<p><strong>Objectives: </strong>To assess the reliability and validity of the Patient Specific Functional Scale when administered to people living with Parkinson’s Disease.<strong></strong></p> <p><strong>Methods and Materials: </strong>Twenty six people living with Parkinson’s Disease from Hamilton and Burlington were interviewed four times within a four month period. The participants answered the Movement Disorders Sponsored Unified Disease Rating Scale part II, the Parkinson’s Disease Questionnaire 39, and the Patient Specific Functional Scale. Reliability assessment addressed test-retest reliability and reliability of the change scores using Intraclass Correlation Coefficients. Validity assessment focused on convergent construct validity and longitudinal validity by correlating the Patient Specific Functional Scale with the other measures administered.</p> <p><strong>Results: </strong>The<strong> </strong>test retest reliability of the scores yielded by the PSFS was ICCpre= 0.72 (95%CI=0.47-0.86); ICCpost=0.83 (95%CI=0.66-0.92). The reliability of change scores was 0.50. In relation to the validity, no significant correlations were found between the Patient Specific Functional Scale and the other measures. <strong></strong></p> <p><strong>Conclusions: </strong>The PSFS yields reliable scores when it is administered to people living with PD. The Patient Specific Functional Scale does not target the same outcomes as the MDS-UPDRS part II and the PDQ-39. The PSFS does not detect change in functioning in people living with PD within a four month period.</p> / Master of Science (MSc)

[EN] Chronic pain disease has 35-50% of prevalence worldwide. When drugs stop working, spinal cord stimulation (SCS) therapy is a non-drug alternative treatment for several conditions of chronic pain, such as neuropathic pain. In the last 40 years, SCS computational modeling has been the key tool to analyze and understand the effect of the stimulation parameters on neural response. However, the lack of realistic models limits the model-based predictions accuracy for SCS therapy optimization concerning the stimulation parameters management and the development of clinical applications. This thesis presents three improvements in SCS modeling from cellular to organic levels: · Cellular level: a human A -beta sensory myelinated nerve fiber model is shown. The model simulates the action potential creation and propagation of human sensory fibers produced by electrical stimulation. Moreover, to consider the current losses produced at the internodal compartments, a realistic myelin model is included. · Organic level: two spinal cord volume conductor models are presented. The first one is a generalized SCS model, which is based on in vivo 3T high-resolution magnetic resonance images from the human spinal cord, solving then one of the main limitations of previous SCS models, which is the inclusion of cadaveric measurements. The second one is a 3D patient-specific SCS model, which includes the entire spinal cord geometry variation of three different vertebral levels (T8, T9, and T10) from patients undergoing SCS treatment. This novel approach is validated clinically, showing that patient-specific modeling improves model-based predictions accuracy compared to generalized SCS models. In addition to this, this thesis presents three studies related to SCS therapy by using the three computational models developed previously: - Role of stimulation frequency: it is performed using the human A-beta sensory myelinated nerve fiber model. The outcome of this study showed that frequency could have a significant influence on the reduction or increase of the neuron activity, participating thus in the selection of the targeted neural elements in SCS therapy, in tonic stimulation. - Effect of electrode polarity: using the 3D generalized SCS model, the effect of the most used and known polarities (bipolar, guarded cathode, and dual-guarded cathode) is shown. The results showed that, unlike guarded cathode, dual-guarded cathode maximized the activating area and depth in dorsal columns, also increasing the probability of activating dorsal roots fibers. - Clinical applications: the pre-implantation selection of the electrode polarity was performed with the 3D patient-specific model. The findings showed that this clinical application could determine the electrode configurations that best overlapped paresthesia coverage to the painful dermatomes of the patient before the SCS device implant. On the other hand, the effect of offset electrodes was also investigated. In this case, the results revealed that staggered offset placement canceled the left- or right-activation displacement in the dorsal columns, suggesting that offset electrodes placement should be avoided in tonic stimulation. / [ES] El dolor crónico es una enfermedad que tiene una prevalencia de entre el 35% y el 50% de la población mundial. Cuando los fármacos dejan de hacer efecto, la terapia de estimulación de médula espinal (EME) es una alternativa no farmacológica que se usa para el tratamiento de diversas condiciones de dolor crónico, como el dolor neuropático. En los últimos 40 años, el modelado computacional de la EME ha sido la herramienta clave para analizar y entender el efecto de los parámetros de estimulación eléctrica en la respuesta neuronal. Sin embargo, la falta de modelos realistas limita la precisión de las predicciones de los modelos para la optimización de la terapia de EME, en referencia a la programación de los parámetros de estimulación y el desarrollo de aplicaciones clínicas. Esta tesis presenta tres mejoras en el modelado computacional de la terapia de EME, desde el nivel celular hasta el nivel orgánico: · Nivel celular: se presenta un modelo de fibra mielínica A-beta sensitiva humana. El modelo simula la creación y propagación del potencial de acción de fibras humanas sensitivas que se produce bajo el efecto de un estímulo eléctrico. Además, con el fin de considerar las pérdidas de