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Rivera-Rivera LA, Vikner T, Eisenmenger L, Johnson SC, Johnson KM. Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities. NMR IN BIOMEDICINE 2024; 37:e5082. [PMID: 38124351 PMCID: PMC11162953 DOI: 10.1002/nbm.5082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 10/03/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023]
Abstract
Neurological disorders can manifest with altered neurofluid dynamics in different compartments of the central nervous system. These include alterations in cerebral blood flow, cerebrospinal fluid (CSF) flow, and tissue biomechanics. Noninvasive quantitative assessment of neurofluid flow and tissue motion is feasible with phase contrast magnetic resonance imaging (PC MRI). While two-dimensional (2D) PC MRI is routinely utilized in research and clinical settings to assess flow dynamics through a single imaging slice, comprehensive neurofluid dynamic assessment can be limited or impractical. Recently, four-dimensional (4D) flow MRI (or time-resolved three-dimensional PC with three-directional velocity encoding) has emerged as a powerful extension of 2D PC, allowing for large volumetric coverage of fluid velocities at high spatiotemporal resolution within clinically reasonable scan times. Yet, most 4D flow studies have focused on blood flow imaging. Characterizing CSF flow dynamics with 4D flow (i.e., 4D CSF flow) is of high interest to understand normal brain and spine physiology, but also to study neurological disorders such as dysfunctional brain metabolite waste clearance, where CSF dynamics appear to play an important role. However, 4D CSF flow imaging is challenged by the long T1 time of CSF and slower velocities compared with blood flow, which can result in longer scan times from low flip angles and extended motion-sensitive gradients, hindering clinical adoption. In this work, we review the state of 4D CSF flow MRI including challenges, novel solutions from current research and ongoing needs, examples of clinical and research applications, and discuss an outlook on the future of 4D CSF flow.
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Affiliation(s)
- Leonardo A Rivera-Rivera
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Tomas Vikner
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Radiation Sciences, Radiation Physics and Biomedical Engineering, Umeå University, Umeå, Sweden
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Sterling C Johnson
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Winter P, Berhane H, Moore JE, Aristova M, Reichl T, Wollenberg J, Richter A, Jarvis KB, Patel A, Caprio FZ, Abdalla RN, Ansari SA, Markl M, Schnell S. Automated intracranial vessel segmentation of 4D flow MRI data in patients with atherosclerotic stenosis using a convolutional neural network. FRONTIERS IN RADIOLOGY 2024; 4:1385424. [PMID: 38895589 PMCID: PMC11183785 DOI: 10.3389/fradi.2024.1385424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 05/13/2024] [Indexed: 06/21/2024]
Abstract
Introduction Intracranial 4D flow MRI enables quantitative assessment of hemodynamics in patients with intracranial atherosclerotic disease (ICAD). However, quantitative assessments are still challenging due to the time-consuming vessel segmentation, especially in the presence of stenoses, which can often result in user variability. To improve the reproducibility and robustness as well as to accelerate data analysis, we developed an accurate, fully automated segmentation for stenosed intracranial vessels using deep learning. Methods 154 dual-VENC 4D flow MRI scans (68 ICAD patients with stenosis, 86 healthy controls) were retrospectively selected. Manual segmentations were used as ground truth for training. For automated segmentation, deep learning was performed using a 3D U-Net. 20 randomly selected cases (10 controls, 10 patients) were separated and solely used for testing. Cross-sectional areas and flow parameters were determined in the Circle of Willis (CoW) and the sinuses. Furthermore, the flow conservation error was calculated. For statistical comparisons, Dice scores (DS), Hausdorff distance (HD), average symmetrical surface distance (ASSD), Bland-Altman analyses, and interclass correlations were computed using the manual segmentations from two independent observers as reference. Finally, three stenosis cases were analyzed in more detail by comparing the 4D flow-based segmentations with segmentations from black blood vessel wall imaging (VWI). Results Training of the