Image‐Based Biological Heart Age Estimation Reveals Differential Aging Patterns Across Cardiac Chambers

Abstract

Background Biological heart age estimation can provide insights into cardiac aging. However, existing studies do not consider differential aging across cardiac regions. Purpose To estimate biological age of the left ventricle (LV), right ventricle (RV), myocardium, left atrium, and right atrium using magnetic resonance imaging radiomics phenotypes and to investigate determinants of aging by cardiac region. Study type Cross‐sectional. Population A total of 18,117 healthy UK Biobank participants including 8338 men (mean age = 64.2 ± 7.5) and 9779 women (mean age = 63.0 ± 7.4). Field Strength/Sequence A 1.5 T/balanced steady‐state free precession. Assessment An automated algorithm was used to segment the five cardiac regions, from which radiomic features were extracted. Bayesian ridge regression was used to estimate biological age of each cardiac region with radiomics features as predictors and chronological age as the output. The “age gap” was the difference between biological and chronological age. Linear regression was used to calculate associations of age gap from each cardiac region with socioeconomic, lifestyle, body composition, blood pressure and arterial stiffness, blood biomarkers, mental well‐being, multiorgan health, and sex hormone exposures ( n = 49). Statistical Test Multiple testing correction with false discovery method (threshold = 5%). Results The largest model error was with RV and the smallest with LV age (mean absolute error in men: 5.26 vs. 4.96 years). There were 172 statistically significant age gap associations. Greater visceral adiposity was the strongest correlate of larger age gaps, for example, myocardial age gap in women (Beta = 0.85, P = 1.69 × 10 −26 ). Poor mental health associated with large age gaps, for example, “disinterested” episodes and myocardial age gap in men (Beta = 0.25, P = 0.001), as did a history of dental problems (eg LV in men Beta = 0.19, P = 0.02). Higher bone mineral density was the strongest associate of smaller age gaps, for example, myocardial age gap in men (Beta = −1.52, P = 7.44 × 10 −6 ). Data Conclusion This work demonstrates image‐based heart age estimation as a novel method for understanding cardiac aging. Evidence Level 1. Technical Efficacy Stage 1.

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