Matthew Lee’s research on CT biomarkers could improve understanding of aging
Age is just a number, and CT biomarkers offer a practical alternative to calculating the cumulative effects of aging and disease not captured by chronological age.
Chronological age drives health care decisions though it is an imperfect measure of health. Biological age can provide a more holistic evaluation of the cumulative effects of aging and aging-related disease.
“Imaging biomarkers are an underutilized tool that can improve our understanding of aging and age-related disease,” Matthew Lee, MD, said in the RSNA news article “With CT Imaging Biomarkers, Age Really Is Just a Number.”
Dr. Lee co-authored a RadioGraphics review on CT biomarkers of aging along with John Garrett, PhD; Daniel Liu, MD; and Perry Pickhardt, MD. In 2024, The Wisconsin Alumni Research Foundation recognized Drs. Garrett and Pickhardt as Innovation Awards finalists for their work on developing AI learning-based tools that can be used to determine a biological age and guide improvements in health.
Calculating biological age is typically done using epigenomics, transcriptomics, proteomics and metabolomics. However, CT biomarkers of muscle, fat, aortic calcification, and bone are accessible, can be reproduced, and “reflect big-picture net phenotypic effects of aging at the tissue level,” according to the RadioGraphics review.
Additionally, advancements in AI enable scaling of image-based approaches for population-level impact.
“CT-based biological age expands the role and impact of imaging from disease detection to opportunistic, value-added health assessment with direct relevance to prevention, prognosis and longitudinal care that could transform the healthcare landscape,” Dr. Lee said.
Learn more in the RSNA news article and in the RadioGraphics review.