Key result
Automated CMR predicts functional heart age exceeds chronological age by ~5 years in comorbid patients.
Why the study?
Cardiac ageing contributes to declining performance, and CMR can detect age-related remodelling, motivating the development of a fully automated model to predict functional heart age.
Does a fully automated CMR model accurately predict functional heart age and detect accelerated cardiac aging in patients with cardiovascular comorbidities?
Cross-Sectional (n=557)
Yes
Does a fully automated CMR model accurately predict functional heart age and detect accelerated cardiac aging in patients with cardiovascular comorbidities?
Effect estimate: Difference 4.6 years (95% CI 1.6-7.6 years)
p-value: p=0.003
A fully automated CMR model using left atrial parameters can estimate functional heart age, demonstrating accelerated cardiac aging in patients with obesity, hypertension, diabetes, and atrial fibrillation.
Supports CMR-derived functional age as marker of comorbidity burden; leaves open utility for risk prediction or management.
Aims Cardiac ageing involves a series of anatomical and physiological changes contributing to a decline in overall performance. Cardiac magnetic resonance (CMR) provides comprehensive structural and functional assessment for detecting age-related cardiovascular remodelling. We aimed to develop a fully automated CMR model to predict functional heart age. Methods and results This international, multi-centre, retrospective observational study enrolled 191 healthy individuals with normal body mass index (BMI), free of metabolic, cardiovascular, and respiratory disease as the derivation cohort. Left atrial (LA) end-systolic volume and LA ejection fraction were selected for the final model. The model was validated on 366 patients with BMI >25 kg/m2 and one or more comorbidities [hypertension, diabetes mellitus (DM), atrial fibrillation (AF), and obesity]. In healthy individuals [median age: 34 years, 105 (55%) female], CMR-derived functional heart age was similar to the chronological age [bias: 0.05%, 95% confidence interval (CI): 9.56–9.67%, P = 0.993]. In the validation cohort [median age: 53 years, 157 (43%) female], CMR-derived functional heart age was 4.6 years higher than chronological age (95% CI: 1.6–7.6 years, P = 0.003). Cardiac magnetic resonance-derived functional heart age was significantly higher in patients with hypertension (P < 0.001), DM (P < 0.001), and AF (P < 0.001) than age-matched healthy controls. Moreover, CMR-derived functional heart age was higher than the chronological age in obesity Class I (P = 0.07), obesity Class II (P = 0.11), and obesity Class III (P < 0.001). Conclusion This study highlights the time course of structural and physiological changes in the heart during healthy and unhealthy ageing. We propose simple equations that should help communicate subtle changes in heart assessment with ageing. Registration ClinicalTrials.gov: NCT05114785
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Assadi et al. (2025) conducted a cross-sectional in Healthy individuals and patients with cardiovascular comorbidities (n=557). CMR-derived functional heart age model vs. Chronological age was evaluated on Difference between CMR-derived functional heart age and chronological age in the validation cohort (Difference 4.6 years, 95% CI 1.6-7.6 years, p=0.003). A fully automated CMR model predicted functional heart age to be 4.6 years higher than chronological age in patients with comorbidities (95% CI: 1.6-7.6 years, P=0.003).
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