Cross-Modality Validation of Abdominal Fat and Muscle Segmentation: A Comparative Study of Dixon MR and CT Imaging
This study evaluates the agreement between Dixon-based MRI and CT in quantifying abdominal muscle and adipose tissue areas, aiming to establish MRI as an accurate, radiation-free alternative to the CT gold standard. Twenty subjects underwent abdominal CT and Dixon MRI on the same day, with matched axial images at L2-L3 and L4-L5 analyzed using semi-automatic software to contour boundaries, apply intensity thresholding, followed by manual refinement of the fat and muscle masks. Bland-Altman plots and linear regression analyses revealed strong agreement between MRI and CT for muscle and subcutaneous adipose tissue (SAT) areas, with mean differences of -0.02 cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and - 1.13 cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and limits of agreement within ±20.46 cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and ±34.71 cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>, respectively, while visceral adipose tissue (VAT) showed larger discrepancies, likely due to compression of the abdomen during MRI, with a mean difference of -18.58 cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and a limit of agreement of 20.34 cm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>. Linear regression confirmed strong correlations with R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> values of 0.89 for muscle, 0.98 for SAT, and 0.93 for VAT. These findings support MRI as a precise and radiation-free alternative for body composition analysis, particularly for muscle and SAT.
Authors
- Elizabeth C. Jones (ORCID: https://orcid.org/0000-0003-4914-8180)
- Li‐Yueh Hsu (ORCID: https://orcid.org/0000-0002-0826-7290)
- Gregg Cohen (ORCID: https://orcid.org/0000-0003-3196-6775)
- Andrew Liu (ORCID: https://orcid.org/0000-0001-9184-6527)
- Andrew Heller
Institutions
- University of America (US)
- National Institutes of Health Clinical Center (US)
- Catholic University of America (US)
Publication Details
- Published
- 2024-12-15
- DOI
- https://doi.org/10.1109/bigdata62323.2024.10826022
- Primary Topic
- Cardiovascular Disease and Adiposity
- Type
- article
- Field-Weighted Citation Impact
- 0.00