Radiomic-based biomarkers: Transforming age and body composition metrics into personalized age-informed indices

Chronological age has been the standard for quantifying the aging process. While it is simple to quantify it cannot fully discern the biological variability of aging between individuals. The growing body of interest in this variability of human aging has led to the introduction of new biomarkers to operationalize biological age. The inclusion of body composition may provide additional value to biological aging as a prediction and estimation factor of individual health outcomes. Diagnostic images based on radiomic techniques such as Computed Tomography contain an untapped wealth of patient-specific data that remain inaccessible to healthcare providers. These images are beneficial for collecting information from body composition that adds precision and granularity when compared to traditional measures. This information can subsequently be aggregated to construct models for changes in the human body associated with aging. In addition, aging leads to a natural decline in the best parameter of drug dosing in older adults, glomerular filtration rate. Since the conventional models of kidney function are correlated with age and body composition, the radiomic biomarkers representing age-related changes in body composition may also serve as potential new imaging biomarkers of kidney function for personalized dosing. Our review introduces potential radiomic biomarkers as measures of body composition change targeting the aging processes. As a functional example, we have hypothesized an age-related model of radiomics as a covariate of kidney function to improve personalized dosing. Future research focusing on evaluating this hypothesis in human subject studies is acknowledged.