corriente producidas en los compartimentos internodales, la mielina se modeliza de forma realista. · Nivel orgánico: se presentan dos modelos de conductor volumétrico de médula espinal. El primero se trata de un modelo de EME generalizado, el cual está basado en imágenes de resonancia magnética de 3T de alta resolución de médula espinal humana obtenidas in vivo. Esta propuesta resuelve una de las principales limitaciones presente en modelos de EME anteriores, que es la inclusión de medidas geométricas obtenidas de cadáveres. El segundo modelo es un modelo tridimensional personalizado al paciente, el cual incluye la variación de la geometría de la médula espinal en tres niveles vertebrales diferentes (T8, T9 y T10) a partir de pacientes sometidos al tratamiento de EME. Esta novedosa propuesta es validada clínicamente, mostrando además que el modelado computacional personalizado mejora la precisión de las predicciones del modelo en comparación a un modelo generalizado. Además, esta tesis presenta tres estudios relacionados con la terapia de EME usando los tres modelos desarrollados previamente: - El papel de la frecuencia de estimulación: se realiza mediante el uso del modelo de fibra mielínica A -beta sensitiva humana. Los resultados de este estudio muestran que la frecuencia podría tener una influencia significante en la reducción o aumento de la actividad de la neurona, participando de este modo en la selección de los elementos neurales objetivo en la terapia de EME, en estimulación tónica. - Efecto de la polaridad del electrodo: usando el modelo 3D generalizado de EME, se muestra el efecto de las polaridades más conocidas y usadas: bipolar, cátodo guardado y doble-cátodo guardado. Los resultados muestran que, a diferencia del cátodo guardado, la polaridad de doble-cátodo guardado maximiza el área y profundidad de activación en los cordones posteriores, aumentando también la probabilidad de activar las fibras de las raíces dorsales. - Aplicaciones clínicas: usando el modelo 3D personalizado al paciente, se ha realizado la selección pre-implante de la polaridad del electrodo. Los resultados muestran que esta aplicación clínica podría determinar las configuraciones de electrodos que mejor solapan la cobertura de parestesia con los dermatomas dolorosos del paciente antes del implante del dispositivo de EME. Por otro lado, también se ha estudiado el efecto de la posición escalonada de los electrodos en el paciente. En este caso, los resultados revelan que el posicionamiento escalonado cancela el desplazamiento izquierdo o derecho de la activación neuronal en los cordones posteriores, sugiriendo así que el posicionamiento escalonado debería evitarse cuando se aplica la estimu / [CAT] El dolor crònic es una enfermetat amb una prevalència d'entre el 35% i el 50% de la població mundial. Quan els fàrmacs deixen de fer efecte, la teràpia d'estimulació de mèdul·la espinal (EME) és una alternativa no farmacològica que s'usa per al tractament de diverses condicions de dolor crònic, com el dolor neuropàtic. En els últims 40 anys, el modelatge computacional de l'EME ha sigut la ferramenta clau per a analitzar i entendre l'efecte dels paràmetres d'estimulació elèctrica en la resposta neuronal. No obstant això, la falta de models realistes limita la precisió de les prediccions dels models per a l'optimizació de la teràpia d'EME, en referència a la programació dels paràmetres d'estimulació i el desenvolupament d'aplicacions clíniques. Esta tesi presenta tres millores en el modelatge computacional de la teràpia d'EME, des del nivell cel·lular fins al nivell orgànic: · Nivell cel·lular: es presenta un model de fibra mielínica A-beta sensitiva humana. El model simula la creació i propagació del potencial d'acció de fibres humanes sensitives que es produeix baix l'efecte d'un estímul elèctric. A més a més, amb la finalitat de considerar les pèrdues de corrent produïdes als compartiments internodals, la mielina es modela de forma realista. · Nivell orgànic: es presenten dos models de conductor volumètric de mèdul·la espinal. El primer es tracta d'un model d'EME generalitzat, el qual es basa en imatges de ressonància magnètica de 3T d'alta resolució de mèdul·la espinal humana obtingudes in vivo. Esta proposta resol una de les principals limitacions present en models d'EME anteriors, que és la inclusió de mesures geomètriques obtingudes de cadàvers. El segon model és un model tridimensional personalitzat al pacient, el qual inclou la variació de la geometria de la mèdul·la espinal en tres nivells vertebrals diferentes (T8, T9 i T10) a partir de pacients sotmesos al tractament d'EME. Aquesta innovadora proposta és validada clínicament, demostrant també que el modelatge computacional personalitzat millora la precisió de les prediccions del model en comparació a un model generalitzat. A més, esta tesi presenta tres estudis relacionats amb la teràpia d'EME utilitzant els tres models desenvolupats prèviament: - El paper de la freqüència d'estimulació: es realitza mitjançant l'ús del model de fibra mielínica A-beta sensitiva humana. Els resultats d'este estudi mostren que la freqüència podria tindre una influència significant en la reducció o augment de l'activitat de la neurona, participant així en la selecció dels elements neurals objectiu en la teràpia d'EME, en estimulació tònica. - Efecte de la polaritat de l'elèctrode: usant el model 3D generalitzat d'EME, es mostra l'efecte de les polaritats més conegudes i utilitzades: bipolar, càtode guardat i doble-càtode guardat. Els resultats mostren que, a diferència del càtode guardat, la polaritat de doble-càtode guardat maximitza l'àrea i profunditat d'activació en els cordons posteriors, augmentant també la probabilitat d'activar les fibres de les arrels dorsals. - Aplicacions clíniques: usant el model 3D personalitzat al pacient, s'ha realitzat la selecció pre-implant de la polaritat de l'elèctrode. Els resultats mostren que esta aplicació clínica podria determinar les configuracions d'elèctrodes que millor solapen la cobertura de parestèsia amb els dermatomes dolorosos del pacient abans de l'implant del dispositiu d'EME. D'altra banda, també s'ha estudiat l'efecte de la posició esglaonada dels elèctrodes en el pacient. En este cas, els resultats revelen que el posicionament esglaonat cancel·la el desplaçament esquerre o dret de l'activació neuronal en els cordons posteriors, sugerint així que el posicionament esglaonat deuria evitar-se quan s'aplica l'estimulació tònica. / Solanes Galbis, C. (2021). Patient-specific computational modeling for spinal cord stimulation therapy optimization [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/176007

