Computerized Automated Quantification of Subcutaneous and Visceral Adipose Tissue From Computed Tomography Scans: Development and Validation Study

Background: Computed tomography (CT) is often viewed as one of the most accurate methods for measuring visceral adipose tissue (VAT). However, measuring VAT and subcutaneous adipose tissue (SAT) from CT is a time-consuming and tedious process. Thus, evaluating patients' obesity levels during clinical trials using CT scans is both cumbersome and limiting.

Objective: To describe an image-processing-based and automated method for measuring adipose tissue in the entire abdominal region.

Methods: The method detects SAT and VAT levels using a separation mask based on muscles of the human body. The separation mask is the region that minimizes the unnecessary space between a closed path and muscle area. In addition, a correction mask, based on bones, corrects the error in VAT.

Results: To validate the method, the volume of total adipose tissue (TAT), SAT, and VAT were measured for a total of 100 CTs using the automated method, and the results compared with those from manual measurements obtained by 2 experts. Dice's similarity coefficients (DSCs) between the first manual measurement and the automated result for TAT, SAT, and VAT are 0.99, 0.98, and 0.97, respectively. The DSCs between the second manual measurement and the automated result for TAT, SAT, and VAT are 0.98, 0.98, and 0.97, respectively. Moreover, intraclass correlation coefficients (ICCs) between the automated method and the results of the manual measurements indicate high reliability as the ICCs for the items are all .99 (P<.001).

Conclusions: The results described in this paper confirm the accuracy and reliability of the proposed method. The method is expected to be both convenient and useful in the clinical evaluation and study of obesity in patients who require SAT and VAT measurements.