Process-based quality management for clinical implementation of adaptive radiotherapy.

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.

[1]  X Allen Li,et al.  Validation of an online replanning technique for prostate adaptive radiotherapy. , 2011, Physics in medicine and biology.

[2]  Sasa Mutic,et al.  Quality control quantification (QCQ): a tool to measure the value of quality control checks in radiation oncology. , 2012, International journal of radiation oncology, biology, physics.

[3]  A Jamshidi,et al.  TU‐C‐BRB‐10: An Electronic Whiteboard and Associated Databases for Physics Workflow Coordination in a Paperless, Multi‐Site Radiation Oncology Department , 2011 .

[4]  Steve B. Jiang,et al.  TU‐E‐BRB‐05: Real‐Time Dose Reconstruction for Treatment Monitoring , 2010 .

[5]  D. Jaffray Image-guided radiotherapy: from current concept to future perspectives , 2012, Nature Reviews Clinical Oncology.

[6]  Deshan Yang,et al.  Automated radiotherapy treatment plan integrity verification. , 2012, Medical physics.

[7]  Fang-Fang Yin,et al.  A planning quality evaluation tool for prostate adaptive IMRT based on machine learning. , 2011, Medical physics.

[8]  Sasa Mutic,et al.  Quality Assurance with Plan Veto: reincarnation of a record and verify system and its potential value. , 2014, International journal of radiation oncology, biology, physics.

[9]  Sasa Mutic,et al.  Eliminating inconsistencies in simulation and treatment planning orders in radiation therapy. , 2013, International journal of radiation oncology, biology, physics.

[10]  L Xing,et al.  Computer verification of fluence map for intensity modulated radiation therapy. , 2000, Medical physics.

[11]  M. Petasecca,et al.  Characterization of a novel two dimensional diode array the "magic plate" as a radiation detector for radiation therapy treatment. , 2012, Medical physics.

[12]  T. K. Yeung,et al.  Quality assurance in radiotherapy: evaluation of errors and incidents recorded over a 10 year period. , 2005, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[13]  L. Beaulieu,et al.  Real-time verification of multileaf collimator-driven radiotherapy using a novel optical attenuation-based fluence monitor. , 2011, Medical physics.

[14]  Kristy K Brock,et al.  Quality assurance of serial 3D image registration, fusion, and segmentation. , 2008, International journal of radiation oncology, biology, physics.

[15]  J. Williamson,et al.  Quality assurance needs for modern image-based radiotherapy: recommendations from 2007 interorganizational symposium on "quality assurance of radiation therapy: challenges of advanced technology". , 2008, International journal of radiation oncology, biology, physics.

[16]  Stephanie A Terezakis,et al.  Safety strategies in an academic radiation oncology department and recommendations for action. , 2011, Joint Commission journal on quality and patient safety.

[17]  Fang-Fang Yin,et al.  Adaptive Radiation Therapy: Technical Components and Clinical Applications , 2011, Cancer journal.

[18]  Todd Pawlicki,et al.  Moving from IMRT QA measurements toward independent computer calculations using control charts. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[19]  D. Jaffray,et al.  An integral quality monitoring system for real-time verification of intensity modulated radiation therapy. , 2009, Medical physics.

[20]  Murty S. Goddu,et al.  Evaluation of the efficiency and effectiveness of independent dose calculation followed by machine log file analysis against conventional measurement based IMRT QA , 2012, Journal of applied clinical medical physics.

[21]  D. Low,et al.  Experience-based quality control of clinical intensity-modulated radiotherapy planning. , 2011, International Journal of Radiation Oncology, Biology, Physics.

[22]  Benedick A Fraass,et al.  A method for evaluating quality assurance needs in radiation therapy. , 2008, International journal of radiation oncology, biology, physics.