T<sub>1</sub>WI增强纹理参数联合临床病理学特征对脑胶质瘤患者术后1年内复发的预测价值研究

doi:10.3760/cma.j.cn101202-20220115-00015

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摘要目的探讨T₁WI增强纹理参数联合临床病理学特征对脑胶质瘤患者术后1年内复发的预测价值。方法回顾性队列研究。纳入2018年1月—2021年2月川北医学院附属医院及重庆市人民医院经术后病理确诊的脑胶质瘤患者90例。其中男60例、女30例,年龄17~76（47±14）岁,术后1年内复发46例、未复发44例。按照2∶1比例将患者随机分为训练集与验证集。采用MaZda软件于术前MR T₁WI增强图像上提取胶质瘤纹理参数。在训练集中对纹理参数进行降维筛选并利用最小绝对收缩和选择算子（LASSO）算法分析建立预后纹理积分模型。同时在训练集中对术后1年内复发与未复发患者的临床病理学特征及纹理积分进行影响因素分析,构建可视化联合预测模型。观察项目：（1）分析影响脑胶质瘤术后1年内复发的危险因素,并建立联合预测模型。（2）在验证集中,对纹理积分模型及联合预测模型进行验证。采用受试者工作特征（ROC）曲线、校准曲线及决策曲线分析法评价模型的诊断效能与临床净获益。结果单因素分析显示,肿瘤WHO分级、异柠檬酸脱氢酶-1突变、术后放化疗、纹理积分是脑胶质瘤术后1年内复发的影响因素。多因素分析结果显示,WHO分级、异柠檬酸脱氢酶-1突变、术后放化疗及纹理积分均为脑胶质瘤术后1年内复发的独立危险因素[风险比（OR）=6.527、0.160、0.052、6.300,95％可信区间（CI）=1.201~35.485、0.031~0.827、0.004~0.708、1.905~20.841,P=0.030、0.029、0.026、0.003]。联合预测模型预测脑胶质瘤术后1年内复发的效能高于纹理积分模型,其训练集与验证集的曲线下面积（AUC）分别为0.92（95％CI 0.86~0.99）和0.86（95％CI 0.74~0.99）,灵敏度分别为0.90、0.88,特异度分别为0.83、0.79;纹理积分模型在训练集与验证集中的预测AUC分别为0.85（95％CI 0.75~0.95）和0.82（95％CI 0.67~0.97）,灵敏度分别为0.73、0.63,特异度分别为0.90、0.99。在两种模型中,预测概率与实际概率间的一致性及临床净获益均较高。结论基于术前T₁WI增强图像的纹理参数联合临床病理学特征建立的联合预测模型对脑胶质瘤全切术后1年内的复发具有一定的预测价值。

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	谢刚
	唐伍丽
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	李康

关键词 ：神经胶质瘤, 肿瘤复发, 磁共振成像, 纹理参数, 预后

Abstract：Objective This study aimed to investigate the predictive value of contrast-enhanced T₁ weighted imaging (cT₁WI) texture parameters combined with clinicopathological features in postoperative recurrence of glioma. Methods This work was a retrospective cohort study. A total of 90 patients with brain gliomas diagnosed pathologically after operation were included in the Affiliated Hospital of North Sichuan Medical College and Chongqing General Hospital from January 2018 to February 2021. The patients comprised 60 males and 30 females, with an age range of 17-76 (47±14) years. Within 1 year after operation, 46 cases recurred and 44 cases did not. The patients were randomly divided into the training set and verification set following the ratio of 2∶1. The texture parameters of glioma were extracted from preoperative cT₁WI by Mazda software. In the training set, the texture parameters were screened, and the prognostic texture score was established by using the least absolute shrinkage and selection operator. Factor analysis was performed on the clinicopathological characteristics and texture score of patients with recurrence and non-recurrence within 1 year after operation in the training set. A visual combined prediction model was then constructed. (1) The risk factors of glioma recurrence within 1 year after operation were analyzed, and a combined prediction model was established. (2) In the verification set, the texture score and combined prediction model were verified. Receiver operating characteristic curve, calibration curve, and decision curve analysis were used to evaluate the diagnostic efficacy and clinical net benefit of the model. Results Univariate analysis showed that WHO grade, isocitrate dehydrogenase-1 mutation, postoperative chemoradiotherapy, and texture score were the influencing factors of glioma recurrence within 1 year after operation. Multivariate analysis showed that all of them were independent risk factors for the recurrence of glioma within 1 year after operation (odds ratio [OR]=6.527, 0.160, 0.052,and 6.300; 95％ confidence interval [CI]=1.201-35.485, 0.031-0.827, 0.004-0.708, and 1.905-20.841; P =0.030, 0.029, 0.026, and 0.003). The efficiency of the combined model in predicting the recurrence of glioma within 1 year after operation was higher than that of the texture score model. In the combined model, the training and verification sets had area under curve (AUCs) of 0.92 (95％ CI 0.86-0.99) and 0.86 (95％ CI 0.74-0.99), sensitivity of 0.90 and 0.88, and specificity of 0.83 and 0.79, respectively. In the texture score model, the training and verification sets had AUCs of 0.85 (95％ CI 0.75-0.95) and 0.82 (95％ CI 0.67-0.97), sensitivity of 0.73 and 0.63, and specificity of 0.90 and 0.99, respectively. In the two prediction models, the consistency between prediction probability and actual probability and clinical net benefit was quite good. Conclusion The combined model based on the texture parameters of preoperative cT₁WI and clinicopathological features has good predictive value for the recurrence of glioma within 1 year after total resection.

Key words： Glioma Neoplasm recurrence Magnetic resonance imaging Texture parameter Prognosis

收稿日期: 2022-01-15

基金资助:重庆市科技局技术创新与应用发展专项（CSTC2020JSCX-SBW0024）; 重庆市科技局、市卫健委联合科研项目（2019ZDXM008）; 重庆市渝中区基础研究与前沿探索项目（20180107）; 重庆巿人民医院医学科技创新基金项目（Y2019ZDXM01）

通讯作者: 李康,Email：Likang@ucas.ac.cn

引用本文:

谢刚, 唐伍丽, 刘军, 李康. T₁WI增强纹理参数联合临床病理学特征对脑胶质瘤患者术后1年内复发的预测价值研究[J]. 中华解剖与临床杂志, 2022, 27(8): 539-544.
Xie Gang, Tang Wuli, Liu Jun, Li Kang. Predictive value of contrast-enhanced T₁ weighted imaging texture parameters combined with clinicopathological features in postoperative recurrence of glioma. Chinese Journal of Anatomy and Clinics, 2022, 27(8): 539-544.

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http://www.cjac.com.cn/CN/10.3760/cma.j.cn101202-20220115-00015 或 http://www.cjac.com.cn/CN/Y2022/V27/I8/539

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