Associations of MRI-derived Paraspinal IMAT and LMM with Cardiometabolic Risk Factors: Results from a German Cohort

Radiology 2026

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Authors: Sebastian Ziegelmayer, Hartmut Häntze, Christian Mertens, Felix Busch, Tristan Lemke, Markus Graf, Nassir Navab, Shahrooz Faghihroohi, Jakob Nikolas Kather, Daniel Truhn, Thomas J. Kröncke, Jacqueline Lammert
+19 more Su Hwan Kim, Benedikt Wiestler, Jeanette Schulz-Menger, Annette Peters, Henry Völzke, Robin Bülow, Thoralf Niendorf, H U Kauczor, Tobias Nonnenmacher, Tobias Pischon, Steffen Ringhof, Christopher L. Schlett, Jakob Weiss, Fabian Bamberg, Ulrike Streit, Martin Hadamitzky, Marcus R. Makowski, Lisa Adams, Keno Bressem
DOI: 10.1148/radiol.251347
Cited by: 1
References: 33

Abstract

Artificial intelligence–derived muscle composition from whole-body MRI scans identified individuals with cardiometabolic risk factors but no pre-existing conditions in a nationwide population.

Fields of Study & Subjects

Cardiac tumors and thrombi Cerebrovascular and Carotid Artery Diseases Advanced MRI Techniques and Applications

Publication details

Journal / source
Radiology
Publisher
Radiological Society of North America (RSNA)
Volume
319
Issue
2
Pages
e251347–e251347
Publication date
1 May 2026
Language
EN