La compréhension clinique et le traitement des maladies cardiovasculaires est extrêmement complexe. Pour chaque patient, les cardiologues sont confrontés à des difficultés pour déterminer la pathologie, choisir une thérapie ou encore sélectionner les patients susceptibles de bien répondre à un traitement donné. Afin de fournir une aide additionnelle aux cardiologues, de nombreuses équipes de recherche étudient la possibilité de planifier de telles thérapies grâce à des modèles biophysiques du cœur. Ils formulent l'hypothèse que l'on peut combiner les données fonctionnelles et anatomiques afin de créer des modèles cardiaques personnalisés à chaque patient qui auraient le potentiel de prédire les bénéfices des différentes thérapies. Les simulations électromécaniques du cœur sont basées sur des modèles informatiques qui peuvent représenter la géométrie, le mouvement et la propagation d'ondes électriques pendant un cycle cardiaque avec suffisamment de précision. L'intégration d'information anatomique, mécanique et électrophysiologique pour un patient donné est essentielle pour construire ce type de modèle.Dans cette thèse, nous présentons tout d'abord les méthodes de personnalisations géométriques, cinématiques et électrophysiologiques nécessaires à toutes modélisations mécaniques. Nous utilisons ensuite le modèle électromécanique de Bestel-Clément-Sorine qui a déjà prouvé avoir un bon réalisme sans être trop complexe au vu des données disponibles. Nous commençons par détailler la nouvelle implémentation de ce modèle dans une plateforme efficace de simulation médicale ayant l'avantage d'être libre et interactive, puis nous analysons les résultats de la simulation par une étude de sensibilité complète.Dans un deuxième temps, nous étudions la possibilité de personnaliser les paramètres mécaniques de ce modèle à partir d'images médicales (IRM). Pour cela, nous proposons en premier lieu une méthode automatique de calibration qui estime les paramètres mécaniques globaux à partir de courbes de pressions et volumes. Cette technique testée sur 6 volontaires et 2 cas pathologiques nous a permis de faire une étude de spécificité qui consiste à déterminer les paramètres pertinents capables de différencier les cas pathologiques des cas sains.Une fois initialisés à ces valeurs calibrées, les paramètres sont personnalisés localement avec un algorithme d'optimisation plus complexe. Le « Reduced Order Unscented Kalman Filtering » est utilisé pour estimer les contractilités de toutes les zones AHA du ventricule gauche à partir des volumes régionaux extraits des séquences d'images IRM. Cette stratégie de personnalisation a été validée et testée sur plusieurs cas pathologiques et volontaires. Ces différentes contributions ont montré des résultats prometteurs tout au long de cette thèse et certains sont déjà utilisés pour quelques études de recherche. / The clinical understanding and treatment of cardiovascular diseases is highly complex. For each patient, cardiologists face issues in determining the pathology, choosing a therapy or selecting suitable patients for the therapy. In order to provide additional guidance to cardiologists, many research groups are investigating the possibility to plan such therapies based on biophysical models of the heart. The hypothesis is that one may combine anatomical and functional data to build patient-specific cardiac models that could have the potential to predict the benefits of different therapies. Cardiac electromechanical simulations are based on computational models that can represent the heart geometry, motion and electrophysiology patterns during a cardiac cycle with sufficient accuracy. Integration of anatomical, mechanical and electrophysiological information for a given subject is essential to build such models.In this thesis, we first introduce the geometry, kinematics and electrophysiology personalizations that are necessary inputs to mechanical modeling. We propose to use the Bestel-Cl'ement-Sorine electromechanical model of the heart, which is sufficiently accurate without being over-parametrized for the available data. We start by presenting a new implementation of this model in an efficient opensource framework for interactive medical simulation and we analyze the resulting simulations through a complete sensitivity analysis.In a second step, the goal is to personalize the mechanical parameters from medical images (MRI data). To this end, we first propose an automatic calibration algorithm that estimates global mechanical parameters from volume and pressure curves. This technique was tested on 7 volunteers and 2 heart failure cases and allowed to perform a preliminary specificity study that intends to determine the relevant parameters able to differentiate the pathological cases from the control cases.Once initialized with the calibrated values, the parameters are then locally personalized with a more complex optimization algorithm. Reduced Order Unscented Kalman Filtering is used to estimate the contractilities on all of the AHA zones of the Left Ventricle, matching the regional volumes extracted from cine MRI data. This personalization strategy was validated and tested on several pathological and healthy cases. These contributions have led to promising results through this thesis and some are already used for various research studies.

