Meeting Banner
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 Borga2,3,4, Olaf Dahlqvist Leinhard2,3,5, Thobias Romu2,3,4, Patrik Tunon2, Nickolas Szeverenyi6, Gavin Hamilton6, Tanya Wolfson6,7, Anthony Gamst6,7, 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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here