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Towards a Combined Statistical Shape and Musculoskeletal Modeling Framework for Pediatric Shoulder Joint

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Towards a Combined Statistical Shape and Musculoskeletal Modeling Framework for Pediatric Shoulder Joint THESE DE DOCTORAT DE L’ÉCOLE NATIONALE SUPERIEURE MINES-TELECOM ATLANTIQUE BRETAGNE PAYS DE LA LOIRE - IMT ATLANTIQUE ECOLE DOCTORALE N° 601 Mathématiques et Sciences et Technologies de l'Information et de la Communication Spécialité : Signal, Image Vision Par Asma SALHI Towards a Combined Statistical Shape and Musculoskeletal Modeling Framework for Pediatric Shoulder Joint Thèse présentée et soutenue à Brest, le 21/06/2019 Unité de recherche : LaTIM (Laboratoire de traitement de l’Information Médicale) Thèse N° : 2019IMTA0137 Rapporteurs avant soutenance : Composition du Jury : Laurence CHEZE Professeure, Université Claude Dominique LE NEN PU-PH, CHU, Université de Brest Bernard Lyon 1 Président Faten CHAIEB MCU, HDR, INSAT, Tunis Laurence CHEZE Professeure, Université Claude Bernard Lyon 1 Rapportrice Faten CHAIEB MCU, HDR, INSAT, Tunis Rapportrice Marcel LUTHI MCU, Université de Bâle, Suisse Examinateur Bhushan BOROTIKAR Ingénieur de Recherche, CHU, Brest Encadrant Valérie BURDIN Professeure, IMT Atlantique, Brest Directrice de thèse Sylvain BROCHARD PU-PH, CHU, Université de Brest Co-directeur de thèse Acknowledgments I would like to sincerely thank Pr. Valerie Burdin for being supportive and helpful throughout my PhD research and academics. Her guidance in my thesis was truly exceptional. I would also like to express my deepest gratitude to my supervisor Dr. Bhushan Borotikar, whose knowledge and patience have been phenomenal in the completion of this work. His timely inputs and expertise were essential to all the aspects of this thesis project. A particular thanks to Pr. Sylvain Brochard for his constructive recommendations on this project and guidance with the clinical aspects of my work. I appreciate all the discussions with him, which were very valuable in helping me better understand the interest of this project from a clinical perspective. Many thanks to my colleagues from ITI department and LaTIM. I am very fortunate to have worked with many great researchers, clinicians, and surgeons. Their professional and personal support are gratefully acknowledged. I would also like to thank my friends for their support and encouragement. Last but not the least, I would like to thank my family for being the pillar of strength in my success and accomplishments. Vers un framework combinant la modélisation statistique de forme et la modélisation musculo-squelettique pour l’articulation de l’épaule pédiatrique : Résumé étendu 1. Contexte et Motivations L'appareil locomoteur humain est une structure complexe composée d'os, d'articulations, de cartilages articulaires, de muscles et de ligaments [1]. Les mouvements sains du système musculo-squelettique exigent une synchronisation et un équilibre des forces produites par de multiples muscles qui sont contrôlés par le système neuro-musculaire [1, 3]. En cas de maladie ou de trouble, une ou plusieurs composantes de l'appareil locomoteur sont perturbées, ce qui entraîne des mouvements anormaux ou douloureux. Le nombre de maladies et blessures, u’elles soient musculaires ou osseuses, est en augmentation dans le monde entier selon le rapport du CDC de 2017 [4] ou de Barroso et Thiele [5] qui rapportent une tendance similaire. Alors que les maladies musculo-squelettiques résultent d'une réponse physiopathologique à des facteurs internes ou externes, les troubles représentent une perturbation du fonctionnement normal due à ces maladies [2, 3, 6-8]. De nombreux types de maladies, transmissibles et non transmissibles, affectent négativement le système musculo-squelettique. Non seulement cela menace le mode de vie normal des individus, mais cela a aussi un impact négatif sur les dépenses de santé. De plus, les maladies non transmissibles et les blessures sportives perturbent l'appareil locomoteur humain et peuvent rendre la personne vulnérable aux troubles musculo-squelettiques (TMS) (ex. arthrose précoce), ce qui affecte sa qualité de vie [6, 9]. Inévitablement, ces conditions limitent les activités de plein air des populations concernées, réduisent ainsi la croissance normale des enfants et restreignent galeet l’itgatio soiale des séniors. Les pogs ipotats de es deies aes e atie d’iageie diale et des dispositifs diau d’ue pat et des avancées technologiques (Machine Learning, Modélisation computationnelle, impression 3D, etc, ...) d’aute pat, permettent de mieux diagnostiquer et traiter les TMS. C'est particulièrement le cas pour les TMS chez la population pédiatrique où le résultat de ces traitements a un impact à long terme sur le système musculo-squelettique, et par conséquent sur leur qualité de vie [7]. Dans le traitement des TMS pédiatriques, l'imagerie