Dataset Information

Validation of aortic valve pressure gradient quantification using semi-automated 4D flow CMR pipeline.

ABSTRACT:

Objective

Doppler echocardiographic aortic valve peak velocity and peak pressure gradient assessment across the aortic valve (AV) is the mainstay for diagnosing aortic stenosis. Four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) is emerging as a valuable diagnostic tool for estimating the peak pressure drop across the aortic valve, but assessment remains cumbersome. We aimed to validate a novel semi-automated pipeline 4D flow CMR method of assessing peak aortic value pressure gradient (AVPG) using the commercially available software solution, CAAS MR Solutions, against invasive angiographic methods.

Results

We enrolled 11 patients with severe AS on echocardiography from the EurValve programme. All patients had pre-intervention doppler echocardiography, invasive cardiac catheterisation with peak pressure drop assessment across the AV and 4D flow CMR. The peak AVPG was 51.9 ± 35.2 mmHg using the invasive pressure drop method and 52.2 ± 29.2 mmHg for the 4D flow CMR method (semi-automated pipeline), with good correlation between the two methods (r = 0.70, p = 0.017). Assessment of AVPG by 4D flow CMR using the novel semi-automated pipeline method shows excellent agreement to invasive assessment when compared to doppler-based methods and advocate for its use as complementary to echocardiography.

SUBMITTER: Grafton-Clarke C

PROVIDER: S-EPMC9052497 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Validation of aortic valve pressure gradient quantification using semi-automated 4D flow CMR pipeline.

Grafton-Clarke Ciaran C Njoku Paul P Aben Jean-Paul JP Ledoux Leon L Zhong Liang L Westenberg Jos J Swift Andrew A Archer Gareth G Wild James J Hose Rod R Flather Marcus M Vassiliou Vassilios S VS Garg Pankaj P

BMC research notes 20220429 1

<h4>Objective</h4>Doppler echocardiographic aortic valve peak velocity and peak pressure gradient assessment across the aortic valve (AV) is the mainstay for diagnosing aortic stenosis. Four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) is emerging as a valuable diagnostic tool for estimating the peak pressure drop across the aortic valve, but assessment remains cumbersome. We aimed to validate a novel semi-automated pipeline 4D flow CMR method of assessing peak aortic value p ...[more]

PMID: 35488286

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Project description:PurposeTo 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 methodsThe 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 (RvolINDIRECT), semiautomated quantification of Rvol using valve tracking (RvolVALVE), and semiautomated quantification of Rvol using flow tracking (RvolFLOW). 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.ResultsRvolFLOW was higher (median, 24.8 mL; interquartile range [IQR], 14.3-45.7 mL) than RvolVALVE (median, 9.9 mL; IQR, 6.0-16.9 mL; P < .001). Both RvolFLOW and RvolVALVE differed significantly from RvolINDIRECT (median, 19.1 mL; IQR, 4.1-47.5 mL; P = .03). RvolFLOW agreed more with RvolINDIRECT (ŷ = 0.78x + 12, r = 0.88) than with RvolVALVE (ŷ = 0.16x + 8.1, r = 0.53). Bland-Altman analysis revealed underestimation of RvolVALVE in severe MV regurgitation. Interobserver agreement was excellent for RvolFLOW (r = 0.95, coefficient of variation = 27%) and moderate for RvolVALVE (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).ConclusionFlow 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.

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Dataset Information

Validation of aortic valve pressure gradient quantification using semi-automated 4D flow CMR pipeline.

Objective

Results

Publications

Validation of aortic valve pressure gradient quantification using semi-automated 4D flow CMR pipeline.

Similar Datasets

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