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Poster presented at:

Each parameter tested by the QC was considered as a potential failure mode (FM). For each FM, a Risk Priority Number (RPN) was calculated from the product

of three indexes: likelihood of occurrence (O), severity of effect (S) and lack of detectability (D). Forty tests were examined simulating a parameter value just above

the expected tolerance levels. Indexes O, S, and D were scored from 1 (lowest risk) to 10 (highest risk) using two approaches:

A survey was submitted to each of the medical physicists of our institute involved in linac QC

A semi-quantitative analysis (SQ) was performed through the simulation of mechanical FMs in the treatment planning system and using studies

reported in literature. The SQ was based on results obtained by the QC data analysis over a period of three years.

The average RPN for each test was obtained taking into account both methods. For each linac, the tests were then sorted by their frequency (daily, monthly or

annual) and RPN value. Two different Varian linacs (DBX, Unique) were considered, the first used only for conformal therapy and the second one used essentially

with volumetric modulated arc therapy (VMAT) technique.

The increased complexity of modern linac-based radiotherapy requires more thorough quality assurance programs to reduce the risk of errors and ensure patient

safety. However, these demands are cumbersome and the efforts should be optimized in order to take maximum advantage of the available resources. In this

context, prospective methods for risk analysis, such as Failure Mode and Effects Analysis (FMEA), can be useful tools. Aim of this work was to evaluate

advantages and limits of the application of FMEA to the optimization of linac quality controls (QCs).

APPLICATION OF FAILURE AND EFFECTS ANALYSIS

TO LINAC QUALITY CONTROLS: ADVANTAGES AND LIMITS

F.Bonfantini1, T. Giandini1, S.Meroni1, C. Stucchi1, M. Carrara1, V. Mongioj1, I. Veronese2, E.Pignoli1

1 Medical Physics Unit, Foundation IRCCS National Cancer Institute of Milan, Italy 2 Physic Department of the University of Milan, Italy

PURPOSE

MATERIALS AND METHODS

FMEA is a useful tool to optimize and prioritize the linac QCs. It allowed to identify the tests more relevant for patient safety by

taking into account the specific equipment, treatment modalities and clinical practice. FMEA scores cannot be assigned only on

the basis of personal experience and risk perception. A semi-quantitative analysis of each FM and of the QC trend should be

always performed to evaluate the impact of each FM on patient dose.

CONCLUSIONS

RESULTS

A high variability was found in the O-D-S scores of the survey, as shown in

the box plots example for 14 dosimetric tests of Varian Unique linac (figure

1). Nevertheless, a lower variability was obtained for RPNs, highlighting at

the same time the more relevant tests.

Foundation IRCCS National Cancer Institute via Venezian 1 Milan, ITALY

ACKNOWLEDGEMENTS

This study was partially

funded by LILT Lega Italiana

per la Lotta contro i Tumori

(Milan-Italy)

Figure 1: Box-plots example of survey results for FMEA score for 14 dosimetric failure modes for Unique linac.

1. X-ray output constancy (monthly)

6. Physical wedge factor 10. Dyn. wedge transmission vs gantry angle

2. X-ray output constancy (daily) 7. Dynamic wedge factor 11. X-ray beam quality

3. Photon MU linearity 8. Dynamic wedge factor (daily) 12. Output constancy vs gantry angle

4. X-ray output vs dose rate 9. Check of dynamic wedge angle for 60° full field and for intermediate angle/field size

13. X-ray flatness and symmetry

5. Output factor 14. X-ray off-axis factor constancy

The differences in ranking order in the first positions, except for output constancy,

are due to the treatment techniques implemented on the two linacs: VMAT for

Unique, requiring accurate tests on dose modulation and multi leaf collimator

speed; treatment with multiple isocenters and/or junctions between adjacent

fields for DBX, requiring accurate tests on couch and jaw position indicators.

The large spread seen in all scores of the three indexes is due to the

different risk perception and professional experience of respondents. This

variability can be reduced by FM simulations in TPS and by studying QC

results. The integration of both evaluations (survey and SQ analysis)

provided the RPN-based ranking of tests: an example is shown in figure 2

for monthly tests for DBX and Unique linacs.

Figure 2: Classification of priority monthly tests, based on RPN scores, for DBX and Unique linacs.

PO-0908Francesca Bonfantini DOI: 10.3252/pso.eu.ESTRO36.2017

Physics track: Implementation of new technology, techniques, clinical protocols or trials (including QA & audit)