2406. Comparison of Fully Automated CT-Based Adiposity Assessment at the L1 and L3 Vertebral Levels for Predicting Overall Survival
Authors* Denotes Presenting Author
Daniel Liu *;
University of Wisconsin-Madison School of Medicine and Public Health
John Garrett;
University of Wisconsin-Madison School of Medicine and Public Health
Matthew Lee;
University of Wisconsin-Madison School of Medicine and Public Health
Ryan Zea;
University of Wisconsin-Madison School of Medicine and Public Health
Ronald Summers;
National Institutes of Health Clinical Center
Perry Pickhardt;
University of Wisconsin-Madison School of Medicine and Public Health
Objective:
Quantification of subcutaneous and visceral adipose tissue offers potentially valuable clinical information beyond a patient’s weight or body mass index (BMI). Adipose tissue is metabolically active and contributes to or exacerbates pathological states. Direct quantification of visceral (VAT) and subcutaneous (SAT) adipose tissue is possible with automated techniques and often involves sampling with a region of interest (ROI) is created on a single axial slice, usually between L3-5. The purpose of this study is to compare fully automated CT-based measures of adipose tissue at the L1 level versus the standard L3 level for predicting mortality.
Materials and Methods:
This was a retrospective study of 9066 asymptomatic adults (mean SD age, 57.1 ± 7.8 [SD] years; 4020 men, 5046 women) undergoing unenhanced low-dose abdominal CT for colorectal cancer screening. A previously validated artificial intelligence (AI) tool was used to assess cross-sectional VAT and SAT areas, as well as their ratio (VSR) at the L1 and L3 levels. PostCT survival prediction was compared using area under the ROC curve (ROC AUC) and hazard ratios (HRs).
Results:
Median clinical follow-up interval after CT was 8.8 years (interquartile range (IQR), 5.2–11.6 years), during which 5.9% died (532/9066). No significant difference (p > 0.05) for mortality was observed between L1 and L3 VAT and SAT at 10-year ROC AUC. However, L3 measures were significantly better for VSR at 10-year AUC (p < 0.001). For men, L1 and L3 VSR are likewise different (p < 0.01) and there is also a significant difference between L1 and L3 SAT 10-year AUC (p < 0.001). For women, only L1 and L3 VSR were different (p < 0.01), with a notable increase in the ROC AUC for VSR from 0.612 (95% CI, 0.570-0.655) at L3 to 0.663 (0.622–0.703) at L1. HRs comparing worst-to-best quartiles for mortality at L1 vs. L3 were 2.12 (95% CI, 1.65–2.72) and 2.22 (1.74–2.83) for VAT; 1.20 (0.95–1.52) and 1.16 (0.92–1.46) for SAT; and 2.26 (1.7–2.93) and 3.05 (2.32–4.01) for VSR. In women, the corresponding HRs for VSR were 2.58 (1.80–3.69) (L1) and 4.49 (2.98–6.78) (L3).
Conclusion:
Automated CT-based measures of visceral fat (VAT and VSR) at L1 are predictive of survival, although overall measures of adiposity at L1 level are somewhat inferior to the standard L3 level measures. There were slight differences in the predictive value between men and women, likely attributable to differences in body habitus. Utilizing predictive L1 level fat measures could expand opportunistic screening to chest CT imaging.
