11 research outputs found

    Caractérisation 3d d'images IRM pour l'analyse de l'ostéochondrite primitive de la hanche

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    - L'interface utilisateur dĂ©veloppĂ©e fournit des indices coxomĂ©triques pour caractĂ©riser l'Ă©tat global de l'articulation de la hanche. Le logiciel 3D Slicer sert d'interface pour la visualisation 3D. La technique des ensembles de niveaux est utilisĂ©e pour segmenter chaque type de structure. Elle s'adapte Ă  la topologie de la maladie Ă  caractĂ©riser (fragmentation) et au type d'examen IRM (T1 ou T2). Un modĂšle gĂ©omĂ©trique est ensuite construit. Des indices gĂ©omĂ©triques tridimensionnels sont calculĂ©s automatiquement : excentration de la tĂȘte, volume de la tĂȘte, volume des cartilages cĂ©phalique et acĂ©tabulaire, distance tĂȘte-cotyle. Ces mesures exploitent l'ensemble des images planes IRM et quantifient les dĂ©formations liĂ©es Ă  la maladie. Elles peuvent servir Ă  prĂ©parer une intervention chirurgicale ou Ă  surveiller l'Ă©volution de la maladie

    Comparison of patient-specific computational models vs. clinical follow-up, for adjacent segment disc degeneration and bone remodelling after spinal fusion

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    Spinal fusion is a standard surgical treatment for patients suffering from low back pain attributed to disc degeneration. However, results are somewhat variable and unpredictable. With fusion the kinematic behaviour of the spine is altered. Fusion and/or stabilizing implants carrying considerable load and prevent rotation of the fused segments. Associated with these changes, a risk for accelerated disc degeneration at the adjacent levels to fusion has been demonstrated. However, there is yet no method to predict the effect of fusion surgery on the adjacent tissue levels, i.e. bone and disc. The aim of this study was to develop a coupled and patient-specific mechanoregulated model to predict disc generation and changes in bone density after spinal fusion and to validate the results relative to patient follow-up data. To do so, a multiscale disc mechanoregulation adaptation framework was developed and coupled with a previously developed bone remodelling algorithm. This made it possible to determine extra cellular matrix changes in the intervertebral disc and bone density changes simultaneously based on changes in loading due to fusion surgery. It was shown that for 10 cases the predicted change in bone density and degeneration grade conforms reasonable well to clinical follow-up data. This approach helps us to understand the effect of surgical intervention on the adjacent tissue remodelling. Thereby, providing the first insight for a spine surgeon as to which patient could potentially be treated successfully by spinal fusion and in which patient has a high risk for adjacent tissue changes
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