{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T12:20:01Z","timestamp":1787746801497,"version":"build-2784847793"},"reference-count":120,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T00:00:00Z","timestamp":1786924800000},"content-version":"vor","delay-in-days":16,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J cachexia sarcopenia muscle"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>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\u2010specific literatures, limiting a unified understanding of its clinical utility. This review synthesizes current evidence on IMAT biology, imaging\u2010based quantification, disease\u2010specific distribution and clinical implications, with emphasis on its value as a risk\u2010stratification 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\u2010derived area, volume and attenuation; MRI\u2010based segmentation and proton density fat fraction; ultrasound echo intensity; and PET\u2010derived metabolic activity. Deep learning\u2013based segmentation methods have improved large\u2010scale IMAT quantification and reproducibility across anatomical regions. Mechanistically, IMAT is associated with chronic low\u2010grade 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\u2010based 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\u2010making.<\/jats:p>","DOI":"10.1002\/jcsm.70366","type":"journal-article","created":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T02:41:16Z","timestamp":1787020876000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Intermuscular Adipose Tissue as a Multimodality Quantitative Imaging Biomarker: Evidence Across Metabolic, Cardiovascular and Oncologic Diseases"],"prefix":"10.1002","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3204-1855","authenticated-orcid":false,"given":"Feier","family":"Ding","sequence":"first","affiliation":[{"name":"Department of Radiology The University of Osaka Graduate School of Medicine  Suita Osaka 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