Utilizing Opportunistic Computed Tomography Imaging to Refine Lean Body Weight Estimates in Patients with Obesity.

Abstract

Introduction: While dual-energy X-ray absorptiometry (DEXA) is the gold standard for measuring lean body weight (LBW), computed tomography (CT) provides muscle composition and distribution metrics that can refine LBW for better weight-based dosing. We explored how existing computed tomography (CT) images could be utilized to better estimate LBW.

Methods: Sixty-three adult patients (71.4% female) with a median age of 53.4 years and mean BMI of 36.84 having both DEXA and CT scans were retrospectively analyzed to assess the relationship between CT-based skeletal muscle variables and DEXA-derived LBW.

Results: Linear regression results revealed significant correlations. CT-derived skeletal muscle area (SMA) strongly predicted DEXA-derived LBW (p value < 0.05 and R² between 0.67 and 0.80) at four different vertebra levels. DEXA-derived LBW showed a strong correlation with a height, weight, and sex-based estimate of LBW using an equation developed in 2005 (LBW₂₀₀₅). A final model incorporating SMA with the LBW₂₀₀₅ equation improved the coefficient of determination at all four vertebra levels (R² 0.82-0.86).

Discussions/conclusion: This study demonstrates opportunistic CT scan data may improve an existing equation for LBW that has been predictive of select drug pharmacokinetic parameters. Improving LBW estimation may enable improved personalized drug dosing strategies in patients with obesity and other populations that benefit from using LBW over total body weight.