KBRT has been proved its advantages and reliability, and has been accepted for planning in practical work. Mainly includes the establishment of DVH prediction model and model training.[5–9] The establishment of DVH prediction model is to calculate the Geometry—Based Expected Dose (GED) of each organ in the provided treatment plan. GED is to evaluate the volume of the PTV and the OARs, the distance between them and the dose distribution at this distance. The training of the model uses the principal component analysis method to carry out regression analysis on the planned GED and DVH to obtain the DVH and geometric condition related parameters of each anatomical structure. When designing a new plan, the DVH prediction model calculates the possible DVH fluctuation range of the plan result through the correlation parameters according to the mutual positional relationship between the PTV on the patient image and the normal tissue, and selects its lowest dose limit as the target optimization condition.
This paper mainly discusses whether a "plan-model-plan-model" internal feedback system with interactive improvement can be formed in the closed-loop state. The results showed that the P2 is better than P1 in MU, CI, bladder V10, left femoral head V40. Beside in other aspects, the difference is also very small. Among them, left femoral head V10, V20, V30 and right femoral head V20, V30, Dmean index change is more obvious; bladder V30, V40, rectum V40, Dmean and other indicators change little; especially bladder V40, rectum Dmean index change less than 0.5%. Because plan optimization is multi-objective optimization, there will be some improvement of indicators, some indicators have not improved or even become worse, but overall can be controlled within the required range, its changes are floating within the required range.
The larger the chi square value of the model, the smaller the probability of independence and the greater the probability of correlation. In this study, the chi square value of the organ index of M2 is greater than that of M1.It showed that the closer it is to the requirements set by us for the model, the better it can reflect the plan we use to train the model. The M2 is relatively stable, and it can better reflect the requirements of the clinical plan.
The reason for this is that KBRT is to integrate the past treatment experience into the treatment of new patients. It uses a large number of previous similar plans to train fitting models. The verified model will be used to evaluate the anatomical structure and prescription dosage of new patients, especially the distance and interlacing between PTV and OARs. According to this, the model predicts the target parameters of DVH that the case may reach. The plan used to build the model affects the use effect of the model. In addition, in the process of using the model, due to the individual differences of cases and different clinical requirements, and in order to achieve the effect of excellence, physicists sometimes have to make manual fine adjustments. In the process of establishing the experimental model, M1 is established based on P0, then P1 is generated, and then M2 is established through P1 to generate P2. From M1, P0 to M2, P2, the artificial influence factor of the automatic planning model is gradually weakened, but also a positive factor in the process of planning optimization is weakened, or the influence of this positive factor is an increasing trend for the forward model.
Varian KBRT divided the OARs into 4 parts: (1) shooting into the field and scattering; (2) The exposure dose between leaves is lower; (3) In the shooting field, the irradiated dose has obvious influence; (4) The PTV overlap, and the irradiated dose is equivalent to the PTV dose. This part has the most important influence on the PTV dose distribution. The process of establishing Rapid Plan model is to import the image, outline, dose, DVH, etc. of case intensity adjustment plan into Eclipse-Rapid Plan planning system for regression analysis of DVH curves of various OARs to create DVH prediction model. When a new plan is made by using the established model, after matching, the DVH prediction model will automatically generate the irradiation dose volume range of tissues and organs and give the optimal DVH curve satisfying the current plan, which will become the target center of the dose limit value for the next optimization. This calculation method is a two-dimensional algorithm, while the plan involves three-dimensional images, so the two-dimensional algorithm has its limitations in calculating the three-dimensional volume and dose distribution. It may be more appropriate to use a three-dimensional calculation method. The improvement of algorithm should play a more critical and core role in the improvement of Rapid Plan model.
The source plan on which M2 is built is in a non-advantageous state compared with the source plan used by M1, which we want to avoid but exist. However, even under such circumstances, the plan generated by M2 can be improved in some aspects. At the same time, the stability of M2 is better than M1.