Room: Exhibit Hall
Purpose: The purpose of this study was to test the clinical viability of applying a RapidPlan model trained on a lung stereotactic body radiation therapy (SBRT) technique to standard fractionation (SF) lung planning.
Methods: RapidPlan Henry Ford Health System (HFHS) Lung SBRT model (RP model), published by Varian, was used to test the possibility of its use for SF lung planning. Modified model (mRP model) was created from HFHS model by modifying objectives and priorities for the targets and organs at risk (OARs) to achieve superior organ sparing and planning quality consistency. Model OARs included lung-GTV, esophagus, heart, spinal cord, and planning risk volume (PRV) spinal cord. 20 SF plans for lung cancer patients treated at our institution were reoptimized in Eclipse treatment planning system (V13.7) with mRP model. The applicability of the model was evaluated for different techniques: VMAT and IMRT (65%:35%) and tumor locations: right lung, mediastinum and left lung (20%:50%:30%). Total treatment dose prescription varied from 37.5Gy to 60Gy with PTV volume ranged from 91.7cc to 721.8cc. One round of optimization was performed without planner intervention. All plans were normalized to PTV coverage V100%=95%.
Results: Compared to clinical plans mRP plans resulted in significantly lower mean doses for esophagus by 12.8%Â±13.0% (p=0.0002) and heart by 16.0%Â±18.6% (p=0.001). mRP plans were comparable to clinical plans with respect to target conformity and remaining OAR doses. Hot spots were comparable to clinical plans; 35% of mRP plans had maximum doses between 110 and 112%. In addition, the plans generated with mRP model were expedited with total optimization time of 12Â±3 min.
Conclusion: This work demonstrates the possibility of use of mRP model to generate clinically acceptable treatment plans of high quality. If mRP model is utilized for SF Lung planning, manual processing of hot spot is recommended after the optimization.
Lung, Radiation Therapy, Treatment Planning
TH- External beam- photons: VMAT dose optimization algorithms