Authors
Feier Ding, Atsushi Nakamoto, Xiaohan Zheng, Toru Honda, Gongzheng Wang, Yuwei Liu, Hideyuki Fukui, Takashi Ota, Masahiro Yanagawa, Noriyuki Tomiyama
Published in
Journal of cachexia, sarcopenia and muscle. Volume 17. Issue 4. Pages e70366.
Abstract
Intermuscular adipose tissue (IMAT) refers to adipose tissue located between muscle groups or beneath the muscle fascia, and its accumulation is closely linked to impaired muscle quality, reduced contractile function, and adverse metabolic profiles, establishing it as a core component of myosteatosis. Unlike subcutaneous and visceral adipose tissue, which reside outside the muscle architecture, IMAT expands within the muscle environment, where local metabolic and mechanical interactions may affect muscle integrity and performance. Elevated IMAT has been associated with diminished strength, impaired mobility, frailty, insulin resistance, and adverse cardiometabolic profiles, underscoring its clinical relevance beyond a passive fat depot. However, IMAT evidence remains dispersed across imaging techniques, anatomical regions, and disease-specific literatures, limiting a unified understanding of its clinical utility. This review synthesizes current evidence on IMAT biology, imaging-based quantification, disease-specific distribution and clinical implications, with emphasis on its value as a risk-stratification biomarker. Recent advances in medical imaging, including computed tomography (CT), magnetic resonance imaging (MRI), ultrasound and positron emission tomography (PET), have enabled noninvasive and reproducible IMAT quantification. These modalities provide complementary measures of muscle fat infiltration, including CT-derived area, volume and attenuation; MRI-based segmentation and proton density fat fraction; ultrasound echo intensity; and PET-derived metabolic activity. Deep learning-based segmentation methods have improved large-scale IMAT quantification and reproducibility across anatomical regions. Mechanistically, IMAT is associated with chronic low-grade inflammation and impaired glucose homeostasis, promoting progressive fat infiltration and muscle degeneration. Human studies indicate that IMAT exhibits an inflammatory secretory profile linked to insulin resistance and metabolic dysfunction. Quantitative imaging shows anatomically heterogeneous IMAT distribution, with frequent involvement of the lower extremities, paraspinal muscles and trunk. Across disease settings, IMAT appears to provide complementary information beyond muscle mass alone by capturing muscle quality and systemic vulnerability. Evidence is strongest in oncology, where elevated IMAT or IMAT-based ratios have repeatedly been associated with poorer survival, recurrence, treatment toxicity, and reduced treatment tolerance. In metabolic and musculoskeletal disorders, IMAT is consistently related to insulin resistance, reduced strength, impaired mobility, and frailty, whereas cardiovascular evidence suggests prognostic relevance but remains less standardized and more heterogeneous. Clinically, IMAT imaging may help identify patients whose preserved muscle size or body mass index masks poor muscle quality, thereby refining prognostic assessment, perioperative risk evaluation, and selection for nutritional, exercise, metabolic, or treatment strategies. Future efforts should focus on standardized acquisition, automated segmentation, harmonized thresholds, and prospective validation to support integration of IMAT metrics into clinical decision-making.
PMID:
42608355
Bibliographic data and abstract were imported from PubMed on 18 Aug 2026.
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