胶质瘤边缘的术中活体共焦内窥镜检查:神经外科医生用户的图像解读性能评估

Yuan Xu, Thomas J. On, Irakliy Abramov, Francesco Restelli, Evgenii Belykh, Andrea M. Mathis, Jürgen Schlegel, Ekkehard Hewer, Bianca Pollo, Theoni Maragkou, Karl Quint, Randall W. Porter, Kris A. Smith, Mark C. Preul
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引用次数: 0

摘要

共焦激光内窥镜(CLE)是一种术中实时细胞分辨率成像技术,可对脑肿瘤组织结构进行成像。此前,我们曾证明神经病理学家可以通过解读 CLE 图像来确定胶质瘤边缘是否存在肿瘤浸润。在这项研究中,我们评估了神经外科医生解读神经胶质瘤边缘 CLE 图像的能力,并将他们的评估结果与神经病理学家的评估结果进行了比较。在神经胶质瘤边缘采集的活体 CLE 图像以前曾由具有 CLE 经验的神经病理学家进行过审查,现在由四位具有 CLE 经验的神经外科医生进行解读。他们采用了从 0 到 5 的数字评分系统和基于病理特征的二分法评分系统。在之前的一项研究中,神经病理学家对苏木精和伊红(H&E)染色切片和 CLE 图像的评估得分也被用来进行比较。神经外科医生的评分与 H&E 结果进行了比较。根据神经外科医生的评分计算出评分者之间的一致性和诊断效果。共有来自 56 个胶质瘤边缘感兴趣区(ROI)的 4275 张图像被纳入分析。采用数字评分系统后,神经外科医生对所有 ROI 的 CLE 图像进行判读的评分者之间的一致性为中等(平均一致性为 61%),明显优于神经病理学家的评分者之间的一致性(平均一致性为 48%)(P < 0.01)。使用二分法评分系统的神经外科医生的评分者之间的一致性为 83%。数字评分系统和二分法评分系统的一致性为 93%。数字评分系统的总体灵敏度、特异性、阳性预测值和阴性预测值分别为78%、32%、62%和50%,二分法评分系统的总体灵敏度、特异性、阳性预测值和阴性预测值分别为80%、27%、61%和48%。神经外科医生和神经病理学家的诊断结果在统计学上没有明显差异。神经外科医生在解读 CLE 图像方面的表现与神经病理学家相当。这些结果表明,CLE 可用作术中指导工具,由神经外科医生在神经病理学家协助或不协助的情况下解读图像。二分法评分系统既稳健又简单,可简化成像过程中对 CLE 图像的快速、同步解读。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intraoperative in vivo confocal endomicroscopy of the glioma margin: performance assessment of image interpretation by neurosurgeon users
Confocal laser endomicroscopy (CLE) is an intraoperative real-time cellular resolution imaging technology that images brain tumor histoarchitecture. Previously, we demonstrated that CLE images may be interpreted by neuropathologists to determine the presence of tumor infiltration at glioma margins. In this study, we assessed neurosurgeons’ ability to interpret CLE images from glioma margins and compared their assessments to those of neuropathologists.In vivo CLE images acquired at the glioma margins that were previously reviewed by CLE-experienced neuropathologists were interpreted by four CLE-experienced neurosurgeons. A numerical scoring system from 0 to 5 and a dichotomous scoring system based on pathological features were used. Scores from assessments of hematoxylin and eosin (H&E)-stained sections and CLE images by neuropathologists from a previous study were used for comparison. Neurosurgeons’ scores were compared to the H&E findings. The inter-rater agreement and diagnostic performance based on neurosurgeons’ scores were calculated. The concordance between dichotomous and numerical scores was determined.In all, 4275 images from 56 glioma margin regions of interest (ROIs) were included in the analysis. With the numerical scoring system, the inter-rater agreement for neurosurgeons interpreting CLE images was moderate for all ROIs (mean agreement, 61%), which was significantly better than the inter-rater agreement for the neuropathologists (mean agreement, 48%) (p < 0.01). The inter-rater agreement for neurosurgeons using the dichotomous scoring system was 83%. The concordance between the numerical and dichotomous scoring systems was 93%. The overall sensitivity, specificity, positive predictive value, and negative predictive value were 78%, 32%, 62%, and 50%, respectively, using the numerical scoring system and 80%, 27%, 61%, and 48%, respectively, using the dichotomous scoring system. No statistically significant differences in diagnostic performance were found between the neurosurgeons and neuropathologists.Neurosurgeons’ performance in interpreting CLE images was comparable to that of neuropathologists. These results suggest that CLE could be used as an intraoperative guidance tool with neurosurgeons interpreting the images with or without assistance of the neuropathologists. The dichotomous scoring system is robust yet simple and may streamline rapid, simultaneous interpretation of CLE images during imaging.
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