penalties or constraints are introduced to reduce gaps and overlaps. This allows XFFD to describe more general discontinuous motions. In addition, we integrate XFFD into a rigorously formulated multiresolution framework by introducing an exact parameter ups ling method. The proposed method has been evaluated in two publicly available datasets: 4D pulmonary CT images from the DIR-Lab dataset and 4D CT liver datasets. The XFFD achieved a Target Registration Error (TRE) of 1.17 ± 0.85 mm in the DIR-lab dataset and 1.94 ± 1.01 mm in the liver dataset, which significantly improves on the performance of the state-of-the-art methods handling discontinuities.
Publisher: Elsevier BV
Date: 10-2016
DOI: 10.1016/J.MEDIA.2016.06.024
Abstract: Medical image analysis has grown into a matured field challenged by progress made across all medical imaging technologies and more recent breakthroughs in biological imaging. The cross-fertilisation between medical image analysis, biomedical imaging physics and technology, and domain knowledge from medicine and biology has spurred a truly interdisciplinary effort that stretched outside the original boundaries of the disciplines that gave birth to this field and created stimulating and enriching synergies. Consideration on how the field has evolved and the experience of the work carried out over the last 15 years in our centre, has led us to envision a future emphasis of medical imaging in Precision Imaging. Precision Imaging is not a new discipline but rather a distinct emphasis in medical imaging borne at the cross-roads between, and unifying the efforts behind mechanistic and phenomenological model-based imaging. It captures three main directions in the effort to deal with the information deluge in imaging sciences, and thus achieve wisdom from data, information, and knowledge. Precision Imaging is finally characterised by being descriptive, predictive and integrative about the imaged object. This paper provides a brief and personal perspective on how the field has evolved, summarises and formalises our vision of Precision Imaging for Precision Medicine, and highlights some connections with past research and current trends in the field.
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Elsevier BV
Date: 11-2016
DOI: 10.1016/J.JBIOMECH.2016.09.040
Abstract: In this study, we examine the effect of collagenase, elastase and glutaraldehyde treatments on the response of porcine aorta to controlled peel testing. Specifically, the effects on the tissue׳s resistance to dissection, as quantified by critical energy release rate, are investigated. We further explore the utility of these treatments in creating model tissues whose properties emulate those of certain diseased tissues. Such model tissues would find application in, for ex le, development and physical testing of new endovascular devices. Controlled peel testing of fresh and treated aortic specimens was performed with a tensile testing apparatus. The resulting reaction force profiles and critical energy release rates were compared across s le classes. It was found that collagenase digestion significantly decreases resistance to peeling, elastase digestion has almost no effect, and glutaraldehyde significantly increases resistance. The implications of these findings for understanding mechanisms of disease-associated biomechanical changes, and for the creation of model tissues that emulate these changes are explored.
Publisher: SPIE
Date: 23-02-2012
DOI: 10.1117/12.911787
Publisher: IEEE
Date: 08-2010
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Springer Berlin Heidelberg
Date: 2008
DOI: 10.1007/978-3-540-85988-8_84
Abstract: Previously almost all biomechanically-based time-critical surgical simulation has ignored the well established features of tissue mechanical response of anisotropy and time-dependence. We address this issue by presenting an efficient solution procedure for anisotropic viscohyperelastic constitutive models which allows use of these in nonlinear explicit dynamic finite element algorithms. We show that the procedure allows incorporation of both anisotropy and viscoelasticity for as little as 5.1% additional cost compared with the usual isotropic elastic models. When combined with high performance GPU execution the complete framework is suitable for time-critical simulation applications such as interactive surgical simulation and intraoperative image registration.
