Abstract #3917

Repeatability and accuracy of a novel, MRI-based, semi-automated analysis method for quantifying abdominal adipose tissue and thigh muscle volumes

Michael Simca Middleton¹, William Haufe¹, Jonathan Hooker¹, Magnus Borga^2,3,4, Olaf Dahlqvist Leinhard^2,3,5, Thobias Romu^2,3,4, Patrik Tunon², Nickolas Szeverenyi⁶, Gavin Hamilton⁶, Tanya Wolfson^6,7, Anthony Gamst^6,7, Rohit Loomba⁸, and Claude B. Sirlin¹

¹Department of Radiology, UCSD, San Diego, CA, United States, ²Advanced MR Analytics AB (AMRA), Linkoping, Sweden, ³Center for Medical Image Science and Visualization, Linkoping University, Linkoping, Sweden, ⁴Department of Biomedical Engineering, Linkoping University, Linkoping, Sweden, ⁵Department of Medicine and Health, Linkoping University, Linkoping, Sweden, ⁶Radiology, UCSD, San Diego, CA, United States, ⁷Computational and Applied Statistics Laboratory (CASL), UCSD, San Diego, CA, United States, ⁸Department of Medicine, UCSD, San Diego, United Kingdom

Current MRI methods to estimate body tissue compartment volumes rely on manual segmentation, which is laborious, expensive, not widely available outside specialized centers, and not standardized. To address these concerns, a novel, semi-automated image analysis method has been developed. Image acquisition takes about six minutes, and uses widely available MRI pulse sequences. We found that this method permits comprehensive body compartment analysis and provides high repeatability and accuracy. Current and future clinical and drug development studies may benefit from this methodology, as may clinical settings where monitoring change in these measures is desired.

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