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Process‐based quality management for clinical implementation of adaptive radiotherapy
Author(s) -
Noel Camille E.,
Santanam Lakshmi,
Parikh Parag J.,
Mutic Sasa
Publication year - 2014
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4890589
Subject(s) - quality assurance , failure mode and effects analysis , computer science , medical physics , task group , radiation treatment planning , radiation therapy , risk management , process (computing) , position paper , risk analysis (engineering) , reliability engineering , medicine , operations management , engineering management , engineering , external quality assessment , management , world wide web , economics , operating system
Purpose: Intensity‐modulated adaptive radiotherapy (ART) has been the focus of considerable research and developmental work due to its potential therapeutic benefits. However, in light of its unique quality assurance (QA) challenges, no one has described a robust framework for its clinical implementation. In fact, recent position papers by ASTRO and AAPM have firmly endorsed pretreatment patient‐specific IMRT QA, which limits the feasibility of online ART. The authors aim to address these obstacles by applying failure mode and effects analysis (FMEA) to identify high‐priority errors and appropriate risk‐mitigation strategies for clinical implementation of intensity‐modulated ART. Methods: An experienced team of two clinical medical physicists, one clinical engineer, and one radiation oncologist was assembled to perform a standard FMEA for intensity‐modulated ART. A set of 216 potential radiotherapy failures composed by the forthcoming AAPM task group 100 (TG‐100) was used as the basis. Of the 216 failures, 127 were identified as most relevant to an ART scheme. Using the associated TG‐100 FMEA values as a baseline, the team considered how the likeliness of occurrence (O), outcome severity (S), and likeliness of failure being undetected (D) would change for ART. New risk priority numbers (RPN) were calculated. Failures characterized by RPN ≥ 200 were identified as potentially critical. Results: FMEA revealed that ART RPN increased for 38% (n = 48/127) of potential failures, with 75% (n = 36/48) attributed to failures in the segmentation and treatment planning processes. Forty‐three of 127 failures were identified as potentially critical. Risk‐mitigation strategies include implementing a suite of quality control and decision support software, specialty QA software/hardware tools, and an increase in specially trained personnel. Conclusions: Results of the FMEA‐based risk assessment demonstrate that intensity‐modulated ART introduces different (but not necessarily more) risks than standard IMRT and may be safely implemented with the proper mitigations.