Automatic assessment of volume asymmetries applied to hip abductor muscles in patients with hip arthroplasty

Christian Klemt; Marc Modat; Jonas Pichat; M. Jorge Cardoso; Joahnn Henckel; Alister Hart; Sebastien Ourselin

doi:10.1117/12.2082341

20 March 2015 Automatic assessment of volume asymmetries applied to hip abductor muscles in patients with hip arthroplasty

Christian Klemt, Marc Modat, Jonas Pichat, M. Jorge Cardoso, Joahnn Henckel, Alister Hart, Sebastien Ourselin

Author Affiliations +

Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 94131M (2015) https://doi.org/10.1117/12.2082341
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Metal-on-metal (MoM) hip arthroplasties have been utilised over the last 15 years to restore hip function for 1.5 million patients worldwide. Althoug widely used, this hip arthroplasty releases metal wear debris which lead to muscle atrophy. The degree of muscle wastage differs across patients ranging from mild to severe. The longterm outcomes for patients with MoM hip arthroplasty are reduced for increasing degrees of muscle atrophy, highlighting the need to automatically segment pathological muscles. The automated segmentation of pathological soft tissues is challenging as these lack distinct boundaries and morphologically differ across subjects. As a result, there is no method reported in the literature which has been successfully applied to automatically segment pathological muscles. We propose the first automated framework to delineate severely atrophied muscles by applying a novel automated segmentation propagation framework to patients with MoM hip arthroplasty. The proposed algorithm was used to automatically quantify muscle wastage in these patients.

Citation Download Citation

Christian Klemt, Marc Modat, Jonas Pichat, M. Jorge Cardoso, Joahnn Henckel, Alister Hart, and Sebastien Ourselin "Automatic assessment of volume asymmetries applied to hip abductor muscles in patients with hip arthroplasty", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94131M (20 March 2015); https://doi.org/10.1117/12.2082341

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