Abstract:

Objective To investigate the clinical value of fully automated three⁃dimensional echocardiog⁃ raphy right ventricular quantification software（3D Auto RV）in evaluating right ventricular systolic function in patients with chronic pulmonary heart disease（CPHD）. Methods According to clinical manifestations，88 patients with CPHD were divided into the compensated group（n = 48）and the decompensated group（n = 40），and 40 healthy subjects served as controls. To measure the routine ultrasound parameters of the subjects ，and apply 3D Auto RV measures right ventricular end ⁃ diastolic volume（RVEDV），right ventricular end ⁃ systolic volume （RVESV），right ventricular stroke volume（RVSV），right ventricular ejection fraction（RVEF），tricuspid annular plane systolic excursion（TAPSE），right ventricular fractional area change（RVFAC），longitudinal strain of free wall（FWLS），longitudinal strain of ventricular septum（SLS），and the difference among groups were compared. Results （1）Compared with the control group，TAPSE，RVFAC，RVEF，FWLS and SLS were decreased，while RVEDV and RVESV were increased in CPHD groups（P < 0.05）. The RVSV of the decompensated group was significantly lower than that of the control group and the compensated patients（P < 0.05），but there was no sig⁃ nificant difference between the compensatory group and the control group（P > 0.05）. Compared with the compensated group，TAPSE，RVFAC，RVEF and FWLS were further decreased，RVEDV and RVESV were further increased in the decompensated group（P < 0.05），and SLS had no significant difference（P > 0.05）.（2）FWLS had a high correlation with RVEF（r = -0.721，P < 0.001）.（3）The optimal cut⁃off value of RVEF for predicting the decompensated phase of CPHD was 41.35%（AUC = 0.95，P < 0.001）.（4）Repeatability test showed that both RVEF and FWLS had good repeatability. Conclusion 3D Auto RV can accurately evaluate the right ventricularsystolic function in patients with CPHD，which is expected to become a new method for clinical evaluation of the severity of CPHD.

Key words:

fully automated three?dimensional echocardiography right ventricular quantification, chronic pulmonary heart disease, ventricular function, right, artificial intelligence