Publisher: Informa UK Limited
Date: 08-2007
DOI: 10.1080/10255840701336794
Abstract: Current development of a laser scanning confocal arthroscope within our school will enable 3D microscopic imaging of joint tissues in vivo. Such an instrument could be useful, for ex le, in assessing the microstructural condition of the living tissues without physical biopsy. It is envisaged also that linked to a suitable microstructural constitutive formulation, such imaging could allow non-invasive patient-specific estimation of tissue mechanical performance. Such a procedure could have applications in surgical planning and simulation, and assessment of engineered tissue replacements, where tissue biopsy is unacceptable. In this first of two papers the development of a suitable constitutive framework for generating such estimates is reported. A microstructure-based constitutive formulation for cartilaginous tissues is presented. The model extends existing fibre composite-type models and accounts for strain-rate sensitivity of the tissue mechanical response through incorporation of a viscoelastic fibre phase. Importantly, the model is constructed so as to allow direct incorporation of structural data from confocal images. A finite element implementation of the formulation suitable for incorporation within commercial codes is also presented.
Publisher: AIP Publishing
Date: 07-07-2023
DOI: 10.1063/5.0144848
Abstract: How prevalent is spontaneous thrombosis in a population containing all sizes of intracranial aneurysms? How can we calibrate computational models of thrombosis based on published data? How does spontaneous thrombosis differ in normo- and hypertensive subjects? We address the first question through a thorough analysis of published datasets that provide spontaneous thrombosis rates across different aneurysm characteristics. This analysis provides data for a subgroup of the general population of aneurysms, namely, those of large and giant size (& mm). Based on these observed spontaneous thrombosis rates, our computational modeling platform enables the first in silico observational study of spontaneous thrombosis prevalence across a broader set of aneurysm phenotypes. We generate 109 virtual patients and use a novel approach to calibrate two trigger thresholds: residence time and shear rate, thus addressing the second question. We then address the third question by utilizing this calibrated model to provide new insight into the effects of hypertension on spontaneous thrombosis. We demonstrate how a mechanistic thrombosis model calibrated on an intracranial aneurysm cohort can help estimate spontaneous thrombosis prevalence in a broader aneurysm population. This study is enabled through a fully automatic multi-scale modeling pipeline. We use the clinical spontaneous thrombosis data as an indirect population-level validation of a complex computational modeling framework. Furthermore, our framework allows exploration of the influence of hypertension in spontaneous thrombosis. This lays the foundation for in silico clinical trials of cerebrovascular devices in high-risk populations, e.g., assessing the performance of flow erters in aneurysms for hypertensive patients.
Publisher: Elsevier BV
Date: 05-2014
DOI: 10.1016/J.MEDIA.2014.03.003
Abstract: Determining corresponding regions between an MRI and an X-ray mammogram is a clinically useful task that is challenging for radiologists due to the large deformation that the breast undergoes between the two image acquisitions. In this work we propose an intensity-based image registration framework, where the biomechanical transformation model parameters and the rigid-body transformation parameters are optimised simultaneously. Patient-specific biomechanical modelling of the breast derived from diagnostic, prone MRI has been previously used for this task. However, the high computational time associated with breast compression simulation using commercial packages, did not allow the optimisation of both pose and FEM parameters in the same framework. We use a fast explicit Finite Element (FE) solver that runs on a graphics card, enabling the FEM-based transformation model to be fully integrated into the optimisation scheme. The transformation model has seven degrees of freedom, which include parameters for both the initial rigid-body pose of the breast prior to mammographic compression, and those of the biomechanical model. The framework was tested on ten clinical cases and the results were compared against an affine transformation model, previously proposed for the same task. The mean registration error was 11.6±3.8mm for the CC and 11±5.4mm for the MLO view registrations, indicating that this could be a useful clinical tool.
Publisher: Springer International Publishing
Date: 2016
Publisher: SPIE
Date: 20-03-2015
DOI: 10.1117/12.2082597
Publisher: Elsevier BV
Date: 12-2005
DOI: 10.1016/J.JBIOMECH.2004.10.007
Abstract: We present four ex les to illustrate the use of a type of numerical approximation as an intermediate step in analytical derivation of seemingly complicated biomechanical equations. The method involves examination of curve shapes to elucidate useful underlying trends, which may otherwise be overlooked through consideration of only the equations themselves. Two ex les of the method's use are drawn from recently published results in the area of experimental methods in biomechanics of very soft tissues, and two others are taken from our current work on cartilage tissue mechanics. We think that such observations provide a useful means of circumventing complexity issues when deriving models for biomechanical analysis, and further that the method, while simple in concept, could be effective in a range of biomechanics applications.