network took approximately 10 h and the average automated segmentation time was 2.2 ± 1.0 s. No significant differences in segmentation performance relative to two independent observers were observed. For the controls, mean DS was 0.85 ± 0.03 for the CoW and 0.86 ± 0.06 for the sinuses. Mean HD was 7.2 ± 1.5 mm (CoW) and 6.6 ± 3.7 mm (sinuses). Mean ASSD was 0.15 ± 0.04 mm (CoW) and 0.22 ± 0.17 mm (sinuses). For the patients, the mean DS was 0.85 ± 0.04 (CoW) and 0.82 ± 0.07 (sinuses), the HD was 8.4 ± 3.1 mm (CoW) and 5.7 ± 1.9 mm (sinuses) and the mean ASSD was 0.22 ± 0.10 mm (CoW) and 0.22 ± 0.11 mm (sinuses). Small bias and limits of agreement were observed in both cohorts for the flow parameters. The assessment of the cross-sectional lumen areas in stenosed vessels revealed very good agreement (ICC: 0.93) with the VWI segmentation but a consistent overestimation (bias ± LOA: 28.1 ± 13.9%). Discussion Deep learning was successfully applied for fully automated segmentation of stenosed intracranial vasculatures using 4D flow MRI data. The statistical analysis of segmentation and flow metrics demonstrated very good agreement between the CNN and manual segmentation and good performance in stenosed vessels. To further improve the performance and generalization, more ICAD segmentations as well as other intracranial vascular pathologies will be considered in the future.
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Affiliation(s)
- Patrick Winter
- Department of Medical Physics, Faculty of Mathematics and Natural Sciences, University of Greifswald, Greifswald, Germany
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Haben Berhane
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Jackson E. Moore
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Maria Aristova
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
- Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicacgo, IL, United States
| | - Teresa Reichl
- Department of Experimental Physics V, University of Wuerzburg, Wuerzburg, Germany
| | - Julian Wollenberg
- Department of Medical Physics, Faculty of Mathematics and Natural Sciences, University of Greifswald, Greifswald, Germany
- Department of Diagnostic Radiology, University Hospital of Greifswald, Greifswald, Germany
| | - Adam Richter
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Kelly B. Jarvis
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Abhinav Patel
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Fan Z. Caprio
- Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicacgo, IL, United States
| | - Ramez N. Abdalla
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Sameer A. Ansari
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
- Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicacgo, IL, United States
| | - Michael Markl
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
| | - Susanne Schnell
- Department of Medical Physics, Faculty of Mathematics and Natural Sciences, University of Greifswald, Greifswald, Germany
- Department of Radiology, Northwestern University, Feinberg School of Medicine, Chicago, IL, United States
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Wieben O, Roberts GS, Corrado PA, Johnson KM, Roldán-Alzate A. Four-Dimensional Flow MR Imaging: Technique and Advances. Magn Reson Imaging Clin N Am 2023; 31:433-449. [PMID: 37414470 DOI: 10.1016/j.mric.2023.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/08/2023]
Abstract
4D Flow MRI is an advanced imaging technique for comprehensive non-invasive assessment of the cardiovascular system. The capture of the blood velocity vector field throughout the cardiac cycle enables measures of flow, pulse wave velocity, kinetic energy, wall shear stress, and more. Advances in hardware, MRI data acquisition and reconstruction methodology allow for clinically feasible scan times. The availability of 4D Flow analysis packages allows for more widespread use in research and the clinic and will facilitate much needed multi-center, multi-vendor studies in order to establish consistency across scanner platforms and to enable larger scale studies to demonstrate clinical value.
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Affiliation(s)
- Oliver Wieben
- Department of Medical Physics, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research, 1111 Highland Avenue, Suite 1127, Madison, WI 53705-2275, USA; Department of Radiology, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research, 1111 Highland Avenue, Suite 1127, Madison, WI 53705-2275, USA.
