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磁共振成像放射组学预测局部晚期下咽癌同步放化疗患者的生存情况

MRI Radiomics for Predicting Survival in Patients with Locally Advanced Hypopharyngeal Cancer Treated with Concurrent Chemoradiotherapy.

作者信息

Siow Tiing Yee, Yeh Chih-Hua, Lin Gigin, Lin Chien-Yu, Wang Hung-Ming, Liao Chun-Ta, Toh Cheng-Hong, Chan Sheng-Chieh, Lin Ching-Po, Ng Shu-Hang

机构信息

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Chang Gung University College of Medicine, Taoyuan 333423, Taiwan.

Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan.

出版信息

Cancers (Basel). 2022 Dec 12;14(24):6119. doi: 10.3390/cancers14246119.

Abstract

A reliable prognostic stratification of patients with locally advanced hypopharyngeal cancer who had been treated with concurrent chemoradiotherapy (CCRT) is crucial for informing tailored management strategies. The purpose of this retrospective study was to develop robust and objective magnetic resonance imaging (MRI) radiomics-based models for predicting overall survival (OS) and progression-free survival (PFS) in this patient population. The study participants included 198 patients (median age: 52.25 years (interquartile range = 46.88-59.53 years); 95.96% men) who were randomly divided into a training cohort ( = 132) and a testing cohort ( = 66). Radiomic parameters were extracted from post-contrast T1-weighted MR images. Radiomic features for model construction were selected from the training cohort using least absolute shrinkage and selection operator-Cox regression models. Prognostic performances were assessed by calculating the integrated area under the receiver operating characteristic curve (iAUC). The ability of radiomic models to predict OS (iAUC = 0.580, 95% confidence interval (CI): 0.558-0.591) and PFS (iAUC = 0.625, 95% CI = 0.600-0.633) was validated in the testing cohort. The combination of radiomic signatures with traditional clinical parameters outperformed clinical variables alone in the prediction of survival outcomes (observed iAUC increments = 0.279 [95% CI = 0.225-0.334] and 0.293 [95% CI = 0.232-0.351] for OS and PFS, respectively). In summary, MRI radiomics has value for predicting survival outcomes in patients with hypopharyngeal cancer treated with CCRT, especially when combined with clinical prognostic variables.

摘要

对于接受同步放化疗(CCRT)的局部晚期下咽癌患者,进行可靠的预后分层对于制定个性化管理策略至关重要。这项回顾性研究的目的是开发基于磁共振成像(MRI)影像组学的强大且客观的模型,以预测该患者群体的总生存期(OS)和无进展生存期(PFS)。研究参与者包括198例患者(中位年龄:52.25岁(四分位间距 = 46.88 - 59.53岁);95.96%为男性),他们被随机分为训练队列( = 132)和测试队列( = 66)。从增强T1加权MR图像中提取影像组学参数。使用最小绝对收缩和选择算子 - Cox回归模型从训练队列中选择用于模型构建的影像组学特征。通过计算受试者操作特征曲线下的综合面积(iAUC)评估预后性能。影像组学模型预测OS(iAUC = 0.580,95%置信区间(CI):0.558 - 0.591)和PFS(iAUC = 0.625,95% CI = 0.600 - 0.633)的能力在测试队列中得到验证。在生存结局预测方面,影像组学特征与传统临床参数的组合优于单独的临床变量(OS和PFS的观察到的iAUC增量分别为0.279 [95% CI = 0.225 - 0.334]和0.293 [95% CI = 0.232 - 0.351])。总之,MRI影像组学对于预测接受CCRT治疗的下咽癌患者的生存结局具有价值,特别是与临床预后变量相结合时。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b88/9775984/a945dc9d3833/cancers-14-06119-g001.jpg

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