Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Apr;31(4):1883-1893.
doi: 10.1007/s00330-020-07287-6. Epub 2020 Sep 24.

MR 4D flow-based mean pulmonary arterial pressure tracking in pulmonary hypertension

Ursula Reiter  1 , Gabor Kovacs  2   3 , Clemens Reiter  4 , Corina Kräuter  4   5 , Volha Nizhnikava  4 , Michael Fuchsjäger  4 , Horst Olschewski  2   3 , Gert Reiter  4   6
Affiliations

MR 4D flow-based mean pulmonary arterial pressure tracking in pulmonary hypertension

Ursula Reiter et al. Eur Radiol. 2021 Apr.

Abstract

Objectives: Longitudinal hemodynamic follow-up is important in the management of pulmonary hypertension (PH). This study aimed to evaluate the potential of MR 4-dimensional (4D) flow imaging to predict changes in the mean pulmonary arterial pressure (mPAP) during serial investigations.

Methods: Forty-four adult patients with PH or at risk of developing PH repeatedly underwent routine right heart catheterization (RHC) and near-term MR 4D flow imaging of the main pulmonary artery. The duration of vortical blood flow along the main pulmonary artery was evaluated from MR 4D velocity fields using prototype software and converted to an MR 4D flow imaging-based mPAP estimate (mPAPMR) by a previously established model. The relationship of differences between RHC-derived baseline and follow-up mPAP values (ΔmPAP) to corresponding differences in mPAPMR (ΔmPAPMR) was analyzed by means of regression and Bland-Altman analysis; the diagnostic performance of ΔmPAPMR in predicting mPAP increases or decreases was investigated by ROC analysis.

Results: Areas under the curve for the prediction of mPAP increases and decreases were 0.92 and 0.93, respectively. With the natural cutoff ΔmPAPMR = 0 mmHg, mPAP increases (decreases) were predicted with an accuracy, sensitivity, and specificity of 91% (91%), 85% (89%), and 94% (92%), respectively. For patients in whom 4D flow allowed a point estimate of mPAP (mPAP > 16 mmHg), ΔmPAPMR correlated strongly with ΔmPAP (r = 0.91) and estimated ΔmPAP bias-free with a standard deviation of 5.1 mmHg.

Conclusions: MR 4D flow imaging allows accurate non-invasive prediction and quantification of mPAP changes in adult patients with PH or at risk of developing PH.

Trial registration: ClinicalTrials.gov identifier: NCT00575692 and NCT01725763 KEY POINTS: • MR 4D flow imaging allows accurate non-invasive prediction of mean pulmonary arterial pressure increases and decreases in adult patients with or at risk of developing pulmonary hypertension. • In adult patients with mean pulmonary arterial pressure > 16 mmHg, MR 4D flow imaging allows estimation of longitudinal mean pulmonary arterial pressure changes without bias with a standard deviation of 5.1 mmHg.

Keywords: Follow-up studies; Hemodynamics; Magnetic resonance imaging; Pulmonary hypertension.

PubMed Disclaimer

Conflict of interest statement

The authors of this manuscript declare relationships with the following companies: Gert Reiter is an employee of Siemens Healthcare Diagnostics GmbH, Austria. The study was performed under a Master Research Agreement between the Medical University of Graz, Graz University of Technology, and Siemens Healthcare Diagnostics GmbH.

The other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Figures

Fig. 1
Fig. 1
Velocity color-encoded 3-dimensional vector representation of vortical blood flow along the main pulmonary artery in a patient with PH at baseline (upper panel) and 2-year follow-up (lower panel). Color encoding of both representations was set to an equal scale. %RR, percentage of the cardiac interval; #ph, cardiac phase in the RR interval; (Δ)mPAP, mean pulmonary arterial pressure (difference) measured by right heart catheterization; (Δ)mPAPMR, mean pulmonary arterial pressure (difference) estimated by 4D flow; PV, main pulmonary artery peak velocity magnitude. mPAP differences are written in red
Fig. 2
Fig. 2
Distributions of mPAP at baseline and at follow-up as well as the mPAP changes of the study population. nPH,BL, number of subjects with PH at baseline; nnoPH,BL, number of subjects without PH at baseline; nPH,FU, number of subjects with PH at follow-up; nnoPH,FU, number of subjects without PH at follow-up; nPH, number of subjects with PH at baseline and follow-up
Fig. 3
Fig. 3
ROC curves for the prediction of mPAP increase (a) and decrease (b) based on ΔmPAPMR for the entire study population, as well as for mPAP increase (c) and decrease (d) for patients with PH at baseline RHC
Fig. 4
Fig. 4
Linear regression and Bland-Altman plots of mean pulmonary arterial pressures measured at right heart catheterization (mPAP) and estimated from vortex duration (mPAPMR) at baseline (a, b) and follow-up (c, d). Light gray shading indicates the area between 95% limits of agreement, dark gray shadings indicate 95% confidence intervals of bias and 95%-limits of agreement. nmPAP > 16,BL, number of subjects with mPAP > 16 mmHg at baseline; nmPAP > 16,FU, number of subjects with mPAP > 16 mmHg at follow-up; r, correlation coefficient
Fig. 5
Fig. 5
Linear regression (a) and Bland-Altman (b) plot of mean pulmonary arterial pressure differences between baseline and follow-up measured by right heart catheterization (ΔmPAP). Light gray shading indicates the area between 95% limits of agreement, dark gray shadings indicate 95% confidence intervals of bias and 95% limits of agreement. nmPAP > 16, number of subjects with mPAP > 16 mmHg at baseline and follow-up
See this image and copyright information in PMC

References

    1. Simonneau G, Montani D, Celermajer DS, et al. Haemodynamic definitions and updated clinical classification of pulmonary hypertension. Eur Respir J. 2019;53:1801913. doi: 10.1183/13993003.01913-2018. - DOI - PMC - PubMed
    1. Galiè N, Humbert M, Vachiery J-L, et al. 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS) Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT) Eur Heart J. 2016;37:67–119. doi: 10.1093/eurheartj/ehv317. - DOI - PubMed
    1. McLaughlin VV, Gaine SP, Howard LS, et al. Treatment goals of pulmonary hypertension. J Am Coll Cardiol. 2013;62:D73–D81. doi: 10.1016/j.jacc.2013.10.034. - DOI - PubMed
    1. Wright LM, Dwyer N, Celermajer D, Kritharides L, Marwick TH (2016) Follow-Up of Pulmonary Hypertension With Echocardiography. JACC Cardiovasc Imaging 9:733–746. 10.1016/j.jcmg.2016.02.022 - PubMed
    1. Sato T, Tsujino I, Ohira H, et al. Accuracy of echocardiographic indices for serial monitoring of right ventricular systolic function in patients with precapillary pulmonary hypertension. PLoS One. 2017;12:e0187806. doi: 10.1371/journal.pone.0187806. - DOI - PMC - PubMed

Associated data