Automating quality assurance of digital linear accelerators using a radioluminescent phosphor coated phantom and optical imaging

Abstract

Purpose To develop a novel strategy to automate the predominantly manual process of mechanical and geometric tests in routine quality assurance (QA) of digital linear accelerator (LINAC). Methods The autonomous QA system consists of three parts: (1) a customized phantom coated with radioluminescent material; (2) an optical imaging system capable of visualizing the incidence of the radiation beam, light field or lasers on the phantom; and (3) software to process the captured signals. The radioluminescent phantom, which enables visualization of the radiation beam on the same surface as the light field and lasers, was placed on the couch and imaged while a predefined treatment plan was delivered from the LINAC. The captured images were then processed to self-calibrate the system and perform measurements for evaluating light field/radiation coincidence, jaw position indicators, cross-hair centering, treatment couch position indicators and localizing laser alignment. System accuracy was probed by intentionally introducing errors and by comparing with current practice. The accuracy of self-calibration was evaluated by examining measurement repeatability under fixed and variable phantom setups. Results The integrated system was able to automatically collect, analyze and report the results for all tests. The average difference between introduced and measured errors was 0.13 mm. The system was shown to be consistent with current techniques. Measurement variability increased slightly from 0.1 mm to 0.2 mm when the phantom setup was varied, but no significant difference in the mean measurement value was detected. Total measurement time was less than 10 minutes for all tests as a result of automation. Conclusions The integrated QA system succeeded in autonomously performing mechanical alignment tests specified by TG-142. The system’s unique features of a phosphor-coated phantom and fully automated, operator independent self-calibration offer the potential to streamline the QA process for modern LINACs.

Scintillation imaging as a high‐resolution, remote, versatile 2D detection system for MR‐linac quality assurance

“…To transform the viewing angle to a beam’s eye view, a 6 × 7 square checkerboard printed on a 2 cm slab of ABS plastic was placed at the same position as the solid water slab and a calibration image was acquired. Using the points defined at the vertices of the checkerboard, a projective transformation matrix was generated, and applied to all scintillation images to provide a beam’s eye view, as performed in previous studies 16,17,25 . An example of the transformation is shown in Figs.…”

“…Using the points defined at the vertices of the checkerboard, a projective transformation matrix was generated, and applied to all scintillation images to provide a beam's eye view, as performed in previous studies. 16,17,25 An example of the transformation is shown in Figs. 1(b)-1(c).…”

“…Camera-based positional verification methods using the light field and fiducial markers have been developed for some mechanical quality control tasks, 12,13 while Ma et al and Jenkins et al have both used 2D imaging of radioluminescent sources for routine quality assurance procedures and real-time beam monitoring. [14][15][16][17] Optical time-synchronized imaging using intensified cameras, including scintillation and Cherenkov imaging, have been shown as useful tools in patient treatment, linac QA, and dosimetry. [18][19][20][21][22][23][24] Miao et al demonstrated the potential value of Cherenkov imaging for 2D beam shaped analysis compared with film.…”

“…Optical methods have been used for linear accelerator QA, especially for 2D field measurements relevant to intensity modulated radiation therapy (IMRT). Camera‐based positional verification methods using the light field and fiducial markers have been developed for some mechanical quality control tasks, 12,13 while Ma et al and Jenkins et al have both used 2D imaging of radioluminescent sources for routine quality assurance procedures and real‐time beam monitoring 14–17 . Optical time‐synchronized imaging using intensified cameras, including scintillation and Cherenkov imaging, have been shown as useful tools in patient treatment, linac QA, and dosimetry 18–24 .…”

Assessing the robustness of artificial intelligence powered planning tools in radiotherapy clinical settings—a phantom simulation approach

“…Recent years saw substantial amount of efforts in improving efficiency of the radiation therapy workflow while maintaining quality (1). These efforts include auto contouring (2), treatment planning automation (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16), and QA automation (17)(18)(19)(20)(21).…”