Controlling the Error on Target Motion through Real-time Mesh Adaptation: Applications to Deep Brain Stimulation

We present an error-controlled mesh refinement procedure for needle insertion simulation and apply it to the simulation of electrode implantation for deep brain stimulation, including brain shift. Our approach enables to control the error in the computation of the displacement and stress fields around the needle tip and needle shaft by suitably refining the mesh, whilst maintaining a coarser mesh in other parts of the domain. We demonstrate through academic and practical examples that our approach increases the accuracy of the displacement and stress fields around the needle without increasing the computational expense. This enables real-time simulations. The proposed methodology has direct implications to increase the accuracy and control the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anesthesia, or cryotherapy and can be essential to the development of robotic guidance.Comment: 21 pages, 14 figure

Real-time Error Control for Surgical Simulation

Objective: To present the first real-time a posteriori error-driven adaptive finite element approach for real-time simulation and to demonstrate the method on a needle insertion problem. Methods: We use corotational elasticity and a frictional needle/tissue interaction model. The problem is solved using finite elements within SOFA. The refinement strategy relies upon a hexahedron-based finite element method, combined with a posteriori error estimation driven local $h$-refinement, for simulating soft tissue deformation. Results: We control the local and global error level in the mechanical fields (e.g. displacement or stresses) during the simulation. We show the convergence of the algorithm on academic examples, and demonstrate its practical usability on a percutaneous procedure involving needle insertion in a liver. For the latter case, we compare the force displacement curves obtained from the proposed adaptive algorithm with that obtained from a uniform refinement approach. Conclusions: Error control guarantees that a tolerable error level is not exceeded during the simulations. Local mesh refinement accelerates simulations. Significance: Our work provides a first step to discriminate between discretization error and modeling error by providing a robust quantification of discretization error during simulations.Comment: 12 pages, 16 figures, change of the title, submitted to IEEE TBM

Evaluation of local and global atrophy measurement techniques with simulated Alzheimer's disease data

The main goal of this work was to evaluate several well-known methods which provide global (BSI and SIENA) or local (Jacobian integration) estimates of atrophy in brain structures using Magnetic Resonance images. For that purpose, we have generated realistic simulated Alzheimer's disease images in which volume changes are modelled with a Finite Element thermoelastic model, which mimic the patterns of change obtained from a cohort of 19 real controls and 27 probable Alzheimer's disease patients. SIENA and BSI results correlate very well with gold standard data (BSI mean absolute error <0.29%; SIENA <0.44%). Jacobian integration was guided by both fluid and FFD-based registration techniques and resulting deformation fields and associated Jacobians were compared, region by region, with gold standard ones. The FFD registration technique provided more satisfactory results than the fluid one. Mean absolute error differences between volume changes given by the FFD-based technique and the gold standard were: sulcal CSF <2.49%; lateral ventricles 2.25%; brain <0.36%; hippocampi <0.42%

Accuracy assessment of global and local atrophy measurement techniques with realistic simulated longitudinal data

The main goal of this work was to assess the accuracy of several well-known methods which provide global (BSI and SIENA) or local (Jacobian integration) estimates of longitudinal atrophy in brain structures using Magnetic Resonance images. For that purpose, we have generated realistic simulated images which mimic the patterns of change obtained from a cohort of 19 real controls and 27 probable Alzheimer's disease patients. SIENA and BSI results correlate very well with gold standard data (BSI mean absolute error < 0.29%; SIENA < 0.44%). Jacobian integration was guided by both fluid and FFD-based registration techniques and resulting deformation fields and associated Jacobians were compared, region by region, with gold standard ones. The FFD registration technique provided more satisfactory results than the fluid one. Mean absolute error differences between volume changes given by the FFD-based technique and the gold standard were: sulcal CSF < 2.49%; lateral ventricles < 2.25%; brain < 0.36%; hippocampi < 1.42%

Grid simulation services for the medical community

The first part of this paper presents a selection of medical simulation applications, including image reconstruction, near real-time registration for neuro-surgery, enhanced dose distribution calculation for radio-therapy, inhaled drug delivery prediction, plastic surgery planning and cardio-vascular system simulation. The latter two topics are discussed in some detail. In the second part, we show how such services can be made available to the clinical practitioner using Grid technology. We discuss the developments and experience made during the EU project GEMSS, which provides reliable, efficient, secure and lawful medical Grid services

A theoretical model of the endothelial cell morphology due to different waveforms