Publisher: SPIE
Date: 20-03-2015
DOI: 10.1117/12.2082599
Publisher: The Endocrine Society
Date: 02-2015
DOI: 10.1210/JC.2014-3199
Abstract: Bone mass is low and fracture risk is higher in obese children. Hormonal changes in relation to skeletal microstructure and biomechanics have not been studied in obese children. The objective of the study was to ascertain the relationships of obesity-related changes in hormones with skeletal microstructure and biomechanics. High resolution peripheral quantitative computed tomography (HR-pQCT) was used to compare three-dimensional cortical and trabecular microstructure and biomechanics at load-bearing and nonload bearing sites in obese and lean children. The relationship between leptin, adiponectin, testosterone, estrogen, osteocalcin and sclerostin and skeletal microstructure was also determined. The study was conducted at a tertiary pediatric endocrine unit in the United Kingdom. Obese and lean children were matched by gender and pubertal stage. Radial cortical porosity (mean difference −0.01 [95% CI: −0.02, −0.004], P = .003) and cortical pore diameter (mean difference −0.005 mm [95% CI: −0.009, −0.001], P = .011) were lower in obese children. Tibial trabecular thickness was lower (mean difference −0.009 mm [95% CI: −0.014, −0.004], P = .003), and trabecular number was higher (mean difference 0.23 mm−1 [95% CI: 0.08, 0.38], P = .004) in obese children. At the radius, fat mass percentage negatively correlated with cortical porosity (r = −0.57, P & .001) and pore diameter (r = −0.38, P = .02) and negatively correlated with trabecular thickness (r = −0.62, P & .001) and trabecular von Mises stress (r = −0.39, P = .019) at the tibia. No difference was observed in the other biomechanical parameters of the radius and tibia. Leptin was higher in obese children (805.3 ± 440.6 pg/ml vs 98.1 ± 75.4 pg/ml, P & .001) and was inversely related to radial cortical porosity (r = 0.60, 95% CI: [−0.80, −0.30], P & .001), radial cortical pore diameter (r = 0.51, 95% CI [−0.75, −0.16], P = .002), tibial trabecular thickness (r = 0.55, 95% CI: [−0.78, −0.21], P = .001) and tibial trabecular von Mises stress (r = −0.39, 95% CI: −0.65, 0.04, P = .02). Childhood obesity alters radial and tibial microstructure. Leptin may direct these changes. Despite this, the biomechanical properties of the radius and tibia do not adapt sufficiently in obese children to withstand the increased loading potential from a fall. This may explain the higher incidence of fracture in obese children.
Publisher: Springer International Publishing
Date: 2016
Publisher: IOP Publishing
Date: 15-12-2011
DOI: 10.1088/0031-9155/57/2/455
Abstract: Physically realistic simulations for large breast deformation are of great interest for many medical applications such as cancer diagnosis, image registration, surgical planning and image-guided surgery. To support fast, large deformation simulations of breasts in clinical settings, we proposed a patient-specific biomechanical modelling framework for breasts, based on an open-source graphics processing unit-based, explicit, dynamic, nonlinear finite element (FE) solver. A semi-automatic segmentation method for tissue classification, integrated with a fully automated FE mesh generation approach, was implemented for quick patient-specific FE model generation. To solve the difficulty in determining material parameters of soft tissues in vivo for FE simulations, a novel method for breast modelling, with a simultaneous material model parameter optimization for soft tissues in vivo, was also proposed. The optimized deformation prediction was obtained through iteratively updating material model parameters to maximize the image similarity between the FE-predicted MR image and the experimentally acquired MR image of a breast. The proposed method was validated and tested by simulating and analysing breast deformation experiments under plate compression. Its prediction accuracy was evaluated by calculating landmark displacement errors. The results showed that both the heterogeneity and the anisotropy of soft tissues were essential in predicting large breast deformations under plate compression. As a generalized method, the proposed process can be used for fast deformation analyses of soft tissues in medical image analyses and surgical simulations.
