预测降型鼻咽癌远处转移的放射组学谱图的建立与验证

Qin Yang, Yu Chen, Rui Huang, Wenya Yin, Shuang Zhang, Qianlong Tang, Xinyue Chen, Jinyi Lang, Gang Yin, Peng Zhang
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引用次数: 0

摘要

鼻咽癌远端转移是鼻咽癌治疗失败的主要原因之一,降型鼻咽癌(D型鼻咽癌)更容易发生远端转移。很少有人探讨淋巴结放射组学特征与D型鼻咽癌远处转移的关系。因此,我们建立了一个基于放射组学危险因素的nomogram来预测D型NPC患者的远处转移。本研究回顾性纳入144例D型NPC (T1-2N2-3MO, AJCC第8期)。分别从治疗前的CT和MRI检查中提取2600个特征。通过最小绝对收缩和选择算子回归进行特征选择。采用二元logistic回归模型构建模态图,并利用c指数和标定曲线对模态图的辨别力和准确度进行评价。将CT和MRI放射组学特征与多模态放射组学模型相结合,合成少数过采样技术(SMOTE)数据集的平均曲线下面积为0.873(95%可信区间[CI]: 0.797-0.949)。原始数据集的训练集和验证集的c指数分别为0.91 (95% CI: 0.848 ~ 0.972)和0.815 (95% CI: 0.664 ~ 0.967);灵敏度分别为0.75、0.545,特异度分别为0.932、0.903,准确度分别为0.882、0.81。因此,我们认为多模态放射组学模型在预测下行型鼻咽癌患者的远处转移方面是很好的。该模型可为精准治疗和预测预后提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Establishment and verification of a radiomics nomogram to predict distant metastasis in patients with descending type of nasopharyngeal carcinoma

Establishment and verification of a radiomics nomogram to predict distant metastasis in patients with descending type of nasopharyngeal carcinoma

Distant metastasis is one of the main reasons for the failure of nasopharyngeal carcinoma (NPC) treatment, and descending type of nasopharyngeal carcinoma (type D NPC) is more prone to distant metastasis. Few people have explored the relationship between the radiomics characteristics of lymph nodes and the distant metastasis of type D NPC. Therefore, we establish a nomogram based on radiomics risk factors to predict distant metastasis in patients with type D NPC. This study retrospectively included 144 type D NPC (T1-2N2-3MO, AJCC 8th). 2600 features were extracted each from CT and MRI examinations conducted before treatment, respectively. Feature selection was performed by least absolute shrinkage and selection operator regression. A binary logistic regression model was used to construct a nomogram, and the C-index and calibration curve were used to evaluate the discrimination and accuracy of the nomogram. Combining CT and MRI radiomics features with a multimodal radiomics model, the average area under curve of the synthetic minority oversampling technique (SMOTE) data set was 0.873 (95% confidence interval [CI]: 0.797–0.949). The C-index in the training and validation sets of the original data set were 0.91 (95% CI: 0.848–0.972) and 0.815 (95% CI: 0.664–0.967); the sensitivity were 0.75 and 0.545, the specificity were 0.932 and 0.903, and the accuracy were 0.882 and 0.81. Therefore, we concluded that the multimodal radiomics model in predicting distant metastasis in descending type of NPC patients was good. The proposed model can provide a reference for precise treatment and prognosis prediction.

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