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  • 1.
    Dunås, Tora
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Holmgren, Madelene
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience, Clinical Neuroscience.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Accuracy of blood flow assessment in cerebral arteries with 4D flow MRI: Evaluation with three segmentation methods2019In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 50, no 2, p. 511-518Article in journal (Refereed)
    Abstract [en]

    Background: Accelerated 4D flow MRI allows for high‐resolution velocity measurements with whole‐brain coverage. Such scans are increasingly used to calculate flow rates of individual arteries in the vascular tree, but detailed information about the accuracy and precision in relation to different postprocessing options is lacking.

    Purpose: To evaluate and optimize three proposed segmentation methods and determine the accuracy of in vivo 4D flow MRI blood flow rate assessments in major cerebral arteries, with high‐resolution 2D PCMRI as a reference.

    Study Type: Prospective.

    Subjects: Thirty‐five subjects (20 women, 79 ± 5 years, range 70–91 years).

    Field Strength/Sequence: 4D flow MRI with PC‐VIPR and 2D PCMRI acquired with a 3 T scanner.

    Assessment: We compared blood flow rates measured with 4D flow MRI, to the reference, in nine main cerebral arteries. Lumen segmentation in the 4D flow MRI was performed with k‐means clustering using four different input datasets, and with two types of thresholding methods. The threshold was defined as a percentage of the maximum intensity value in the complex difference image. Local and global thresholding approaches were used, with evaluated thresholds from 6–26%.

    Statistical Tests: Paired t‐test, F‐test, linear correlation (P < 0.05 was considered significant) along with intraclass correlation (ICC).

    Results: With the thresholding methods, the lowest average flow difference was obtained for 20% local (0.02 ± 15.0 ml/min, ICC = 0.97, n = 310) or 10% global (0.08 ± 17.3 ml/min, ICC = 0.97, n = 310) thresholding with a significant lower standard deviation for local (F‐test, P = 0.01). For all clustering methods, we found a large systematic underestimation of flow compared with 2D PCMRI (16.1–22.3 ml/min).

    Data Conclusion: A locally adapted threshold value gives a more stable result compared with a globally fixed threshold. 4D flow with the proposed segmentation method has the potential to become a useful reliable clinical tool for assessment of blood flow in the major cerebral arteries.

    Level of Evidence: 2

    Technical Efficacy: Stage 2

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  • 2.
    Holmgren, Madelene
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Dunås, Tora
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI). Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Assessment of Cerebral Blood Flow Pulsatility and Cerebral Arterial Compliance With 4D Flow MRI2019In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Four-dimensional flow magnetic resonance imaging (4D flow MRI) enables efficient investigation of cerebral blood flow pulsatility in the cerebral arteries. This is important for exploring hemodynamic mechanisms behind vascular diseases associated with arterial pulsations.

    PURPOSE: To investigate the feasibility of pulsatility assessments with 4D flow MRI, its agreement with reference two-dimensional phase-contrast MRI (2D PC-MRI) measurements, and to demonstrate how 4D flow MRI can be used to assess cerebral arterial compliance and cerebrovascular resistance in major cerebral arteries.

    STUDY TYPE: Prospective.

    SUBJECTS: Thirty-five subjects (20 women, 79 ± 5 years, range 70-91 years).

    FIELD STRENGTH/SEQUENCE: 4D flow MRI (PC-VIPR) and 2D PC-MRI acquired with a 3T scanner.

    ASSESSMENT: Time-resolved flow was assessed in nine cerebral arteries. From the pulsatile flow waveform in each artery, amplitude (ΔQ), volume load (ΔV), and pulsatility index (PI) were calculated. To reduce high-frequency noise in the 4D flow MRI data, the flow waveforms were low-pass filtered. From the total cerebral blood flow, total PI (PItot ), total volume load (ΔVtot ), cerebral arterial compliance (C), and cerebrovascular resistance (R) were calculated.

    STATISTICAL TESTS: Two-tailed paired t-test, intraclass correlation (ICC).

    RESULTS: There was no difference in ΔQ between 4D flow MRI and the reference (0.00 ± 0.022 ml/s, mean ± SEM, P = 0.97, ICC = 0.95, n = 310) with a cutoff frequency of 1.9 Hz and 15 cut plane long arterial segments. For ΔV, the difference was -0.006 ± 0.003 ml (mean ± SEM, P = 0.07, ICC = 0.93, n = 310) without filtering. Total R was 11.4 ± 2.41 mmHg/(ml/s) (mean ± SD) and C was 0.021 ± 0.009 ml/mmHg (mean ± SD). ΔVtot was 1.21 ± 0.29 ml (mean ± SD) with an ICC of 0.82 compared with the reference. PItot was 1.08 ± 0.21 (mean ± SD).

    DATA CONCLUSION: We successfully assessed 4D flow MRI cerebral arterial pulsatility, cerebral arterial compliance, and cerebrovascular resistance. Averaging of multiple cut planes and low-pass filtering was necessary to assess accurate peak-to-peak features in the flow rate waveforms.

    LEVEL OF EVIDENCE: 2

    Technical Efficacy Stage: 2

    J. Magn. Reson. Imaging 2019.

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  • 3.
    Vikner, Tomas
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Nyberg, Lars
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Department of Integrative Medical Biology (IMB). Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Holmgren, Madelene
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Malm, Jan
    Umeå University, Faculty of Medicine, Department of Pharmacology and Clinical Neuroscience.
    Eklund, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Wåhlin, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences. Umeå University, Faculty of Medicine, Umeå Centre for Functional Brain Imaging (UFBI).
    Characterizing pulsatility in distal cerebral arteries using 4D flow MRI2019In: Journal of Cerebral Blood Flow and Metabolism, ISSN 0271-678X, E-ISSN 1559-7016Article in journal (Refereed)
    Abstract [en]

    Recent reports have suggested that age-related arterial stiffening and excessive cerebral arterial pulsatility cause blood-brain barrier breakdown, brain atrophy and cognitive decline. This has spurred interest in developing non-invasive methods to measure pulsatility in distal vessels, closer to the cerebral microcirculation. Here, we report a method based on four-dimensional (4D) flow MRI to estimate a global composite flow waveform of distal cerebral arteries. The method is based on finding and sampling arterial waveforms from thousands of cross sections in numerous small vessels of the brain, originating from cerebral cortical arteries. We demonstrate agreement with internal and external reference methods and show the ability to capture significant increases in distal cerebral arterial pulsatility as a function of age. The proposed approach can be used to advance our understanding regarding excessive arterial pulsatility as a potential trigger of cognitive decline and dementia.

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