Suppr超能文献

评估CortexID定量分析在颞叶癫痫患者致痫区定位中的疗效。

Evaluating the Efficacy of CortexID Quantitative Analysis in Localization of the Epileptogenic Zone in Patients with Temporal Lobe Epilepsy.

作者信息

Li Shuangshuang, Guo Kun, Wang Yuanyuan, Wu Dianwei, Wang Yang, Feng Lanlan, Wang Junling, Meng Xiaoli, Ma Lei, He Hua, Kang Fei

机构信息

Department of Neurology, Xijing Hospital of Air Force Military Medical University, Xi'an, 710032, Shaanxi, China.

Medical School, Yan'an University, Yan'an, 716000, Shaanxi, China.

出版信息

Neurol Ther. 2024 Oct;13(5):1403-1414. doi: 10.1007/s40120-024-00646-1. Epub 2024 Aug 2.

Abstract

INTRODUCTION

There remains a critical need for precise localization of the epileptogenic foci in individuals with drug-resistant epilepsy (DRE). F-Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging can reveal hypometabolic regions during the interval between seizures in patients with epilepsy. However, visual-based qualitative analysis is time-consuming and strongly influenced by physician experience. CortexID Suite is a quantitative analysis software that helps to evaluate PET imaging of the human brain. Therefore, we aimed to evaluate the efficacy of CortexID quantitative analysis in the localization of the epileptogenic zone in patients with temporal lobe epilepsy (TLE).

METHODS

A total of 102 patients with epilepsy who underwent F-FDG-PET examinations were included in this retrospective study. The PET visual analysis was interpreted by two nuclear medicine physicians, and the quantitative analysis was performed automatically using CortexID analysis software. The assumed epileptogenic zone was evaluated comprehensively by two skilled neurologists in the preoperative assessment of epilepsy. The accuracy of epileptogenic zone localization in PET visual analysis was compared with that in CortexID quantitative analysis.

RESULTS

The diagnostic threshold for the difference in the metabolic Z-score between the right and left sides of medial temporal lobe epilepsy (MTLE) was calculated as 0.87, and that for lateral temporal lobe epilepsy (LTLE) was 2.175. In patients with MTLE, the area under the curve (AUC) was 0.922 for PET visual analysis, 0.853 for CortexID quantitative analysis, and 0.971 for the combined diagnosis. In patients with LTLE, the AUC was 0.842 for PET visual analysis, 0.831 for CortexID quantitative analysis, and 0.897 for the combined diagnosis. These results indicate that the diagnostic efficacy of CortexID quantitative analysis is not inferior to PET visual analysis (p > 0.05), while combined analysis significantly increases diagnostic efficacy (p < 0.05). Among the 23 patients who underwent surgery, the sensitivity and specificity of PET visual analysis for localization were 95.4% and 66.7%, and the sensitivity and specificity of CortexID quantitative analysis were 100% and 50%.

CONCLUSION

The diagnostic efficacy of CortexID quantitative analysis is comparable to PET visual analysis in the localization of the epileptogenic zone in patients with TLE. CortexID quantitative analysis combined with visual analysis can further improve the accuracy of epileptogenic zone localization.

摘要

引言

对于耐药性癫痫(DRE)患者,精确确定致痫灶仍极为必要。氟脱氧葡萄糖正电子发射断层扫描(FDG-PET)成像可揭示癫痫患者发作间期的代谢减低区域。然而,基于视觉的定性分析耗时且受医生经验影响较大。CortexID Suite是一款有助于评估人脑PET成像的定量分析软件。因此,我们旨在评估CortexID定量分析在颞叶癫痫(TLE)患者致痫区定位中的有效性。

方法

本回顾性研究纳入了102例接受F-FDG-PET检查的癫痫患者。PET视觉分析由两名核医学医生解读,定量分析使用CortexID分析软件自动进行。在癫痫术前评估中,由两名经验丰富的神经科医生综合评估假定的致痫区。比较PET视觉分析和CortexID定量分析在致痫区定位方面的准确性。

结果

内侧颞叶癫痫(MTLE)左右两侧代谢Z评分差异的诊断阈值计算为0.87,外侧颞叶癫痫(LTLE)为2.175。在MTLE患者中,PET视觉分析的曲线下面积(AUC)为0.922,CortexID定量分析为0.853,联合诊断为0.971。在LTLE患者中,PET视觉分析的AUC为0.842,CortexID定量分析为0.831,联合诊断为0.897。这些结果表明,CortexID定量分析的诊断效能不低于PET视觉分析(p>0.05),而联合分析显著提高了诊断效能(p<0.05)。在23例接受手术的患者中,PET视觉分析定位的敏感性和特异性分别为95.4%和66.7%,CortexID定量分析的敏感性和特异性分别为100%和50%。

结论

CortexID定量分析在TLE患者致痫区定位中的诊断效能与PET视觉分析相当。CortexID定量分析与视觉分析相结合可进一步提高致痫区定位的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6243/11393372/1bb2c8ca7714/40120_2024_646_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验