Application and Challenges of Statistical Process Control in Radiation Therapy Quality Assurance.


Journal

International journal of radiation oncology, biology, physics
ISSN: 1879-355X
Titre abrégé: Int J Radiat Oncol Biol Phys
Pays: United States
ID NLM: 7603616

Informations de publication

Date de publication:
01 Jan 2024
Historique:
received: 12 05 2023
revised: 21 07 2023
accepted: 08 08 2023
medline: 6 12 2023
pubmed: 22 8 2023
entrez: 21 8 2023
Statut: ppublish

Résumé

Quality assurance (QA) is important for ensuring precision in radiation therapy. The complexity and resource-intensive nature of QA has increased with the continual evolution of equipment and techniques. An effective approach is to improve the process control technology and resource optimization. Statistical process control is an economical and efficient tool that has been widely used to monitor, control, and improve quality management processes and is now being increasingly used for radiation therapy QA. This article reviews the development and methodology of statistical process control technology, evaluates its suitability in radiation therapy QA practices, and assesses its importance and challenges in optimizing radiation therapy QA processes.

Identifiants

pubmed: 37604239
pii: S0360-3016(23)07795-7
doi: 10.1016/j.ijrobp.2023.08.020
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

295-305

Informations de copyright

Copyright © 2023 Elsevier Inc. All rights reserved.

Auteurs

Qing Xiao (Q)

Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

Guangjun Li (G)

Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China; Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China. Electronic address: gjnick829@sina.com.

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Classifications MeSH