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Quantification of Mitral Valve Regurgitation from 4D Flow MRI Using Semiautomated Flow Tracking

Authors :
Geertruida P. Bijvoet
Carmen P.S. Blanken
Aart J. Nederveen
R. Nils Planken
Pim van Ooij
Jean-Paul Aben
Tim Leiner
Jos J.M. Westenberg
S. Matthijs Boekholdt
Steven A. J. Chamuleau
Cardiology
ACS - Atherosclerosis & ischemic syndromes
ACS - Heart failure & arrhythmias
Graduate School
Radiology and Nuclear Medicine
ACS - Diabetes & metabolism
ACS - Pulmonary hypertension & thrombosis
Amsterdam Neuroscience - Brain Imaging
Amsterdam Movement Sciences
AMS - Ageing & Vitality
AMS - Sports
Source :
Radiol Cardiothorac Imaging, Radiology: Cardiothoracic Imaging, 2(5):e200004, Radiology: Cardiothoracic Imaging, 2(5):e200004. Radiological Society of North America Inc.
Publication Year :
2020
Publisher :
Radiological Society of North America (RSNA), 2020.

Abstract

PURPOSE: To compare the accuracy of semiautomated flow tracking with that of semiautomated valve tracking in the quantification of mitral valve (MV) regurgitation from clinical four-dimensional (4D) flow MRI data obtained in patients with mild, moderate, or severe MV regurgitation. MATERIALS AND METHODS: The 4D flow MRI data were retrospectively collected from 30 patients (21 men; mean age, 61 years ± 10 [standard deviation]) who underwent 4D flow MRI from 2006 to 2016. Ten patients had mild MV regurgitation, nine had moderate MV regurgitation, and 11 had severe MV regurgitation, as diagnosed by using semiquantitative echocardiography. The regurgitant volume (Rvol) across the MV was obtained using three methods: indirect quantification of Rvol (Rvol(INDIRECT)), semiautomated quantification of Rvol using valve tracking (Rvol(VALVE)), and semiautomated quantification of Rvol using flow tracking (Rvol(FLOW)). A second observer repeated the measurements. Aortic valve flow was quantified as well to test for intervalve consistency. The Wilcoxon signed rank test, orthogonal regression, Bland-Altman analysis, and coefficients of variation were used to assess agreement among measurements and between observers. RESULTS: Rvol(FLOW) was higher (median, 24.8 mL; interquartile range [IQR], 14.3–45.7 mL) than Rvol(VALVE) (median, 9.9 mL; IQR, 6.0–16.9 mL; P < .001). Both Rvol(FLOW) and Rvol(VALVE) differed significantly from Rvol(INDIRECT) (median, 19.1 mL; IQR, 4.1–47.5 mL; P = .03). Rvol(FLOW) agreed more with Rvol(INDIRECT) (ŷ = 0.78x + 12, r = 0.88) than with Rvol(VALVE) (ŷ = 0.16x + 8.1, r = 0.53). Bland-Altman analysis revealed underestimation of Rvol(VALVE) in severe MV regurgitation. Interobserver agreement was excellent for Rvol(FLOW) (r = 0.95, coefficient of variation = 27%) and moderate for Rvol(VALVE) (r = 0.72, coefficient of variation = 57%). Orthogonal regression demonstrated better intervalve consistency for flow tracking (ŷ = 1.2x − 13.4, r = 0.82) than for valve tracking (ŷ = 2.7x − 92.4, r = 0.67). CONCLUSION: Flow tracking enables more accurate 4D flow MRI–derived MV regurgitation quantification than valve tracking in terms of agreement with indirect quantification and intervalve consistency, particularly in severe MV regurgitation. Supplemental material is available for this article. © RSNA, 2020

Details

ISSN :
26386135
Volume :
2
Database :
OpenAIRE
Journal :
Radiology: Cardiothoracic Imaging
Accession number :
edsair.doi.dedup.....a213a3aea04c5f3ee669f1024f348e98
Full Text :
https://doi.org/10.1148/ryct.2020200004