Description du projet :
ENGLISH:
Femoroacetabular impingements (FAI) is defined as a painful dynamic abutment between the hip socket and the femoral head. It is a major cause of primary hip osteoarthritis and one of the key risk factors that may lead to early cartilage and labral damage in young adults. The therapy of FAI involves the surgical resection of the impinging areas of the acetabulum and the proximal femur. Based on a strong research experience on FAI, we know that its diagnosis is difficult and that the current gold standard is problematic as it requires the direct intraoperative visualization of the impingement conflict. A less invasive approach relies on a radiological analysis of standard 2D radiographs and MR images - a task however not automated and whose quality depends on the physician’s expertise. Virtual 3D impingement simulations provide a more objective and accurate way to study FAI but most approaches rely on CT scans, which expose patients to high doses of radiation. MR images were used as a non-invasive alternative to build 3D models for FAI analysis but the resulting approaches were often not fully automatic or required conditions sometimes incompatible with clinical setups (e.g., MR images with large field-of-view (FOV))
This project will develop an efficient method to generate 3D anatomical models using Computed Tomography (CT)-free imaging protocols that are used in clinical routine in order to support computer-assisted diagnosis and surgical planning of FAI. We will devise a fully automatic approach based on multi-modal images combining 2D X-ray radiograph with 3D Magnetic Resonance (MR) Images acquired with small FOV. In order to achieve this goal, we are aiming to develop A) a fully automatic, machine learning based approach for segmenting 3D MRI data acquired with small FOV; B) a disease-specific, articulated statistical shape model (DS-aSSM) based 2D-3D reconstruction technique to generate 3D patient-specific models from 2D X-rays; and C) a robust multi-modal data fusion method to fuse models generated from A) and B).Scientific and Social Impact of the Research ProjectAlthough there are many risk factors contributing to hip osteoarthritis (HOA), it is now generally accepted that more subtle bony abnormalities associated with FAI and/or developmental dysplasia (DD) contribute substantially to HOA. Various studies have suggested that computer-assisted 3D modeling techniques can help clinicians to better understand the dynamic and static factors of FAI - via patient-specific pre-operative planning and intra-operative assessment. Capitalizing on standard FAI diagnosis imaging protocol, i.e., conventional X-rays and MRI, to reduce radiation and to avoid unnecessary disruption to the standard clinical workflow, the proposed CT-free 3D anatomical model generation approach will facilitate a future wide-spread access of computational simulation and virtual surgical planning techniques for patients with FAI and address a key social challenge of our society.
FRENCH:
Le projet vise à développer des approches assistées par ordinateur pour créer des modèles personnalisées de la hanche dans le but d’étudier et traiter les conflits fémoro-acétabulaires.
L’originalité du projet réside dans l’utilisation d’acquisitions radiologiques très peu invasives (radiographies et IRM) et dans la création de méthodes informatisées robustes et totalement automatisées.
Les conflits fémoro-acétabulaires sont une des causes majeures de coxarthrose primaire et sont à l’origine de lésions du cartilage et du labrum chez les jeunes adultes. Il est estimé que 10 à 15% de la population adulte serait atteinte par une des formes de ces conflits. Afin de restituer au patient mobilité et confort, le traitement chirurgical est souvent nécessaire. Celui-ci nécessite alors une planification précise qui se base notamment sur la localisation des conflits sur les surfaces articulaires.
Equipe de recherche au sein de la HES-SO:
Schmid Jérôme
, Chênes Christophe
Partenaires académiques: Zheng Guoyan, Université de Berne, ISTB; Tannast Moritz, Université de Berne, Inselspital
Durée du projet:
01.07.2018 - 30.04.2019
Montant global du projet: 174'463 CHF
Statut: Terminé
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