Adjusting for the effect of IV contrast on automated CT body composition measures during the portal venous phase

Alexander R Moeller; John W Garrett; Ronald M Summers; Perry J Pickhardt

doi:10.1007/s00261-024-04376-8

Adjusting for the effect of IV contrast on automated CT body composition measures during the portal venous phase

Abdom Radiol (NY). 2024 May 15. doi: 10.1007/s00261-024-04376-8. Online ahead of print.

Authors

Alexander R Moeller¹, John W Garrett¹, Ronald M Summers², Perry J Pickhardt³

Affiliations

¹ Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center 600 Highland Ave., Madison, WI, 53792-3252, USA.
² Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA.
³ Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center 600 Highland Ave., Madison, WI, 53792-3252, USA. ppickhardt2@uwhealth.org.

PMID: 38744704
DOI: 10.1007/s00261-024-04376-8

Abstract

Objective: Fully-automated CT-based algorithms for quantifying numerous biomarkers have been validated for unenhanced abdominal scans. There is great interest in optimizing the documentation and reporting of biophysical measures present on all CT scans for the purposes of opportunistic screening and risk profiling. The purpose of this study was to determine and adjust the effect of intravenous (IV) contrast on these automated body composition measures at routine portal venous phase post-contrast imaging.

Methods: Final study cohort consisted of 1,612 older adults (mean age, 68.0 years; 594 women) all imaged utilizing a uniform CT urothelial protocol consisting of pre-contrast, portal venous, and delayed excretory phases. Fully-automated CT-based algorithms for quantifying numerous biomarkers, including muscle and fat area and density, bone mineral density, and solid organ volume were applied to pre-contrast and portal venous phases. The effect of IV contrast upon these body composition measures was analyzed. Regression analyses, including square of the Pearson correlation coefficient (r²), were performed for each comparison.

Results: We found that simple, linear relationships can be derived to determine non-contrast equivalent values from the post-contrast CT biomeasures. Excellent positive linear correlation (r² = 0.91-0.99) between pre- and post-contrast values was observed for all automated soft tissue measures, whereas moderate positive linear correlation was observed for bone attenuation (r² = 0.58-0.76). In general, the area- and volume-based measurement require less adjustment than attenuation-based measures, as expected.

Conclusion: Fully-automated quantitative CT-biomarker measures at portal venous phase abdominal CT can be adjusted to a non-contrast equivalent using simple, linear relationships.

Keywords: Abdomen; CT; Deep learning; Machine learning.