AI-derived ventricular volumes from non-contrast cardiac CT correlated strongly with contrast CT (r=0.91 for LVEDV) and predicted LVEF <40% with 98% negative predictive value and 87% accuracy.
Observational (n=205)
No
Does an AI algorithm applied to non-contrast cardiac CT accurately derive ventricular volumes and ejection fraction compared to contrast CT and MRI in patients undergoing cardiac CT for valve planning?
AI-derived ventricular volumes from non-contrast cardiac CT show strong correlations with contrast CT and MRI, and can serve as a screening tool to rule out significant ventricular dysfunction with high negative predictive value.
Effect estimate: r = 0.91 (LVEDV vs CCT)
Abstract 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.
Chao et al. (Wed,) conducted a observational in Patients undergoing cardiac CT for valve planning (n=205). AI-derived ventricular volumes and ejection fraction from non-contrast cardiac CT (NCCT) vs. Contrast cardiac CT (CCT) and MRI was evaluated on Accuracy of AI-derived ventricular volumes and EF from NCCT compared with CCT and MRI (r = 0.91 (LVEDV vs CCT)). AI-derived ventricular volumes from non-contrast cardiac CT correlated strongly with contrast CT (r=0.91 for LVEDV) and predicted LVEF <40% with 98% negative predictive value and 87% accuracy.