Department of Biotherapy, Cancer Center, West China Hospital of Sichuan University, Chengdu 610041, China.
Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China.
Aging (Albany NY). 2020 Jul 16;12(14):14593-14619. doi: 10.18632/aging.103508.
18-fluorodeoxyglucose positron emission tomography/computed tomography (F-PET/CT) has been widely applied for the imaging of head and neck squamous cell carcinoma (HNSCC). This study examined whether pre- and post-treatment F-PET/CT features can help predict the survival of HNSCC patients.
Three radiomics features were identified as prognostic factors. Radiomics score calculated from these features significantly predicted overall survival (OS) and disease-free disease (DFS). The clinicopathological characteristics combined with pre- or post-treatment nomograms showed better ROC curves and decision curves than the nomogram based only on clinicopathological characteristics.
Combining clinicopathological characteristics with radiomics features of pre-treatment PET/CT or post-treatment PET/CT assessment of primary tumor sites as positive or negative may substantially improve prediction of OS and DFS of HNSCC patients.
171 patients who received pre-treatment F-PET/CT scans and 154 patients who received post-treatment F-PET/CT scans with HNSCC in the Cancer Imaging Achieve (TCIA) were included. Nomograms that combined clinicopathological features with either pre-treatment PET/CT radiomics features or post-treatment assessment of primary tumor sites were constructed using data from 154 HNSCC patients. Receiver operating characteristic (ROC) curves and decision curves were used to compare the predictions of these models with those of a model incorporating only clinicopathological features.
18-氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描(F-PET/CT)已广泛应用于头颈部鳞状细胞癌(HNSCC)的成像。本研究旨在探讨治疗前后 F-PET/CT 特征是否有助于预测 HNSCC 患者的生存情况。
鉴定出 3 个放射组学特征为预后因素。基于这些特征计算的放射组学评分显著预测了总生存期(OS)和无病生存期(DFS)。将临床病理特征与治疗前后的列线图相结合,与仅基于临床病理特征的列线图相比,ROC 曲线和决策曲线显示出更好的性能。
将治疗前 PET/CT 或治疗后肿瘤原发部位的临床病理特征与放射组学特征相结合,评估为阳性或阴性,可能显著提高对 HNSCC 患者 OS 和 DFS 的预测能力。
本研究纳入了癌症影像学档案(TCIA)中 171 例接受治疗前 F-PET/CT 扫描和 154 例接受治疗后 F-PET/CT 扫描的 HNSCC 患者。利用 154 例 HNSCC 患者的数据,构建了将临床病理特征与治疗前 PET/CT 放射组学特征或治疗后肿瘤原发部位评估相结合的列线图。使用 ROC 曲线和决策曲线比较了这些模型与仅包含临床病理特征的模型的预测能力。