Elastic-to-muscular pulmonary artery area ratio and echocardiographic pulmonary arterial systolic pressure in the prediction of pulmonary hypertension: a retrospective cohort study
摘要
This study aimed to evaluate the diagnostic accuracy of the elastic-to-muscular pulmonary artery area ratio (EM-AR) derived from 3D digital models for predicting pulmonary hypertension (PH), both alone and in combination with echocardiographic pulmonary arterial systolic pressure (PASP).
MethodsThis retrospective diagnostic study enrolled 80 patients with suspected PH, using invasive mean pulmonary arterial pressure (mPAP) from right heart catheterization as the reference standard. Cross-sectional areas of elastic (third-order) and muscular (sixth-order) pulmonary arteries in the right lower lobe were measured from 3D digital models to calculate EM-AR. A multivariate linear regression model combining EM-AR and PASP was developed to predict mPAP (mPAPpredicted).
ResultsQuantitative analysis revealed significant remodeling of the pulmonary arterial tree in the PH group, characterized by enlargement of elastic arteries (p < 0.001), reduction in muscular artery area (P < 0.001), and a consequent elevation in the EM-AR (P < 0.001). The EM-AR showed the strongest correlation with invasive mPAP (r = 0.73, P < 0.001) compared to its individual components (elastic artery: r = 0.54, P < 0.001; muscular artery: r = − 0.52, P < 0.001). The composite mPAP, derived from a multiple linear regression model of EM-AR and PASP, correlated strongly with invasive mPAP (r = 0.82, P < 0.001) and achieved superior diagnostic accuracy for PH (AUC = 0.95). At the optimal cut-off of 23.9 mmHg, it identified PH with 83.1% sensitivity and 95.2% specificity.
ConclusionsThe EM-AR derived from 3D-printed digital models appears to be a promising indicator of pulmonary vascular remodeling. In our cohort, a multivariable model combining EM-AR with echocardiographic PASP demonstrated excellent diagnostic performance for the noninvasive prediction of pulmonary hypertension.