临床变量和基于磁共振成像的放射组学预测口咽癌的人乳头瘤病毒状态。
Clinical variables and magnetic resonance imaging-based radiomics predict human papillomavirus status of oropharyngeal cancer.
机构信息
Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Department of Head and Neck Oncology and Surgery, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
出版信息
Head Neck. 2021 Feb;43(2):485-495. doi: 10.1002/hed.26505. Epub 2020 Oct 7.
BACKGROUND
Human papillomavirus (HPV)-positive oropharyngeal squamous cell carcinoma (OPSCC) have better prognosis and treatment response compared to HPV-negative OPSCC. This study aims to noninvasively predict HPV status of OPSCC using clinical and/or radiological variables.
METHODS
Seventy-seven magnetic resonance radiomic features were extracted from T1-weighted postcontrast images of the primary tumor of 153 patients. Logistic regression models were created to predict HPV status, determined with immunohistochemistry, based on clinical variables, radiomic features, and its combination. Model performance was evaluated using area under the curve (AUC).
RESULTS
Model performance showed AUCs of 0.794, 0.764, and 0.871 for the clinical, radiomic, and combined models, respectively. Smoking, higher T-classification (T3 and T4), larger, less round, and heterogeneous tumors were associated with HPV-negative tumors.
CONCLUSION
Models based on clinical variables and/or radiomic tumor features can predict HPV status in OPSCC patients with good performance and can be considered when HPV testing is not available.
背景
与 HPV 阴性口咽鳞癌 (OPSCC) 相比，人乳头瘤病毒 (HPV) 阳性 OPSCC 的预后和治疗反应更好。本研究旨在使用临床和/或影像学变量无创预测 OPSCC 的 HPV 状态。
方法
从 153 名患者的原发肿瘤 T1 加权对比增强图像中提取了 77 个磁共振放射组学特征。根据免疫组织化学确定的 HPV 状态，使用逻辑回归模型创建了基于临床变量、放射组学特征及其组合预测 HPV 状态的模型。使用曲线下面积 (AUC) 评估模型性能。
结果
临床、放射组学和联合模型的 AUC 分别为 0.794、0.764 和 0.871。吸烟、较高的 T 分期（T3 和 T4）、更大、形状不规则和不均匀的肿瘤与 HPV 阴性肿瘤相关。
结论
基于临床变量和/或肿瘤放射组学特征的模型可以很好地预测 OPSCC 患者的 HPV 状态，在 HPV 检测不可用时可以考虑使用。
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