Kim Tae-Shin, Kuh Jae Hee, Kim Junhoe, Yuh Woon Tak, Han Junghoon, Lee Chang-Hyun, Kim Chi Heon, Chung Chun Kee
Department of Neurosurgery, Seoul National University Hospital, Seoul, Korea.
Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Korea.
Neurospine. 2024 Sep;21(3):890-902. doi: 10.14245/ns.2448468.234. Epub 2024 Sep 30.
Classification guides the surgical approach and predicts prognosis. However, existing classifications of spinal schwannomas often result in a high 'unclassified' rate. Here, we aim to develop a new comprehensive classification for spinal schwannomas based on their presumed origin. We compared the new classification with the existing classifications regarding the rate of 'unclassified'. Finally, we assessed the surgical strategies, outcomes, and complications according to each type of the new classification.
A new classification with 9 types was created by analyzing the anatomy of spinal nerves and the origin of significant tumor portions and cystic components in preoperative magnetic resonance images. A total of 482 patients with spinal schwannomas were analyzed to compare our new classification with the existing classifications. We defined 'unclassified' as the inability to classify a patient with spinal schwannoma using the classification criteria. Surgical approaches and outcomes were also aligned with our new classification.
Our classification uniquely reported no 'unclassified' cases, indicating full applicability. Also, the classification has demonstrated usefulness in predicting the surgical outcome with the approach planned. Gross total removal rates reached 88.0% overall, with type 1 and type 2 tumors at 95.3% and 96.0% respectively. The approach varied with tumor type, with laminectomy predominantly used for types 1, 2, and 9, and facetectomy with posterior fixation used for type 3 tumors.
The new classification for spinal schwannomas based on presumed origin is applicable to all spinal schwannomas. It could help plan a surgical approach and predict its outcome, compared with existing classifications.
分类指导手术方式并预测预后。然而，现有的脊柱神经鞘瘤分类常常导致较高的“未分类”率。在此，我们旨在基于脊柱神经鞘瘤的假定起源制定一种新的综合分类。我们将新分类与现有分类在“未分类”率方面进行了比较。最后，我们根据新分类的每种类型评估了手术策略、结果及并发症。
通过分析术前磁共振图像中脊神经的解剖结构以及显著肿瘤部分和囊性成分的起源，创建了一种包含9种类型的新分类。共分析了482例脊柱神经鞘瘤患者，以将我们的新分类与现有分类进行比较。我们将“未分类”定义为无法使用分类标准对脊柱神经鞘瘤患者进行分类。手术方式和结果也与我们的新分类相对应。
我们的分类独特地报告无“未分类”病例，表明其具有完全适用性。此外，该分类在通过计划的手术方式预测手术结果方面已证明有用。总体全切率达到88.0%，1型和2型肿瘤的全切率分别为95.3%和96.0%。手术方式因肿瘤类型而异，椎板切除术主要用于1型、2型和9型，而3型肿瘤采用小关节突切除术并进行后路固定。
基于假定起源的脊柱神经鞘瘤新分类适用于所有脊柱神经鞘瘤。与现有分类相比，它有助于规划手术方式并预测其结果。
