Diagnostic index: an open-source tool to classify TMJ OA condyles

Beatriz Paniagua; Laura Pascal; Juan Prieto; Jean Baptiste Vimort; Liliane Gomes; Marilia Yatabe; Antonio Carlos Ruellas; Francois Budin; Steve Pieper; Martin Styner; Erika Benavides; Lucia Cevidanes

doi:10.1117/12.2254070

13 March 2017 Diagnostic index: an open-source tool to classify TMJ OA condyles

Beatriz Paniagua, Laura Pascal, Juan Prieto, Jean Baptiste Vimort, Liliane Gomes, Marilia Yatabe, Antonio Carlos Ruellas, Francois Budin, Steve Pieper, Martin Styner, Erika Benavides, Lucia Cevidanes

Author Affiliations +

Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101372H (2017) https://doi.org/10.1117/12.2254070
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Osteoarthritis (OA) of temporomandibular joints (TMJ) occurs in about 40% of the patients who present TMJ disorders. Despite its prevalence, OA diagnosis and treatment remain controversial since there are no clear symptoms of the disease, especially in early stages. Quantitative tools based on 3D imaging of the TMJ condyle have the potential to help characterize TMJ OA changes. The goals of the tools proposed in this study are to ultimately develop robust imaging markers for diagnosis and assessment of treatment efficacy. This work proposes to identify differences among asymptomatic controls and different clinical phenotypes of TMJ OA by means of Statistical Shape Modeling (SSM), obtained via clinical expert consensus. From three different grouping schemes (with 3, 5 and 7 groups), our best results reveal that that the majority (74.5%) of the classifications occur in agreement with the groups assigned by consensus between our clinical experts. Our findings suggest the existence of different disease-based phenotypic morphologies in TMJ OA. Our preliminary findings with statistical shape modeling based biomarkers may provide a quantitative staging of the disease. The methodology used in this study is included in an open source image analysis toolbox, to ensure reproducibility and appropriate distribution and dissemination of the solution proposed.

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Beatriz Paniagua, Laura Pascal, Juan Prieto, Jean Baptiste Vimort, Liliane Gomes, Marilia Yatabe, Antonio Carlos Ruellas, Francois Budin, Steve Pieper, Martin Styner, Erika Benavides, and Lucia Cevidanes "Diagnostic index: an open-source tool to classify TMJ OA condyles", Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101372H (13 March 2017); https://doi.org/10.1117/12.2254070

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