Artificial Intelligence-Based Assessment of Indices of Right Ventricular Function.

OBJECTIVES:Echocardiographic assessment of right ventricular (RV) function is based largely on visual estimation of tricuspid annulus and motion of the free wall. Regional strain analysis has provided an objective measure of myocardial performance assessment, but is limited in use by vendor-specific software. The study was designed to investigate statistical correlation between RV region-specific strain and echocardiographic parameters of RV function using a vendor-neutral RV-specific strain assessment program. DESIGN:This is a retrospective study. SETTING:Tertiary hospital. PARTICIPANTS:One hundred seven patients undergoing coronary artery bypass graft, valve repair or replacement, or a combination of procedures. INTERVENTION:None. MEASUREMENTS AND MAIN RESULTS:One hundred seven patients underwent comprehensive echocardiographic of RV function intraoperatively. Off-line analysis of global, longitudinal, and septal strain was performed using a vendor-neutral software. The 2 values were compared statistically. All pairs demonstrated strong statistical significance; the strongest relationships were between (1) RV fractional area change (FAC) (%)-RV longitudinal strain (r2 = 0.83, p < 0.001), and (2) tricuspid annular plane systolic excursion (mm)-lateral S' velocity (cm/s) (r2 = 0.80, p < 0.001). The weakest correlations were (1) RV FAC (%)-lateral S' velocity (cm/s) (r2 = 0.37, p < 0.001), and (2) lateral S' velocity (cm/s)-RV longitudinal strain (r2 = 0.40, p < 0.001). CONCLUSION:RV function can be assessed objectively by strain analyses across different platforms using the artificial intelligence-based vendor-neutral strain analysis software. There is a statistically significant correlation between strain values and conventional 2-dimensional echocardiographic parameters of RV function.