To apply failure mode and effect analysis (FMEA) to generate an effective and efficient initial physics plan checklist. Methods: A team of physicists, dosimetrists, and therapists was setup to reconstruct the workflow processes involved in the generation of a treatment plan beginning from simulation. The team then identified possible failure modes in each of the processes. For each failure mode, the severity (S), frequency of occurrence (O), and the probability of detection (D) was assigned a value and the risk priority number (RPN) was calculated. The values assigned were based on TG 100. Prior to assigning a value, the team discussed the values in the scoring system to minimize randomness in scoring. A local database of errors was used to help guide the scoring of frequency. Results: Twenty-seven process steps and 50 possible failure modes were identified starting from simulation to the final approved plan ready for treatment at the machine. Any failure mode that scored an average RPN value of 20 or greater was deemed "eligible" to be placed on the second checklist. In addition, any failure mode with a severity score value of 4 or greater was also considered for inclusion in the checklist. As a by-product of this procedure, safety improvement methods such as automation and standardization of certain processes (e.g., dose constraint checking, check tools), removal of manual transcription of treatment-related information as well as staff education were implemented, although this was not the team's original objective. Prior to the implementation of the new FMEA-based checklist, an in-service for all the second checkers was organized to ensure further standardization of the process. Conclusion: The FMEA proved to be a valuable tool for identifying vulnerabilities in our workflow and processes in generating a treatment plan and subsequently a new, more effective initial plan checklist was created.

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Purpose: In this study, patient setup accuracy was compared between surface guidance and tattoo markers for radiation therapy treatment sites of the thorax, abdomen and pelvis.Methods and materials: A total of 608 setups performed on 59 patients using both surface-guided and tattoo-based patient setups were analyzed. During treatment setup, patients were aligned to room lasers using their tattoos, and then the six-degree-of-freedom (6DOF) surface-guided offsets were calculated and recorded using AlignRT system. While the patient remained in the same post-tattoo setup position, target localization imaging (radiographic or ultrasound) was performed and these image-guided shifts were recorded. Finally, surface-guided vs tattoo-based offsets were compared to the final treatment position (based on radiographic or ultrasound imaging) to evaluate the accuracy of the two setup methods.Results: The overall average offsets of tattoo-based and surface-guidance-based patient setups were comparable within 3.2 mm in three principal directions, with offsets from tattoo-based setups being slightly less. The maximum offset for tattoo setups was 2.2 cm vs. 4.3 cm for surface-guidance setups. Larger offsets (ranging from 2.0 to 4.3 cm) were observed for surface-guided setups in 14/608 setups (2.3%). For these same cases, the maximum observed tattoo-based offset was 0.7 cm. Of the cases with larger surface-guided offsets, 13/14 were for abdominal/pelvic treatment sites. Additionally, larger rotations (>3°) were recorded in 18.6% of surface-guided setups. The majority of these larger rotations were observed for abdominal and pelvic sites (~84%).Conclusions: The small average differences observed between tattoo-based and surface-guidance-based patient setups confirm the general equivalence of the two potential methods, and the feasibility of tattooless patient setup. However, a significant number of larger surface-guided offsets (translational and rotational) were observed, especially in the abdominal and pelvic regions. These cases should be anticipated and contingency setup methods planned for.

A toolkit (BEUDcal) has been developed for evaluating the effectiveness and for predicting the outcome of treatment plans by calculating the biologically effective uniform dose (BEUD) and complication-free tumor control probability. The input for the BEUDcal is the differential dosevolume histograms of organs exported from the treatment planning system. A clinical database is built for the dose-response parameters of different tumors and normal tissues. Dose-response probabilities of all the examined organs are illustrated together with the corresponding BEUDs and the P + values. Furthermore, BEUDcal is able to generate a report that simultaneously presents the radiobiological evaluation together with the physical dose indices, showing the complementary relation between the physical and radiobiological treatment plan analysis performed by BEUDcal. Comparisons between treatment plans for helical tomotherapy and multileaf collimator-based intensity modulated radiotherapy of a lung patient were demonstrated to show the versatility of BEUDcal in the assessment and report of dose-response relations.

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