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Rothenberger SM, Zhang J, Markl M, Craig BA, Vlachos PP, Rayz VL. 4D flow MRI velocity uncertainty quantification. Magn Reson Med 2024. [PMID: 39270010 DOI: 10.1002/mrm.30287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 07/27/2024] [Accepted: 08/20/2024] [Indexed: 09/15/2024]
Abstract
PURPOSE An automatic method is presented for estimating 4D flow MRI velocity measurement uncertainty in each voxel. The velocity distance (VD) metric, a statistical distance between the measured velocity and local error distribution, is introduced as a novel measure of 4D flow MRI velocity measurement quality. METHODS The method uses mass conservation to assess the local velocity error variance and the standardized difference of means (SDM) velocity to estimate the velocity error correlations. VD is evaluated as the Mahalanobis distance between the local velocity measurement and the local error distribution. The uncertainty model is validated synthetically and tested in vitro under different flow resolutions and noise levels. The VD's application is demonstrated on two in vivo thoracic vasculature 4D flow datasets. RESULTS Synthetic results show the proposed uncertainty quantification method is sensitive to aliased regions across various velocity-to-noise ratios and assesses velocity error correlations in four- and six-point acquisitions with correlation errors at or under 3.2%. In vitro results demonstrate the method's sensitivity to spatial resolution, venc settings, partial volume effects, and phase wrapping error sources. Applying VD to assess in vivo 4D flow MRI in the aorta demonstrates the expected increase in measured velocity quality with contrast administration and systolic flow. CONCLUSION The proposed 4D flow MRI uncertainty quantification method assesses velocity measurement error owing to sources including noise, intravoxel phase dispersion, and velocity aliasing. This method enables rigorous comparison of 4D flow MRI datasets obtained in longitudinal studies, across patient populations, and with different MRI systems.
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Affiliation(s)
- Sean M Rothenberger
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Jiacheng Zhang
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Michael Markl
- Department of Radiology at the Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Bruce A Craig
- Department of Statistics, Purdue University, West Lafayette, Indiana, USA
| | - Pavlos P Vlachos
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Vitaliy L Rayz
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA
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Degenhardt K, Schmidt S, Aigner CS, Kratzer FJ, Seiter DP, Mueller M, Kolbitsch C, Nagel AM, Wieben O, Schaeffter T, Schulz-Menger J, Schmitter S. Toward accurate and fast velocity quantification with 3D ultrashort TE phase-contrast imaging. Magn Reson Med 2024; 91:1994-2009. [PMID: 38174601 DOI: 10.1002/mrm.29978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 11/28/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE Traditional phase-contrast MRI is affected by displacement artifacts caused by non-synchronized spatial- and velocity-encoding time points. The resulting inaccurate velocity maps can affect the accuracy of derived hemodynamic parameters. This study proposes and characterizes a 3D radial phase-contrast UTE (PC-UTE) sequence to reduce displacement artifacts. Furthermore, it investigates the displacement of a standard Cartesian flow sequence by utilizing a displacement-free synchronized-single-point-imaging MR sequence (SYNC-SPI) that requires clinically prohibitively long acquisition times. METHODS 3D flow data was acquired at 3T at three different constant flow rates and varying spatial resolutions in a stenotic aorta phantom using the proposed PC-UTE, a Cartesian flow sequence, and a SYNC-SPI sequence as reference. Expected displacement artifacts were calculated from gradient timing waveforms and compared to displacement values measured in the in vitro flow experiments. RESULTS The PC-UTE sequence reduces displacement and intravoxel dephasing, leading to decreased geometric distortions and signal cancellations in magnitude images, and more spatially accurate velocity quantification compared to the Cartesian flow acquisitions; errors increase with velocity and higher spatial resolution. CONCLUSION PC-UTE MRI can measure velocity vector fields with greater accuracy than Cartesian acquisitions (although pulsatile fields were not studied) and shorter scan times than SYNC-SPI. As such, this approach is superior to traditional Cartesian 3D and 4D flow MRI when spatial misrepresentations cannot be tolerated, for example, when computational fluid dynamics simulations are compared to or combined with in vitro or in vivo measurements, or regional parameters such as wall shear stress are of interest.
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Affiliation(s)
- Katja Degenhardt
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Simon Schmidt
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Christoph S Aigner
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
| | - Fabian J Kratzer
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel P Seiter
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Max Mueller
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Christoph Kolbitsch
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
| | - Armin M Nagel
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Oliver Wieben
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin Madison, Madison, Wisconsin, USA
| | - Tobias Schaeffter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
- School of Imaging Science and Biomedical Engineering, King's College London, London, United Kingdom
- Department of Medical Engineering, Technical University of Berlin, Berlin, Germany
| | - Jeanette Schulz-Menger
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrueck Center for Molecular Medicine, Berlin, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- Department of Cardiology and Nephrology, HELIOS Hospital Berlin-Buch, Berlin, Germany
| | - Sebastian Schmitter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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2D Projection Maps of WSS and OSI Reveal Distinct Spatiotemporal Changes in Hemodynamics in the Murine Aorta during Ageing and Atherosclerosis. Biomedicines 2021; 9:biomedicines9121856. [PMID: 34944672 PMCID: PMC8698968 DOI: 10.3390/biomedicines9121856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/24/2021] [Accepted: 12/02/2021] [Indexed: 11/17/2022] Open
Abstract
Growth, ageing and atherosclerotic plaque development alter the biomechanical forces acting on the vessel wall. However, monitoring the detailed local changes in wall shear stress (WSS) at distinct sites of the murine aortic arch over time has been challenging. Here, we studied the temporal and spatial changes in flow, WSS, oscillatory shear index (OSI) and elastic properties of healthy wildtype (WT, n = 5) and atherosclerotic apolipoprotein E-deficient (Apoe-/-, n = 6) mice during ageing and atherosclerosis using high-resolution 4D flow magnetic resonance imaging (MRI). Spatially resolved 2D projection maps of WSS and OSI of the complete aortic arch were generated, allowing the pixel-wise statistical analysis of inter- and intragroup hemodynamic changes over time and local correlations between WSS, pulse wave velocity (PWV), plaque and vessel wall characteristics. The study revealed converse differences of local hemodynamic profiles in healthy WT and atherosclerotic Apoe-/- mice, and we identified the circumferential WSS as potential marker of plaque size and composition in advanced atherosclerosis and the radial strain as a potential marker for vascular elasticity. Two-dimensional (2D) projection maps of WSS and OSI, including statistical analysis provide a powerful tool to monitor local aortic hemodynamics during ageing and atherosclerosis. The correlation of spatially resolved hemodynamics and plaque characteristics could significantly improve our understanding of the impact of hemodynamics on atherosclerosis, which may be key to understand plaque progression towards vulnerability.
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