Machine learning-driven spleen imaging and genomics uncover a splenic connection to coronary artery disease.

Deep learning analysis of spleen MRI features reveals 10 associations with coronary artery disease in over 44,000 participants.

• Why it matters: Understanding the spleen's role in CAD could uncover new mechanisms beyond traditional risk factors, addressing a significant gap in cardiovascular research and improving disease prediction.
• What they did: The study used deep learning to extract 107 radiomic features from MRI scans and performed genome-wide association analysis, identifying 219 genetic loci linked to splenic features and CAD.
• The result: Findings suggest a potential splenic involvement in CAD, especially related to 9p21 variants, but clinical translation faces challenges due to variability in imaging protocols and patient heterogeneity.