Safety and Efficiency Analysis of Operational Decision-Making During Cone Beam Computed Tomography-Based Online Adaptive Radiation Therapy.

PURPOSE: Cone beam computed tomography (CBCT)-based online adaptive radiation therapy (ART) is especially beneficial for patients with large interfractional anatomic changes. However, treatment planning and review decisions need to be made at the treatment console in real-time and may be delegated to clinical staff whose conventional scope of practice does not include making such decisions. Therefore, implementation can create new safety risks and inefficiencies. The objective of this work is to systematically analyze the safety and efficiency implications of human decision-making during the treatment session for CBCT-based online ART. METHODS AND MATERIALS: The analysis was performed by applying the Systems-Theoretical Process Analysis technique and its extension for human decision-making. Four centers of different CBCT-based online ART practice models comprised the analysis team. RESULTS: The general radiation therapy control structure was refined to model the interactions between routine treatment delivery staff and in-person or remote support staff. The treatment delivery staff perform 6 key control actions. Eighteen undesirable states of those control actions were identified as affecting safety and/or efficiency. In turn, 97 hazardous clinical scenarios were identified, with the control action "prepare and position patient" having the least number of scenarios and "delineate/edit influencer and target structures" having the most. Five of these are specific to either in-person or remote support during the treatment session, and 12 arise from staff support in general. CONCLUSIONS: An optimally safe and efficient online ART program should require little to no support staff at the treatment console to reduce staff coordination. Uptraining of the staff already at the treatment console is needed to achieve this goal. Beyond the essential knowledge and skills such as contour editing and the selection of an optimal plan, uptraining should also target the specific cognitive biases identified in this work and the cognitive strategies to overcome these biases. Additionally, technological and organizational changes are necessary.

Cone-beam computed tomography-guided online adaptive radiotherapy is feasible for prostate cancer patients.

Background and purpose: Studies have shown the potential of cone-beam computed tomography (CBCT)-guided online adaptive radiotherapy (oART) for prostate cancer patients in a simulation environment. The aim of this study was to evaluate the feasibility of the clinical implementation of CBCT-guided oART for prostate cancer patients. Materials and methods: Between February and July 2020, eleven prostate cancer patients were treated with CBCT-guided oART using a fractionation scheme of 20 × 3 Gy to the prostate and 20 × 2.7/3.0 Gy to the seminal vesicles for more advanced stages. The on-couch adaptive workflow consisted of influencer (prostate, seminal vesicles, rectum, bladder) review, target review, scheduled (re-calculated) and adapted (re-optimized) plan generation, an independent QA procedure and treatment delivery. Treatment time, proportion of adapted fractions and reasons for plan adaptation were evaluated. Results: Mean total treatment time (±SD) from CBCT acquisition to end of treatment delivery was 17.5 ±â€¯3.2 min (range: 10.8-28.8 min). In all 220 fractions, the PTV coverage was increased for the adapted plan compared to the scheduled plan. The V60Gy of bladder and rectum were below the constraints (<5% and <3%) for both scheduled and adapted plans in 171 out of 220 fractions and for the adapted plan only in 30 out of 220 fractions. In 19 out of 220 fractions, the V60Gy of the bladder and/or rectum was above the constraint for the adapted plan. Conclusions: The clinical implementation of CBCT-guided oART is feasible for prostate cancer patients. The adaptive workflow is possible within twenty minutes on average with a dedicated team.