Publisher: Elsevier BV
Date: 11-2016
Publisher: Elsevier BV
Date: 10-2015
DOI: 10.1016/J.JMR.2015.08.008
Abstract: Nuclear magnetic resonance (NMR) has proven of enormous value in the investigation of porous media. Its use allows to study pore size distributions, tortuosity, and permeability as a function of the relaxation time, diffusivity, and flow. This information plays an important role in plenty of applications, ranging from oil industry to medical diagnosis. A complete NMR analysis involves the solution of the Bloch-Torrey (BT) equation. However, solving this equation analytically becomes intractable for all but the simplest geometries. We present an efficient numerical framework for solving the complete BT equation in arbitrarily complex domains. In addition to the standard BT equation, the generalised BT formulation takes into account the flow and relaxation terms, allowing a better representation of the phenomena under scope. The presented framework is flexible enough to deal parametrically with any order of convergence in the spatial domain. The major advantage of such approach is to allow both faster computations and sensitivity analyses over realistic geometries. Moreover, we developed a second-order implicit scheme for the temporal discretisation with similar computational demands as the existing explicit methods. This represents a huge step forward for obtaining reliable results with few iterations. Comparisons with analytical solutions and real data show the flexibility and accuracy of the proposed methodology.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2008
Publisher: Elsevier BV
Date: 04-2009
DOI: 10.1016/J.MEDIA.2008.10.001
Abstract: Efficient and accurate techniques for simulation of soft tissue deformation are an increasingly valuable tool in many areas of medical image computing, such as biomechanically-driven image registration and interactive surgical simulation. For reasons of efficiency most analyses are based on simplified linear formulations, and previously almost all have ignored well established features of tissue mechanical response such as anisotropy and time-dependence. We address these latter issues by firstly presenting a generalised anisotropic viscoelastic constitutive framework for soft tissues, particular cases of which have previously been used to model a wide range of tissues. We then develop an efficient solution procedure for the accompanying viscoelastic hereditary integrals which allows use of such models in explicit dynamic finite element algorithms. We show that the procedure allows incorporation of both anisotropy and viscoelasticity for as little as 5.1% additional cost compared with the usual isotropic elastic models. Finally we describe the implementation of a new GPU-based finite element scheme for soft tissue simulation using the CUDA API. Even with the inclusion of more elaborate constitutive models as described the new implementation affords speed improvements compared with our recent graphics API-based implementation, and compared with CPU execution a speed up of 56.3 x is achieved. The validity of the viscoelastic solution procedure and performance of the GPU implementation are demonstrated with a series of numerical ex les.
Publisher: The Royal Society
Date: 15-12-2017
Abstract: There is emerging evidence suggesting that Alzheimer's disease is a vascular disorder, caused by impaired cerebral perfusion, which may be promoted by cardiovascular risk factors that are strongly influenced by lifestyle. In order to develop an understanding of the exact nature of such a hypothesis, a biomechanical understanding of the influence of lifestyle factors is pursued. An extended poroelastic model of perfused parenchymal tissue coupled with separate workflows concerning subject-specific meshes, permeability tensor maps and cerebral blood flow variability is used. The subject-specific datasets used in the modelling of this paper were collected as part of prospective data collection. Two cases were simulated involving male, non-smokers (control and mild cognitive impairment (MCI) case) during two states of activity (high and low). Results showed a marginally reduced clearance of cerebrospinal fluid (CSF)/interstitial fluid (ISF), elevated parenchymal tissue displacement and CSF/ISF accumulation and drainage in the MCI case. The peak perfusion remained at 8 mm s −1 between the two cases.
Publisher: Informa UK Limited
Date: 10-2007
DOI: 10.1080/10255840701336828
Abstract: The theoretical framework developed in a companion paper (Part I) is used to derive estimates of mechanical response of two meniscal cartilage specimens. The previously developed framework consisted of a constitutive model capable of incorporating confocal image-derived tissue microstructural data. In the present paper (Part II) fibre and matrix constitutive parameters are first estimated from mechanical testing of a batch of specimens similar to, but independent from those under consideration. Image analysis techniques which allow estimation of tissue microstructural parameters form confocal images are presented. The constitutive model and image-derived structural parameters are then used to predict the reaction force history of the two meniscal specimens subjected to partially confined compression. The predictions are made on the basis of the specimens' in idual structural condition as assessed by confocal microscopy and involve no tuning of material parameters. Although the model does not reproduce all features of the experimental curves, as an unfitted estimate of mechanical response the prediction is quite accurate. In light of the obtained results it is judged that more general non-invasive estimation of tissue mechanical properties is possible using the developed framework.
