版权说明 操作指南
首页 > 成果 > 详情

Thoracic CT radiomics analysis for predicting synchronous brain metastasis in patients with lung cancer

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
Ding, Zhimin;Wang, Yuancheng;Xia, Cong;Meng, Xiangpan;Yu, Qian;...
通讯作者:
Ju, SH
作者机构:
[Ju, SH; Ju, Shenghong; Yu, Qian; Ding, Zhimin; Wang, Yuancheng; Meng, Xiangpan; Xia, Cong] Southeast Univ, Zhongda Hosp, Dept Radiol,Med Sch, Jiangsu Key Lab Mol & Funct Imaging, Nanjing, Peoples R China.
[Ding, Zhimin] Warman Med Coll, Yijishan Hosp, Dept Radiol, Wuhu, Peoples R China.
通讯机构:
[Ju, SH ] S
Southeast Univ, Zhongda Hosp, Dept Radiol,Med Sch, Jiangsu Key Lab Mol & Funct Imaging, Nanjing, Peoples R China.
语种:
英文
期刊:
Diagnostic and Interventional Radiology
年:
2022
卷:
28
期:
1
页码:
39-49
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [81830053, 92059202]; Key Project of Scientific Research Fund of Wannan Medical College [WK2019ZF05]; Scientific Research Project of the Chinese Red Cross foundation [XM_ HR_YXFN_2021_05_24]
机构署名:
本校为其他机构
摘要:
PURPOSE We aimed to assess the feasibility of radiomics analysis based on non-contrast-enhanced thoracic CT images in predicting synchronous brain metastasis (SBM) in lung cancer patients at initial diagnosis. METHODS This retrospective study enrolled 371 lung cancer patients (with SBM n=147, without SBM n=224) confirmed by histopathology. Patients were allocated to the training set (n=258) and testing set (n=113). The optimal radiomics features were selected by using the least absolute shrinkage and selection operator (LASSO) algorithm. The radiomics, clinicoradiologic, and combined models we...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com