Application programming interface guided QA plan generation and analysis automation.


Journal

Journal of applied clinical medical physics
ISSN: 1526-9914
Titre abrégé: J Appl Clin Med Phys
Pays: United States
ID NLM: 101089176

Informations de publication

Date de publication:
Jun 2021
Historique:
revised: 15 04 2021
received: 12 03 2021
accepted: 23 04 2021
pubmed: 27 5 2021
medline: 22 6 2021
entrez: 26 5 2021
Statut: ppublish

Résumé

Linear accelerator quality assurance (QA) in radiation therapy is a time consuming but fundamental part of ensuring the performance characteristics of radiation delivering machines. The goal of this work is to develop an automated and standardized QA plan generation and analysis system in the Oncology Information System (OIS) to streamline the QA process. Automating the QA process includes two software components: the AutoQA Builder to generate daily, monthly, quarterly, and miscellaneous periodic linear accelerator QA plans within the Treatment Planning System (TPS) and the AutoQA Analysis to analyze images collected on the Electronic Portal Imaging Device (EPID) allowing for a rapid analysis of the acquired QA images. To verify the results of the automated QA analysis, results were compared to the current standard for QA assessment for the jaw junction, light-radiation coincidence, picket fence, and volumetric modulated arc therapy (VMAT) QA plans across three linacs and over a 6-month period. The AutoQA Builder application has been utilized clinically 322 times to create QA patients, construct phantom images, and deploy common periodic QA tests across multiple institutions, linear accelerators, and physicists. Comparing the AutoQA Analysis results with our current institutional QA standard the mean difference of the ratio of intensity values within the field-matched junction and ball-bearing position detection was 0.012 ± 0.053 (P = 0.159) and is 0.011 ± 0.224 mm (P = 0.355), respectively. Analysis of VMAT QA plans resulted in a maximum percentage difference of 0.3%. The automated creation and analysis of quality assurance plans using multiple APIs can be of immediate benefit to linear accelerator quality assurance efficiency and standardization. QA plan creation can be done without following tedious procedures through API assistance, and analysis can be performed inside of the clinical OIS in an automated fashion.

Identifiants

pubmed: 34036736
doi: 10.1002/acm2.13288
pmc: PMC8200500
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

26-34

Informations de copyright

© 2021 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.

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Auteurs

Matthew C Schmidt (MC)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.
Department of Physics, University of Massachusetts Lowell, Lowell, MA, USA.

Caleb A Raman (CA)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Yu Wu (Y)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Mahmoud M Yaqoub (MM)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Yao Hao (Y)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Rebecca Nichole Mahon (RN)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Matthew J Riblett (MJ)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Nels C Knutson (NC)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Erno Sajo (E)

Department of Physics, University of Massachusetts Lowell, Lowell, MA, USA.

Piotr Zygmanski (P)

Brigham and Women's/ Dana Farber Cancer Institute/ Harvard Medical School, Boston, MA, USA.

Marian Jandel (M)

Department of Physics, University of Massachusetts Lowell, Lowell, MA, USA.

Francisco J Reynoso (FJ)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

Baozhou Sun (B)

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA.

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Classifications MeSH