This study investigates the use of scripting via RayStation™ TPS in the EBRT for EC. Our aim was to reduce the dose to the OARs using structures automatically created by the scripting tool. This method was used to derive seven additional contours (rectum-PTV, bladder-PTV, bowel-PTV, left femoral head-PTV, right femoral head-PTV, sacral plexus-PTV, and body-PTV) as well as those used in manual planning. Since manually creating a VMAT plan is already a very time-consuming process, delineating these seven structures manually in daily practice will make the process even longer. Our results showed that scripting allows saving approximately six minutes per one plan which yields a clear advantage over manual planning. Although the time-reducing advantage of the scripting during treatment planning has been reported for other types of cancer, this study is the first one in the literature comparing the results for EC patients (12–14).
All manually and automatically generated treatment plans met the acceptance criteria set out in Table 1. However, the protection of the OARs was increased by using scripted planning while target doses remained stable. All DVH parameters for the rectum were significantly reduced. The scripting technique also resulted in lower doses to the urinary bladder compared to the manual plans for almost all dosimetric endpoints analyzed. The mean doses and D50% values were also significantly lower for the small bowel. Our results indicate that this technique can allow dose sparing of the rectum, small bowel and bladder and reduce the risk and severity of toxicity. Previously, Yang et al. (15) reported that the IronPython language designed by RayStation™ TPS has a clinical application value in the design of automatic RT plans for nasopharyngeal carcinoma. Their results showed that the D1% received by the brain stem, spinal cord, optic nerves, chiasm, lenses and temporal lobes with scripted planning was significantly lower than those with manual planning and the dose was reduced by 1.8%, 2.7%, 4.9%, 1%, and 1.6% for the respective OARs. The authors concluded that the dose distribution for the target and OARs with the scripted plans was similar to or better than those with the manual planning. Han et al. (16) reported that automatic planning using Python scripting helps to reduce the dose to the normal brain and improve planning efficiency for hypofractionated multimetastatic brain stereotactic radiosurgery. On the other hand, there are studies that reported no significant difference between the scripted and manual plans for the OAR doses in breast, head and neck, and lung irradiation (17–19).
Total MU values were significantly increased with the scripted plan in our study. In general, the number of MU increases as the number of the subfields increases. Therefore, the increase in the total value of MU is thought to be due to the higher number of the subfields with the scripted plans than with the manual plans. Previously, Han et al. (16) showed that the total MU per fraction was significantly reduced by 20% with the RayStation™ scripted plans when compared with Pinnacle™ (Philips Radiation Oncology Systems, USA) scripting tool. This result shows that Raystation's scripting tool is advantageous in terms of MU values although there is an increase in MU values compared to manual planning. Considering plans created with high MU values will exhaust the treatment machines more than those created with low MU values, this situation appears to be a disadvantage for the scripted planning. In addition, increasing MU values causes an increase in beam on time which will affect the operating time of the device. In this study, we did not measure how much the increase in MU values increased the irradiation time. However, considering the mean difference was 223 MU, we can assume the beam-on time will increase by approximately 20 sec per treatment when the dose rate is 600 MU/min.
Since the PTV and OAR volumes overlap, dose constraints for the PTV would increase the dose of the intersected volume during optimization while OAR dose limitations would reduce the dose to this volume. We have eliminated these optimization problems by creating additional structures. The creation of seven structures played an important role in the optimization process. Defining dose limitations to these structures helped to reduce the dose to the OARs, as shown in Fig. 2. Previously, Xhaferllari et al. (20) performed a similar study for IMRT planning of head and neck, prostate and anal cancers. The authors generated various derived contours such as PTV, planning organ-at-risk volumes (PRVs) for required OARs, and various dose-limiting ring structures for IMRT optimization purposes, and concluded that scripting improves IMRT planning quality and efficiency.
The scripted plans showed sharper dose fall-off for the body in our study. The 50% volume of the prescribed dose was used to compare the dose fall-off for the body. This finding confirms the usefulness of body-PTV as a dose-limiting structure for the areas outside the PTV. It was reported that a decreased dose to the distant sites could reduce the risk of second cancers (21).
The treatment planning process is time-consuming and the plan quality is dependent on the experience of the planner. Automating this process is one of the recommended ways to solve these problems (22). Recently, artificial intelligence (AI) has been suggested to automate the treatment planning process (23). Machine learning, a sub-branch of AI has been integrated into the TPSs (24). Another promising AI technique is deep learning which yields rapid dose prediction during the planning process (25–27). However, creating a deliverable plan is still very difficult with these methods and it is still not used widespread in planning systems. Another issue is that studies with AI are mostly conducted on prostate and head and neck cancer patients (26). Little is known about the performance of these models for other cancers. Although AI is more promising in the future for automatic planning, scripting is already more common in TPSs. Therefore, it is easier for planners to access and routinely use the scripts in the clinic. To the best of our knowledge, our study is the first to demonstrate that automatic planning with scripting is advantageous over manual planning in the treatment of patients with EC
The necessity of similarity of patient characteristics is the main limitation of automatic planning with scripting. In this study, the script was designed to create two arcs for VMAT plans. The arc angles are standard and the gantry returns from 181º to 179º in clockwise and counterclockwise directions. In patients unsuitable for treatment at these gantry angles, e.g. with a hip prosthesis, scripted planning cannot be used. As it is recommended avoiding beam entrance from hip prostheses, gantry angles need to be rearranged in this case.
The results of our study show that the treatment plans of EC patients can be made automatically using scripting. The scripted planning also reduces the changes in the plan quality due to the different experiences of the planners (28). Since our scripts include clinical protocols, standard dose prescriptions, standard margin for the PTVs, in-house standards and standard dose limitations, we believe that scripting would assist the standardization of pelvic irradiation in EC.