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

Master of Science

thesisTraumatic brain injury is a devastating medical problem worldwide. Contusion, which involves direct damage of both brain tissue and surrounding blood vessels, has been called the hallmark of head injury. Controlled cortical impact (CCI) is a commonly used experimental model to study contusion and may be useful in the study of vascular injury, but there is currently no way to measure strain in the cortex or in the cortical blood vessels. Finite element (FE) models have been utilized to characterize the deformation of brain tissue during CCI, but none have explored strains relevant to the blood vessels. Specifically, these models have reported strains relative to the global reference frame only. The objective of this research was to characterize strains tangent to the surface of the cortex in order to estimate deformations that vessels on the surface of the brain may experience during CCI. An FE model was built from coronal section images of a mouse brain. The brain, pia-arachnoid complex, dura, and skull were separately modeled along with a rigid indenter. Global strains were transformed to the local coordinate system defined by the orientation of the brain surface at the point of interest. Strain distributions were investigated in the baseline model and showed that circumferential strain is the primary contributor to principal strain, while radial strain is high in the center but contributes little to tensile strains away from the very center. In order to characterize the influence of experimental parameters on predicted deformations, indentation rate, depth, craniotomy size, indentation angle, and indenter tip shape were each varied, and the resulting strain distribution was compared to the baseline results. Tip shape was the most influential parameter, producing the highest strain concentration on the surface of the brain. Indentation depth, rate, and angle also significantly influenced the strain distribution on the brain. Based on previously reported values of failure strain for cerebral arteries, simulations consistently predicted the occurrence of vessel injury, a frequent outcome of CCI

Injury and Skeletal Biomechanics

This book covers many aspects of Injury and Skeletal Biomechanics. As the title represents, the aspects of force, motion, kinetics, kinematics, deformation, stress and strain are examined in a range of topics such as human muscles and skeleton, gait, injury and risk assessment under given situations. Topics range from image processing to articular cartilage biomechanical behavior, gait behavior under different scenarios, and training, to musculoskeletal and injury biomechanics modeling and risk assessment to motion preservation. This book, together with "Human Musculoskeletal Biomechanics", is available for free download to students and instructors who may find it suitable to develop new graduate level courses and undergraduate teaching in biomechanics

Dynamic Deformation and Mechanical Properties of Brain Tissue

Traumatic brain injury is an important medical problem affecting millions of people. Mathematical models of brain biomechanics are being developed to simulate the mechanics of brain injury and to design protective devices. However, because of a lack of quantitative data on brain-skull boundary conditions and deformations, the predictions of mathematical models remain uncertain. The objectives of this dissertation are to develop methods and obtain experimental data that will be used to parameterize and validate models of traumatic brain injury. To that end, this dissertation first addresses the brain-skull boundary conditions by measuring human brain motion using tagged magnetic resonance imaging. Magnetic resonance elastography was performed in the ferret brain to measure its mechanical properties in vivo. Brain tissue is not only heterogeneous, but may also be anisotropic. To characterize tissue anisotropy, an experimental procedure combining both shear testing and indentation was developed and applied to white matter and gray matter. These measurements of brain-skull interactions and mechanical properties of the brain will be valuable in the development and validation of finite element simulations of brain biomechanics

Computational Assessment of Neural Probe and Brain Tissue Interface Under Transient Motion

The functional longevity of a neural probe is dependent upon its ability to minimize injury risk during the insertion and recording period in vivo, which could be related to motion-related strain between the probe and surrounding tissue. A series of finite element analyses was conducted to study the extent of the strain induced within the brain in an area around a neural probe. This study focuses on the transient behavior of neural probe and brain tissue interface with a viscoelastic model. Different stages of the interface from initial insertion of neural probe to full bonding of the probe by astro-glial sheath formation are simulated utilizing analytical tools to investigate the effects of relative motion between the neural probe and the brain while friction coefficients and kinematic frequencies are varied. The analyses can provide an in-depth look at the quantitative benefits behind using soft materials for neural probes

Improving the forward model for electrical impedance tomography of brain function through rapid generation of subject specific finite element models

Electrical Impedance Tomography (EIT) is a non-invasive imaging method which allows internal electrical impedance of any conductive object to be imaged by means of current injection and surface voltage measurements through an array of externally applied electrodes. The successful generation of the image requires the simulation of the current injection patterns on either an analytical or a numerical model of the domain under examination, known as the forward model, and using the resulting voltage data in the inverse solution from which images of conductivity changes can be constructed. Recent research strongly indicates that geometric and anatomical conformance of the forward model to the subject under investigation significantly affects the quality of the images. This thesis focuses mainly on EIT of brain function and describes a novel approach for the rapid generation of patient or subject specific finite element models for use as the forward model. After introduction of the topic, methods of generating accurate finite element (FE) models using commercially available Computer-Aided Design (CAD) tools are described and show that such methods, though effective and successful, are inappropriate for time critical clinical use. The feasibility of warping or morphing a finite element mesh as a means of reducing the lead time for model generation is then presented and demonstrated. This leads on to the description of methods of acquiring and utilising known system geometry, namely the positions of electrodes and registration landmarks, to construct an accurate surface of the subject, the results of which are successfully validated. The outcome of this procedure is then used to specify boundary conditions to a mesh warping algorithm based on elastic deformation using well-established continuum mechanics procedures. The algorithm is applied to a range of source models to empirically establish optimum values for the parameters defining the problem which can successfully generate meshes of acceptable quality in terms of discretization errors and which more accurately define the geometry of the target subject. Further validation of the algorithm is performed by comparison of boundary voltages and image reconstructions from simulated and laboratory data to demonstrate that benefits in terms of image artefact reduction and localisation of conductivity changes can be gained. The processes described in the thesis are evaluated and discussed and topics of further work and application are described