Purpose: To describe biological-based optimization and Monte Carlo (MC) dose calculation-based treatment planning for volumetric modulated arc therapy (VMAT) delivery of stereotactic body radiation therapy (SBRT) in lung, liver, and prostate patients. Methods: Optimization strategies and VMAT planning parameters using a biological-based optimization MC planning system were analyzed for 24 SBRT patients. Patients received a median dose of 45 Gy range, 34-54 Gy for lung tumors in 1-5 fxs and a median dose of 52 Gy range, 48-60 Gy for liver tumors in 3-6 fxs. Prostate patients received a fractional dose of 10 Gy in 5 fxs. Biological-cost functions were used for plan optimization, and its dosimetric quality was evaluated using the conformity index (CI), the conformation number (CN), the ratio of the volume receiving 50 of the prescription dose over the planning target volume (Rx/PTV50). The quality and efficiency of the delivery were assessed according to measured quality assurance (QA) passing rates and delivery times. For each disease site, one patient was replanned using physical cost function and compared to the corresponding biological plan. Results: Median CI, CN, and Rx/PTV50 for all 24 patients were 1.13 (1.02-1.28), 0.79 (0.70-0.88), and 5.3 (3.1-10.8), respectively. The median delivery rate for all patients was 410 MU/min with a maximum possible rate of 480 MU/min (85%). Median QA passing rate was 96.7%, and it did not significantly vary with the tumor site. Conclusions: VMAT delivery of SBRT plans optimized using biological-motivated cost-functions result in highly conformal dose distributions. Plans offer shorter treatment-time benefits and provide efficient dose delivery without compromising the plan conformity for tumors in the prostate, lung, and liver, thereby improving patient comfort and clinical throughput. The short delivery times minimize the risk of patient setup and intrafraction motion errors often associated with long SBRT treatment delivery times.
- biological-based optimization
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging