Longitudinal evaluation of intra-patient changes in computed tomography-based body composition measures.
Authors
Affiliations (3)
Affiliations (3)
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, USA. [email protected].
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, USA.
- Imaging Biomarkers and Computer-aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, USA.
Abstract
To report longitudinal intra-patient changes in CT-based body composition using fully automated AI tools in an adult patient sample. This retrospective longitudinal study included 15,616 adult patients (mean age at first CT, 53.0āĀ±ā14.7 years; 7096 male, 8520 female) who underwent at least two abdominal CT examinations at least five years apart (mean study interval, 9.1āĀ±ā3.3 years, range, 5.0-20.4 years) at a single academic institution between January 1, 2000 and February 28, 2021. CT examinations were not restricted based on patient setting, clinical indication, or IV contrast media use. Seven fully automated AI body composition tools quantifying vertebral trabecular attenuation, skeletal muscle area and attenuation, visceral adipose tissue (VAT) area and attenuation, subcutaneous adipose tissue (SAT) area, and VAT/SAT ratio (VSR) were applied to each patient's first and last available abdominal CT. Change in body composition per year were determined using the first and last available CT scans. T-test and linear regression were used to assess sex and age as predictors of longitudinal body composition change, respectively. Significant differences in sex-specific mean rates of change were observed for all measures (pā<ā0.05) except muscle attenuation. Certain CT biomarkers showed varying rates of change among younger, middle-age, and older adults. Age significantly predicted body composition measures except VSR in female patients, although effect size was small (R<sup>2</sup> values 0.002-0.040). There are significant age and sex-specific differences in longitudinal, intra-patient body composition changes over time.