Key result
Non-contrast cardiac CT AI accurately measures LVEDV with ~0.91 correlation to contrast CT.
Why the study?
EF and ESV are prognostic markers, but MRI cost limits use, whereas NCCT may offer functional information alongside coronary artery disease screening.
Does AI-derived ventricular volume and ejection fraction from non-contrast ECG-gated cardiac CT accurately correlate with contrast cardiac CT and MRI in patients undergoing valve planning?
Cohort (n=205)
No
Does AI-derived ventricular volume and ejection fraction from non-contrast ECG-gated cardiac CT accurately correlate with contrast cardiac CT and MRI in patients undergoing valve planning?
Effect estimate: r = 0.91
AI-derived ventricular volumes from non-contrast cardiac CT show strong correlations with contrast CT and can serve as an effective screening tool to reliably rule out significant ventricular dysfunction with a high negative predictive value.
May support non-contrast CT for LVEF screening in valve planning; leaves open prospective MRI validation and outcome studies.
Aims Ejection fraction (EF) and end-systolic volume (ESV) are prognostic markers in cardiovascular disease. While MRI provides accurate assessments, its cost limits widespread use. Non-contrast cardiac CT (NCCT), used for coronary artery disease screening, may offer additional functional information. To evaluate the accuracy of AI-derived ventricular volumes and EF from NCCT compared with contrast cardiac CT (CCT) and MRI. Methods and results This single center study included 205 patients who underwent cardiac CT for valve planning, divided into retrospective and prospective cohorts. A validated AI algorithm was applied to low-dose NCCT images at end-diastole and end-systole. Right (RV) and left ventricles (LV) volumes and their EFs were compared with CCT and MRI. In the prospective cohort (49 women, 53 men; mean age 73.9 ± 10.3 years), NCCT correlated strongly with CCT for LVEDV (152 mL; –14.2% relative difference; r = 0.91) and LVESV (96 mL; +32.6%; r = 0.84), with similar correlations for RVEDV (163 mL; –8.4%; r = 0.82) and RVESV (121.4 mL; +33.1%; r = 0.85). NCCT predicted LVEF <40% with 98% negative predictive value and 87% accuracy. LVEDV correlated strongly with MRI (n = 16) for CCT (240 mL; +4.2%; r = 0.99) and NCCT (197 mL; –14.3%; r = 0.97), as did LVESV for CCT (115 mL; –5%; r = 0.99) and NCCT (134 mL; +11%; r = 0.97). Conclusion AI-derived ventricular volumes from NCCT show moderate to strong correlations, but EF is underestimated. The derived EF can be a screening tool to rule out significant ventricular dysfunction.
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Chao et al. (2025) conducted a cohort in Cardiovascular disease (undergoing valve planning) (n=205). AI-derived ventricular volume and ejection fraction from non-contrast cardiac CT vs. Contrast cardiac CT and cardiac MRI was evaluated on Correlation of left ventricular end-diastolic volume (LVEDV) between non-contrast CT and contrast CT in the prospective cohort (r = 0.91). AI-derived measurements from non-contrast cardiac CT correlated strongly with contrast CT for left ventricular end-diastolic volume (r = 0.91) and accurately predicted LVEF <40% with a 98% negative predictive value.
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