Publisher: Elsevier BV
Date: 07-2015
DOI: 10.1016/J.JMBBM.2015.03.011
Abstract: This paper describes a constitutive model for ballistic gelatin at the low strain rates experienced, for ex le, by soft tissues during surgery. While this material is most commonly associated with high speed projectile penetration and impact investigations, it has also been used extensively as a soft tissue simulant in validation studies for surgical technologies (e.g. surgical simulation and guidance systems), for which loading speeds and the corresponding mechanical response of the material are quite different. We conducted mechanical compression experiments on gelatin specimens at strain rates spanning two orders of magnitude (~0.001-0.1s(-1)) and observed a nonlinear load-displacement history and strong strain rate-dependence. A compact and efficient visco-hyperelastic constitutive model was then formulated and found to fit the experimental data well. An Ogden type strain energy density function was employed for the elastic component. A single Prony exponential term was found to be adequate to capture the observed rate-dependence of the response over multiple strain rates. The model lends itself to immediate use within many commercial finite element packages.
Publisher: SPIE
Date: 21-03-2016
DOI: 10.1117/12.2216244
Publisher: Elsevier BV
Date: 07-2016
DOI: 10.1016/J.JMBBM.2016.02.018
Abstract: Large quantities of diseased tissue are required in the research and development of new generations of medical devices, for ex le for use in physical testing. However, these are difficult to obtain. In contrast, porcine arteries are readily available as they are regarded as waste. Therefore, reliable means of creating from porcine tissue physical models of diseased human tissue that emulate well the associated mechanical changes would be valuable. To this end, we studied the effect on mechanical response of treating porcine thoracic aorta with collagenase, elastase and glutaraldehyde. The alterations in mechanical and failure properties were assessed via uniaxial tension testing. A constitutive model composed of the Gasser-Ogden-Holzapfel model, for elastic response, and a continuum damage model, for the failure, was also employed to provide a further basis for comparison (Calvo and Peña, 2006 Gasser et al., 2006). For the concentrations used here it was found that: collagenase treated s les showed decreased fracture stress in the axial direction only elastase treated s les showed increased fracture stress in the circumferential direction only and glutaraldehyde s les showed no change in either direction. With respect to the proposed constitutive model, both collagenase and elastase had a strong effect on the fibre-related terms. The model more closely captured the tissue response in the circumferential direction, due to the smoother and sharper transition from damage initiation to complete failure in this direction. Finally, comparison of the results with those of tensile tests on diseased tissues suggests that these treatments indeed provide a basis for creation of physical models of diseased arteries.
Publisher: Elsevier BV
Date: 12-2010
DOI: 10.1016/J.PBIOMOLBIO.2010.09.009
Abstract: Statistical shape models (SSM) are widely used in medical image analysis to represent variability in organ shape. However, representing subject-specific soft-tissue motion using this technique is problematic for applications where imaging organ changes in an in idual is not possible or impractical. One solution is to synthesise training data by using biomechanical modelling. However, for many clinical applications, generating a biomechanical model of the organ(s) of interest is a non-trivial task that requires a significant amount of user-interaction to segment an image and create a finite element mesh. In this study, we investigate the impact of reducing the effort required to generate SSMs and the accuracy with which such models can predict tissue displacements within the prostate gland due to transrectal ultrasound probe pressure. In this approach, the finite element mesh is based on a simplified geometric representation of the organs. For ex le, the pelvic bone is represented by planar surfaces, or the number of distinct tissue compartments is reduced. Such representations are much easier to generate from images than a geometrically accurate mesh. The difference in the median root-mean-square displacement error between different SSMs of prostate was <0.2 mm. We conclude that reducing the geometric complexity of the training model in this way made little difference to the absolute accuracy of SSMs to recover tissue displacements. The implication is that SSMs of organ motion based on simulated training data may be generated using simplified geometric representations, which are much more compatible with the time constraints of clinical workflows.
