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Program Information

A Real-Time Virtual Delivery System for Photon Radiotherapy Delivery Monitoring

F Shi

F Shi1*, X Gu1 , Y Graves2 , S Jiang1 , X Jia1 , (1) UT Southwestern Medical Center, Dallas, TX, (2) University of California, San Diego, La Jolla, CA


MO-G-BRE-1 Monday 4:30PM - 6:00PM Room: Ballroom E

Purpose: Treatment delivery monitoring is important for radiotherapy, which enables catching dosimetric error at the earliest possible opportunity. This project develops a virtual delivery system to monitor the dose delivery process of photon radiotherapy in real-time using GPU-based Monte Carlo (MC) method.

Methods: The simulation process consists of 3 parallel CPU threads. A thread T1 is responsible for communication with a linac, which acquires a set of linac status parameters, e.g. gantry angles, MLC configurations, and beam MUs every 20 ms. Since linac vendors currently do not offer interface to acquire data in real time, we mimic this process by fetching information from a linac dynalog file at the set frequency. Instantaneous beam fluence map (FM) is calculated. A FM buffer is also created in T1 and the instantaneous FM is accumulated to it. This process continues, until a ready signal is received from thread T2 on which an in-house developed MC dose engine executes on GPU. At that moment, the accumulated FM is transferred to T2 for dose calculations, and the FM buffer in T1 is cleared. Once the calculation finishes, the resulting 3D dose distribution is directed to thread T3, which displays it in three orthogonal planes overlaid on the CT image for treatment monitoring. This process continues to monitor the 3D dose distribution in real-time.

Results: An IMRT and a VMAT cases used in our patient-specific QA are studied. Maximum dose differences between our system and treatment planning system are 0.98% and 1.58% for the two cases, respectively. The average time per MC calculation is 0.1sec with <2% relative uncertainty. The update frequency of ~10Hz is considered as real time.

Conclusion: By embedding a GPU-based MC code in a novel data/work flow, it is possible to achieve real-time MC dose calculations to monitor delivery process.

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