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用于预测早期声门癌患者无进展生存期的双能计算机断层扫描的影像组学

Radiomics of dual-energy computed tomography for predicting progression-free survival in patients with early glottic cancer.

作者信息

Li Wenfei, Zhang Huanlei, Ren Lei, Zou Ying, Tian Fengyue, Ji Xiaodong, Li Qing, Wang Wei, Ma Guolin, Xia Shuang

机构信息

Department of Radiology, The First Central Clinical School, Tianjin Medical University, No. 24 Fukang Road, Nankai District, Tianjin, 300192, China.

Department of Radiology, The First Hospital of Qinhuangdao, No. 258 Wenhua Road, Haigang District, Qinhuangdao, 066000, China.

出版信息

Future Oncol. 2022 May;18(15):1873-1884. doi: 10.2217/fon-2021-1125. Epub 2022 Mar 16.

Abstract

This study aimed to predict progression-free survival (PFS) in patients with early glottic cancer using radiomic features on dual-energy computed tomography iodine maps. Radiomic features were extracted from arterial and venous phase iodine maps, and radiomic risk scores were determined by univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator regression with tenfold cross-validation. The Kaplan-Meier method was used to evaluate the association between radiomic risk scores and PFS. Patients were stratified into low-risk and high-risk groups using radiomics, the PFS corresponding rates with statistical significance between the two groups. The high-risk group showed better survival, benefiting from laryngectomy. Radiomics could provide a promising biomarker for predicting the PFS of early glottic cancer patients.

摘要

本研究旨在利用双能计算机断层扫描碘图上的放射组学特征预测早期声门癌患者的无进展生存期(PFS)。从动脉期和静脉期碘图中提取放射组学特征,并通过单变量Cox比例风险回归分析以及采用十折交叉验证的最小绝对收缩和选择算子回归确定放射组学风险评分。采用Kaplan-Meier方法评估放射组学风险评分与PFS之间的关联。使用放射组学将患者分为低风险组和高风险组,两组之间PFS对应率具有统计学意义。高风险组显示出更好的生存率,得益于喉切除术。放射组学可为预测早期声门癌患者的PFS提供一种有前景的生物标志物。

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