Repeatability of automated body composition measurement on low dose chest CT in male subjects

BACKGROUND: The objective was to determine the most repeatable of three automated body composition methods applied to baseline and short-term follow-up chest CT scans. METHODS: Areas of skeletal muscle and subcutaneous adipose tissue (SAT) were analyzed in a 1 mm slice close to the aortic arch in a subset of males from the NELSON lung cancer screening trial with baseline and 3-4 month repeat CT scan. We compared three pre-existing machine learning methods we call: truncated field of view (FOV), compensated FOV, and extended FOV, of which the last two can deal with non-overlapping FOV in scans. Repeatability was assessed using Bland-Altman plots and paired T-tests. RESULTS: Of 562 males the median (interquartile range) age was 60.8 (56.3-64.8) years. Mean skeletal muscle areas were similar for truncated (212 cm²) and extended FOV (211 cm²), and slightly lower for compensated FOV (208 cm²) (p < 0.001). SAT areas were higher with extended FOV (156 cm²) compared to truncated (132 cm²) and compensated FOV (125 cm²) (p < 0.001). A small systematic longitudinal difference in skeletal muscle was observed for extended FOV (mean±SD 1.7 ± 17.3 cm2, p = 0.017). Limits of agreement for skeletal muscle area were -18.9% to 20.4% for truncated FOV, -11.1% to 11.6% for compensated FOV, and -16.7% to 18.2% for extended FOV. Corresponding values for SAT area were -37.3% to 38.3%,-30.2% to 29.3%, and -29.1% to 29.9%. CONCLUSION: Extended FOV had the second-most repeatable measurements and was unaffected by FOV cutoff. Compensated FOV was most repeatable, but underestimated SAT.