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1.
Chinese Journal of Radiation Oncology ; (6): 536-542, 2019.
Article in Chinese | WPRIM | ID: wpr-755067

ABSTRACT

Objective To evaluate the feasibility of utilizing dose-volume histogram (DVH) prediction models of organs at risk (OARs) to deliver automatic treatment planning of prostate cancer.Methods The training set included 30 cases randomly selected from a database of 42 cases of prostate cancer receiving treatment planning.The bladder and rectum were divided into sub-volumes (Ai) of 3 mm in layer thickness according to the spatial distance from the boundary of planning target volume (PTV).A skewed normal Gaussian function was adopted to fit the differential DVH of Ai,and a precise mathematical model was built after optimization.Using the embedded C++ subroutine of Pinnacle scripa,ahe volume of each Ai of the remaining validation set for 12 patients was obtained to predict the DVH parameters of these OARa,ahich were used as the objective functions to create personalized Pinnacle script.Finalla,automatic plans were generated using the script.The dosimetric differences among the original clinical plannina,aredicted value and the automatic treatment planning were statistically compared with paired t-test.Results DVH residual analysis demonstrated that predictive volume fraction of the bladder and rectum above 6 000 cGy were lower than those of the original clinical planning.The automatic treatment planning significantly reduced the V70,V60,V50 of the bladder and the V70 and V60 of the rectum than the original clinical planning (all P<0.05),the coverage and conformal index (CI) of PTV remained unchangea,and the homogeneity index (HI) was slightly decreased with no statistical significance (P> 0.05).Conclusion The automatic treatment planning of the prostate cancer based on the DVH prediction models can reduce the irradiation dose of OARs and improve the treatment planning efficiency.

2.
Chinese Journal of Radiation Oncology ; (6): 661-666, 2017.
Article in Chinese | WPRIM | ID: wpr-618861

ABSTRACT

Objective To develop an automatic algorithm to predict the dose-volume histogram (DVH) and implement it in clinical practice.Methods Based on the prior information in the existing plan,such as dosimetric results of organs at risk (OARs) and OAR-target spatial relationship,a two-dimensional kernel density estimation was implemented to predict the DVH of OARs.The predicted DVH curves were converted into objective functions that would be implemented in the Pinnacle treatment planning system.Comparisons between predicted and actual values and between Auto-plan and manual planning were made by paired t test.Results We applied this algorithm to 10 rectal cancer patients,10 breast cancer patients,and 10 nasopharyngeal carcinoma patients.The predicted DVH of OARs showed that the deviation between the actual and predicted values at important clinical dose points were within 5%(P>0.05).The re-planning for the 10 breast cancer patients using Auto-plan showed that the heart dose was significantly reduced and the target coverage was increased,which was consistent with the predicted results.Conclusions The method proposed in this study allows for accurat DVH prediction,and,combined with Auto-plan,can be used to generate clinically accepted treatment plans.

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