De nos jours, les progrès de l’informatisation de l’imagerie médicale assistent au plus près les médecins dans leur soin au patient. Des modèles personnalisés computationnels sont utilisés pour le diagnostique, prognostique et planification du traitement, en diminuant lesrisques pour le patient, et potentiellement les frais médicaux.Heartflow est l’exemple même d’une compagnie qui réussit ce service dans le domaine cardiovasculaire. À partir d’un modèle extrait d’images tomographiques rayons X, les lésions avec impact fonctionnel sont identifiées dans les artères coronaires. Cette analyse qui combine l’anatomie à la fonction est néanmoins limitée par la résolution de l’image. En aval de ces larges vaisseaux, un examen fonctionnel dénommé Imagerie de Perfusion du Myocarde (IPM) met en évidence les régions du myocarde affectées par un déficit de flux sanguin. Cependant, l’IPM n’établie pas de relation fonctionnelle avec les larges vaisseaux coronaires lésés en amont.L’objectif de ce projet est de construire la connexion fonctionnelle entre les coronaires et le myocarde, en extrapolant l’analyse fonctionnelle depuis les larges vaisseaux vers le lit capillaire. À cette fin, il faut étendre le modèle vasculaire jusqu'aux microvaisseaux, et mener une analyse fonctionnelle en direction du comportement myocardique.Nous étendons une méthode de génération d’arbre vasculaire basée sur la satisfaction de principes fonctionnels, nommée Constrained Constructive Optimization (Optimization Constructive sous Contraintes), pour qu’elle s’applique à de multiples arbres vasculaires en compétition. L’algorithme simule l’angiogénèse avec minimisation du volume vasculaire sous contraintes de flux et de géométrie adaptant la croissance simultanée des arbres aux caractéristiques du patient. Cette méthode fournit un modèle hybride composé de coronaires épicardiales extraites d’images et de vaisseaux synthétiques jusqu’aux artérioles, emplissant le ventricule gauche du myocarde.Puis, nous construisons un pipeline d’analyse fonctionnelle multi-échelle pour étendre la simulation de flux depuis les coronaires vers le myocarde. Cela consiste en un modèle de flux coronaire 1D compatible avec la vasculature hybride, et l’analyse de la distribution spatiale des flux provenant des segments terminaux. Cette dernière est réalisée dans une nomenclature similaire à celle de l’IPM pour permettre la comparaison avec des données de vérité terrain fonctionnelles.Nous avons relié l’anatomie du réseau vasculaire à la distribution de flux dans le myocarde pour plusieurs patients. Cette analyse multi-échelle permet d’identifier des pistes pour affiner les méthodes de génération vasculaire et de simulation de flux. Cette extrapolation anatomique et fonctionnelle personnalisée est une première passerelle pour la simulation de perfusion du myocarde à partir d’imagerie tomographique scanner. La construction d’un tel modèle computationnel personnalisé pourrait aider à la compréhension de la physio-pathologie cardiovasculaire complexe et, enfin, à la santé du patient. / Recent advances in medical image computing have allowed automatedsystems to closely assist physicians in patient therapy. Computationaland personalized patient models benefit diagnosis, prognosisand treatment planning, with a decreased risk for the patient,as well as potentially lower cost. HeartFlow Inc. is a successfull exampleof a company providing such a service in the cardiovascularcontext. Based on patient-specific vascular model extracted from XrayCT images, they identify functionally significant disease in largecoronary arteries. Their combined anatomical and functional analysisis nonetheless limited by the image resolution. At the downstreamscale, a functional exam called Myocardium Perfusion Imaging (MPI)highlights myocardium regions with blood flow deficit. However,MPI does not functionally relate perfusion to the upstream coronarydisease.The goal of our project is to build the functional bridge betweencoronary and myocardium, by extrapolating the functional analysisfrom large coronary toward the capillary bed. This objective requiresextension from the coronary model down to the microvasculaturecombined with a functional analysis leading to the myocardium compartment.We expand a tree generation method subjected to functional principles,named Constrained Constructive Optimization, to generate multiplecompeting vascular trees. The algorithm simulates angiogenesisunder vascular volume minimization with flow-related and geometricalconstraints, adapting the simultaneous tree growths to patientpriors. This method provides a hybrid image-based and synthetic geometricmodel, starting from segmented epicardium coronary downto synthetic arterioles, filling the left ventricle myocardium.We then build a multiscale functional analysis pipeline to allowblood flow simulation from the coronaries to the myocardium. Thisis achieved with a 1D coronary model compatible with the hybridvasculature, and a spatial blood flow distribution analysis of the terminalsegments. The latter is performed using a similar nomenclatureto MPI, to enable patient-specific comparison with functional groundtruthdata.We connected the vascular anatomy to blood flow distribution inthe myocardium on several patient datasets. This multiscale frameworkpoints out several leads to refine the vascular network generationand fluid simulation methods. This patient-specific anatomicaland functional extrapolation is a first gateway toward myocardiumperfusion from X-ray CT data. Building such personalized computational model of patient could potentially help investigating cardiovascularcomplex physio-pathology, and, finally, improve the patientcare.

