Abstract

This study aims to investigate a characteristic cerebellar hemisphere enhancement pattern on magnetic resonance imaging (MRI) that could aid in early and specific diagnosis of intracranial dural arteriovenous fistulas (DAVFs). Pretreatment MR images of 57 patients with intracranial DAVFs between January 1, 2017, and February 28, 2023, were retrospectively analyzed. A total of 128 patients with confirmed alternative cerebellar lesions during the same period were included as a control group. All patients underwent enhanced MRI with a 3.0T scanner. The presence or absence of parallel enhanced linear striations on the surface of the cerebellar lesions was documented. Statistically significant differences were determined by the Fisher exact test. Cerebellar lesions were identified in 4 intracranial DAVF patients (7.0%). All 4 patients were male, with an average age of 64 years (range: 58-76 years). The pretreatment MR images of all 4 DAVF patients with cerebellar lesions demonstrated the characteristic tigroid enhancement pattern. Tortuous flow voids were present in the MR images of 3 of the 4 patients. Tigroid enhancement pattern was not observed in the remaining 53 intracranial DAVF patients and all control patients. The differences in the incidence of the pattern were significant (p=0.01). A characteristic tigroid enhancement pattern of the cerebellar hemisphere on MRI may aid in the early and specific diagnosis of intracranial DAVFs, allowing timely treatment and improving outcomes. The identification of a characteristic tigroid enhancement pattern on MRI for cerebellar hemisphere lesions holds significant promise for clinical practice. This pattern serves as a distinctive marker aiding in the early and specific diagnosis of intracranial dural arteriovenous fistulas (DAVFs). Clinicians can now utilize this innovative finding to expedite diagnostic workflows, enabling timely intervention and management strategies. The incorporation of this novel imaging feature enhances diagnostic accuracy, potentially reducing misdiagnosis rates and preventing delays in treatment initiation. Ultimately, this advancement may lead to improved patient outcomes and quality of care in neurosurgical and neuroradiological practice.

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