Positron Emission Tomography-Based Short-Term Efficacy Evaluation and Prediction in Patients With Non-Small Cell Lung Cancer Treated With Hypo-Fractionated Radiotherapy - Jiang, Yi-Qing; Gao, Qin; Chen, Han; Shi, Xiang-Xiang; Wu, Jing-Bo; Chen, Yue; Zhang, Yan; Pang, Hao-Wen; Lin, Sheng (Frontiers in Oncology, 2021)
Background: Positron emission tomography is known to provide more accurate estimates than computed tomography when staging non-small cell lung cancer. The aims of this prospective study were to contrast the short-term efficacy of the two imaging methods while evaluating the effects of hypo-fractionated radiotherapy in nonsmall cell lung cancer, and to establish a short-term efficacy prediction model based on the radiomics features of positron emission tomography. Methods: This nonrandomized-controlled trial was conducted from March 2015 to June 2019. Thirty-one lesions of 30 patients underwent the delineation of the regions of interest on positron emission tomography and computed tomography 1 month before, and 3 months after hypo-fractionated radiotherapy. Each patient was evaluated for the differences in local objective response rate between the two images. The Kaplan Meier method was used to analyze the local objective response and subsequent survival duration of the two imaging methods. The 3D Slicer was used to extract the radiomics features based on positron emission tomography. Least absolute shrinkage and selection operator regression was used to eliminate redundant features, and logistic regression analysis was used to develop the curative-effect-predicting model, which was displayed through a radiomics nomogram. Receiver operating characteristic curve and decision curve were used to evaluate the accuracy and clinical usefulness of the prediction model. Results: Positron emission tomography-based local objective response rate was significantly higher than that based on computed tomography [70.97% (22 / 31) and 12.90% (4 / 31), respectively (p<0.001)]. The mean survival time of responders and non-responders assessed by positron emission tomography was 28.6 months vs. 11.4 months (p=0.29), whereas that assessed by computed tomography was 24.5 months vs. 26 months (p=0.66), respectively. Three radiomics features were screened to establish a personalized prediction nomogram with high area under curve (0.94, 95% CI 0.85-0.99, p<0.001). The decision curve showed a high clinical value of the radiomics nomogram. Conclusions: We recommend positron emission tomography for evaluating the shortterm efficacy of hypo-fractionated radiotherapy in non-small cell lung cancer, and that the radiomics nomogram could be an important technique for the prediction of shortterm efficacy, which might enable an improved and precise treatment.