Predicting the Outcome of Microvascular Decompression for Trigeminal Neuralgia Using Magnetic Resonance Tomographic Angiography

Abstract

To investigate the role of preoperative magnetic resonance tomographic angiography (MRTA) in predicting the clinical outcomes of trigeminal neuralgia (TN) patients following microvascular decompression (MVD). Preoperative MRTA imaging was performed on 167 consecutive patients with TN. The characteristics of offending vessels were determined by MRTA prior to MVD. The relationship of neurovascular contact was classified into 3 types: positive, negative, and contralateral positive, which were compared with the surgical findings and clinical outcomes. MRTA showed obvious neurovascular compression in accordance with surgical findings in 144 patients. Among the remaining 23 patients with negative finding on preoperative MRTA images, neurovascular compression (vein alone or in combination with artery) were found in 16, no definite vascular compression in 7. The sensitivity of MRTA on the symptomatic side was therefore 90%, the specificity was 100% in our series. A correlation was found between clinical outcomes and preoperative findings on MRTA. In 144 MRTA-positive patients, 136 achieved "excellent" or "good" outcomes after MVD and were significantly better than the MRTA-negative group (P < .01). The outcomes of patients with a single artery compression were significantly better than those with venous compression, vein in combination with artery compression, or without obvious neurovascular contact (P < .01). Seven of 23 MRTA-negative patients obtained poor outcomes after operation, venous compression were identified intraoperatively in 4 of them, no definite offending vessel was found in 3 patients. This study suggests that the curative rate of TN following MVD is higher in the MRTA-positive group. Venous compression and no neurovascular contact that were negative on MRTA image are poor prognostic factors for surgical outcome of TN. Thus, preoperative MRTA serves as a useful tool in patient selection and outcome prediction.