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凸面脑膜瘤的术前影像学分类以预测生存率及侵袭性脑膜瘤行为。

Preoperative radiologic classification of convexity meningioma to predict the survival and aggressive meningioma behavior.

作者信息

Liu Yi, Chotai Silky, Chen Ming, Jin Shi, Qi Song-tao, Pan Jun

机构信息

Department of Neurosurgery, Nanfang Hospital of Southern Medical University, Guangzhou, China.

出版信息

PLoS One. 2015 Mar 18;10(3):e0118908. doi: 10.1371/journal.pone.0118908. eCollection 2015.

DOI:10.1371/journal.pone.0118908
PMID:25786236
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4364713/
Abstract

BACKGROUND

A subgroup of meningioma demonstrates clinical aggressive behavior. We set out to determine if the radiological parameters can predict histopathological aggressive meningioma, and propose a classification to predict survival and aggressive meningioma behavior.

METHODS

A retrospective review of medical records was conducted for patients who underwent surgical resection of their convexity meningioma. WHO-2007 grading was used for histopathological diagnosis. Preoperative radiologic parameters were analyzed, each parameter was scored 0 or 1. Signal intensity on diffusion weighted MRI (DWI) (hyperintensity=1), heterogeneity on T1-weighted gadolinium enhanced MRI (heterogeneity=1), disruption of arachnoid at brain-tumor interface=1 and peritumoral edema (PTE) on T2-weighted MRI (presence of PTE=1) and tumor shape (irregular shape=1). Multivariate logistic regression analyses were conducted to determine association of radiological parameters to histopathological grading. Kaplan-Meier and Cox regression models were used to determine the association of scoring system to overall survival and progression free survival (PFS). Reliability of the classification was tested using Kappa co-efficient analysis.

RESULTS

Hyperintensity on DWI, disruption of arachnoid at brain-tumor interface, PTE, heterogenicitiy on T1-weighted enhanced MRI and irregular tumor shape were independent predictors of non-grade I meningioma. Mean follow-up period was 94.6 months (range, 12-117 months). Median survival and PFS in groups-I, II and III was 114.1±1.2 and 115.7± 0.8, 88± 3.3 and 58.5±3.9, 43.2± 5.1 and 18.2±1.7 months respectively. In cox regression analysis model, age (P<0.0001, OR-1.039, CI-1.017-0.062), WHO non-grade-I meningioma (P=0.017, OR-3.014, CI-1.217-7.465), radiological classification groups II (P=0.002, OR-6.194, CI-1.956-19.610) and III (P<0.0001, OR-21.658, CI-5.701-82.273) were independent predictors of unfavorable survival outcomes.

CONCLUSIONS

Preoperative radiological classification can be used as a supplement to the histopathological grading. Group-I meningiomas demonstrate benign radiological, histopathological and clinical features; group-III demonstrates aggressive features. Group-II meningiomas demonstrate intermediate features; the need for more aggressive follow-up and/or treatment should be further investigated.

摘要

背景

一部分脑膜瘤表现出临床侵袭性行为。我们旨在确定放射学参数是否能够预测组织病理学上具有侵袭性的脑膜瘤,并提出一种分类方法以预测生存情况和脑膜瘤的侵袭性行为。

方法

对接受凸面脑膜瘤手术切除的患者的病历进行回顾性分析。组织病理学诊断采用世界卫生组织2007年分级标准。分析术前放射学参数,每个参数评分为0或1。扩散加权磁共振成像(DWI)上的信号强度(高信号=1)、T1加权钆增强磁共振成像上的异质性(异质性=1)、脑肿瘤界面蛛网膜的破坏=1、T2加权磁共振成像上的瘤周水肿(PTE)(存在PTE=1)以及肿瘤形状(不规则形状=1)。进行多变量逻辑回归分析以确定放射学参数与组织病理学分级之间的关联。采用Kaplan-Meier法和Cox回归模型确定评分系统与总生存和无进展生存(PFS)之间的关联。使用Kappa系数分析检验分类的可靠性。

结果

DWI上的高信号、脑肿瘤界面蛛网膜的破坏、PTE、T1加权增强磁共振成像上的异质性以及不规则肿瘤形状是非I级脑膜瘤的独立预测因素。平均随访期为94.6个月(范围:12 - 117个月)。I组、II组和III组的中位生存时间和PFS分别为114.1±1.2和115.7±0.8、88±3.3和58.5±3.9、43.2±5.1和18.2±1.7个月。在Cox回归分析模型中,年龄(P<0.0001,OR - 1.039,CI - 1.017 - 0.062)、世界卫生组织非I级脑膜瘤(P = 0.017,OR - 3.014,CI - 1.217 - 7.465)、放射学分类II组(P = 0.002,OR - 6.194,CI - 1.956 - 19.610)和III组(P<0.0001,OR - 21.658,CI - 5.701 - 82.273)是不良生存结局的独立预测因素。

结论

术前放射学分类可作为组织病理学分级的补充。I组脑膜瘤表现出良性的放射学、组织病理学和临床特征;III组表现出侵袭性特征。II组脑膜瘤表现出中间特征;对于更积极的随访和/或治疗的必要性应进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6b1/4364713/a68211eacdfc/pone.0118908.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6b1/4364713/b2ba10fff1e9/pone.0118908.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6b1/4364713/a68211eacdfc/pone.0118908.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6b1/4364713/b2ba10fff1e9/pone.0118908.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6b1/4364713/43645ddef37f/pone.0118908.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6b1/4364713/1caaeb3f5b80/pone.0118908.g003.jpg
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