ArticleJournal of applied clinical medical physics2024
The performance of a new type accelerator uRT-linac 506c evaluated by a quality assurance automation system.
Article in Journal of applied clinical medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Surface-Guided Radiotherapy for Vulvar Cancer in the Frog-Leg Position: Setup Accuracy and BMI Effects.Journal of applied clinical medical physics · 2026Article
- Assessment of the mechanical performance of a novel CT-linac treatment couch.Frontiers in oncology · 2026Article
- Auto-Segmentation and Auto-Planning in Automated Radiotherapy for Prostate Cancer.Bioengineering (Basel, Switzerland) · 2025Article
- The performance of a new type accelerator uRT-linac 506c evaluated by a quality assurance automation system.Journal of applied clinical medical physics · 2024Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
purposeThe purpose of this study was to evaluate the performance of our quality assurance (QA) automation system and to evaluate the machine performance of a new type linear accelerator uRT-linac 506c within 6 months using this system.
methodsThis QA automation system consists of a hollow cylindrical phantom with 18 steel balls in the phantom surface and an analysis software to process electronic portal imaging device (EPID) measurement image data and report the results. The performance of the QA automation system was evaluated by the tests of repeatability, archivable precision, detectability of introduced errors, and the impact of set-up errors on QA results. The performance of this linac was evaluated by 31 items using this QA system over 6 months.
resultsThis QA system was able to automatically deliver QA plan, EPID image acquisition, and automatic analysis. All images acquiring and analysis took approximately 4.6 min per energy. The preset error of 0.1 mm in multi-leaf collimator (MLC) leaf were detected as 0.12 ± 0.01 mm for Bank A and 0.10 ± 0.01 mm in Bank B. The 2 mm setup error was detected as -1.95 ± 0.01 mm, -2.02 ± 0.01 mm, 2.01 ± 0.01 mm for X, Y, Z directions, respectively. And data from the tests of repeatability and detectability of introduced errors showed the standard deviation were all within 0.1 mm and 0.1°. and data of the machine performance were all within the tolerance specified by AAPM TG-142.
conclusionsThe QA automation system has high precision and good performance, and it can improve the QA efficiency. The performance of the new accelerator has also performed very well during the testing period.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.