Background Pulmonary hypertension (PH) is defined by a resting mean pulmonary artery pressure (mPAP) ≥25 mmHg by right heart catheterization. Systolic pulmonary artery pressures are used as surrogate non-invasive markers of PH. A direct prediction tool of non-invasive mPAP would provide the capacity to diagnose disease through non-invasive means. It remains unclear if a multi-parametric cardiac magnetic resonance (CMR) integrated approach can provide an accurate measure of invasive mPAP.
Purpose This study sought to develop a novel CMR model using both established and newly derived CMR metrics for estimating mean pulmonary artery pressure.
Methods 18 patients were prospectively recruited at a large tertiary PH unit. All patients underwent right heart catheterisation (RHC) and CMR on the 1.5 T scanner (HDx scanner, GE Healthcare, Waukesha, Wisconsin, USA), using an 8-channel cardiac coil. CMR protocol included long and short axis cines and through-plane pulmonary artery phase contrast acquisition. The velocity encoded images were analysed for the following: mean pulmonary artery pan-systolic velocity (PASV), MPA stroke volume, MPA wall shear stress (WSS) and wall shear rate (WSR). The 4-chamber cine was used to measure end-diastolic right atrial area. Right ventricular volumes were analysed using standard methods. Stepwise multiple regression model of significantly associated parameters (p<0.05) was developed.
Results Mean age of the 18 patients was 68.78±7.46 years (44% males). The following CMR metrics demonstrated significant association to the measured mPAP: RA area (r=0.65 p=0.03); MPA mean pan-systolic velocity (r=−0.57 p=0.01); RVEDV (r=0.52 p=0.03); RVEF (r=−0.40 p=0.10); RVESV (r=0.58 p=0.01). In stepwise multiple regression, only two parameters demonstrated independent association to mPAP - RA Area and MPA mean pan-systolic velocity. The predicted mPAP demonstrated good correlation to the measured mPAP (R=0.76, p<0.001).
Conclusion(s) Mean pulmonary artery systolic velocity and right atrial area are independently associated with mPAP. Ournovel CMR prediction model for mPAP, comprising of these two metrics, demonstrates high association to the measured mPAP by invasive haemodynamic study.
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