Department of Neurosurgery, Chinese PLA General Hospital, Beijing, China.
Department of Neurosurgery, Chinese PLA General Hospital, Beijing, China; Department of Neurosurgery, University Erlangen-Nurnberg, Erlangen, Germany.
World Neurosurg. 2018 May;113:e499-e507. doi: 10.1016/j.wneu.2018.02.069. Epub 2018 Feb 21.
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).
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.
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.
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.
探讨基于多模态影像的虚拟现实技术在检测和评估神经血管压迫症（NVC）特征方面的可行性和预测价值，特别是在检测引起症状的血管、神经根受压程度方面，这些特征在接受微血管减压术治疗非病变性三叉神经痛和半面痉挛（HFS）的患者中尤为重要。
本前瞻性研究纳入了 42 例因经典原发性三叉神经痛或 HFS 接受微血管减压术的连续患者。所有患者均接受术前 1.5T 磁共振成像（MRI）检查，采用 T2 加权三维（3D）采样完美技术，应用不同翻转角演化，3D 时间飞跃磁共振血管造影和 3D T1 加权钆增强序列相结合，其中 2 例患者额外进行了术前 7.0T MRI 扫描，采用相同的成像方案。多模态 MRI 随后使用开源软件 3D Slicer 进行配准，然后进行 3D 图像重建，以生成虚拟现实（VR）图像，用于检测桥小脑角可能存在的 NVC。由 2 名评估者进行评估，并与术中发现进行比较。
对于 NVC 的检测，基于多模态影像的 VR 技术的敏感性为 97.6%（40/41），特异性为 100%（1/1）。与术中发现相比，预测致病血管和压迫程度的 κ 系数均>0.75（P<0.001）。7.0T 扫描可更清晰地显示桥小脑角的血管，这可能对检测 HFS 中相对血流速度较慢的小口径致病血管具有重要意义。
采用 T2 加权三维采样完美技术，应用不同翻转角演化，结合 3D 时间飞跃磁共振血管造影序列的多模态影像 VR 技术在检测 NVC 和预测神经根受压程度方面是可靠的。VR 图像模拟与真实手术视图相关性良好。
