[1]张文华,陈韬,张明慧,等.基于放射组学的胃肠道间质瘤分类模型[J].南方医科大学学报,2018,(01):55.
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基于放射组学的胃肠道间质瘤分类模型()
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《南方医科大学学报》[ISSN:1673-4254/CN:44-1627/R]

卷:
期数:
2018年01期
页码:
55
栏目:
出版日期:
2018-01-20

文章信息/Info

Title:
A radiomics-based model for differentiation between benign and malignant gastrointestinal stromal tumors
作者:
张文华陈韬张明慧刘平平卢振泰
关键词:
胃肠道间质瘤多变量分析分类模型放射组学
Keywords:
gastrointestinal stromal tumors multivariate analysis classification model radiomics
摘要:
目的通过对CT图像中提取的大量纹理特征进行多变量分析建立一个用于胃肠道间质瘤良恶性分类的模型。方法本研 究包含110个患有胃肠道间质瘤的病人(80个作为训练集,30个作为验证集)。首先在初始特征集中应用0.632+自助法进行特征 降维,然后在特征子集中进行逐步前向的特征选择,最后通过逻辑回归建立分类模型。结果6个纹理特征建立的分类模型能够 在训练集和验证集中成功地区分良恶性胃肠道间质瘤。该模型在训练集中得到的AUC、敏感性、特异性和分类准确率分别为 0.93、0.88、0.85和0.87;验证集中分别为0.91、0.87、0.86和0.86。结论本文以放射组学的研究方法建立了一个分类模型,对胃 肠道间质瘤良恶性分类具有优良的预测性能,因此可以将其作为术前肿瘤分类的辅助工具。
Abstract:
Objective To establish a model for discrimination between benign and malignant gastrointestinal stromal tumors (GIST) by analyzing the texture features extracted from computed tomography (CT) images. Methods The CT datasets were collected from 110 patients with GIST (including 80 as the training cohort and 30 as the validation cohort). Feature set reduction was executed with the 0.632 + bootstrap method in the initial feature set followed by stepwise forward feature selection in the feature subset, and the classification model was generated by logistic regression. Results The 6-texture-featurebased classification model successfully discriminated between benign and malignant GIST in both the training and validation cohorts with AUCs of 0.93 and 0.91, sensitivity of 0.88 and 0.87, specificity of 0.85 and 0.86, and accuracy of 0.87 and 0.86 in the two cohorts, respectively. Conclusion This classification model established by radiomics analysis is capable of discrimination between benign and malignant GIST to provide assistance in preoperative diagnosis of GIST.
更新日期/Last Update: 1900-01-01