Intracellular redox potential (IRP) is a measure of how oxidising or reducing the environment is within a cell. It is a function of numerous factors including redox couples, antioxidant enzymes and reactive oxygen species. Disruption of the tightly regulated redox status has been linked to the initiation and progression of cancer. However, there is very limited knowledge about the quantitative nature of the redox potential and pH gradients that exist in cancer tumour models. Multicellular tumour spheroids (MTS) are three-dimensional cell cultures that possess their own microenvironments, similar to those found in tumours. From the necrotic core to the outer proliferating layer there exist gradients of oxygen, lactate, pH and drug penetration. Tumours also have inadequate vasculature resulting in a state of hypoxia. Hypoxia is a key player in metabolic dysregulation but can also provide cells with resistance against cancer treatments, particularly chemotherapy and radiation therapy. The primary hypoxia regulators are HIFs (Hypoxia Inducible Factors) which under low O2 conditions bind a hypoxia response element, inhibiting oxidative phosphorylation and upregulating glycolysis which has two significant implications: the first is an increase in levels of NADPH/NADH, the main electron donors found in cells which impacts the redox state, whilst the second is a decrease in intracellular pH (pHi) because of increased lactate production. Thus, redox state and intracellular pHi can be used as indicators of metabolic changes within 3D cultures and provide insight into cellular response to therapy. Surface-Enhanced Raman Spectroscopy (SERS) provides a real-time, high resolution method of measuring pHi and IRP in cell culture. It allows for quick and potentially portable analysis of MTS, providing a new platform for monitoring response to drugs and therapy in an unobtrusive manner. Redox and pH-active probes functionalised to Au nanoshells were readily taken up by prostate cancer cell lines and predominantly found to localise in the cytosol. These probes were characterised by density functional theory and spectroelectrochemistry, and their in vitro behaviour modelled by the chemical induction of oxidative and reductive stress. Next, targeting nanosensors to different zones of the MTS allowed for spatial quantification of redox state and pHi throughout the structure and the ability to map the effects of drug treatments on MTS redox biology. The magnitude of the potential gradient can be quantified as free energy (ΔG) and used as a measurement of MTS viability. Treatment of PC3 MTS with staurosporine, an apoptosis inducer, was accompanied by a decrease in free energy gradients over time, whereas treatment of MTS with cisplatin, a drug to which they are resistant, showed an increase in viability indicating a compensatory mechanism and hence resistance. Finally, using this technique the effects of ionising radiation on IRP and pHi in the tumour model was explored. Following exposure to a range of doses of x-ray radiation, as well as single and multi-fractionated regimes, IRP and pHi were measured and MTS viability assessed. Increased radiation dosage diminished the potential gradient across the MTS and decreased viability. Similarly, fractionation of a single large dose was found to enhance MTS death. This novel SERS approach therefore has the potential to not only be used as a mode of drug screening and tool for drug development, but also for pre-clinical characterisation of tumours enabling clinicians to optimise radiation regimes in a patient-specific manner.

