Role of multimodal image-based 3D reconstruction for primary trigeminal neuralgia

Abstract

Objective: To address the feasibility and predictive value of multimodal image-based 3D reconstruction in assessing features of neurovascular relationship particularly regarding the detection of offending vessels, degree of compression exerted on the nerve root, in patients who underwent microvascular decompression for primary trigeminal neuralgia. Methods: This study includes 58 patients who underwent microvascular decompression for primary trigeminal neuralgia. All patients underwent preoperative 3.0-T magnetic resonance imaging (MRI) scan of 3D-TOF MRA and 3D-FIESTA sequences in combination. Multimodal MRIs were then registered with open-source software 3D Slicer, followed by 3D image reconstruction to get 3D models for detection of possible neurovascular relationship in the cerebellopontine angle (CPA). Evaluations were performed by 2 doctors and compared with the intraoperative findings and surgery video. Results: For detection of offending vessels, multimodal image-based 3D reconstruction sensitivity was 93.1% (54/58). Compared with the intraoperative findings, the k coefficients for evaluating the offending vessel and the degree of compression were >0.70 (P < 0.05). Conclusions: Multimodal image-based 3D reconstruction proved to be reliable and practical in detecting offending vessel and in predicting the degree of nerve compression. The 3D anatomical model is consistent with the structural position found during surgery, which means that the method is valuable in the formulation of preoperative plans.

Keywords

• Primary Trigeminal Neuralgia
• Microvascular decompression
• Multimodal image
• Offending vessel
• Image reconstruction