Cardiac Magnetic Resonance Imaging for the Evaluation of Pulmonary Hypertension

Abstract Purpose Evaluate the utility of cardiac magnetic resonance imaging for noninvasive estimation of the key hemodynamic parameters that are measured by the right heart catheterization i.e. mean pulmonary artery pressure, pulmonary artery wedge pressure and pulmonary vascular resistance through cardiac magnetic resonance based numerical models. Materials and Methods 29 pulmonary hypertension patients, fitting the inclusion criteria were randomly selected and included in the study. CMR Imaging and right- sided heart catheterization (RHC) were performed within 1 month. 3 Cardiac MRI based models in literature that showed high accuracy were tested. Two equations for mPAP calculation; mPAP= - 231.423 + loge inter-ventricular septal angle X 53.8 + log10 ventricular mass index (right ventricular mass/left ventricular mass) X 8.708 + diastolic pulmonary artery area X 0.009 and mPAP = –4.6 + (interventricular septal angle × 0.23) + (ventricular mass index × 16.3). One equation for PAWP; PAWP = 6.43 + LA volume index x 0.22. Results The Pearson correlation test correlation between invasively quantified and CMR-estimated mPAP had good correlation with r = 0.594 and r = 0.599 (p < 0.001) for CMR based mPAP model 1 and 2, respectively. While, Altman and Bland test showed that The mean bias between the RHC-derived and CMR-estimated mPAP was 7.9 (agreement interval -24.8 to 40.6 mmHg) and mean bias -3 (agreement interval -34.8 to 28.2 mmHg) for CMR based mPAP model 1 and 2, respectively. There was no correlation between invasively quantified and CMR-estimated PAWP with (p = 0.092) for CMR based PAWP model. The mean bias between the RHC- derived and CMR-estimated PAWP was 2.4 (agreement interval –13.5 to 18.2 mmHg). The correlation between invasively calculated and CMR-estimated PVR had good correlation with r = 0.703 and r = 0.704 (p < 0.001) for CMR based PVR model 1 and 2, respectively. The mean bias between the RHC-derived and CMR- estimated mPAP was 0.6 (agreement interval -11.6 to 12.8 mmHg) and mean bias -1.3 (agreement interval -12.1 to 9.5 mmHg) for CMR based mPAP model 1 and 2, respectively. Conclusion our results showed good correlations between CMR findings and RHC as regard mPAP and PVR. Thus Non-invasive estimation of mPAP, PAWP and PVR using CMR is feasible but needs further studies to improve accuracy.