Fast 4D flow MRI intracranial segmentation and quantification in tortuous arteries

• PurposeTo describe, validate, and implement a centerline processing scheme (CPS) for semiautomated segmentation and quantification in carotid siphons of healthy subjects. 4D flow MRI enables blood flow measurement in all major cerebral arteries with one scan. Clinical translational hurdles are time demanding postprocessing and user-dependence induced variability during analysis. Materials and MethodsA CPS for 4D flow data was developed to automatically separate cerebral artery trees. Flow parameters were quantified at planes along the centerline oriented perpendicular to the vessel path. At 3T, validation against 2D phase-contrast (PC) magnetic resonance imaging (MRI) and 4D flow manual processing was performed on an intracranial flow phantom for constant flow, while pulsatile flow validation was performed in the internal carotid artery (ICA) of 10 healthy volunteers. The CPS and 4D manual processing times were measured and compared. Flow and area measurements were also demonstrated along the length of the ICA siphon. ResultsPhantom measurements for area and flow were highly correlated between the CPS and 2D measurements (area: R=0.95, flow: R=0.94), while in vivo waveforms were highly correlated (R=0.93). Processing time was reduced by a factor of 4.6 compared with manual processing. Whole ICA measurements revealed a significantly decreased area in the most distal segment of the carotid siphon (P=0.0017), with flow unchanged (P=0.84). ConclusionThis study exhibits fast semiautomated analysis of intracranial 4D flow MRI. Internal consistency was shown through flow conservation along the tortuous ICA siphon, which is typically difficult to assess. J. Magn. Reson. Imaging 2015;42:1458-1464.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)

Nyckelord

4D flow MRI

vascular

segmentation

automated processing

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