Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?
- PMID: 39709028
- DOI: 10.1016/j.radonc.2024.110694
Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?
Abstract
Background and purpose: Knowledge-based planning (KBP) can consistently and efficiently create high-quality Volumetric Arc Therapy (VMAT) plans for cervix cancer. This study describes the cross-validation of two KBP models on geographically distinct populations and their comparison to manual plans from 67 centers. The purpose was to determine the universal applicability of a generic KBP model.
Materials and methods: Based on the EMBRACE-II protocol, two KBP models were developed at Tata Memorial Centre, India and Aarhus University Hospital, Denmark using respective patient plans. The KBP models were exchanged between three institutions with different geo-ethnic populations and validated on reference manual plans of 20 node-positive and 20 node-negative patients. Additionally, one patient case was manually planned by 67 centres. These manual treatment plans were compared to the two KBP model plans using a score out of 80, based on 20 DVH parameters.
Results: The manual and the KBP plans adhered to the EMBRACE II protocol. OAR sparing in KBP plans was similar or slightly improved as compared to the manual plans. The differences between the medians of manual and either KBP model plans were significant for 8 parameters among node positive patients, and 4 parameters among node negative patients. The comparison between the Tata and Aarhus KBP model plans to manual plans from 67 institutions showed that the two KPBs had superior plan quality in 88-99% of instances.
Conclusion: KBP has the potential to generate high-quality plans across institutions and geo-ethnic populations by reducing inter-planner variation, thereby facilitating the global standardisation of radiotherapy for cervical cancer.
Keywords: Automated EBRT Planning; Intensity-modulated radiation therapy (IMRT); Knowledge-based planning; Radiotherapy; Uterine cervical neoplasms.
Copyright © 2024 Elsevier B.V. All rights reserved.
Conflict of interest statement
Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Supriya Chopra and Kari Tanderup receive funding from Varian Medical Systems.
