Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
World Neurosurg. 2024 Jan;181:e567-e577. doi: 10.1016/j.wneu.2023.10.095. Epub 2023 Oct 27.
High-resolution magnetic resonance imaging (MRI) of the trigeminal nerve is indispensable for workup of trigeminal neuralgia (TN) before microvascular decompression; however, the evaluation is often subjective and prone to variability. We aim to develop and assess sequential thresholding-based automated reconstruction of the trigeminal nerve (STAR-TN) as an algorithm for segmenting the trigeminal nerve and contacting structures that will allow for a structured method for assessing neurovascular conflict.
A total of 42 patients with TN who underwent high-resolution MRI before microvascular decompression in 2022 were included in our study. Segmentation of the trigeminal nerve and contacting structures was performed on preoperative MRI scans using STAR-TN. The segmentations were then evaluated for neurovascular conflict and compared to the preoperative radiology and operative notes. Geometric features, including the area of contact and distance to conflict, were extracted.
Of the 42 patients, 32 (76.2%) were found to show neurovascular conflict based solely on their STAR-TN segmentations and 10 (23.8%) were found to not show neurovascular conflict. Compared with the intraoperative findings, this resulted in a sensitivity of 78.0% and specificity of 100%. In contrast, assessments of neurovascular conflict by radiologists using only 2-dimensional MRI views had a sensitivity of 68.3% and specificity of 100%. Of the 32 patients with neurovascular conflict, 29 (90.9%) had conflict within the root entry zone. Overall, the patients had a median area of contact of 10.66 mm.
STAR-TN allows for 3-dimensional visualization and identification of neurovascular conflict with improved sensitivity compared with neuroradiologist assessments from MRI slices.
高分辨率磁共振成像(MRI)对三叉神经痛(TN)微血管减压术前的检查是不可或缺的;然而,这种评估往往是主观的,容易出现差异。我们旨在开发和评估基于连续阈值的三叉神经自动重建(STAR-TN)作为一种分割三叉神经和接触结构的算法,从而为评估神经血管冲突提供一种结构化的方法。
本研究共纳入 2022 年 42 例接受微血管减压术前高分辨率 MRI 的 TN 患者。使用 STAR-TN 对术前 MRI 扫描进行三叉神经和接触结构的分割。然后评估这些分割结果是否存在神经血管冲突,并与术前放射学和手术记录进行比较。提取了包括接触面积和距离冲突等几何特征。
在 42 例患者中,仅根据 STAR-TN 分割结果,有 32 例(76.2%)发现存在神经血管冲突,10 例(23.8%)发现不存在神经血管冲突。与术中发现相比,敏感性为 78.0%,特异性为 100%。相比之下,放射科医生仅使用二维 MRI 视图评估神经血管冲突的敏感性为 68.3%,特异性为 100%。在 32 例存在神经血管冲突的患者中,有 29 例(90.9%)在神经根进入区存在冲突。总体而言,患者的接触面积中位数为 10.66mm。
与 MRI 切片的神经放射科医生评估相比,STAR-TN 允许进行三维可视化和识别神经血管冲突,敏感性更高。