Journal Article

Single-slice CT measurements allow for accurate assessment of sarcopenia and body composition

Gerecht Lukas, Pinto dos Santos Daniel, Knuever Jana, Borggrefe, Jan, Schlaak, Max, Zopfs, David, Theurich Sebastian, Große Hokamp Nils

2020

Overview

ObjectivesTo evaluate the correlation between simple planimetric measurements in axial computed tomography (CT) slices and measurements of patient body composition and anthropometric data performed with bioelectrical impedance analysis (BIA) and metric clinical assessments.MethodsIn this prospective cross-sectional study, we analyzed data of a cohort of 62 consecutive, untreated adult patients with advanced malignant melanoma who underwent concurrent BIA assessments at their radiologic baseline staging by CT between July 2016 and October 2017. To assess muscle and adipose tissue mass, we analyzed the areas of the paraspinal muscles as well as the cross-sectional total patient area in a single CT slice at the height of the third lumbar vertebra. These measurements were subsequently correlated with anthropometric (body weight) and body composition parameters derived from BIA (muscle mass, fat mass, fat-free mass, and visceral fat mass). Linear regression models were built to allow for estimation of each parameter based on CT measurements.ResultsLinear regression models allowed for accurate prediction of patient body weight (adjusted R2 = 0.886), absolute muscle mass (adjusted R2 = 0.866), fat-free mass (adjusted R2 = 0.855), and total as well as visceral fat mass (adjusted R2 = 0.887 and 0.839, respectively).ConclusionsOur data suggest that patient body composition can accurately and quantitatively be determined by using simple measurements in a single axial CT slice. This could be useful in various medical and scientific settings, where the knowledge of the patient’s anthropometric parameters is not immediately or easily available.Key Points• Easy to perform measurements on a single CT slice highly correlate with clinically valuable parameters of body composition.• Body composition data were acquired using bioelectrical impedance analysis to correlate CT measurements with a non-imaging-based method, which is frequently lacking in previous studies.• The obtained equations facilitate a quick, opportunistic assessment of relevant parameters of body composition.

• Publisher: Springer Nature B.V
• Subject: Adipose tissue / Anthropometry / Assessments / Bioelectricity / Body composition / Body fat / Body weight / Computed tomography / Correlation analysis / Data acquisition / Fat-free body mass / Impedance / Melanoma / Muscles / Parameter estimation / Patients / Regression analysis / Regression models / Sarcopenia / Vertebrae