Publisher: Springer Berlin Heidelberg
Date: 2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2011
Publisher: SPIE-Intl Soc Optical Eng
Date: 13-05-2015
Publisher: Springer International Publishing
Date: 2017
Publisher: Springer Berlin Heidelberg
Date: 2010
DOI: 10.1007/978-3-642-15745-5_48
Abstract: Reduced order modelling, in which a full system response is projected onto a subspace of lower dimensionality, has been used previously to accelerate finite element solution schemes by reducing the size of the involved linear systems. In the present work we take advantage of a secondary effect of such reduction for explicit analyses, namely that the stable integration time step is increased far beyond that of the full system. This phenomenon alleviates one of the principal drawbacks of explicit methods, compared with implicit schemes. We present an explicit finite element scheme in which time integration is performed in a reduced basis. The computational benefits of the procedure within a GPU-based execution framework are examined, and an assessment of the errors introduced is given. Speedups approaching an order of magnitude are feasible, without introduction of prohibitive errors, and without hardware modifications. The procedure may have applications in medical image-guidance problems in which both speed and accuracy are vital.
Publisher: Springer Science and Business Media LLC
Date: 21-09-2014
Publisher: IEEE
Date: 12-2012
Publisher: Elsevier BV
Date: 08-2017
Publisher: Elsevier BV
Date: 07-2017
DOI: 10.1016/J.JMBBM.2017.03.004
Abstract: In this paper, we study the dissection of arterial layers by means of a stiff, planar, penetrating external body (a 'wedge'), and formulate a novel model of the process using cohesive zone formalism. The work is motivated by a need for better understanding of, and numerical tools for simulating catheter-induced dissection, which is a potentially catastrophic complication whose mechanisms remain little understood. As well as the large deformations and rupture of the tissue, models of such a process must accurately capture the interaction between the tissue and the external body driving the dissection. The latter feature, in particular, distinguishes catheter-induced dissection from, for ex le, straightforward peeling, which is relatively well-studied. As a step towards such models, we study a scenario involving a geometrically simpler penetrating object (the wedge), which affords more reliable comparison with experimental observations, but which retains the key feature of dissection driven by an external body, as described. Particular emphasis is placed on assessing the reliability of cohesive zone approaches in this context. A series of wedge-driven dissection experiments on porcine aorta were undertaken, from which tissue elastic and fracture parameters were estimated. Finite element models of the experimental configuration, with tissue considered to be a hyperelastic medium, and evolution of tissue rupture modelled with a consistent large-displacement cohesive formulation, were then constructed. Model-predicted and experimentally measured reaction forces on the wedge throughout the dissection process were compared and found to agree well. The performance of the cohesive formulation in modelling externally driven dissection is finally assessed, and the prospects for numerical models of catheter-induced dissection using such approaches is considered.
Publisher: Elsevier BV
Date: 06-2010
DOI: 10.1016/J.CMPB.2009.09.002
Abstract: A large number of algorithms have been developed to perform non-rigid registration and it is a tool commonly used in medical image analysis. The free-form deformation algorithm is a well-established technique, but is extremely time consuming. In this paper we present a parallel-friendly formulation of the algorithm suitable for graphics processing unit execution. Using our approach we perform registration of T1-weighted MR images in less than 1 min and show the same level of accuracy as a classical serial implementation when performing segmentation propagation. This technology could be of significant utility in time-critical applications such as image-guided interventions, or in the processing of large data sets.
