Radiomics (Oncoradiomics SA), Liège, Belgium.
The D-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.
Sci Rep. 2023 May 3;13(1):7198. doi: 10.1038/s41598-023-34162-3.
The paper deals with the evaluation of the performance of an existing and previously validated CT based radiomic signature, developed in oropharyngeal cancer to predict human papillomavirus (HPV) status, in the context of anal cancer. For the validation in anal cancer, a dataset of 59 patients coming from two different centers was collected. The primary endpoint was HPV status according to p16 immunohistochemistry. Predefined statistical tests were performed to evaluate the performance of the model. The AUC obtained here in anal cancer is 0.68 [95% CI (0.32-1.00)] with F1 score of 0.78. This signature is TRIPOD level 4 (57%) with an RQS of 61%. This study provides proof of concept that this radiomic signature has the potential to identify a clinically relevant molecular phenotype (i.e., the HPV-ness) across multiple cancers and demonstrates potential for this radiomic signature as a CT imaging biomarker of p16 status.
本文探讨了一种已有的、经过验证的 CT 放射组学特征在预测人类乳头瘤病毒（HPV）状态方面的性能评估，该特征最初是在口咽癌中开发的，现应用于肛门癌。为了在肛门癌中进行验证，我们收集了来自两个不同中心的 59 名患者的数据。主要终点是根据 p16 免疫组化确定的 HPV 状态。我们进行了预定的统计检验来评估该模型的性能。在肛门癌中，AUC 为 0.68（95%CI：0.32-1.00），F1 评分为 0.78。该特征的 TRIPOD 分级为 4 级（57%），RQS 为 61%。这项研究提供了一个概念验证，即该放射组学特征有可能在多种癌症中识别出具有临床意义的分子表型（即 HPV 状态），并证明了该放射组学特征作为 p16 状态 CT 成像生物标志物的潜力。