médicale est généralement utilisée à des fins diagnostiques, tandis que les dispositifs médicaux sont davantage utilisés pour le traitement et la réadaptation. Les outils technologiques tels que la modélisation statistique des formes peuvent aider les chirurgiens et les cliniciens pour l'évaluation morphologique de la structure musculo-squelettique [10]. Cependant, ces outils peuvent fournir des informations (tant qualitatives que quantitatives), et une aide précieuse à chaque étape de la gestion des TMS pour évaluer les mécanismes articulaires sous-jacents et les déséquilibres de force [11]. Ces informations comprennent un diagnostic précis (du déséquilibre des forces), des stratégies de traitement optimisées (pour la chirurgie ou la réadaptation), une évaluation précise de la récupération et des visites de suivi (en rétablissant des mécanismes articulaires sains) [12- 16]. Les domaines de modélisation computationnelle comprennent généralement (mais sans s'y limiter) la modélisation par éléments finis, la modélisation par éléments physiques discrets et la modélisation musculo-squelettique multi-corps. La modélisation multi-corps est un moyen efficace et non invasif pour évaluer le fonctionnement du système musculo-squelettique en utilisant des principes de dynamique et en dérivant des paramètres musculaires et articulaires tels que les moments articulaires, les forces musculaires et les bras de levier [17, 18]. Ainsi, la modélisation musculo-squelettique multi-corps permet d'obtenir des cinématiques prédictives, d'effectuer des études de simulation, d'identifier les relations « cause-effet ». Toutefois, le problème de disponibilité des données associées de la structure musculo- squelettique représente un obstacle à la réalisation et l’utilisatio de es odles [1]. En effet, le système musculo-squelettique humain dispose d’u gad oe de variables qui sont difficilement mesurables. L'articulation de l'épaule, l'une des articulations les plus complexes de l'appareil locomoteur, est souvent soumise à de multiples TMS [7, 19-22]. Les troubles les plus courants de l'articulation de l'épaule sont les déchirures de la coiffe des rotateurs, l'arthrose, l'épaule gelée, les fractures et les malformations de l'épaule [8, 9, 20-22]. Pour la plupart de ces TMS, une chirurgie est nécessaire pour la récupération maximale de la otiit de l’paule. Durant la phase préopératoire, il est primordial de connaître la forme pré-morbide de l'os pour optimiser les guides de coupe et mettre en place l'implant, ce qui, à son tour, permet de restaurer la fonction normale de l'épaule. Chez les enfants, d’autes TMS existent comme la paralysie obstétricale de plexus brachiale (POPB). La POPB est une lésion nerveuse qui entraîne une déformation et une paralysie partielle ou totale de membre supérieur [7, 19, 23]. Des interventions thérapeutiques rééducatives et souvent chirurgicales sont souvent proposées pour favoriser la récupération maximale de la motricité. Toutefois, le manque de compréhension du comportement musculaire anormal réduit considérablement le succès du traitement. La modélisation musculo- squelettique peut être utilisée efficacement pour élucider les mécanismes patho-mécaniques de la POBP afin de développer les stratégies d'évaluation clinique, de rééducation fonctionnelle ou de traitement. Cependant, les modèles musculo-squelettiques de l'articulation de l'épaule sont limités dans la littérature et, à ce jour, il n'existe aucun modèle pédiatrique de l'épaule développé pour représenter et étudier le fonctionnement anormal de l’épaule chez les enfants avec POBP [16]. La modélisation musculo-squelettique a été largement utilisée dans la littérature pour évaluer le fonctionnement de l'épaule [22, 24, 25]. Des modèles biomécaniques de l'épaule adulte ont été développés et utilisés pour comprendre les problèmes cliniques [26, 27]. Toutefois, les hypothèses multiples et les cadres de modélisation génériques utilisés dans ces études réduisent l'utilité clinique de ces modèles. Une façon d'éliminer les hypothèses est de mener des expériences, mais ce n'est pas toujours faisable, car la plupart des expériences visant à obtenir de tels paramètres ont tendance à être soit invasives, soit coûteuses. L'imagerie médicale peut également être utilisée pour obtenir certains paramètres. Cependant, les individus doivent passer par un processus d'imagerie qui peut ne pas toujours être faisable ou souhaitable. Par exemple, dans la population pédiatrique, il ’est pas souhaitable d’epose l’efat à plusieus doses de radiation. Une troisième approche novatrice consisterait à combiner la modélisation musculo-squelettique avec des outils de modélisation statistique des formes (MSF) pour profiter des avancées technologiques de chaque domaine. De multiples paramètres nécessaires pour personnaliser les modèles musculo-squelettiques générique pourraient être obtenus en utilisant la
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