S2871
RTT - RTT education, training, and advanced practice
ESTRO 2026
indicate fewer workload anomalies on critical days and faster identification of optimal treatment configurations. Conclusion: The introduction of an automated optimisation module demonstrates promising potential for improving radiotherapy scheduling in environments with heterogeneous treatment machines. Preliminary results suggest a notable reduction in operational workload and enhanced stability in treatment-room utilisation. Next steps include completing the testing phase, validating parameters over a longer observation period, and quantifying the overall impact on service efficiency. Keywords: Scheduling, automated, optimization A comparison of clinical outcomes at 1 year from Oncologist vs Therapist-led MRI-guided ultra-hypo- fractionated, adaptive prostate radiation therapy Amanda Moreira 1 , Tara Rosewall 1,2 , Jennifer Dang 1 , Aran Kim 1 , Jeff Winter 1,2 , Winnie Li 1,2 , Peter Chung 1,2 1 Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Canada. 2 Department of Radiation Oncology, University of Toronto, Toronto, Canada Purpose/Objective: A key barrier to widespread MRI-guided adaptive radiation therapy (ART) is the need for daily radiation oncologist (RO)-led re-contouring and re-optimization. This has been addressed for prostate ART through radiation therapist (RTT)-led workflows. This study evaluated the impact on toxicity and outcomes between RO- and RTT-led prostate treatment in an ART program. Material/Methods: Proffered Paper 3014 All intermediate risk prostate ART patients treated on a 1.5T MR-Linac were retrospectively reviewed and grouped by workflow into consecutive cohorts: RO-led (September 2019 – November 2021) and RTT-led (April 2022 – October 2023), with a break during training and handover. All patients were treated with 25 – 42.7 Gy in 5 – 7 alternate day fractions, 9-field IMRT using adapt to shape (ATS) workflow. Patients with 30Gy or less also received brachytherapy prior to EBRT. The clinical target volume (CTV) included the prostate and any extracapsular or seminal vesicle extension. PTV margins were 5mm (all RO-led), 5mm (RT-led 25-30Gy) or 4mm (3mm left-right) (RTT-led 42.7Gy). Clinical outcomes were assessed using the Phoenix definition of BRFS at 12-months. Toxicity was quantified prospectively using CTCAE v3.0. Mean doses for each cohort PTV, bladder, urethra and rectum were summarized from summation of the adapted plan
The integrated PET/4DCT protocol enables acquisition of both diagnostic and respiratory motion-managed CT images in a single session. This approach maintains image quality, improves patient experience, and significantly reduces resource use in the Radiation Therapy Department without additional workload for the Nuclear Medicine Department. Keywords: Resource optimisation, 4DCT, PET/CT Digital Poster 3006 Automated Optimization Module for Radiotherapy Scheduling in Multi-LINAC Departments Sandro Spinosa, Marco De Summa, Stefania Fusaro Dipartimento di diagnostica per Immagini e Radioterapia Oncologica, Medipass, Rome, Italy Purpose/Objective: The aim of this project is to develop and evaluate an automated optimisation module designed to streamline scheduling workflows in radiotherapy departments equipped with multiple LINACs with heterogeneous capabilities, treatment types, and session durations. The module seeks to reduce variability in treatment-room workload, improve the distribution of treatment starts and completions, and decrease the manual effort currently required from staff managing daily agendas. Material/Methods: The optimisation module applies operations-research techniques and dedicated algorithms to automatically propose simulation and treatment dates, taking into account room configurations, working hours, planned downtimes, treatment type and duration, urgency category, and reimbursement regime.Our centre operates five LINACs with differing technical characteristics and treatment offerings. The current project phase focuses on integration with existing scheduling tools and departmental information systems. Internal testing compares the existing manual Excel-based workflow with the automated approach. Evaluation metrics include: time required to generate weekly schedules, weekly variability in room workload, reduction of overload/underload anomalies, and acceptance rate of automated proposals by clinicians. Results: Initial testing shows that the algorithmic module generates scheduling proposals consistent with clinical and technical constraints while substantially reducing manual intervention. A more balanced distribution of treatment starts has been observed, with reduced week-to-week fluctuations and improved workload stability across the LINACs. The average time needed to prepare a weekly schedule has already decreased compared to the manual method. Early data also
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