SU-F-T-433: Evaluation of a New Dose Mimicking Application for Clinical Flexibility and Reliability

Purpose: Clinical workflow and machine down time occasionally require patients to be temporarily treated on a system other than the initial treatment machine. A new commercial dose mimicking application provides automated cross-platform treatment planning to expedite this clinical flexibility. The aim of this work is to evaluate the feasibility of automatic plan creation and establish a robust clinical workflow for prostate and pelvis patients. Methods: Five prostate and five pelvis patients treated with helical plans were selected for re-planning with the dose mimicking application, covering both simple and complex scenarios. Two-arc VMAT and 7- and 9-field IMRT plans were generated for each case, with the objective function of achieving similar dose volume histogram from the initial helical plans. Dosimetric comparisons include target volumes and organs at risk (OARs) (rectum, bladder, small bowel, femoral heads, etc.). Dose mimicked plans were evaluated by a radiation oncologist, and patient-specific QAs were performed to validate delivery. Results: Overall plan generation and transfer required around 30 minutes of dosimetrist’s time once the dose-mimicking protocol is setup for each site. The resulting VMAT and 7- and 9-field IMRT plans achieved equivalent PTV coverage and homogeneity (D99/DRx = 97.3%, 97.2%, 97.2% and HI = 6.0, 5.8, and 5.9, respectively), compared to helical plans (97.6% and 4.6). The OAR dose discrepancies were up to 6% in rectum Dmean, but generally lower in bladder, femoral heads, bowel and penile bulb. In the context of 1–5 fractions, the radiation oncologist evaluated the dosimetric changes as not clinically significant. All delivery QAs achieved >90% pass with a 3%/3mm gamma criteria. Conclusion: The automated dose-mimicking workflow offers a strategy to avoid missing treatment fractions due to machine down time with non-clinically significant changes in dosimetry. Future work will further optimize dose mimicking plans and investigate other cross-platform treatment delivery options.