IMAGING BIOMARKERS OF SARCOPENIA IN METABOLIC DISEASES: TOWARD PRECISION DIAGNOSIS AND RISK STRATIFICATION
Main Article Content
Keywords
Sarcopenia, Metabolic syndrome, Myosteatosis.
Abstract
Sarcopenia, characterized by loss of skeletal muscle mass and quality, is increasingly recognized as a key contributor to metabolic diseases such as metabolic syndrome, type 2 diabetes mellitus, obesity, and NAFLD/MASLD. Conventional clinical assessments lack the ability to directly quantify muscle composition, whereas imaging modalities offer objective and reproducible biomarkers.
Aim and Objectives: This narrative review aimed to synthesize current evidence on quantitative imaging biomarkers of sarcopenia assessed using CT, MRI, DXA, and ultrasound in adults with metabolic diseases.
Methodology: A structured literature search was conducted across PubMed/MEDLINE, Embase, Scopus, and Web of Science to identify relevant original studies published between 2015 and 2025. Original studies involving adult populations with metabolic diseases and imaging-based assessments of muscle mass or quality were included. Data were qualitatively synthesized due to heterogeneity in study designs and sarcopenia definitions.
Results: Across imaging modalities, reduced muscle mass and increased myosteatosis were consistently associated with metabolic diseases. CT- and MRI-derived biomarkers revealed strong associations with metabolic syndrome, insulin resistance, NAFLD/MASLD progression, and type 2 diabetes. The prevalence of sarcopenia or adverse muscle composition ranged from approximately 14% to 36% depending on population and disease type.
Conclusion: Quantitative imaging biomarkers provide valuable insights into muscle quantity and quality that extend beyond traditional anthropometric measures. Incorporation of CT, MRI, DXA, and ultrasound into clinical and opportunistic screening can enhance early detection, precision diagnosis, and risk stratification of sarcopenia in metabolic diseases.
Standardization of imaging thresholds and longitudinal validation are needed to support broader clinical implementation.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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Mr. Bharat Bhushan Dagur
PhD Scholar, Department of Radiodiagnosis, SMC, Santosh Deemed to be University, Ghaziabad Uttar Pradesh, India.
Dr. Ashish Kumar Shukla
Professor and HOD, Department of Radiodiagnosis, SMC, Santosh Deemed to be University, Ghaziabad Uttar Pradesh, India
Ms. Rukamanee
PhD Scholar, Department of Radiodiagnosis, SMC, Santosh Deemed to be University,
Ghaziabad Uttar Pradesh, India
Mr. Shivanshu Chauhan
PhD Scholar, Department of Radiodiagnosis, SMC,Santosh Deemed to be University, Ghaziabad Uttar Pradesh, India.
Ms. Anshu Kumari
PhD Scholar, Department of Radiodiagnosis, SMC,Santosh Deemed to be University,
Ghaziabad Uttar Pradesh, India
Ms. Vratika Arya
PhD Scholar, Department of Radiodiagnosis, SMC,Santosh Deemed to be University, Ghaziabad Uttar Pradesh, India
