Practice-based Training Strategy for Therapist-Driven Prostate MR-Linac Adaptive Radiotherapy
MO-0146
Abstract
Practice-based Training Strategy for Therapist-Driven Prostate MR-Linac Adaptive Radiotherapy
Authors: Winnie Li1, Patricia Lindsay1, Jerusha Padayachee1, Inmaculada Navarro1, Jeff Winter1, Jennifer Dang1, Srinivas Raman1, Vickie Kong1, Alejandro Berlin1, Charles Catton1, Rachel Glicksman1, Victor Malkov1, Kaushik Kataki1, Peter Chung1
1Princess Margaret Cancer Centre, Radiation Oncology, Toronto, Canada
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Purpose or Objective
Online adaptive MR-guided radiotherapy is resource intensive, requiring a team of radiation therapists (RTs), medical physicists (MPs), and radiation oncologists (ROs) for each fraction. Implementation of a new treatment paradigm offers the opportunity to evaluate roles for each member of the multidisciplinary team, and optimize the use of each skillset to maximize efficiency. Here we report a three phase practice-based training strategy developed to transition from RO-driven contouring to RT-driven contouring for whole gland prostate MR-Linac radiotherapy to maximize resource efficiency.
Material and Methods
In Phase One, seven MR-Linac RTs independently contoured the target and organs-at-risk on T2-weighted MR images from 11 previously treated MR-Linac prostate patients. The case mix was chosen to ensure a broad representation of differing patient anatomy. The Dice similarity coefficient (DSC) was calculated against contours RO generated during the online session. The RO also performed a qualitative contour review of the RT-generated contours using a 5 point Likert scale; a score of 4 or 5 was deemed a pass, and a 90% pass rate was required for Phase One. Phase Two involved RO supervised online contouring, plan generation and assessment during adaptive treatment fractions, with participants requiring a score of autonomy (no direction required by RO) on 10 cases (minimum 8 patients) to advance. The final phase of training involved independent RT-driven contouring and planning, supported by offline contour and plan review by RO prior to the next fraction.
Results
In Phase One, the mean DSC was 0.916 (range 0.847-0.966) for prostate, 0.895 (range 0.645-0.99) for bladder, and 0.981 (range 0.962-0.998) for rectum. Mean Likert scores for the prostate was 3.7 (range 3-4), the bladder was 4.1 (range 3.7-4.6), and the rectum was 4.3 (range 3.6-4.7). Qualitative prostate contour differences included under-delineation at the base, and variation at the apex. Five RTs did not attain a pass rate of 90%, attended follow-up one-on-one review, and subsequently performed additional contours on a further training set of cases (n=5). Each participant completed a median of 12 (range 10 – 13) cases in Phase Two. Minor direction were required from the RO on 5 cases related to target contouring (contour shape, and contour variability at the rectum prostate interface, prostate base, and prostate apex). ROs reviewed 179 treatment fractions in Phase Three over 5 months; 5 cases were marked acceptable but with suggestions for next fraction (4 involved contours, 1 the adapted plan), all other cases were deemed acceptable.
Conclusion
A training strategy was developed to enable a RT-driven workflow for prostate adaptive radiotherapy for MR-Linac treatment. This model may be adapted for other anatomical sites to maximize efficiencies for MR-Linac radiotherapy.