Abstract #4516

Automatic segmentation for volume quantification of quadriceps muscle head in athletes during an extreme mountain ultra-marathon

Benjamin Gilles¹, Charles de Bourguignon², Pierre Croisille³, Grégoire Millet⁴, Magalie Viallon³, and Olivier Beuf⁵

¹LIRMM; CNRS (UMR 5506) Université de Montpellier, Montpellier, France, ²Radiology Dept, CHU de Saint Etienne, Saint Etienne, France, ³CREATIS, Université de Lyon ; CNRS UMR5220 ; Inserm U1044 ; INSA-Lyon ; Université Claude Bernard Lyon 1, Saint Etienne, France, ⁴Institute of Sport Sciences, University of Lausanne, Lausanne, Switzerland, ⁵CREATIS, Université de Lyon ; CNRS UMR5220 ; Inserm U1044 ; INSA-Lyon ; Université Claude Bernard Lyon 1, Villeurbanne, France

Acute loss of skeletal muscle mass is a common feature of several pathologies such as stroke, cancer, chronic obstructive pulmonary disease. Having a none invasive method to accurately quantify muscle mass is of crucial interest to follow procedure that could prevent muscle wasting and restore physical capacity, mobility and optimize motor recovery. The aim of the current study is to propose an automatic segmentation technique to quantify muscle mass. The automatic segmentation of 3D quadriceps volumes was performed using a deformable registration technique applied to 3D isotropic in-phase (IN), out-phase (OUT), and calculated fat (F) and water (W) images obtained using a double-echo gradient echo Dixon coronal acquisition in order to test the best contrast channel for segmentation. The method was tested in a longitudinal study in athletes enrolled for the most extreme mountain ultra-marathon (The Tor des Géants, Courmayeur, Italy: +24000 positive elevation, 330km). 51 athletes were scans at departure, 27 finishers at the arrival and 2 days after recovery, leading to 105 datasets that were segmented in total. The best automatic segmentation accuracy was obtained when using the calculated Water image (DSC=0,946).

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