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

Authors :
Winnie Li
Jerusha Padayachee
Inmaculada Navarro
Jeff Winter
Jennifer Dang
Srinivas Raman
Vickie Kong
Alejandro Berlin
Charles Catton
Rachel Glicksman
Victor Malkov
Andrew McPartlin
Kaushik Kataki
Patricia Lindsay
Peter Chung
Source :
Technical Innovations & Patient Support in Radiation Oncology, Vol 27, Iss , Pp 100212- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Purpose: To develop a practice-based training strategy to transition from radiation oncologist to therapist-driven prostate MR-Linac adaptive radiotherapy. Methods and materials: In phase 1, 7 therapists independently contoured the prostate and organs-at-risk on T2-weighted MR images from 11 previously treated MR-Linac prostate patients. Contours were evaluated quantitatively (i.e. Dice similarity coefficient [DSC] calculated against oncologist generated online contours) and qualitatively (i.e. oncologist using a 5-point Likert scale; a score ≥ 4 was deemed a pass, a 90% pass rate was required to proceed to the next phase). Phase 2 consisted of supervised online workflow with therapists required no intervention from the oncologist on 10 total cases to advance. Phase 3 involved unsupervised therapist-driven workflow, with offline support from oncologists prior to the next fraction. Results: In phase 1, the mean DSC was 0.92 (range 0.85–0.97), and mean Likert score was 3.7 for the prostate. Five therapists did not attain a pass rate (3–5 cases with prostate contour score

Details

Language :
English
ISSN :
24056324
Volume :
27
Issue :
100212-
Database :
Directory of Open Access Journals
Journal :
Technical Innovations & Patient Support in Radiation Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.1e33595fa04040b78897c5a677b23b08
Document Type :
article
Full Text :
https://doi.org/10.1016/j.tipsro.2023.100212