Quality assurance for on‐table adaptive magnetic resonance guided radiation therapy: A software tool to complement secondary dose calculation and failure modes discovered in clinical routine. Issue 3 (12th January 2022)

• Record Type: Journal Article
• Authors: Rippke, Carolin; Schrenk, Oliver; Renkamp, C. Katharina; Buchele, Carolin; Hörner‐Rieber, Juliane; Debus, Jürgen; Alber, Markus; Klüter, Sebastian
• Is Part Of: Journal of applied clinical medical physics. Volume 23:Issue 3(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-01-12
• Subjects: adaptive radiotherapy -- failure mode and effect analysis (FMEA) -- image‐guided radiotherapy -- MR‐guided radiation therapy -- online adaptive -- on‐table adaptive -- quality assurance -- risk management; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.13523
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: Online adaption of treatment plans on a magnetic resonance (MR)‐Linac enables the daily creation of new (adapted) treatment plans using current anatomical information of the patient as seen on MR images. Plan quality assurance (QA) relies on a secondary dose calculation (SDC) that is required because a pretreatment measurement is impossible during the adaptive workflow. However, failure mode and effect analysis of the adaptive planning process shows a large number of error sources, and not all of them are covered by SDC. As the complex multidisciplinary adaption process takes place under time pressure, additional software solutions for pretreatment per‐fraction QA need to be used. It is essential to double‐check SDC input to ensure a safe treatment delivery. Here, we present an automated treatment plan check tool for adaptive radiotherapy (APART) at a 0.35 T MR‐Linac. It is designed to complement the manufacturer‐provided adaptive QA tool comprising SDC. Checks performed by APART include contour analysis, electron density map examinations, and fluence modulation complexity controls. For nine of 362 adapted fractions (2.5%), irregularities regarding missing slices in target volumes and organs at risks as well as in margin expansion of target volumes have been found. This demonstrates that mistakes occur and can be detected by additional QA measures, especially contour analysis. Therefore, it is recommended to implement further QA tools additional to what the manufacturer provides to facilitate an informed decision about the quality of the treatment plan.