Portable simulation framework for diffusion MRI

The numerical simulation of the diffusion MRI signal arising from complex tissue micro-structures is helpful for understanding and interpreting imaging data as well as for designing and optimizing MRI sequences. The discretization of the Bloch-Torrey equation by finite elements is a more recently developed approach for this purpose, in contrast to random walk simulations, which has a longer history. While finite element discretization is more difficult to implement than random walk simulations, the approach benefits from a long history of theoretical and numerical developments by the mathematical and engineering communities. In particular, software packages for the automated solutions of partial differential equations using finite element discretization, such as FEniCS, are undergoing active support and development. However, because diffusion MRI simulation is a relatively new application area, there is still a gap between the simulation needs of the MRI community and the available tools provided by finite element software packages. In this paper, we address two potential difficulties in using FEniCS for diffusion MRI simulation. First, we simplified software installation by the use of FEniCS containers that are completely portable across multiple platforms. Second, we provide a portable simulation framework based on Python and whose code is open source. This simulation framework can be seamlessly integrated with cloud computing resources such as Google Colaboratory notebooks working on a web browser or with Google Cloud Platform with MPI parallelization. We show examples illustrating the accuracy, the computational times, and parallel computing capabilities. The framework contributes to reproducible science and open-source software in computational diffusion MRI with the hope that it will help to speed up method developments and stimulate research collaborations.La Caixa 201

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities

Finite element simulations: computations and applications to aerodynamics and biomedicine.

171 p.Las ecuaciones en derivadas parciales describen muchos fenómenos de interés práctico y sus solucionessuelen necesitar correr simulaciones muy costosas en clústers de cálculo.En el ámbito de los flujos turbulentos, en particular, el coste de las simulaciones es demasiado grande sise utilizan métodos básicos, por eso es necesario modelizar el sistema.Esta tesis doctoral trata principalmente de dos temas en Cálculo Científico.Por un lado, estudiamos nuevos desarrollos en la modelización y simulación de flujos turbulentos;utilizamos un Método de Elementos Finitos adaptativo y un modelo de ¿número de Reynolds infinito¿para reducir el coste computacional de simulaciones que, sin estas modificaciones, serían demasiadocostosas.De esta manera conseguimos lograr simulaciones evolutivas de flujos turbulentos con número deReynolds muy grande, lo cual se considera uno de los mayores retos en aerodinámica.El otro pilar de esta tesis es una aplicación biomédica.Desarrollamos un modelo computacional de Ablación (Cardiaca) por Radiofrecuencia, una terapiacomún para tratar varias enfermedades, por ejemplo algunas arritmias.Nuestro modelo mejora los modelos existentes en varias maneras, y en particular en tratar de obteneruna aproximación fiel de la geometría del sistema, lo cual se descubre ser crítico para simularcorrectamente la física del fenómeno

Neurite Orientation Dispersion and Density Imaging in a Rodent Model of Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) has become a focal point within the medical community due to its increased prevalence in recent years. Unfortunately, there is currently no neuroimaging technique able to accurately diagnose and monitor mTBI in-vivo. One technique that has shown great promise is neurite orientation dispersion and density imaging (NODDI). NODDI is a diffusion MRI (dMRI) technique used to characterize microstructural complexity through the compartmental modelling of neural water fractions into Intra-neurite, Extra-neurite and CSF volume fractions. The overreaching theme of this thesis was to validate NODDI in a preclinical setting to then be applied to imaging of early mTBI. In the first study, NODDI was shown to have high precision and repeatability both between and within subject. Furthermore, it was found that small biological changes