L'anévrisme de l'aorte abdominale est une pathologie devant être traitée par chirurgie quand son diamètre atteint 5.5cm, en raison d’un risque de rupture qui est souvent mortelle. La chirurgie endovasculaire consiste à déployer une endoprothèse dans l’anévrisme pour l’exclure de la circulation sanguine. Cette chirurgie souffre cependant d'un taux relativement élevé de complications post-opératoires à long terme, nécessitant des interventions coûteuses. Ces complications sont principalement d’origine mécanique et pourraient être anticipées grâce à la simulation numérique.Cette thèse a pour objectif d'élaborer une méthodologie de simulation personnalisée de déploiement d'endoprothèses dans des anévrismes, dans le but final de fournir un outil d'aide à la décision aux praticiens hospitaliers pour améliorer leur planning pré-opératoire.Une méthodologie permettant de déployer numériquement des endoprothèses bifurquées, composées de plusieurs modules, dans des anévrismes aortiques personnalisés, de géométries quelconques, a été conçue. Des simulations numériques ont été effectuées sur cinq cas cliniques réels, dont des cas fortement tortueux et complexes àplanifier pour les praticiens hospitaliers. La méthodologie a été validée par comparaison des résultats numériques avec la position des stents sur les scanners post-opératoires.La capacité de la méthodologie numérique à simuler le déploiement d’endoprothèses dans des géométries personnalisées d’anévrismes aortiques a été démontrée. Ces simulations possèdent un fort potentiel, en pouvant permettre de mieux adapter les endoprothèses aux patients et d’anticiper les complications post-opératoires dès le planning pré-opératoire. / Abdominal aortic aneurysm is a pathology which needs to be treated by surgery when its diameter reaches 5.5cm, due to high risk of rupture that is often lethal. Endovascular repair consists in deploying a stent-graft inside the aneurysmal sac to exclude it from the blood flow. However, the drawback of this surgery is the relatively important post-operative complication rate at long-term, requiring costly secondary interventions. The origin of these complications is mainly related to mechanics and therefore, they could be prevented thanks to numerical simulation.The objective of this thesis is to elaborate a simulation methodology to deploy in silico stent-grafts in patient-specific aneurysms. The ultimate goal is to provide practioners with a computer aided decision tool to improve their pre-operative planning.A methodology was developed to simulate the deployment of bifurcated stent-grafts, composed of several modules, in patient-specific aortic aneurysms, whatever their geometry. Finite-element analyses were performed on several clinical cases from real patients, some of them which were highly tortuous and complex for practioners to achieve an accurate preoperative planning. The methodology was validated by comparing numerical results with the position of the stents in the post-operative scans.The ability of finite-element analyses to simulate stent-graft deployment in patient-specific aortic aneurysm geometries was proved in this thesis. Simulations have great potential for adapting stent-grafts to each patient and for anticipating possible post-operative complications at the stage of pre-operative planning.

This doctoral thesis is devoted to studying the possibilities of using additive manufacturing (AM) and design based on computed tomography (CT), for the production of patient-specific implants within orthopedic surgery, initially in a broad perspective and, in the second part of the thesis focusing on customized clavicle osteosynthesis plates. The main AM method used in the studies is the Electron Beam Melting (EBM) technology. Using AM, the parts are built up directly from 3D computer models, by melting or in other ways joining thin layers of material, layer by layer, to build up the part. Over the last 20 years, this fundamentally new way of manufacturing and the rapid development of software for digital 3D reconstruction of anatomical models from medical imaging, have opened up entirely new opportunities for the design and manufacturing of patient-specific implants. Based on the information in a computed tomography (CT) scan, both digital and physical models of the anatomy can be created and of implants that are customized based on the anatomical models.   The main method used is a number of case studies performed, focusing on different parts of the production chain, from CT-scan to final implant, and with several aims: learning about the details of the different steps in the procedure, finding suitable applications, developing the method and trying it out. The first study was on customized hip stems, focusing on the EBM method and its special preconditions and possibilities. It was followed by a study of bone plates, designed to follow the patient-specific bone contour, in this case a tibia fracture including the whole production chain. Further, four cases of patient-specific plates for clavicle fracture fixation were performed in order to develop and evaluate the method. The plates fit towards the patient’s bone were tested in cooperation with an orthopedic surgeon at Östersund hospital. In parallel with the case studies, a method for finite element (FE) analysis of fixation plates placed on a clavicle bone was developed and used for the comparative strength analysis of different plates and plating methods. The loading on the clavicle bone in the FE model was defined on a muscle and ligament level using multibody musculoskeletal simulation for more realistic loading than in earlier similar studies.    The initial studies (papers I and II) showed that the EBM method has great potential, both for the application of customized hip stems and bone plates; in certain conditions EBM manufacturing can contribute to significant cost reductions compared to conventional manufacturing methods due to material savings and savings in file preparation time. However, further work was needed in both of the application areas before implementation. The studies on the fracture fixation using patient-specific clavicle plates indicated that the method can facilitate the work for the surgeon both in the planning and in the operating room, with the potential of a smoother plate with a better fit and screw positioning tailored to the specific fracture (paper VI). However, a large clinical trial is required to investigate the clinical benefit of using patient-specific plates. The FE simulations showed similar stress distributions and displacements in the patient-specific plates and the commercial plates (papers III to VI).   To summarize: the results of this thesis contribute to the area of digital design and AM in patient-specific implants with broad basis of knowledge regarding the technologies used and areas in which further work is needed for the implementation of the technology on a larger scale. Further, a method has been developed and initially evaluated for implementation in the area of clavicle fracture fixation, including an approach for comparing the strength of different clavicle plates.