Publisher: Wiley
Date: 15-07-2017
DOI: 10.1002/MRM.26333
Abstract: MR elastography (MRE) of the brain is being explored as a biomarker of neurodegenerative disease such as dementia. However, MRE measures for healthy brain have varied widely. Differing wave delivery methodologies may have influenced this, hence finite element-based simulations were performed to explore this possibility. The natural frequencies of a series of cranial models were calculated, and MRE-associated vibration was simulated for different wave delivery methods at varying frequency, using simple isotropic viscoelastic material models for the brain. Displacement fields and the corresponding brain constitutive properties estimated by standard inversion techniques were compared across delivery methods and frequencies. The delivery methods produced widely different MRE displacement fields and inversions. Furthermore, resonances at natural frequencies influenced the displacement patterns. Consequently, some delivery methods led to lower inversion errors than others, and the error on the storage modulus varied by up to 11% between methods. Wave delivery has a considerable impact on brain MRE reliability. Assuming small variations in brain biomechanics, as recently reported to accompany neurodegenerative disease (e.g., 7% for Alzheimer's disease), the effect of wave delivery is important. Hence, a consensus should be established on a consistent methodology to ensure diagnostic and prognostic consistency. Magn Reson Med 78:341-356, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Publisher: Wiley
Date: 29-09-2016
DOI: 10.1002/MRM.25881
Abstract: Magnetic resonance elastography (MRE) of the brain has demonstrated potential as a biomarker of neurodegenerative disease such as dementia but requires further evaluation. Cranial anatomical features such as the falx cerebri and tentorium cerebelli membranes may influence MRE measurements through wave reflection and interference and tissue heterogeneity at their boundaries. We sought to determine the influence of these effects via simulation. MRE-associated mechanical stimulation of the brain was simulated using steady state harmonic finite element analysis. Simulations of geometrical models and anthropomorphic brain models derived from anatomical MRI data of healthy in iduals were compared. Constitutive parameters were taken from MRE measurements for healthy brain. Viscoelastic moduli were reconstructed from the simulated displacement fields and compared with ground truth. Interference patterns from reflections and heterogeneity resulted in artifacts in the reconstructions of viscoelastic moduli. Artifacts typically occurred in the vicinity of boundaries between different tissues within the cranium, with a magnitude of 10%-20%. Given that MRE studies for neurodegenerative disease have reported only marginal variations in brain elasticity between controls and patients (e.g., 7% for Alzheimer's disease), the predicted errors are a potential confound to the development of MRE as a biomarker of dementia and other neurodegenerative diseases. Magn Reson Med 76:645-662, 2016. © 2015 Wiley Periodicals, Inc.
Publisher: Springer International Publishing
Date: 2016
Publisher: Springer International Publishing
Date: 07-07-2015
Publisher: Elsevier BV
Date: 2023
DOI: 10.1016/J.MEDIA.2022.102678
Abstract: Deformable image registration (DIR) can be used to track cardiac motion. Conventional DIR algorithms aim to establish a dense and non-linear correspondence between independent pairs of images. They are, nevertheless, computationally intensive and do not consider temporal dependencies to regulate the estimated motion in a cardiac cycle. In this paper, leveraging deep learning methods, we formulate a novel hierarchical probabilistic model, termed DragNet, for fast and reliable spatio-temporal registration in cine cardiac magnetic resonance (CMR) images and for generating synthetic heart motion sequences. DragNet is a variational inference framework, which takes an image from the sequence in combination with the hidden states of a recurrent neural network (RNN) as inputs to an inference network per time step. As part of this framework, we condition the prior probability of the latent variables on the hidden states of the RNN utilised to capture temporal dependencies. We further condition the posterior of the motion field on a latent variable from hierarchy and features from the moving image. Subsequently, the RNN updates the hidden state variables based on the feature maps of the fixed image and the latent variables. Different from traditional methods, DragNet performs registration on unseen sequences in a forward pass, which significantly expedites the registration process. Besides, DragNet enables generating a large number of realistic synthetic image sequences given only one frame, where the corresponding deformations are also retrieved. The probabilistic framework allows for computing spatio-temporal uncertainties in the estimated motion fields. Our results show that DragNet performance is comparable with state-of-the-art methods in terms of registration accuracy, with the advantage of offering analytical pixel-wise motion uncertainty estimation across a cardiac cycle and being a motion generator. We will make our code publicly available.
Publisher: Springer International Publishing
Date: 2015
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: Australia
No related grants have been discovered for Zeike Taylor.