Surgical Planning Laboratory - Brigham & Women's Hospital - Boston, Massachusetts USA - a teaching affiliate of Harvard Medical School

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Multimodal Image-Based Virtual Reality Presurgical Simulation and Evaluation for Trigeminal Neuralgia and Hemifacial Spasm

Institution:
1Department of Neurosurgery, Chinese PLA General Hospital, Beijing, China.
2Department of Neurosurgery, University Erlangen-Nurnberg, Erlangen, Germany.
3Surgical Planning Laboratory, Brigham and Women's Hospital, Harvard University, Boston, USA.
Publication Date:
May-2018
Journal:
World Neurosurg
Volume Number:
113
Pages:
e499-e507
Citation:
World Neurosurg. 2018 May;113:e499-e507.
PubMed ID:
29476993
Keywords:
Hemifacial spasm, Microvascular decompression, Neurovascular confliction, Trigeminal neuralgia, Virtual reality
Appears in Collections:
NAC, SPL
Generated Citation:
Yao S., Zhang J., Zhao Y., Hou Y., Xu X., Zhang Z., Kikinis R., Chen X. Multimodal Image-Based Virtual Reality Presurgical Simulation and Evaluation for Trigeminal Neuralgia and Hemifacial Spasm. World Neurosurg. 2018 May;113:e499-e507. PMID: 29476993.
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OBJECTIVE: To address the feasibility and predictive value of multimodal image-based virtual reality in detecting and assessing features of neurovascular confliction (NVC), particularly regarding the detection of offending vessels, degree of compression exerted on the nerve root, in patients who underwent microvascular decompression for nonlesional trigeminal neuralgia and hemifacial spasm (HFS). METHODS: This prospective study includes 42 consecutive patients who underwent microvascular decompression for classic primary trigeminal neuralgia or HFS. All patients underwent preoperative 1.5-T magnetic resonance imaging (MRI) with T2-weighted three-dimensional (3D) sampling perfection with application-optimized contrasts by using different flip angle evolutions, 3D time-of-flight magnetic resonance angiography, and 3D T1-weighted gadolinium-enhanced sequences in combination, whereas 2 patients underwent extra experimental preoperative 7.0-T MRI scans with the same imaging protocol. Multimodal MRIs were then coregistered with open-source software 3D Slicer, followed by 3D image reconstruction to generate virtual reality (VR) images for detection of possible NVC in the cerebellopontine angle. Evaluations were performed by 2 reviewers and compared with the intraoperative findings. RESULTS: For detection of NVC, multimodal image-based VR sensitivity was 97.6% (40/41) and specificity was 100% (1/1). Compared with the intraoperative findings, the κ coefficients for predicting the offending vessel and the degree of compression were >0.75 (P < 0.001). The 7.0-T scans have a clearer view of vessels in the cerebellopontine angle, which may have significant impact on detection of small-caliber offending vessels with relatively slow flow speed in cases of HFS. CONCLUSIONS: Multimodal image-based VR using 3D sampling perfection with application-optimized contrasts by using different flip angle evolutions in combination with 3D time-of-flight magnetic resonance angiography sequences proved to be reliable in detecting NVC and in predicting the degree of root compression. The VR image-based simulation correlated well with the real surgical view.