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CT-derived body composition and clinical outcomes in ovarian cancer patients: A scoping review
Nikolaj Ohm1, Maria Møller Andersen2, Jakob Ohm Oreskov3
1Department of Gynecology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark; University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen, Denmark.
Introduction:
Epithelial ovarian cancer (EOC) is associated with poor prognosis. Computed tomography (CT)-derived body composition, encompassing muscle and adipose tissue metrics, has emerged as a potential biomarker for prognosis and treatment guidance. This scoping review maps current evidence on associations between CT-derived body composition and clinical outcomes in EOC, with attention to methodological variation and research gaps.
Methods:
The review protocol was prospectively registered in the Open Science Framework on December 11, 2024: https://osf.io/4p5u6. A comprehensive literature search was conducted in Medline (via PubMed), Embase (via Ovid), and Web of Science, following JBI methodology for scoping reviews and PRISMA-ScR guidelines. Eligible studies assessed CT-derived body composition in relation to clinical outcomes among EOC patients.
Results:
50 studies were included, 47 retrospective. Muscle and fat quantities were measured as cross-sectional areas or volumetric estimates, while muscle quality was assessed as skeletal muscle radiodensity in Hounsfield Units (HU). Considerable heterogeneity was observed in measurement techniques, anatomical landmarks, and cut-off definitions for sarcopenia and adiposity. Outcomes investigated included survival, chemotherapy-related, and surgical endpoints. Muscle quality, joint fat-muscle measures, and treatment-related muscle loss were more consistently predictive of survival than muscle mass or adipose tissue alone. Associations with chemotherapy-related and surgical outcomes were less consistent.
Conclusion:
CT-derived body composition may have prognostic relevance in EOC; however, associations remain inconsistent and is largely based on retrospective studies. Findings should therefore be considered hypothesis-generating. Methodological inconsistencies limit clinical applicability and highlight the need for standardized measurement techniques, consensus cut-offs, and prospective validation.
