Literature DB >> 33338293

Auto-Trending daily quality assurance program for a pencil beam scanning proton system aligned with TG 224.

Chengyu Shi1, Qing Chen1, Francis Yu1, Jingqiao Zhang, Minglei Kang1, Shikui Tang2, Chang Chang3,4, Haibo Lin1.   

Abstract

The Daily Quality Assurance (DQA) for a proton modality is not standardized. The modern pencil beam scanning proton system is becoming a trend and an increasing number of proton centers with PBS are either under construction or in planning. The American Association of Physicists in Medicine has a Task Group 224 report published in 2019 for proton modality routine QA. Therefore, there is a clinical need to explore a DQA procedure to meet the TG 224 guideline. The MatriXX PT and a customized phantom were used for the dosimetry constancy checking. An OBI box was used for imaging QA. The MyQA(TM) software was used for logging the dosimetry results. An in-house developed application was applied to log and auto analyze the DQA results. Another in-house developed program "DailyQATrend" was used to create DQA databases for further analysis. All the functional and easy determined tasks passed. For dosimetry constancy checking, the outputs for four gantry rooms were within ±3% with room to room baseline differences within ±1%. The energy checking was within ±1%. The spot location checking from the baseline was within 0.63 mm and the spot size checking from the baseline was within -1.41 ± 1.27 mm (left-right) and -0.24 ± 1.27 mm (in-out) by averaging all the energies. We have found that there was also a trend for the beam energies of two treatment rooms slowly going down (0.76% per month and 0.48 per month) after analyzing the whole data trend with linear regression. A DQA program for a PBS proton system has been developed and fully implemented into the clinic. The DQA program meets the TG 224 guideline and has web-based logging and auto treading functions. The clinical data show the DQA program is efficient and has the potential to identify the PBS proton system potential issue.
© 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.

Entities:  

Keywords:  DQA; PBS; ProBeam; Proton; TG 224; automation

Mesh:

Substances:

Year:  2020        PMID: 33338293      PMCID: PMC7856486          DOI: 10.1002/acm2.13117

Source DB:  PubMed          Journal:  J Appl Clin Med Phys        ISSN: 1526-9914            Impact factor:   2.102


  22 in total

1.  10 prescribing, recording, and reporting treatment.

Authors: 
Journal:  J ICRU       Date:  2007-12

2.  Task Group 142 report: quality assurance of medical accelerators.

Authors:  Eric E Klein; Joseph Hanley; John Bayouth; Fang-Fang Yin; William Simon; Sean Dresser; Christopher Serago; Francisco Aguirre; Lijun Ma; Bijan Arjomandy; Chihray Liu; Carlos Sandin; Todd Holmes
Journal:  Med Phys       Date:  2009-09       Impact factor: 4.071

3.  A technique for the quantitative evaluation of dose distributions.

Authors:  D A Low; W B Harms; S Mutic; J A Purdy
Journal:  Med Phys       Date:  1998-05       Impact factor: 4.071

4.  Predicting VMAT patient-specific QA results using a support vector classifier trained on treatment plan characteristics and linac QC metrics.

Authors:  Dal A Granville; Justin G Sutherland; Jason G Belec; Daniel J La Russa
Journal:  Phys Med Biol       Date:  2019-04-29       Impact factor: 3.609

5.  A deep learning-based prediction model for gamma evaluation in patient-specific quality assurance.

Authors:  Seiji Tomori; Noriyuki Kadoya; Yoshiki Takayama; Tomohiro Kajikawa; Katsumi Shima; Kakutarou Narazaki; Keiichi Jingu
Journal:  Med Phys       Date:  2018-07-31       Impact factor: 4.071

6.  Technical Note: An efficient daily QA procedure for proton pencil beam scanning.

Authors:  James E Younkin; Jiajian Shen; Martin Bues; Daniel G Robertson; Daniel W Mundy; Edward Clouser; Wei Liu; Xiaoning Ding; Joshua B Stoker
Journal:  Med Phys       Date:  2018-02-19       Impact factor: 4.071

7.  Machine Learning for Patient-Specific Quality Assurance of VMAT: Prediction and Classification Accuracy.

Authors:  Jiaqi Li; Le Wang; Xile Zhang; Lu Liu; Jun Li; Maria F Chan; Jing Sui; Ruijie Yang
Journal:  Int J Radiat Oncol Biol Phys       Date:  2019-08-01       Impact factor: 7.038

8.  Implementation of the structural SIMilarity (SSIM) index as a quantitative evaluation tool for dose distribution error detection.

Authors:  Jiayuan Peng; Chengyu Shi; Eric Laugeman; Weigang Hu; Zhen Zhang; Sasa Mutic; Bin Cai
Journal:  Med Phys       Date:  2020-01-28       Impact factor: 4.071

9.  Daily QA in proton therapy using a single commercially available detector.

Authors:  Jamil Lambert; Christian Bäumer; Benjamin Koska; Xiaoning Ding
Journal:  J Appl Clin Med Phys       Date:  2014-11-08       Impact factor: 2.102

10.  Prediction of the output factor using machine and deep learning approach in uniform scanning proton therapy.

Authors:  Hardev S Grewal; Michael S Chacko; Salahuddin Ahmad; Hosang Jin
Journal:  J Appl Clin Med Phys       Date:  2020-05-17       Impact factor: 2.102

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.