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通过基于CT的放射学模型预测口腔状细胞癌中对免疫治疗的反应

Qifan Ma¹, Jiliang Ren¹, Rui Wang¹

¹Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No.639 Zhizaoju Road, Shanghai, 200010, China.

BMC medical imaging

|October 7, 2024

概括

治疗前CT扫描的放射学模型在预测口腔状细胞癌 (OSCC) 免疫治疗反应方面表现有希望. 这种方法可能有助于确定可能从治疗中受益的患者.

科学领域:

放射学放射学是一门学科.
在瘤学瘤学.
人工智能的人工智能

背景情况:

口腔状细胞癌 (OSCC) 治疗对免疫疗法的反应可能有所不同.
预测治疗疗效对于个性化患者管理至关重要.

研究的目的:

评估预治疗CT扫描中的放射学模型,以预测OSCC中的免疫治疗反应.
评估放射学在指导患者选择免疫治疗方面的潜力.

主要方法:

对40名OSCC患者的回顾性分析.
从预处理CT图像中提取和选择放射性特征,使用单变量分析和LASSO回归.
机器学习模型 (神经网络,SVM,随机森林,物流回归) 的开发和验证,并进行一次性交叉验证.

主要成果:

七个放射学特征被选中用于模型开发.
神经网络模型展示了最高的预测性能.
神经网络模型实现了0.864的AUC,准确度,灵敏度和特异性为82.5%.

结论:

基于CT的预治疗放射学模型显示,在OSCC中预测免疫治疗反应具有显著的潜力.
放射学可能是一个有价值的,非侵入性工具,用于选择谁将从免疫治疗中受益的患者.

关键词:

免疫治疗是一种免疫疗法.机器学习是机器学习.口腔状细胞癌的癌症.无线电学 (Radiomics) 是一种无线电学.响应预测响应预测

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