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Four-Dimensional Magnetic Resonance Pulmonary Flow Imaging for Assessing Pulmonary Vasculopathy in Patients with Postcapillary Pulmonary Hypertension.

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Abstract

Noninvasive techniques for diagnosing combined postcapillary pulmonary hypertension (CpcPH) are unavailable. : To assess the diagnostic performance of cardiac magnetic resonance (CMR)-based four-dimensional (4D)-flow analysis in identifying CpcPH. : Prospective observational study of heart failure (HF) patients with suspected pulmonary hypertension (PH) who underwent simultaneous CMR and right heart catheterization. The 4D-flow biomarkers were calculated using an automatic pipeline. A predictive model including 4D-flow biomarkers associated with CpcPH with a -value < 0.20 was built to determine the diagnostic performance of 4D-flow analysis to identify CpcPH. : A total of 46 HF patients (55.4 ± 14 years, 63% male) with confirmed PH (19 [41%] isolated postcapillary PH [IpcPH], 27 [59%] CpcPH) were included. No differences were found in baseline characteristics, echocardiography, or CMR anatomical and functional parameters, except for a higher Doppler-estimated systolic pulmonary pressure and larger pulmonary artery in CpcPH patients. The 4D-flow CMR analysis was performed in 31 patients (67%). The maximal peak velocity (67.1 [62.2-77.5] cm/s-IpcPH vs. 58.2 [45.8-66.0] cm/s-CpcPH; = 0.021) and maximal helicity (339.9 [290.0-391.8]) cm/s-IpcPH vs. 226.0 (173.5-343.7) cm/s-CpcPH; = 0.026) were significantly lower in patients with CpcPH. A maximal multivariable model including sex, maximal average, and peak velocities, Reynolds number, flow rate, and helicity showed fair diagnostic performance (area under the curve: 0.768 [95%-CI: 0.572-0.963]; sensitivity: 100%; specificity: 55%). : In HF patients with PH, 4D-flow-derived maximal peak velocity and maximal helicity were significantly lower in CpcPH patients. A multiparametric model including maximal 4D-flow-derived biomarkers showed good diagnostic performance for identifying CpcPH.

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This research was funded by the European Regional Development Fund and the Carlos III Research Institute through a grant from the Health Strategy Action (PI17/01569). Jorge Nuche received a predoctoral grant (Jordi Soler Soler) through CIBERCV. JR-C was funded by the Spanish AEI-MCIN (PID2021-123238OB-I00 and PDC2021-121696-I00). B.I. is supported by the European Commission (ERC-CoG 819775, and H2020-HEALTH 945118), by the Spanish Ministry of Science and Innovation (PID2022-140176OB-I00), and by the Comunidad de Madrid (P2022/BMD-7403, RENIM-CM). The CNIC is supported by the ISCIII, the Ministry of Science and Innovation, and the Pro CNIC Foundation. CNIC is a Severo Ochoa Center of Excellence (grant CEX2020-001041-S funded by MICIN/AEI/10.13039/501100011033).

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J Clin Med. 2025 Jan 31;14(3):929.

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