Les techniques de chirurgie assistée par ordinateur suscitent depuis quelques années un vif intérêt, depuis l’aide au diagnostic jusqu’à l’intervention chirurgicale elle-même, en passant pas les prises de décision. Dans ce but, l’Analyse par Éléments Finis (AEF) du comportement de modèles biomécaniques tridimensionnels est une des méthodes numériques les plus utilisées et les plus efficaces. Cependant, la fiabilité des solutions de l’AEF dépend fortement de la qualité et de la finesse de la représentation des organes sous la forme de maillages d'éléments finis (MEF). Or la génération de tels maillages peut être extrêmement longue et exigeante en ressources computationnelles, car il est nécessaire de procéder à l’extraction précise de la géométrie de l’organe-cible à partir d’images médicales avant de recourir à des algorithmes sophistiqués de maillage. Confrontés à ces enjeux, certains travaux se sont attachés à éviter la procédure de maillage en exploitant des méthodes fondées pour chaque patient sur la déformation géométrique d’un maillage défini sur un sujet de référence, dit « Atlas ». Mais ces méthodes nécessitent toujours une description géométrique précise de l’organe-cible du patient, sous la forme de contours, de modèles surfaciques tridimensionnels ou d’un ensemble de points de référence. Dans ce contexte, le but de la thèse est de développer une méthodologie de conception automatique de maillages « patient-spécifiques », basée sur un Atlas, mais évitant cette étape de segmentation de la géométrie de l’organe-cible du patient. Dans une première partie de la thèse, nous proposons une méthode automatique qui, dans une première phase, procède au recalage volumétrique de l'image anatomique de l’Atlas sur celle du patient, afin d’extraire la transformation géométrique permettant de passer de l’Atlas au patient, puis, dans une seconde phase, déforme le maillage de l’Atlas et l’adapte au patient en lui appliquant cette transformation. Le processus de recalage est conçu de telle manière que la transformation géométrique préserve la régularité et la haute qualité du maillage. L’évaluation de notre méthode, à savoir l'exactitude du processus de recalage inter-sujets, s’est faite en deux étapes. Nous avons d’abord utilisé un ensemble d’images CT de la cage thoracique, en accès libre. Puis nous avons exploité des données IRM de la langue que nous avons recueillies pour deux sujets sains et deux patients souffrant de cancer de la langue, en condition pré- et post-opératoire.Dans une seconde partie, nous développons une nouvelle méthode, toujours basée sur un Atlas, qui exploite à la fois l'information fournie par les images anatomiques et celle relative à la disposition des fibres musculaires telles qu’elle est décrite par imagerie par résonance magnétique du tenseur de diffusion (RM-DT). Cette nouvelle démarche s’appuie ainsi, d’abord sur le recalage anatomique proposé dans notre première méthode, puis sur l’identification et le recalage d’un ensemble de faisceaux de fibres musculaires qui seront ensuite intégrés aux maillages « patient-spécifiques ». Contrairement aux techniques usuelles de recalage d’images RM-DT, qui impliquent pour chaque image la réorientation des tenseurs de diffusion soit au cours de l'estimation de la transformation géométrique, soit après celle-ci, notre technique ne nécessite pas cette réorientation et recale directement les faisceaux de fibres de l’Atlas sur ceux du patient. Notre démarche est très importante, car la détermination et l’identification précises de toutes les sous-structures musculaires nécessiteraient une intervention manuelle pour analyser des milliers, voire des millions, de fibres, qui sont grandement influencées par les limitations et aux distorsions inhérentes aux images RM-DT et aux techniques de tractographie des fibres. L’efficacité de notre méthodologie est démontrée par son évaluation sur un ensemble d’images IRM et RM-DT de la langue d’un sujet. / During the last years, there has been considerable interest in using computer-aided medical design, diagnosis, and decision-making techniques that are rapidly entering the treatment mainstreams. Finite Element Analysis (FEA) of 3D models is one of the most popular and efficient numerical methods that can be utilized for solving complex problems like deformation of soft tissues or orthopedic implant designs/configurations. However, the accuracy of solutions highly depends upon the quality and accuracy of designed Finite Element Meshes (FEMs). The generation of such high-quality subject/patient-specific meshes can be extremely time consuming and labor intensive as the process includes geometry extraction of the target organ and meshing algorithms. In clinical applications where the patient specifiity has to be taken into account via the generation of adapted meshes these problems become methodological bottlenecks. In this context, various studies have addressed these challenges by bypassing the meshing phase by employing atlas-based frameworks using the deformation of an atlas FE mesh. However, these methods still rely on the geometrical description of the target organ, such as contours, 3D surface models, or a set of land-marks.In this context, the aim of this thesis is to investigate how registration techniques can overcome these bottlenecks of atlas-based approaches.We first propose an automatic atlas-based method that includes the volumetric anatomical image registration and the morphing of an atlas FE mesh. The method extracts a 3D transformation by registering the atlas' volumetric image to the subject's one. The subject-specific mesh is then generated by deforming a high-quality atlas FE mesh using the derived transformation. The registration process is designed is such a way to preserve the regularity and the quality of meshes for subsequent FEAs. A first step towards the evaluation of our approach, namely the accuracy of the inter-subject registration process, is