Practice-based training strategy for therapist-driven prostate MR-Linac adaptive radiotherapy.

Area of Science:

• Medical Physics
• Radiation Oncology
• Medical Imaging

Background:

• Adaptive radiotherapy (ART) is crucial for optimizing treatment accuracy.
• Magnetic Resonance-Linear Accelerator (MR-Linac) technology enables real-time imaging for ART.
• Transitioning to therapist-driven workflows can improve efficiency in MR-Linac procedures.

Purpose of the Study:

• To develop and implement a practice-based training strategy for therapists.
• To facilitate a transition from radiation oncologist to therapist-driven prostate MR-Linac ART.
• To establish a sustainable model for autonomous therapist-led adaptive treatments.

Main Methods:

• A phased training approach was designed, starting with independent contouring and progressing to supervised and unsupervised workflows.
• Therapists contoured prostate and organs-at-risk on MR images, evaluated by Dice Similarity Coefficient (DSC) and Likert scores.
• Performance benchmarks (e.g., 90% pass rate) were set for progression through training phases.

Main Results:

• Phase 1 demonstrated high contouring accuracy (mean DSC 0.92) with minor remediation needed for some therapists.
• Phase 2 showed successful supervised online workflow with minimal oncologist intervention.
• Phase 3 confirmed feasibility of unsupervised therapist-driven workflow with high acceptance rates of treatment fractions.

Conclusions:

• A stepwise training program effectively enabled therapist-driven adaptive radiotherapy for prostate cancer on MR-Linac.
• The developed strategy supports a successful transition to autonomous therapist-led ART.
• This approach has the potential to enhance the efficiency and scalability of MR-Linac treatments.