Endothelial cells are key units in the regulatory biological process of blood vessels. They represent an interface to transmit variations on the fluid dynamic changes. They are able to adapt its cytoskeleton, by means of microtubules reorientation and F-actin reorganization, due to new mechanical environments. Moreover, they are responsible for initiating a huge cascade of biological processes, such as the release of endothelins (ET-1), in charge of the constriction of the vessel and growth factors such as TGF-ß and PDGF. Although a huge efforts have been made in the experimental characterization and description of these two issues the computational modeling has not gained such an attention. In this work we study the 3D remodeling of endothelial cells based on the main features of blood flow. In particular we study how different oscillatory shear index and the time average wall shear stresses modify the endothelial cell shape. We found our model fitted the experimental works presented before in in vitro studies. We also include our model within a computational fluid dynamics simulation of a carotid artery to evaluate endothelial cell shape index which is a key predictor of atheroma plaque formation. Moreover, our approach can be coupled with models of collagen and smooth muscle cell growth, where remodeling and the associated release of chemical substance are involved.Peer ReviewedPostprint (author's final draft

Phenomenological model of diffuse global and regional atrophy using finite-element methods

The main goal of this work is the generation of ground-truth data for the validation of atrophy measurement techniques, commonly used in the study of neurodegenerative diseases such as dementia. Several techniques have been used to measure atrophy in cross-sectional and longitudinal studies, but it is extremely difficult to compare their performance since they have been applied to different patient populations. Furthermore, assessment of performance based on phantom measurements or simple scaled images overestimates these techniques' ability to capture the complexity of neurodegeneration of the human brain. We propose a method for atrophy simulation in structural magnetic resonance (MR) images based on finite-element methods. The method produces cohorts of brain images with known change that is physically and clinically plausible, providing data for objective evaluation of atrophy measurement techniques. Atrophy is simulated in different tissue compartments or in different neuroanatomical structures with a phenomenological model. This model of diffuse global and regional atrophy is based on volumetric measurements such as the brain or the hippocampus, from patients with known disease and guided by clinical knowledge of the relative pathological involvement of regions and tissues. The consequent biomechanical readjustment of structures is modelled using conventional physics-based techniques based on biomechanical tissue properties and simulating plausible tissue deformations with finite-element methods. A thermoelastic model of tissue deformation is employed, controlling the rate of progression of atrophy by means of a set of thermal coefficients, each one corresponding to a different type of tissue. Tissue characterization is performed by means of the meshing of a labelled brain atlas, creating a reference volumetric mesh that will be introduced to a finite-element solver to create the simulated deformations. Preliminary work on the simulation of acquisition artefa- - cts is also presented. Cross-sectional and

Finite-element modelling of mechanobiological factors influencing sesamoid tissue morphology in the patellar tendon of an ostrich

The appearance and shape of sesamoid bones within a tendon or ligament wrapping around a joint are understood to be influenced by both genetic and epigenetic factors. Ostriches (Struthio camelus) possess two sesamoid patellae (kneecaps), one of which (the distal patella) is unique to their lineage, making them a good model for investigating sesamoid tissue development and evolution. Here we used finite-element modelling to test the hypothesis that specific mechanical cues in the ostrich patellar tendon favour the formation of multiple patellae. Using three-dimensional models that allow application of loading conditions in which all muscles, or only distal or only proximal muscles to be activated, we found that there were multiple regions within the tendon where transformation from soft tissue to fibrocartilage was favourable and therefore a potential for multiple patellae based solely upon mechanical stimuli. While more studies are needed to better understand universal mechanobiological principles as well as full developmental processes, our findings suggest that a tissue differentiation algorithm using shear strain and compressive strain as inputs may be a roughly effective predictor of the tissue differentiation required for sesamoid development

Stress management in composite biopolymer networks

Living tissues show an extraordinary adaptiveness to strain, which is crucial for their proper biological functioning. The physical origin of this mechanical behaviour has been widely investigated using reconstituted networks of collagen fibres, the principal load-bearing component of tissues. However, collagen fibres in tissues are embedded in a soft hydrated polysaccharide matrix which generates substantial internal stresses whose effect on tissue mechanics is unknown. Here, by combining mechanical measurements and computer simulations, we show that networks composed of collagen fibres and a hyaluronan matrix exhibit synergistic mechanics characterized by an enhanced stiffness and delayed strain-stiffening. We demonstrate that the polysaccharide matrix has a dual effect on the composite response involving both internal stress and elastic reinforcement. Our findings elucidate how tissues can tune their strain-sensitivity over a wide range and provide a novel design principle for synthetic materials with programmable mechanical properties