ABSTRACT
Objective:Utilizing multi-criterion optimization (MCO) technology to improve plan design quality based on knowledge-based planning (KBP) model.Methods:Fifty-five patients with nasopharyngeal carcinoma (NPC) who had completed radiotherapy were selected, and fixed-field intensity-modulated radiotherapy (IMRT) technology was used in each case. Among them, 40 cases were randomly selected as training set 1. Then, IMRT plans in training set 1 were preprocessed by MCO technology to construct a new training set 2. With the initial training set 1 and the processed training set 2 as training samples, the traditional KBP model and the MCO-KBP model refined by MCO technology were trained, respectively. Among the remaining 15 cases, 5 cases were randomly selected as the validation set, and the remaining 10 cases were used as the test set. After verification, the test set was used to statistically analyze the plan quality of the initial manual plan and the automatic plan generated by the traditional KBP model and the MCO-KBP model.Results:The target dose (D 95%) of plans generated by the traditional KBP model and the MCO-KBP model met the clinical requirements. Conformity index (CI) and homogeneity index (HI) were almost the same ( P>0.05), and the doses of organ at risk (OAR) of the automatic plans generated by the MCO-KBP model were lower than those of the traditional KBP model. For example, compared with the traditional KBP model, the average D max of the brainstem in the automatic plans generated by the MCO-KBP model was lower by 2.13 Gy, the average D mean of the left parotid gland was lower by 1.39 Gy, the average D mean of the right parotid gland was lower by 1.59 Gy, and the average D max of the left optic nerve was lower by 1.42 Gy, the average D max of the right optic nerve was lower by 1.16 Gy, and the average D max of the pituitary gland was lower by 1.88 Gy. All of the above-mentioned dosimetry indexes were statistically significant. Conclusion:Compared with the traditional KBP model, the IMRT plans designed by the refined MCO-KBP model have obvious advantages in the protection of OAR, which proves the feasibility of utilizing MCO technology to improve the plan design quality of the KBP model.
ABSTRACT
Objective:To develope a self-adjustable automatic planning method of intensity modulated radiotherapy based on predicted dose, in order to enhance the robustness of automatic planning.Methods:After the patients′ dose by 3D U-Res-Net_B network was predicted, the current dose was calculated based on the last iteration result, then the predicted dose was combined to calculate the target dose and optimized. With all iterations completed or exit conditions satisfied, final treatment plannings would be acquired. A total of 30 cases of rectal cancer were tested to verify the effectiveness of the algorithm.Results:The mean value of planning target volumes′ V100% was (95.03±0.91)% for clinical plans, close to (94.67±1.96)% for automatical plans( P>0.05), and better than (92.90±2.13)% for predicted dose with the statisically significant difference ( t=29.0, P<0.05). Automatic planning′s indexes such as V35 of small intestines, V40 of bladders and V20 - V40 of femoral heads were lower than predicted and clinical ones, with the statisically significant difference( t=4.5-118.0, P<0.05). Discrepancy in other indexes of organs at risk was not statistically significantly different( P>0.05). Conclusions:This method made automatic planning processes more robust and more adaptive to difficult clinical situations.