| | - Grant S Roberts
- Department of Medical Physics, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research, 1111 Highland Avenue, Madison, WI 53705-2275, USA
| | - Philip A Corrado
- Accuray Incorporated, 1414 Raleigh Road, Suite 330, DurhamChapel Hill, NC 27517, USA
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research, 1111 Highland Avenue, Room 1133, Madison, WI 53705-2275, USA; Department of Radiology, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research, 1111 Highland Avenue, Room 1133, Madison, WI 53705-2275, USA
| | - Alejandro Roldán-Alzate
- Department of Mechanical Engineering, University of Wisconsin-Madison, Room: 3035, 1513 University Avenue, Madison, WI 53706, USA; Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA
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Roberts GS, Peret A, Jonaitis EM, Koscik RL, Hoffman CA, Rivera-Rivera LA, Cody KA, Rowley HA, Johnson SC, Wieben O, Johnson KM, Eisenmenger LB. Normative Cerebral Hemodynamics in Middle-aged and Older Adults Using 4D Flow MRI: Initial Analysis of Vascular Aging. Radiology 2023; 307:e222685. [PMID: 36943077 PMCID: PMC10140641 DOI: 10.1148/radiol.222685] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/06/2023] [Accepted: 02/06/2023] [Indexed: 03/23/2023]
Abstract
Background Characterizing cerebrovascular hemodynamics in older adults is important for identifying disease and understanding normal neurovascular aging. Four-dimensional (4D) flow MRI allows for a comprehensive assessment of cerebral hemodynamics in a single acquisition. Purpose To establish reference intracranial blood flow and pulsatility index values in a large cross-sectional sample of middle-aged (45-65 years) and older (>65 years) adults and characterize the effect of age and sex on blood flow and pulsatility. Materials and Methods In this retrospective study, patients aged 45-93 years (cognitively unimpaired) underwent cranial 4D flow MRI between March 2010 and March 2020. Blood flow rates and pulsatility indexes from 13 major arteries and four venous sinuses and total cerebral blood flow were collected. Intraobserver and interobserver reproducibility of flow and pulsatility measures was assessed in 30 patients. Descriptive statistics (mean ± SD) of blood flow and pulsatility were tabulated for the entire group and by age and sex. Multiple linear regression and linear mixed-effects models were used to assess the effect of age and sex on total cerebral blood flow and vessel-specific flow and pulsatility, respectively. Results There were 759 patients (mean age, 65 years ± 8 [SD]; 506 female patients) analyzed. For intra- and interobserver reproducibility, median intraclass correlation coefficients were greater than 0.90 for flow and pulsatility measures across all vessels. Regression coefficients β ± standard error from multiple linear regression showed a 4 mL/min decrease in total cerebral blood flow each year (age β = -3.94 mL/min per year ± 0.44; P < .001). Mixed effects showed a 1 mL/min average annual decrease in blood flow (age β = -0.95 mL/min per year ± 0.16; P < .001) and 0.01 arbitrary unit (au) average annual increase in pulsatility over all vessels (age β = 0.011 au per year ± 0.001; P < .001). No evidence of sex differences was observed for flow (β = -1.60 mL/min per male patient ± 1.77; P = .37), but pulsatility was higher in female patients (sex β = -0.018 au per male patient ± 0.008; P = .02). Conclusion Normal reference values for blood flow and pulsatility obtained using four-dimensional flow MRI showed correlations with age. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Steinman in this issue.
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Affiliation(s)
- Grant S. Roberts
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Anthony Peret
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Erin M. Jonaitis
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Rebecca L. Koscik
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Carson A. Hoffman
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Leonardo A. Rivera-Rivera
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Karly A. Cody
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Howard A. Rowley
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Sterling C. Johnson
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Oliver Wieben
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Kevin M. Johnson
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
| | - Laura B. Eisenmenger
- From the Department of Medical Physics (G.S.R., L.A.R.R., O.W.,
K.M.J.), Department of Radiology (A.P., C.A.H., H.A.R., O.W., K.M.J., L.B.E.),
Wisconsin Alzheimer’s Institute (E.M.J., R.L.K., S.C.J.), and Wisconsin
Alzheimer’s Disease Research Center (E.M.J., L.A.R.R., K.A.C., S.C.J.),
University of Wisconsin School of Medicine and Public Health, 600 Highland Ave,
Madison, WI 53792-3252; and Geriatric Research Education and Clinical Center,
William S. Middleton Memorial Veterans Hospital, Madison, Wis (S.C.J.)
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