Abstract / Summary
Background/Objectives: Advanced Computed Tomography (CT) enables multiparametric characterization of local perivascular and regional or systemic adipose tissue, potentially providing markers of vascular inflammation and cardiometabolic remodeling beyond conventional assessment of the vessel lumen and plaque. However, evidence remains fragmented across CT technologies, adipose depots and vascular territories. This systematic review evaluated human studies of adipose-tissue biomarkers derived from dual-layer spectral-detector CT (DLSCT), dual-source dual-energy CT (DS-DECT), rapid kVp-switching dual-energy CT (rsDECT), and photon-counting CT (PCCT) in coronary and carotid atherosclerosis. Methods: PubMed and Scopus were systematically searched for English-language human studies published from 1 January 2020, to 13 September 2026, supplemented by backward and forward citation searching of eligible studies and reference-list screening of relevant reviews. Two reviewers independently performed study selection and risk-of-bias assessment. Because of clinical, technical, and methodological heterogeneity, findings were synthesized narratively without meta-analysis. Results: Nineteen reports representing 15 likely independent study clusters met the inclusion criteria. DLSCT-derived pericoronary adipose-tissue attenuation; DECT-derived carotid perivascular adipose-tissue parameters; PCCT-derived adipose attenuation, volume, and radiomic features; and spectral measures of hepatic or visceral adiposity were associated with coronary artery disease, stenosis severity, high-risk plaque features, coronary calcification, or symptomatic carotid disease. Reported discrimination estimates were heterogeneous across populations, endpoints, and model structures and were predominantly derived from unvalidated development samples. Conclusions: Advanced CT-derived adipose-tissue biomarkers may complement conventional assessment of the vessel lumen and plaque by characterizing local vessel–adipose interactions and systemic cardiometabolic phenotype. However, current measurements are protocol- and platform-dependent, and clinical utility has not been established. Standardized measurement pipelines, biological validation, and prospective multicenter studies are required before routine clinical implementation.