Keywords: Flow, Heart, Athlete; Pulmonary artery; 4D flow
Motivation: Long-term intense training in athletes can lead to pathological cardiac remodeling (CR) and potential myocardial fibrosis (MF), raising cardiovascular risks.
Goal(s): Employ 4D flow MRI to study pulmonary arterial hemodynamics in athletes and explore correlations with CR and MF.
Approach: Scanned 121 athletes and 21 controls using 3 T MRI scanner; 4D flow data analysis on CVI42; built machine learning models for differentiation based on cardiovascular conditions.
Results: Found significant associations between the altered pulmonary arterial hemodynamics parameters and CR and/or MF. Machine learning models identified athletes with cardiac anomalies.
Impact: We indicated that exercise can induce remodeling of the pulmonary circulation in athletes. The evaluation of pulmonary arterial 4D flow hemodynamics parameters can be beneficial for clinical follow-up of athletes.
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