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Objective:To propose an automatic planning approach for Eclipse15.6 planning system based on Eclipse scripting application programming interface (ESAPI) and evaluate its clinical application.Methods:20 patients with nasopharyngeal carcinoma and 20 cases of rectal cancer were selected in the clinical planning. The developed automatic planning script SmartPlan and RapidPlan were used for automatic planning and dosimetric parameters were compared with manual planning. The differences were compared between two groups by using Wilcoxon signed rank test. Results:The dosimetric results of automatic and manual plans could meet clinical requirements. There was no significant difference in target coverage in nasopharyngeal carcinoma planning between two groups ( P>0.05), and automatic plans were superior to manual plans in organs at risk sparing ( P<0.05). Except for the homogeneity index of PTV and the maximum dose of bowel in rectal cancer plans, the other dosimetric parameters of the automatic plans were better than those of the manual plans (all P<0.05). Conclusions:Compared with the manual plans, the automatic plans have the same or similar target coverage, similar or better protection of organs at risk, and more convenient implementation. The developed SmartPlan based on ESAPI has clinical feasibility and effectiveness.
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Objective:To develop a verification platform based on Monte Carlo (MC) for independent dose verification of volumetric modulated arc therapy (VMAT) plans.Methods:The head model including collimator of Varian TrueBeam linear accelerator was constructed by using EGSnrc/BEAMnrc, and the independent dose verification platform for the patients’ VMAT plans was built based on the head model and an in-house code. The percent depth dose (PDD) curves and off-axis ratios for different field sizes, the dose distribution of two irregular fields and three VMAT plans of the head and neck, chest, and pelvis were simulated using the platform. The simulated results of the PDD curves and the off-axis ratios of different field sizes were compared with the blue water measurement results. The difference between the irregular fields and the actual ArcCHECK measurements was also investigated. Besides, the differences among the MC simulated dose, TPS calculated dose and the ArcCHECK measured dose were analyzed by several methods, such as γ analysis and dose-volume histogram to verify whether the platform could be independently employed for dose verification.Results:The MC simulated results of PDD curves and off-axis ratios from 4 cm×4 cm to 40 cm×40 cm were in good agreement with the measured results. And the γ passing rates between the MC simulation and the ArcCHECK measurement for the irregular fields were above 98.1% and 99.1% for 3%/2 mm and 3%/3 mm, respectively. For VMAT plans of three patients, the γ results between the MC simulated dose and ArcCHECK measured dose were better than 93.8% and 95.9% under the criteria of 3%/2 mm and 3%/3 mm respectively. At the same time, the γ passing rates of nasopharyngeal, lung, and rectal cancers were 95.2%, 98.6% and 98.9% based on 3D γ analysis using TPS calculated dose and MC simulated dose under the criteria of 3%/3 mm; the passing rates of these three were 90.3%, 95.1% and 96.7% for 3%/2 mm, respectively.Conclusions:The simulation results of the MC-based verification platform developed in this study show a good agreement with the actual measurement results, and the simulation results are closer to the real dose distribution using the patients’ data. The preliminary results demonstrate that the platform can be used for accurate independent dose verification of VMAT plans.
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Objective:To propose an automatic planning method of intensity-modulated radiotherapy (IMRT) for esophageal cancer based on dose volume histogram prediction and beam angle optimization in Raystation treatment planning system.Methods:50 IMRT plans of esophageal cancer were selected as the training set to establish a dose prediction model for organs at risk. Another 20 testing plans were optimized in Raystation using RuiPlan and manual method, and the beam angle optimization and dose volume histogram prediction functions of RuiPlan were used for automatic planning. Dosimetric differences and planning efficiency between two methods were statistically compared with paired t-test. Results:There were no significant dosimetric differences in the conformity index (CI), homogeneity index (HI) of PTV, V 5Gy of both lungs and D max of the spinal cord between automatic and manual plans (all P>0.05). Compared with those in the manual plans, the V 20Gy and D mean of the left and right lungs generated from automatic plans were reduced by 1.1%, 0.37 Gy and 1.2%, 0.38 Gy (all P<0.05), and the V 30Gy, V 40Gy and D mean of the heart in automatic plans were significantly decreased by 5.1%, 3.0% and 1.41 Gy, respectively (all P<0.05). The labor time, computer working time, and monitor unit (MU) number of automatic plans were significantly decreased by 65.8%, 14.1%, and 17.2%, respectively (all P<0.05). Conclusion:RuiPlan automatic planning scripts can improve the efficiency of esophageal cancer planning by dose prediction and beam angle optimization, providing an alternative for esophageal cancer radiotherapy planning.
