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Related Experiment Video

Updated: Nov 16, 2025

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Radiotherapy treatment scheduling: Implementing operations research into clinical practice.

Bruno Vieira1,2, Derya Demirtas2,3, Jeroen B van de Kamer1

  • 1Department of Radiation Oncology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands.

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Summary

This study optimized radiotherapy treatment scheduling using an operations research model. The automated approach significantly reduced scheduling time and improved efficiency, demonstrating practical implementation of advanced logistics in cancer care.

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Area of Science:

  • Operations Research
  • Medical Physics
  • Health Informatics

Background:

  • Radiotherapy centers face challenges scheduling patient treatments on linear accelerators due to increasing cancer patient numbers.
  • Manual scheduling is time-consuming and often inefficient, despite the growing need for optimized patient care logistics.
  • There is limited evidence of operations research models being implemented in clinical practice for radiotherapy scheduling.

Purpose of the Study:

  • To adapt and implement a mathematical operations research model for generating radiotherapy treatment schedules in two Dutch centers.
  • To assess the feasibility and efficiency of the optimized schedules compared to manually developed ones.
  • To demonstrate the practical application of operations research in clinical radiotherapy planning.

Main Methods:

  • Adapted a mathematical operations research model to meet specific technical and medical constraints of two radiotherapy centers.
  • Collected patient data for a one-week planning horizon and verified schedule feasibility with center staff.
  • Compared optimized schedules generated by the model with existing manually created schedules.

Main Results:

  • Achieved a 51% decrease in the average standard deviation of session start times and a 72% reduction in schedule gaps in one center.
  • Reduced patient linac switching from 71 to 0 in one center and 43 to 2 in the other.
  • Automated scheduling required 5 minutes to 1.5 hours of computation time, compared to approximately 1.5 days for manual scheduling.

Conclusions:

  • Successfully implemented a theoretical operations research model into clinical practice for radiotherapy treatment scheduling.
  • Demonstrated that iterative model adaptations, stakeholder engagement, and communication facilitate the adoption of operations research in healthcare.
  • The automated approach provides feasible, high-quality schedules, improving efficiency for radiotherapy planners.