provided using a data set of CT ribcage. Then, subject-specific tongue meshes are generated for two healthy subjects and two patients suffering from tongue cancer, in pre- and post-surgery conditions. In order to illustrate a tentative fully automatic process compatible with the clinical constraints, some functional consequences of a tongue surgery are simulated for one of the patients, where the removal of the tumor and the replacement of the corresponding tissues with a passive flap are modeled. With the extraction of any formal priorknowledge on the shape of the target organ and any meshing algorithm, high-quality subject-specific FE meshes are generated while subject’s geometrical properties are successfully captured.Following this method, we develop an original atlas-based approach that employs the information provided by the anatomical images and diffusion tensor imaging (DTI) based muscle fibers for the recognition and registration of fiber-bundles that can be integrated in the subject-specific FE meshes. In contrast to the DT MR images registration techniques that include reorientation of tensors within or after the transformation estimation, our methodology avoids this issue and directly aligns fiber-bundles. This also enables one to handel limited or distorted DTIs by deformation of an atlas fibers’ structure according to the most reliable and non-distorted subject’s ones. Such a manner becomes very important, since the classification and the determination of muscular sub-structures need manual intervention of thousands or millions of fibers for each subject, which are influenced by the limitations associated with the DTI image acquisition process and fiber tractography techniques. To evaluate the performance of our method in the recognition of subject’s fiber-bundles and accordingly in the deformation of the atlas ones, a simulated data set is utilized. In addition, feasibility of our method is demonstrated on acquired human tongue data set.

1 Abstract: Time-dependent and three-dimensional flow of Newtonian fluid is studied in context of two biomechanical applications, flow in cerebral aneurysms and flow in stenotic valves. In the first part of the thesis, the computational meshes obtained from the medical imaging techniques are used for the computation of hemodynamic parameters associated with the rupture potency of the cerebral aneurysms. The main result is the computation within twenty geometries of aneurysms. It is shown that the aneurysm size has more important role in wall shear stress distribution than the fact whether the aneurysm is ruptured or unruptured. The second part of the thesis is addressed to the flow in stenotic valves. It is shown that the method cur- rently used in medical practice is based on assumptions which are too restrictive to be apply to blood flow in the real case. The full continuum mechanics model is presented with physiologically relevant boundary conditions and it is shown that results are consistent with measured data obtained from literature. Then we focus on the obtaining the pressure field from the velocity field. The presented method provides more accurate pressure approximation than commonly used Pressure Poisson Equation. The last chapter of the thesis is dedicated to Nitsche's method for treating slip boundary...

Heart disease is the leading cause of death in the world. Therefore, numerous studies are undertaken to identify indicators which can be applied to discover cardiac dysfunctions at an early age. Among others, the fluid dynamics of the blood flow (hemodymanics) is considered to contain relevant information related to abnormal performance of the heart.This thesis presents a robust framework for numerical simulation of the fluid dynamics of the blood flow in the left ventricle of a human heart and the fluid-structure interaction of the blood and the aortic leaflets.We first describe a patient-specific model for simulating the intraventricular blood flow. The motion of the endocardial wall is extracted from data acquired with medical imaging and we use the incompressible Navier-Stokes equations to model the hemodynamics within the chamber. We set boundary conditions to model the opening and closing of the mitral and aortic valves respectively, and we apply a stabilized Arbitrary Lagrangian-Eulerian (ALE) space-time finite element method to simulate the blood flow. Even though it is difficult to collect in-vivo data for validation, the available data and results from other simulation models indicate that our approach possesses the potential and capability to provide relevant information about the intraventricular blood flow.To further demonstrate the robustness and clinical feasibility of our model, a semi-automatic pathway from 4D cardiac ultrasound imaging to patient-specific simulation of the blood flow in the left ventricle is developed. The outcome is promising and further simulations and analysis of large data sets are planned.In order to enhance our solver by introducing additional features, the fluid solver is extended by embedding different geometrical prototypes of both a native and a mechanical aortic valve in the outflow area of the left ventricle.Both, the contact as well as the fluid-structure interaction, are modeled as a unified continuum problem using conservation laws for mass and momentum. To use this ansatz for simulating the valvular dynamics is unique and has the expedient properties that the whole problem can be described with partial different equations and the same numerical methods for discretization are applicable.All algorithms are implemented in the high performance computing branch of Unicorn, which is part of the open source software framework FEniCS-HPC. The strong advantage of implementing the solvers in an open source software is the accessibility and reproducibility of the results which enhance the prospects of developing a method with clinical relevance. / <p>QC 20171006</p>