Sawayanagi Subaru, Yamashita Hideomi, Nozawa Yuki, Takenaka Ryosuke, Miki Yosuke, Morishima Kosuke, Ueno Hiroyuki, Ohta Takeshi, Katano Atsuto
Department of Radiology, University of Tokyo Hospital, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
Cancers (Basel). 2022 Aug 10;14(16):3859. doi: 10.3390/cancers14163859.
Stereotactic body radiation therapy (SBRT) for early-stage non-small cell lung cancer (NSCLC) leads to recurrence in approximately 18% of patients. We aimed to extract the radiomic features, with which we predicted clinical outcomes and to establish predictive models. Patients with primary non-metastatic NSCLC who were treated with SBRT between 2002 and 2022 were retrospectively reviewed. The 358 primary tumors were randomly divided into a training cohort of 250 tumors and a validation cohort of 108 tumors. Clinical features and 744 radiomic features derived from primary tumor delineation on pre-treatment computed tomography were examined as prognostic factors of survival outcomes by univariate and multivariate analyses in the training cohort. Predictive models of survival outcomes were established from the results of the multivariate analysis in the training cohort. The selected radiomic features and prediction models were tested in a validation cohort. We found that one radiomic feature showed a significant difference in overall survival (OS) in the validation cohort ( = 0.044) and one predicting model could estimate OS time (mean: 37.8 months) similar to the real OS time (33.7 months). In this study, we identified one radiomic factor and one prediction model that can be widely used.
立体定向体部放射治疗(SBRT)用于早期非小细胞肺癌(NSCLC)时,约18%的患者会出现复发。我们旨在提取放射组学特征,据此预测临床结局并建立预测模型。对2002年至2022年间接受SBRT治疗的原发性非转移性NSCLC患者进行回顾性研究。将358个原发性肿瘤随机分为一个包含250个肿瘤的训练队列和一个包含108个肿瘤的验证队列。在训练队列中,通过单因素和多因素分析,将临床特征以及从治疗前计算机断层扫描上的原发性肿瘤轮廓提取的744个放射组学特征作为生存结局的预后因素进行研究。根据训练队列中的多因素分析结果建立生存结局的预测模型。在验证队列中对所选的放射组学特征和预测模型进行测试。我们发现,在验证队列中,一个放射组学特征在总生存期(OS)方面存在显著差异(P = 0.044),并且一个预测模型能够估算出与实际OS时间(33.7个月)相近的OS时间(平均:37.8个月)。在本研究中,我们识别出了一个可广泛应用的放射组学因素和一个预测模型。