Failure mode and effect analysis-based quality assurance for dynamic MLC tracking systems

Journal Article · Wed Dec 15 04:00:00 EST 2010 · Medical Physics

DOI:https://doi.org/10.1118/1.3517837· OSTI ID:22096846

Sawant, Amit; Dieterich, Sonja; Svatos, Michelle; Keall, Paul ^[1]

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1. Stanford University, Stanford, California 94394 (United States)

Purpose: To develop and implement a failure mode and effect analysis (FMEA)-based commissioning and quality assurance framework for dynamic multileaf collimator (DMLC) tumor tracking systems. Methods: A systematic failure mode and effect analysis was performed for a prototype real-time tumor tracking system that uses implanted electromagnetic transponders for tumor position monitoring and a DMLC for real-time beam adaptation. A detailed process tree of DMLC tracking delivery was created and potential tracking-specific failure modes were identified. For each failure mode, a risk probability number (RPN) was calculated from the product of the probability of occurrence, the severity of effect, and the detectibility of the failure. Based on the insights obtained from the FMEA, commissioning and QA procedures were developed to check (i) the accuracy of coordinate system transformation, (ii) system latency, (iii) spatial and dosimetric delivery accuracy, (iv) delivery efficiency, and (v) accuracy and consistency of system response to error conditions. The frequency of testing for each failure mode was determined from the RPN value. Results: Failures modes with RPN{>=}125 were recommended to be tested monthly. Failure modes with RPN<125 were assigned to be tested during comprehensive evaluations, e.g., during commissioning, annual quality assurance, and after major software/hardware upgrades. System latency was determined to be {approx}193 ms. The system showed consistent and accurate response to erroneous conditions. Tracking accuracy was within 3%-3 mm gamma (100% pass rate) for sinusoidal as well as a wide variety of patient-derived respiratory motions. The total time taken for monthly QA was {approx}35 min, while that taken for comprehensive testing was {approx}3.5 h. Conclusions: FMEA proved to be a powerful and flexible tool to develop and implement a quality management (QM) framework for DMLC tracking. The authors conclude that the use of FMEA-based QM ensures efficient allocation of clinical resources because the most critical failure modes receive the most attention. It is expected that the set of guidelines proposed here will serve as a living document that is updated with the accumulation of progressively more intrainstitutional and interinstitutional experience with DMLC tracking.

• OSTI ID: 22096846
• Journal Information: Medical Physics, Journal Name: Medical Physics Journal Issue: 12 Vol. 37; ISSN 0094-2405; ISSN MPHYA6
• Country of Publication: United States
• Language: English

Related Subjects

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
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ACCURACY
ALLOCATIONS
COLLIMATORS
COMMISSIONING
COMPUTER CODES
EFFICIENCY
ERRORS
EVALUATION
FAILURES
HEALTH HAZARDS
NEOPLASMS
PATIENTS
QUALITY ASSURANCE
RADIOTHERAPY
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