Browse by author
Lookup NU author(s): Nick West, Dr Rachel Pearson
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2024.Background: Current automated planning solutions are calibrated using trial and error or machine learning on historical datasets. Neither method allows for the intuitive exploration of differing trade-off options during calibration, which may aid in ensuring automated solutions align with clinical preference. Pareto navigation provides this functionality and offers a potential calibration alternative. The purpose of this study was to validate an automated radiotherapy planning solution with a novel multi-dimensional Pareto navigation calibration interface across two external institutions for prostate cancer. Methods: The implemented ‘Pareto Guided Automated Planning’ (PGAP) methodology was developed in RayStation using scripting and consisted of a Pareto navigation calibration interface built upon a ‘Protocol Based Automatic Iterative Optimisation’ planning framework. 30 previous patients were randomly selected by each institution (IA and IB), 10 for calibration and 20 for validation. Utilising the Pareto navigation interface automated protocols were calibrated to the institutions’ clinical preferences. A single automated plan (VMATAuto) was generated for each validation patient with plan quality compared against the previously treated clinical plan (VMATClinical) both quantitatively, using a range of DVH metrics, and qualitatively through blind review at the external institution. Results: PGAP led to marked improvements across the majority of rectal dose metrics, with Dmean reduced by 3.7 Gy and 1.8 Gy for IA and IB respectively (p < 0.001). For bladder, results were mixed with low and intermediate dose metrics reduced for IB but increased for IA. Differences, whilst statistically significant (p < 0.05) were small and not considered clinically relevant. The reduction in rectum dose was not at the expense of PTV coverage (D98% was generally improved with VMATAuto), but was somewhat detrimental to PTV conformality. The prioritisation of rectum over conformality was however aligned with preferences expressed during calibration and was a key driver in both institutions demonstrating a clear preference towards VMATAuto, with 31/40 considered superior to VMATClinical upon blind review. Conclusions: PGAP enabled intuitive adaptation of automated protocols to an institution’s planning aims and yielded plans more congruent with the institution’s clinical preference than the locally produced manual clinical plans.
Author(s): Wheeler PA, West NS, Powis R, Maggs R, Chu M, Pearson RA, Willis N, Kurec B, Reed KL, Lewis DG, Staffurth J, Spezi E, Millin AE
Publication type: Article
Publication status: Published
Journal: Radiation Oncology
Year: 2024
Volume: 19
Issue: 1
Online publication date: 08/04/2024
Acceptance date: 15/01/2024
Date deposited: 18/04/2024
ISSN (electronic): 1748-717X
Publisher: BioMed Central Ltd
URL: https://doi.org/10.1186/s13014-024-02404-x
DOI: 10.1186/s13014-024-02404-x
Altmetrics provided by Altmetric
