The feasibility study of generalization of knowledge-based planning for cervical cancer / 中华放射医学与防护杂志

ABSTRACT

Objective:To design a knowledge-based cervical cancer planning model and apply it to cases of endometrial cancer and rectal cancer in order to explore the generalization of the model.Methods:A total of 179 cases of pelvic regions with different prescribed doses of dual-arc volumetric modulated arc therapy clinical plans were collected, of which 99 cases of cervical cancer clinical plans with a prescribed dose of 50.4 Gy were used as the training set to establish the RapidPlan model, and the remaining clinical plans were divided into 4 validation groups with 20 cases in each group. The clinical plans for cervical cancer and endometrial cancer with a prescription dose of 50.4 Gy were named groups A and B, while the clinical plan for endometrial cancer and rectal cancer with a prescription dose of 45 Gy were named groups C and D. The model was used to redesign the clinical plans in the 4 groups and the automatic plans were obtained. The planning target volume (PTV) and organ at risk (OAR) dosimetry parameters were compared between automatic plans and clinical plans.Results:The conformity index (CI) of the automatic plans in the A, B, C, and D groups were equivalent to that of the clinical plans ( P>0.05). The homogeneity index (HI) and D2% of the automatic plans in groups A, B, and C were all lower than those in clinical plans(HI, Z=-3.248, -3.360, -2.329, P<0.05; D2%, Z=-2.987, -3.397, -2.442, P<0.05). The HI and D2% of the automatic plans in group D were similar those in the clinical plans ( P>0.05). While ensuring the PTV coverage, the average value of OAR dosimetry parameters in all automatic plans groups were lower than that of the clinical plans. Conclusions:The RapidPlan model established by the cervical cancer clinical plans can complete the automatic plan design for endometrial cancer and rectal cancer under different prescription doses, which preliminarily proves the possibility of the generalization of the RapidPlan model.