In PloS one ; h5-index 176.0
OBJECTIVE : Waist circumference (WC) is a widely accepted anthropometric parameter of central obesity. We investigated a fully automated body segmentation algorithm for measuring WC on abdominal computed tomography (CT) in comparison to manual WC measurements (WC-manual) and evaluated the performance of CT-measured WC for identifying overweight/obesity.
MATERIALS AND METHODS : This retrospective study included consecutive adults who underwent both abdominal CT scans and manual WC measurements at a health check-up between January 2013 and November 2019. Mid-waist WCs were automatically measured on noncontrast axial CT images using a deep learning-based body segmentation algorithm. The associations between CT-measured WC and WC-manual was assessed by Pearson correlation analysis and their agreement was assessed through Bland-Altman analysis. The performance of these WC measurements for identifying overweight/obesity (i.e., body mass index [BMI] ≥25 kg/m2) was evaluated using receiver operating characteristics (ROC) curve analysis.
RESULTS : Among 763 subjects whose abdominal CT scans were analyzed using a fully automated body segmentation algorithm, CT-measured WCs were successfully obtained in 757 adults (326 women; mean age, 54.3 years; 64 women and 182 men with overweight/obesity). CT-measured WC was strongly correlated with WC-manual (r = 0.919, p < 0.001), and showed a mean difference of 6.1 cm with limits of agreement between -1.8 cm and 14.0 cm in comparison to WC-manual. For identifying overweight/obesity, CT-measured WC showed excellent performance, with areas under the ROC curve (AUCs) of 0.960 (95% CI, 0.933-0.979) in women and 0.909 (95% CI, 0.878-0.935) in men, which were comparable to WC-manual (AUCs of 0.965 [95% CI, 0.938-0.982] and 0.916 [95% CI, 0.886-0.941]; p = 0.735 and 0.437, respectively).
CONCLUSION : CT-measured WC using a fully automated body segmentation algorithm was closely correlated with manually-measured WC. While radiation issue may limit its general use, it can serve as an adjunctive output of abdominal CT scans to identify overweight/obesity.
Joo Ijin, Kwak Min-Sun, Park Dae Hyun, Yoon Soon Ho