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Agata Małgorzata Wilk¹, Andrzej Swierniak², Andrea d'Amico³

¹Department of Systems Biology and Engineering, Silesian University of Technology, Akademicka 16, Gliwice 44-100, Poland; Department of Biostatistics and Bioinformatics, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Wybrzeze AK 15, Gliwice 44-102, Poland.

Computer methods and programs in biomedicine

|June 1, 2025

概括

在放射学分析中包括所有检测到的病变,而不仅仅是主要瘤,显著改善了癌症患者的预后模型. 这种方法通过使用全面的放射性数据来提高生存模型的预测准确性.

科学领域:

放射学和医学成像学医学成像学
计算生物学计算生物学
在瘤学瘤学.

背景情况:

医学图像中的放射性特征提供了预后价值.
选择适当的兴趣区域 (ROI) 对放射学至关重要.
在传播疾病中处理多种病变对当前的放射学模型来说是一个挑战.

研究的目的:

评估将多种病变的放射性数据整合到生存模型中的可行性.
探索将多个ROI纳入预测模型的策略.
为了确定是否包括所有病变与初级瘤分析相比,改善模型性能.

主要方法:

开发方法来汇总特征向量或模拟多个病变的结果.
应用聚合策略来预测115名非小细胞肺癌患者的远程转移风险.
在蒙特卡洛交叉验证框架内利用PET和PET插入的CT数据的放射学.

主要成果:

将所有病变纳入不同生存模型和特征集的c指数得到了持续的改善.
使用所有病变的模型与仅使用原发性瘤的模型 (0.611-0.614) 相比,获得了更高的c指数 (0.632-0.634).
包括所有病变的好处被观察到,无论使用的生存模型如何.

结论:

主要瘤以外的病变的放射性特征包含有价值的预后信息.
在放射学模型中利用所有检测到的病变可以提高预测能力.
拟议的聚合策略对于整合多损伤放射性数据是有效的.

关键词:

有多个ROI.聚乙烯/聚乙烯/聚乙烯投资回报率聚合投资回报率聚合无线电学 (Radiomics) 是一种辐射学.风险聚合风险聚合生存模型的生存模型.

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