TY - JOUR
T1 - Cardiovascular magnetic resonance imaging markers of ageing: A multi-centre, cross-sectional cohort study
AU - Assadi, Hosamadin S.
AU - Zhao, Xiaodan
AU - Matthews, Gareth
AU - Li, Rui
AU - Broncano Cabrero, Jordi
AU - Kasmai, Bahman
AU - Alabed, Samer
AU - Royuela Del Val, Javier
AU - Spohr, Hilmar
AU - Gurung-Koney, Yashoda
AU - Aung, Nay
AU - Nair, Sunil
AU - Swift, Andrew J.
AU - Vassiliou, Vassilios S.
AU - Zhong, Liang
AU - Al-Mohammad, Abdallah
AU - van der Geest, Rob J.
AU - Swoboda, Peter P.
AU - Plein, Sven
AU - Garg, Pankaj
N1 - Data availability: The datasets generated and analysed during the current study are not publicly available. Access to the raw images of patients is not permitted since specialized post-processing imaging-based solutions can identify the study patients in the future. Data are available from the corresponding author upon reasonable request.
Funding: P.G. is funded by the Wellcome Trust (220703/Z/20/Z). The funders had no role in study design, data collection, analysis, publishing decisions, or manuscript preparation. For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.
PY - 2025/5
Y1 - 2025/5
N2 - 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.
AB - 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.
KW - Ageing
KW - Diabetes mellitus
KW - Hypertension
KW - Magnetic resonance imaging (cine)
KW - Obesity
UR - http://www.scopus.com/inward/record.url?scp=105004427267&partnerID=8YFLogxK
U2 - 10.1093/ehjopen/oeaf032
DO - 10.1093/ehjopen/oeaf032
M3 - Article
AN - SCOPUS:105004427267
SN - 2752-4191
VL - 5
JO - European Heart Journal Open
JF - European Heart Journal Open
IS - 3
M1 - oeaf032
ER -
