Program Information
Real-Time Monte Carlo-Based Treatment Dose Reconstruction and Monitoring for Radiotherapy
Z Tian1*, F Shi1 , X Gu1 , Y Graves2 , J Tan1 , N Hassan-Rezaeian1 , S Jiang1 , X Jia1 , (1) UT Southwestern Medical Center, Dallas, Texas, (2) University of California, San Diego, La Jolla, California
Presentations
MO-FG-202-8 (Monday, August 1, 2016) 4:30 PM - 6:00 PM Room: 202
Purpose:This proof-of-concept study is to develop a real-time Monte Carlo (MC) based treatment-dose reconstruction and monitoring system for radiotherapy, especially for the treatments with complicated delivery, to catch treatment delivery errors at the earliest possible opportunity and interrupt the treatment only when an unacceptable dosimetric deviation from our expectation occurs.
Methods:First an offline scheme is launched to pre-calculate the expected dose from the treatment plan, used as ground truth for real-time monitoring later. Then an online scheme with three concurrent threads is launched while treatment delivering, to reconstruct and monitor the patient dose in a temporally resolved fashion in real-time. Thread T1 acquires machine status every 20 ms to calculate and accumulate fluence map (FM). Once our accumulation threshold is reached, T1 transfers the FM to T2 for dose reconstruction ad starts to accumulate a new FM. A GPU-based MC dose calculation is performed on T2 when MC dose engine is ready and a new FM is available. The reconstructed instantaneous dose is directed to T3 for dose accumulation and real-time visualization. Multiple dose metrics (e.g. maximum and mean dose for targets and organs) are calculated from the current accumulated dose and compared with the pre-calculated expected values. Once the discrepancies go beyond our tolerance, an error message will be send to interrupt the treatment delivery.
Results:A VMAT Head-and-neck patient case was used to test the performance of our system. Real-time machine status acquisition was simulated here. The differences between the actual dose metrics and the expected ones were 0.06%-0.36%, indicating an accurate delivery. ~10Hz frequency of dose reconstruction and monitoring was achieved, with 287.94s online computation time compared to 287.84s treatment delivery time.
Conclusion:Our study has demonstrated the feasibility of computing a dose distribution in a temporally resolved fashion in real-time and quantitatively and dosimetrically monitoring the treatment delivery.
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