Sato Mitsuru, Tateishi Kensuke, Murata Hidetoshi, Kin Taichi, Suenaga Jun, Takase Hajime, Yoneyama Tomohiro, Nishii Toshiaki, Tateishi Ukihide, Yamamoto Tetsuya, Saito Nobuhito, Inoue Tomio, Kawahara Nobutaka
a Department of Neurosurgery, Graduate School of Medicine , Yokohama City University , Yokohama , Japan.
b Department of Neurosurgery , The University of Tokyo Graduate School of Medicine , Tokyo , Japan.
Br J Neurosurg. 2018 Oct;32(5):509-515. doi: 10.1080/02688697.2018.1485877. Epub 2018 Jun 26.
The utility of surgical simulation with three-dimensional multimodality fusion imaging (3D-MFI) has been demonstrated. However, its potential in deep-seated brain lesions remains unknown. The aim of this study was to investigate the impact of 3D-MFI in deep-seated meningioma operations.
Fourteen patients with deeply located meningiomas were included in this study. We constructed 3D-MFIs by fusing high-resolution magnetic resonance (MR) and computed tomography (CT) images with a rotational digital subtraction angiogram (DSA) in all patients. The surgical procedure was simulated by 3D-MFI prior to operation. To assess the impact on neurosurgical education, the objective values of surgical simulation by 3D-MFIs/virtual reality (VR) video were evaluated. To validate the quality of 3D-MFIs, intraoperative findings were compared. The identification rate (IR) and positive predictive value (PPV) for the tumor feeding arteries and involved perforating arteries and veins were also assessed for quality assessment of 3D-MFI.
After surgical simulation by 3D-MFIs, near-total resection was achieved in 13 of 14 (92.9%) patients without neurological complications. 3D-MFIs significantly contributed to the understanding of surgical anatomy and optimal surgical view (p < .0001) and learning how to preserve critical vessels (p < .0001) and resect tumors safety and extensively (p < .0001) by neurosurgical residents/fellows. The IR of 3D-MFI for tumor-feeding arteries and perforating arteries and veins was 100% and 92.9%, respectively. The PPV of 3D-MFI for tumor-feeding arteries and perforating arteries and veins was 98.8% and 76.5%, respectively.
3D-MFI contributed to learn skull base meningioma surgery. Also, 3D-MFI provided high quality to identify critical anatomical structures within or adjacent to deep-seated meningiomas. Thus, 3D-MFI is promising educational and surgical planning tool for meningiomas in deep-seated regions.
三维多模态融合成像（3D-MFI）在手术模拟中的效用已得到证实。然而，其在深部脑病变中的潜力仍不明确。本研究的目的是探讨3D-MFI在深部脑膜瘤手术中的影响。
本研究纳入了14例深部脑膜瘤患者。我们通过将高分辨率磁共振（MR）和计算机断层扫描（CT）图像与旋转数字减影血管造影（DSA）融合，为所有患者构建了3D-MFI。术前通过3D-MFI模拟手术过程。为评估对神经外科教育的影响，对3D-MFI/虚拟现实（VR）视频模拟手术的客观值进行了评估。为验证3D-MFI的质量，将术中发现进行了比较。还评估了肿瘤供血动脉以及受累穿支动脉和静脉的识别率（IR）和阳性预测值（PPV），以进行3D-MFI的质量评估。
通过3D-MFI模拟手术后，14例患者中有13例（92.9%）实现了近全切除，且无神经并发症。3D-MFI显著有助于神经外科住院医师/进修医师理解手术解剖结构和最佳手术视野（p <.0001），学习如何保留关键血管（p <.0001）以及安全、广泛地切除肿瘤（p <.0001）。3D-MFI对肿瘤供血动脉以及穿支动脉和静脉的IR分别为100%和92.9%。3D-MFI对肿瘤供血动脉以及穿支动脉和静脉的PPV分别为98.8%和76.5%。
3D-MFI有助于学习颅底脑膜瘤手术。此外，3D-MFI能够高质量地识别深部脑膜瘤内部或附近的关键解剖结构。因此，3D-MFI是深部区域脑膜瘤有前景的教育和手术规划工具。
