• DOI:10.1002/acm2.12946
• Corpus ID: 220305813

Automated and robust beam data validation of a preconfigured ring gantry linear accelerator using a 1D tank with synchronized beam delivery and couch motions

@article{Knutson2020AutomatedAR,
  title={Automated and robust beam data validation of a preconfigured ring gantry linear accelerator using a 1D tank with synchronized beam delivery and couch motions},
  author={Nels Knutson and Matthew C. Schmidt and Francisco J Reynoso and Yao Hao and Thomas R. Mazur and Eric Laugeman and Geoffrey D. Hugo and Sasa Mutic and H. Harold Li and Wilfred Ngwa and Bin Cai and Erno Sajo},
  journal={Journal of Applied Clinical Medical Physics},
  year={2020},
  volume={21},
  pages={200 - 207}
}

• N. Knutson, Matthew C. Schmidt, +9 authors E. Sajo
• Published 2 July 2020
• Medicine
• Journal of Applied Clinical Medical Physics

Abstract Purpose To develop an efficient and automated methodology for beam data validation for a preconfigured ring gantry linear accelerator using scripting and a one‐dimensional (1D) tank with automated couch motions. Materials and methods Using an application programming interface, a program was developed to allow the user to choose a set of beam data to validate with measurement. Once selected the program generates a set of instructions for radiation delivery with synchronized couch motions for the linear accelerator in the form of an extensible markup language (XML) file to be delivered on the ring gantry linear accelerator. The user then delivers these beams while measuring with the 1D tank and data logging electrometer. The program also automatically calculates this set of beams on the measurement geometry within the treatment planning system (TPS) and extracts the corresponding calculated dosimetric data for comparison to measurement. Once completed the program then returns a comparison of the measurement to the predicted result from the TPS to the user and prints a report. In this work lateral, longitudinal, and diagonal profiles were taken for fields sizes of 6 × 6, 8 × 8, 10 × 10, 20 × 20, and 28 × 28 cm2 at depths of 1.3, 5, 10, 20, and 30 cm. Depth dose profiles were taken for all field sizes. Results Using this methodology, the TPS was validated to agree with measurement. All compared points yielded a gamma value less than 1 for a 1.5%/1.5 mm criteria (100% passing rate). Off axis profiles had >98.5% of data points producing a gamma value <1 with a 1%/1 mm criteria. All depth profiles produced 100% of data points with a gamma value <1 with a 1%/1 mm criteria. All data points measured were within 1.5% or 2 mm distance to agreement. Conclusions This methodology allows for an increase in automation in the beam data validation process. Leveraging the application program interface allows the user to use a single system to create the measurement files, predict the result, and then compare to actual measurement increasing efficiency and reducing the chance for user input errors.