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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.
    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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