ESTRO 36 Abstract Book

S244 ESTRO 36 _______________________________________________________________________________________________

effects of a potential problem and the prioritization of actions that can reduce this dysfunction. Our Radiation Therapy Department used the FMECA as a strategy tool to continuously improve treatment quality and safety. This FMECA approach was applied to our Cyberknife (CK) workflow process. Material and Methods Using the FMECA methodology, the CK workflow process was defined with a flow chart and responsibility map including a description of every step of prescription, treatment preparation and treatment delivery. The identification of possible risks was then carried out with their origins and consequences. The evaluation was based on 3 criteria: Severity (S), frequency of Occurrence (O) and probability of Detection (D). Finally, we calculated the Criticality Index (CI = S x O x D) for each of the identified risks. The rating for each criterion is based on a scale from 1 to 4. The Criticality Index can span a range of 1 to 64. Results We defined 10 stages, with corresponding failure modes presented in a table. At each stage, identified failures with possible causes and consequences are listed and the risk level assessed. A detailed scoreboard was obtained presenting the risks and enabling easier identification of priority actions to be undertaken. The board showed 66 possible failure modes. 8 of the top-ranked failure modes were considered for process improvements. We also crossed the scoreboard obtained with the adverse events most often reported on 2015. We found 2 correspondences between failure modes and adverse events reported. We therefore also considered that in the implementation of preventive/improvement actions to take. A review of this analysis was done in September 2016. Therefore, at this moment, a revaluation of the process, failures, ratings and implemented actions was performed with each members of the CK team. The correlation with reported adverse events was also made. We had one failure mode that has to be changed from a moderate to an unacceptable level because an incident was reported following a non-update procedure. New improvement actions have been implemented directly. In order to continue our proactive approach to risk analysis a systematic annual review of this analysis is now introduced in routine. All this, in relation to the reported adverse events. The figure shows an extract of the FMECA scoreboard obtained for CT

simulation

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contouring

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Conclusion The analysis of the potential failures, their causes and effects allowed us to increase the quality and the safety in the CK workflow process. The FMECA technique provides a systematic method to target vulnerabilities before they generate an error. This framework analysis can naturally incorporate further quantification and monitoring. The FMECA method is an effective tool for the management of risks in patient care. PV-0459 Prostate CBCT dose optimization : from an iterative mAs reduction to a sytematic exposure reduction E. Jaegle 1 , M.E. Alayrach 1 , A. Badey 1 , V. Bodez 1 , C. Khamphan 1 , P. Martinez 1 , R. Garcia 1 1 Institut Sainte Catherine, Physique, Avig non, France Purpose or Objective A daily repositioning Cone Beam Computed Tomography image (CBCT) for prostate radiotherapy is realized using exposure templates (mAs, kV) which affect image quality and imaging dose. Settings should be optimized to minimize patient exposure while maintaining sufficient image quality to register the initial planning CT with CBCT using soft tissue matching. Material and Methods 20 prostate patients (without hip prosthesis) with daily CBCT (40 fractions) acquired on a TrueBeam™ (Varian Medical Systems) machine were selected. After the first fraction using the standard pelvis template (125 kV 1080 mAs CTDIw 14 mGy), the therapists manually applied, day after day, a low mAs reduction and assessed if the CBCT image quality was good enough for patient repositioning. The iterative process stopped when image quality was assessed too bad and the last proper mAs were selected. The link between the mAs reduction and corpulence (patient volume inside CBCT FOV) was studied. For one example patient, 23 therapists registered CBCT images with CT for 3 fractions : the first fraction (S 0% ), a fraction with 50% mAs reduction (S -50% ) and the fraction with maximum mAs reduction (S -71% ). Fisher’s test was applied to every direction, to compare the variance between S 0% / S -50% and S 0% / S -71% .