Affiliation:
1. Department of Surgical Sciences, Section of Neuroradiology, Uppsala University, Uppsala, Sweden
2. Department of Neuroscience, Section of Neurosurgery, Uppsala University, Uppsala, Sweden
Abstract
Background Hemodynamic changes are seen in the feeding arteries of arteriovenous malformations (AVMs). Phase-contrast MRI (PC-MRI) enables the acquisition of hemodynamic information from blood vessels. There is insufficient knowledge on which flow or velocity parameter best discriminates AVMs from healthy subjects. Purpose To evaluate PC-MRI-measured flow and velocity in feeding arteries of AVMs before and, when possible, also after treatment and to compare these measurements to corresponding measurements in healthy controls. Materials and Methods Highest flow (HF), lowest flow (LF), mean flow (MF), peak systolic velocity (PSV), end-diastolic velocity (EDV), and mean velocity (MV) were measured in feeding arteries in patients with intracranial AVMs using 2D PC-MRI at 3 T. Measurements were compared to previously reported values in healthy individuals. Values in patients above the 95th percentile in the healthy cohort were categorized as pathological. Nidus volume was measured using 3D time-of-flight MR angiography. Results Ten patients with diagnosed AVMs were examined with PC-MRI. Among these, three patients also underwent follow-up PC-MRI after treatment. Pathological velocities (PSV, EDV, and MV) were seen in all five subjects with a nidus larger or equal to 5.7 cm3, whereas pathological flow values were not seen in all, that is, pathologic HF in three, pathologic LF in two, and pathologic MF in two. After treatment, there was a decrease in flow and velocity (all measured parameters). After treatment, velocities (PSV, EDV, and MV) were no longer abnormal compared to healthy controls. Conclusion Patients with a large AVM nidus show pathological velocities, but less consistent flow increases. Following treatment, velocities normalize.
Funder
Philips Healthcare
Landstinget i Uppsala län
Swedish Stroke Foundation
GE Healthcare