Pulmonary Arteriovenous Pressure Gradient and Time-Averaged Mean Velocity of Small Pulmonary Arteries Can Serve as Sensitive Biomarkers in the Diagnosis of Pulmonary Arterial Hypertension: A Preclinical Study by 4D-Flow MRI

Nahardani, Ali; Leistikow, Simon; Grün, Katja; Krämer, Martin; Herrmann, Karl-Heinz; Schrepper, Andrea; Jung, Christian; Moradi, Sara; Schulze, Paul Christian; Linsen, Lars; Reichenbach, Jürgen R; Hoerr, Verena; Franz, Marcus

Research article (journal) | Peer reviewed

Abstract

(1) Background: Pulmonary arterial hypertension (PAH) is a serious condition that is associated with many cardiopulmonary diseases. Invasive right heart catheterization (RHC) is currently the only method for the definitive diagnosis and follow-up of PAH. In this study, we sought a non-invasive hemodynamic biomarker for the diagnosis of PAH. (2) Methods: We applied prospectively respiratory and cardiac gated 4D-flow MRI at a 9.4T preclinical scanner on three different groups of Sprague Dawley rats: baseline (n = 11), moderate PAH (n = 8), and severe PAH (n = 8). The pressure gradients as well as the velocity values were analyzed from 4D-flow data and correlated with lung histology. (3) Results: The pressure gradient between the pulmonary artery and vein on the unilateral side as well as the time-averaged mean velocity values of the small pulmonary arteries were capable of distinguishing not only between baseline and severe PAH, but also between the moderate and severe stages of the disease. (4) Conclusions: The current preclinical study suggests the pulmonary arteriovenous pressure gradient and the time-averaged mean velocity as potential biomarkers to diagnose PAH.

Details about the publication

JournalDiagnostics
Volume12
Issue1
Page range58--
Article number-
StatusPublished
Release year2022
Language in which the publication is writtenEnglish
DOI10.3390/diagnostics12010058
Link to the full texthttps://api.elsevier.com/content/abstract/scopus_id/85122675690
Keywords4D-flow; Pulmonary hypertension; Treatment response; Cardiac magnetic resonance; Hemodynamics

Authors from the University of Münster

Hörr, Verena
Clinic of Radiology
Leistikow, Simon
Institute of Computer Science
Linsen, Lars
Professorship for Practical Computer Science (Prof. Linsen)