Moving towards process-based radiotherapy quality assurance using statistical process control

Vysakh Raveendran; Ganapathi Raman R; Anjana P T; Saju Bhasi; Ranjith C P; Rajesh Ashok Kinhikar

doi:10.1016/j.ejmp.2023.102651

Moving towards process-based radiotherapy quality assurance using statistical process control

Phys Med. 2023 Aug:112:102651. doi: 10.1016/j.ejmp.2023.102651. Epub 2023 Aug 8.

Authors

Vysakh Raveendran¹, Ganapathi Raman R², Anjana P T³, Saju Bhasi⁴, Ranjith C P³, Rajesh Ashok Kinhikar⁵

Affiliations

¹ Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer, Tata Memorial Centre, Homi Bhabha National Institute, Navi Mumbai, Maharashtra, India.; Department of Physics, Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari District, Tamil Nadu, India.. Electronic address: vraveendran@actrec.gov.in.
² Department of Physics, Saveetha Engineering College (Autonomous), Chennai, Tamil Nadu, India.
³ Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer, Tata Memorial Centre, Homi Bhabha National Institute, Navi Mumbai, Maharashtra, India.
⁴ Division of Radiation Physics, Regional Cancer Centre, Trivandrum, India.
⁵ Department of Medical Physics, Tata Memorial Centre, Homi Bhabha National Institute Parel, Mumbai, India.

PMID: 37562233
DOI: 10.1016/j.ejmp.2023.102651

Abstract

Monitoring Radiotherapy Quality Assurance (QA) using Statistical Process Control (SPC) methods has gained wide acceptance. The significance of understanding the SPC methodologies has increased among the medical physics community with the release of Task Group (TG) reports from the American Association of Physicists in Medicine (AAPM) on patient-specific QA (PSQA) (TG-218) and Proton therapy QA (TG-224). Even though these reports recommend using SPC for QA analysis, physicists have ambiguities and doubts in choosing proper SPC tools and methodologies. This review article summarises the utilisation of SPC methods for different Radiotherapy QAs published in the literature, such as PSQA, routine Linac QA and patient positional verification. QA analysis using SPC could assist the user in distinguishing between 'special' and 'routine' sources of variations in the QA, which can aid in reducing actions on false positive QA results. For improved PSQA monitoring, machine-specific, site-specific, and technique-specific Tolerance Limits and Action Limits derived from a two-stage SPC-based approach can be used. Adopting a combination of Shewhart's control charts and time-weighted control charts for routine Linac QA monitoring could add more insights to the QA process. Incorporating SPC tools into existing image review modules or introducing new SPC software packages specifically designed for clinical use can significantly enhance the image review process. Proper selection and having adequate knowledge of SPC tools are essential for efficient QA monitoring, which is a function of the type of QA data available, and the magnitude of process drift to be monitored.

Keywords: Linac QA; Patient specific IMRT QA; Radiotherapy Quality assurance; Statistical Process control.

Publication types

Review