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Magnetic Resonance Angiography in the Diagnosis of Cerebral Arteriovenous Malformation and Dural Arteriovenous Fistulas: Comparison of Time-Resolved Magnetic Resonance Angiography and Three Dimensional Time-of-Flight Magnetic Resonance Angiography.

BACKGROUND: Traditional digital subtraction angiography (DSA) is currently the gold standard diagnostic method for the diagnosis and evaluation of cerebral arteriovenous malformation (AVM) and dural arteriovenous fistulas (dAVF).

OBJECTIVES: The aim of this study was to analyze different less invasive magnetic resonance angiography (MRA) images, time-resolved MRA (TR-MRA) and three-dimensional time-of-flight MRA (3D TOF MRA) to identify their diagnostic accuracy and to determine which approach is most similar to DSA.

PATIENTS AND METHODS: A total of 41 patients with AVM and dAVF at their initial evaluation or follow-up after treatment were recruited in this study. We applied time-resolved angiography using keyhole (4D-TRAK) MRA to perform TR-MRA and 3D TOF MRA examinations simultaneously followed by DSA, which was considered as a standard reference. Two experienced neuroradiologists reviewed the images to compare the diagnostic accuracy, arterial feeder and venous drainage between these two MRA images. Inter-observer agreement for different MRA images was assessed by Kappa coefficient and the differences of diagnostic accuracy between MRA images were evaluated by the Wilcoxon rank sum test.

RESULTS: Almost all vascular lesions (92.68%) were correctly diagnosed using 4D-TRAK MRA. However, 3D TOF MRA only diagnosed 26 patients (63.41%) accurately. There were statistically significant differences regarding lesion diagnostic accuracy (P = 0.008) and venous drainage identification (P < 0.0001) between 4D-TRAK MRA and 3D TOF MRA. The results indicate that 4D-TRAK MRA is superior to 3D TOF MRA in the assessment of lesions.

CONCLUSION: Compared with 3D TOF MRA, 4D-TRAK MRA proved to be a more reliable screening modality and follow-up method for the diagnosis of cerebral AVM and dAVF.

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