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Acute Cerebral Venous Thrombosis. Three-Dimensional Visualization and Quantification of Hemodynamic Alterations Using 4-Dimensional Flow Magnetic Resonance Imaging

: Schuchardt, F.; Hennemuth, A.; Schroeder, L.; Meckel, S.; Markl, M.; Wehrum, T.; Harloff, A.


Stroke 48 (2017), Nr.3, S.671-677
ISSN: 0039-2499
ISSN: 0749-7954
ISSN: 1524-4628
Fraunhofer MEVIS ()

Background and Purpose-Cerebral venous thrombosis (CVT) affects venous hemodynamics and can provoke severe stroke and chronic intracranial hypertension. We sought to comprehensively analyze 3-dimensional blood flow and hemodynamic alterations during acute CVT including collateral recruitment and at follow-up. Methods-Twenty-two consecutive patients with acute CVT were prospectively included and underwent routine brain magnetic resonance imaging (MRI) and 4-dimensional flow MRI at 3 T for the in vivo assessment of cerebral blood flow. Neurological and MRI follow-up at 6 months was performed in 18 patients. Results-Three-dimensional blood flow visualization and quantification of large dural venous sinuses and deep cerebral veins was successfully performed in all patients. During acute CVT, we observed abnormal flow patterns including stagnant flow, flow acceleration in stenoses, and change of flow directions. In patients with complete recanalization, flow trajectories resembled those known from previously published 4-dimensional flow MRI data in healthy adults. There was a trend toward a relationship between occluded segments and cerebral lesions (not significant). Furthermore, patients with versus without cerebral lesions showed increased mean (0.080.09 versus 0.005 +/- 0.014 m/s) and peak velocities (0.18 +/- 0.21 versus 0.006 +/- 0.02 m/s) within partially thrombosed left and right transverse sinuses (P<0.05) at baseline. Conclusions-Four-dimensional flow MRI was successfully applied for the 3-dimensional visualization and quantification of venous hemodynamics in patients with CVT and provided new dynamic information regarding vessel recanalization. This technique seems promising to investigate the contribution of hemodynamic parameters and collaterals in a larger cohort to identify those at risk of stroke.