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Fully automated CT-based adiposity assessment: comparison of the L1 and L3 vertebral levels for opportunistic prediction

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Abstract

Purpose

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, which would allow for use at both chest (L1) and abdominal (L3) CT.

Methods

This retrospective study of 9066 asymptomatic adults (mean 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 visceral and subcutaneous adipose tissue areas (SAT and VAT), as well as their ratio (VSR) at the L1 and L3 levels. Post-CT 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, 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). 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. Utilizing predictive L1-level fat measures could expand opportunistic screening to chest CT imaging.

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Funding

This study was supported in part by the Intramural Research Program of the National Institutes of Health Clinical Center.

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Author notes

  1. Ronald M. Summers and Perry J. Pickhardt are co-senior authors.

Authors and Affiliations

  1. Department of Radiology, School of Medicine & Public Health, E3/311 Clinical Science Center, University of Wisconsin, 600 Highland Ave, Madison, WI, 53792-3252, USA

    Daniel Liu, John W. Garrett, Matt H. Lee, Ryan Zea & Perry J. Pickhardt

  2. National Institutes of Health Clinical Center, Bethesda, MD, USA

    Ronald M. Summers

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  1. Daniel Liu
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Correspondence to Perry J. Pickhardt.

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Conflict of interest

Author RMS receives royalties from iCAD, ScanMed, PingAn, Philips, Translation Holdings. His lab received research funding through a Cooperative Research and Development Agreement with PingAn. Dr. Pickhardt serves as an advisor to Bracco, Nanox, and GE Healthcare.

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Liu, D., Garrett, J.W., Lee, M.H. et al. Fully automated CT-based adiposity assessment: comparison of the L1 and L3 vertebral levels for opportunistic prediction. Abdom Radiol 48, 787–795 (2023). https://doi.org/10.1007/s00261-022-03728-6

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  • DOI: https://doi.org/10.1007/s00261-022-03728-6

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