Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging

ABSTRACT: Background: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is clinically used to quantify flow. The quantification accuracy is diminished by background phase errors. Image-based background phase correction algorithms are commercially available, but their accuracy is still und...

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Main Authors: Ana Beatriz Solana, Savine C.S. Minderhoud, Piotr A. Wielopolski, Juan Antonio Hernandez-Tamames, Ricardo P.J. Budde, Willem A. Helbing, Martin A. Janich, Alexander Hirsch
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Journal of Cardiovascular Magnetic Resonance
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Online Access:http://www.sciencedirect.com/science/article/pii/S1097664725000572
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author Ana Beatriz Solana
Savine C.S. Minderhoud
Piotr A. Wielopolski
Juan Antonio Hernandez-Tamames
Ricardo P.J. Budde
Willem A. Helbing
Martin A. Janich
Alexander Hirsch
author_facet Ana Beatriz Solana
Savine C.S. Minderhoud
Piotr A. Wielopolski
Juan Antonio Hernandez-Tamames
Ricardo P.J. Budde
Willem A. Helbing
Martin A. Janich
Alexander Hirsch
author_sort Ana Beatriz Solana
collection DOAJ
description ABSTRACT: Background: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is clinically used to quantify flow. The quantification accuracy is diminished by background phase errors. Image-based background phase correction algorithms are commercially available, but their accuracy is still under evaluation. Here, we validate a recently developed non-linear phase contrast correction (nPCcor) algorithm that includes automatic failure mode classification in a large single-vendor multi-scanner retrospective study. Methods: Three hundred forty-six through-plane PC images at the aortic valve (AAo) and pulmonary artery (PA) were acquired on three different GE HealthCare 1.5T clinical MRI scanners. Each PC scan was repeated on a static phantom, and the static phantom-corrected PC series was considered as the reference standard. Two image-based static tissue background phase corrections were applied on each PC series: a linear and the nPCcor. Accuracy of nPCcor was studied by comparing the net flow in the vessel of interest for the uncorrected, linear-corrected, and nPCcor images with respect to the static phantom-corrected series. Accuracy was defined as a difference in net flow ≤10% with respect to the static phantom corrected net flow. Results: Flow measurements using the nPCcor images after nPCcor automatic classification were found to be accurate for 87% (281/323) of PC datasets, 6% and 17% better than using uncorrected and linear-corrected (p<0.05), respectively. Most importantly, nPCcor was able to correctly identify 70% (16/23) PC cases likely to provide inaccurate flow measurements. Flow measurements after nPCcor in the scanner with the largest phase offsets were found to be accurate for 74% (62/84) of PC datasets, 22% better than using the uncorrected images (p<0.05). nPCcor correction was statistically significant more accurate than linear correction for all scanners (p<0.05). The percentage of regurgitation reclassification of ≥1 category decreased to 8% (8/323) after nPCcor correction, 3% better than for uncorrected images. Conclusion: nPCcor with automatic failure mode evaluation improved accuracy with respect to no correction and linear correction and successfully identified PC scans that are likely to result in unreliable flow measurements. nPCcor performance and phase offset errors varied greatly among scanners using the same CMR protocol. nPCcor has higher impact in scanners exhibiting the largest background phase offsets. Trial registration: observational study
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spelling doaj-art-b105c6970cc947dfb29ac6fc5ac2b1be2025-08-20T02:34:16ZengElsevierJournal of Cardiovascular Magnetic Resonance1097-66472025-01-0127110189510.1016/j.jocmr.2025.101895Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imagingAna Beatriz Solana0Savine C.S. Minderhoud1Piotr A. Wielopolski2Juan Antonio Hernandez-Tamames3Ricardo P.J. Budde4Willem A. Helbing5Martin A. Janich6Alexander Hirsch7ASL Europe, GE HealthCare, Munich, GermanyDepartment of Cardiology, Cardiovascular Institute, Thorax Center, Erasmus Medical Center, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the NetherlandsDepartment of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the NetherlandsDepartment of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands; Imaging Physics Department, Applied Physics Faculty, TU Delft, Delft, the NetherlandsDepartment of Cardiology, Cardiovascular Institute, Thorax Center, Erasmus Medical Center, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the NetherlandsDepartment of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands; Department of Pediatrics, Division of Pediatric Cardiology, Erasmus Medical Center, Rotterdam, the NetherlandsASL Europe, GE HealthCare, Munich, GermanyDepartment of Cardiology, Cardiovascular Institute, Thorax Center, Erasmus Medical Center, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus Medical Center, Rotterdam, the Netherlands; Corresponding author.ABSTRACT: Background: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is clinically used to quantify flow. The quantification accuracy is diminished by background phase errors. Image-based background phase correction algorithms are commercially available, but their accuracy is still under evaluation. Here, we validate a recently developed non-linear phase contrast correction (nPCcor) algorithm that includes automatic failure mode classification in a large single-vendor multi-scanner retrospective study. Methods: Three hundred forty-six through-plane PC images at the aortic valve (AAo) and pulmonary artery (PA) were acquired on three different GE HealthCare 1.5T clinical MRI scanners. Each PC scan was repeated on a static phantom, and the static phantom-corrected PC series was considered as the reference standard. Two image-based static tissue background phase corrections were applied on each PC series: a linear and the nPCcor. Accuracy of nPCcor was studied by comparing the net flow in the vessel of interest for the uncorrected, linear-corrected, and nPCcor images with respect to the static phantom-corrected series. Accuracy was defined as a difference in net flow ≤10% with respect to the static phantom corrected net flow. Results: Flow measurements using the nPCcor images after nPCcor automatic classification were found to be accurate for 87% (281/323) of PC datasets, 6% and 17% better than using uncorrected and linear-corrected (p<0.05), respectively. Most importantly, nPCcor was able to correctly identify 70% (16/23) PC cases likely to provide inaccurate flow measurements. Flow measurements after nPCcor in the scanner with the largest phase offsets were found to be accurate for 74% (62/84) of PC datasets, 22% better than using the uncorrected images (p<0.05). nPCcor correction was statistically significant more accurate than linear correction for all scanners (p<0.05). The percentage of regurgitation reclassification of ≥1 category decreased to 8% (8/323) after nPCcor correction, 3% better than for uncorrected images. Conclusion: nPCcor with automatic failure mode evaluation improved accuracy with respect to no correction and linear correction and successfully identified PC scans that are likely to result in unreliable flow measurements. nPCcor performance and phase offset errors varied greatly among scanners using the same CMR protocol. nPCcor has higher impact in scanners exhibiting the largest background phase offsets. Trial registration: observational studyhttp://www.sciencedirect.com/science/article/pii/S1097664725000572Background phase correctionMagnetic resonance imagingStatic phantomPhase contrast velocity imaging
spellingShingle Ana Beatriz Solana
Savine C.S. Minderhoud
Piotr A. Wielopolski
Juan Antonio Hernandez-Tamames
Ricardo P.J. Budde
Willem A. Helbing
Martin A. Janich
Alexander Hirsch
Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging
Journal of Cardiovascular Magnetic Resonance
Background phase correction
Magnetic resonance imaging
Static phantom
Phase contrast velocity imaging
title Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging
title_full Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging
title_fullStr Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging
title_full_unstemmed Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging
title_short Automatic failure mode evaluation using non-linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging
title_sort automatic failure mode evaluation using non linear phase contrast correction to improve flow measurement accuracy in cardiovascular magnetic resonance phase contrast imaging
topic Background phase correction
Magnetic resonance imaging
Static phantom
Phase contrast velocity imaging
url http://www.sciencedirect.com/science/article/pii/S1097664725000572
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