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Objective:To build a systemic and automatic importing scheme for importing CT images and structures into the treatment planning systems (TPSs) of Eclipse and Monaco.Methods:Based on two TPSs of Eclipse and Monaco, the files of CT images and structures were automatically transported from OAR auto-delineation system to the importing directory of these two TPSs using batch script in Windows system. Following the standard importing procedures of these two TPSs, the automatically importing script of CT images and structures were developed using the application of UiBot. Finally, the CT images and structures were imported into these two TPSs opportunely.Results:By comparing the importing time using script and manual methods, the script not only achieved auto-importing CT images and structures into TPSs, but also yielded almost the same efficiency to manual method. The number of imaging layers in most patients was between 130 and 180, and the average manual and automatic importing time within this interval was 76 s and 75 s.Conclusions:Automatic scripts can be developed by using the automation function of UiBot combined with the actual problems of radiotherapy and repeated workflow. The efficiency of radiotherapy work can be significantly improved. Manual and time costs can be saved. It provides a novel alternative for the automation of radiotherapy procedures.
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Objective:To propose an automatic planning platform of the Raystation planning system suitable for multi-disease and multi-plan technique by using the Raystation built-in script function.Methods:IronPython and WPF user interface framework were utilized for programming and resolving the differences in the design of different types of plans for different diseases. The program was designed from prescription identification, visual plan parameter input and cost-function setting. The efficiency of automatic planning and manual planning was compared when applied in whole brain irradiation, nasopharyngeal carcinoma, cervical cancer, esophageal cancer and breast cancer, including IMRT and VMAT. The dosimetric parameters of the whole brain irradiation were chosen.Results:Physicists were only required to enter and select the necessary parameters to achieve the plan design by using the program. Compared with the five types of diseases, the maximum efficiency of automatic planning was 1.4 times higher than that of manual planning. In the dosimetric evaluation of the whole brain irradiation plan, both manual and automatic planning could meet the clinical needs, and the D 2%, CI and HI of the target area did not significantly differ (all P>0.05). The mean D 98% of the target area and the D max of lens in the manual plan were significantly higher than those in the automatic plan by 0.4% and 7.1%(both P<0.05). Conclusion:The developed program has the function of automatic planning system, which can realize the automatic planning of multi-disease and multi-type radiotherapy, significantly improve the efficiency of plan design and has important clinical application value.
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Objective@#To investigate the feasibility of assessing the treatment response using diagnostic-quality CT imaging features during radiotherapy for esophageal cancer.@*Methods@#Thirty-three patients with stage Ⅰ to IV esophageal cancer undergoing intensity-modulated radiotherapy were recruited in this study. CT images were acquired using a CT-on-rail imaging system. Imaging data of CT images including gross tumor volume (GTV), the volume of spinal cord and non-irradiated tissue (NIT), CT mean (MCTN), standard deviation , and skewness were collected and analyzed by using MIM image processing system. Patients were divided into the effective group (complete remission and partial remission, n=24) and ineffective group (no change and progression, n=9) based on the outcomes of 3-month follow-up. The imaging data were statistically compared between two groups using the self-designed Matlab software.@*Results@#The tumor volume and MCTN of 33 patients were gradually decreased with the increase of radiotherapy dose. The tumor volume and MCTN were decreased by 42.46% and 5.76 HU in the effective group, more significant compared with 21.76% and 3.66 HU in the ineffective group (both P<0.005). The skewness in the ineffective group was decreased by 0.503 with the increasing radiation dose, whereas that in the effective group was increased by -0.450(P=0.034). Spinal cord and NIT did not significantly change with the increasing radiation dose.@*Conclusion@#Analysis of the characteristic data of CT images of patients with esophageal cancer during radiotherapy may early predict the clinical efficacy of radiotherapy.
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Objective To investigate the feasibility of assessing the treatment response using diagnostic-quality CT imaging features during radiotherapy for esophageal cancer.Methods Thirty-three patients with stage Ⅰ to Ⅳ esophageal cancer undergoing intensity-modulated radiotherapy were recruited in this study.CT images were acquired using a CT-on-rail imaging system.Imaging data of CT images including gross tumor volume (GTV),the volume of spinal cord and non-irradiated tissue (NIT),CT mean (MCTN),standard deviation,and skewness were collected and analyzed by using MIM image processing system.Patients were divided into the effective group (complete remission and partial remission,n=24) and ineffective group (no change and progression,n=9) based on the outcomes of 3-month follow-up.The imaging data were statistically compared between two groups using the self-designed Matlab software.Results The tumor volume and MCTN of 33 patients were gradually decreased with the increase of radiotherapy dose.The tumor volume and MCTN were decreased by 42.46％ and 5.76 HU in the effective group,more significant compared with 21.76％ and 3.66 HU in the ineffective group (both P＜0.005).The skewness in the ineffective group was decreased by 0.503 with the increasing radiation dose,whereas that in the effective group was increased by-0.450(P=0.034).Spinal cord and NIT did not significantly change with the increasing radiation dose.Conclusion Analysis of the characteristic data of CT images of patients with esophageal cancer during radiotherapy may early predict the clinical efficacy of radiotherapy.