Application of 3D ResSE-Unet-based intelligent delineation of clinical target volume in postoperative radiotherapy for breast cancer / 中华放射医学与防护杂志

ABSTRACT

Objective:To evaluate the effectiveness and feasibility of 3D ResSE-Unet-based intelligent delineation of clinical target volume (CTV) in postoperative adjuvant radiotherapy for breast cancer.Methods:A total of 974 cases of breast cancer treated in the Cancer Diagnosis and Treatment Center of the Fourth Affiliated Hospital of Guangxi Medical University from September 2018 to June 2022 were enrolled in this study, including 614 cases receiving total mastectomy and 360 cases treated with breast-conserving surgery. They were divided into a training set, a validation set, and a testing set. The training set consisted of 874 cases and was used to build a model of 3D ResSE-Unet-based intelligent CTV delineation. The validation set comprised 40 cases and was used to evaluate the feasibility and effectiveness of the clinical application of AI-based CTV design in the radiotherapy for breast cancer. The testing set was composed of 60 cases and was used to test the accuracy of intelligent CTV. The Wilcoxon rank test was used to compare the Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and average surface distance (ASD) obtained using the intelligent delineation model.Results:The intelligent delineation model showed high precision. The CTV of cases treated with total mastectomy (CTV cw) and the CTV of cases treated with breast-conserving surgery (CTV b) had DSCs greater than 0.80 and greater than 0.88, respectively. Therefore, compared with CTV cw, CTV b had a higher DSC (0.91 ± 0.03 vs.0.83 ± 0.05, t = 7.11, P < 0.05). Both CTV cw and CTV b had lower HD 95 [(7.56 ± 3.42) mm vs.(8.77 ± 5.89) mm] and ASD [(1.85 ± 0.71) mm vs.(1.86 ± 0.83)mm], without statistically significant difference ( P > 0.05). The left/right supraclavicular and infraclavicular CTV (CTV2) had DSCs greater than 0.8. CTV2 also had low average HD95 and ASD, without statistically significant difference ( P > 0.05). Conclusions:The 3D ResSE-Unet-based intelligent CTV delineation has better consistency and feasibility in postoperative adjuvant radiotherapy for breast cancer, especially the CTVs after breast-conserving surgery.