Evaluation of Automatic Segmentation Model With Dosimetric Metrics for Radiotherapy of Esophageal Cancer - Zhu, Ji; Chen, Xinyuan; Yang, Bining; Bi, Nan; Zhang, Tao; Men, Kuo; Dai, Jianrong (Frontiers in Oncology, 2020)
Background: Automatic segmentation model is proven to be efficient in delineation of organs at risk (OARs) in radiotherapy; its performance is usually evaluated with geometric differences between automatic and manual delineations. However, dosimetric differences attract more interests than geometric differences in clinics. Therefore, this study evaluates the performance of automatic segmentation with dosimetric metrics for volumetric modulated arc therapy of esophageal cancer patients. Methods: Nineteen esophageal cancer cases were assessed in this study. Physicians manually delineated the target volumes and the OARs for each case. Another set of OARs was automatically generated using convolutional neural network models. The radiotherapy plans were optimized with the manually delineated targets and the automatically delineated OARs. Segmentation accuracy was evaluated by Dice similarity coefficient (DSC) and mean distance to agreement (MDA). Dosimetric metrics of manually and automatically delineated OARs were obtained and compared. The clinically acceptable dose difference and volume difference of OARs between manual and automatic delineations are supposed to be within 1 Gy and 1%, respectively. Results: Average DSC values were above 0.92 except for the spinal cord (0.82), and average MDA values were below 0.90 mm except for the heart (1.74 mm). 11 of the 20 dosimetric metrics of the OARs were not significant (p > 0.05). Although there were significant differences (p < 0.05) for the spinal cord (D2%), left lung (V10, V20, V30 and mean dose), and bilateral lung (V10, V20, V30 and mean dose), their absolute differences were small and acceptable for the clinic. The maximum dosimetric metrics differences of OARs between manual and automatic delineations were ∆D2% = 0.35 Gy for the spinal cord and ∆V30 = 0.4% for the bilateral lung, which were within the clinical criteria in this study. Conclusion: Dosimetric metrics were proposed to evaluate the automatic delineation in radiotherapy planning of esophageal cancer. Consequently, the automatic delineation could substitute the manual delineation for esophageal cancer radiotherapy planning based on the dosimetric evaluation in this study.