TY - JOUR
T1 - Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?
AU - Jain, Jeevanshu
AU - Serban, Monica
AU - Assenholt, Marianne Sanggaard
AU - Hande, Varsha
AU - Swamidas, Jamema
AU - Seppenwoolde, Yvette
AU - Alfieri, Joanne
AU - Tanderup, Kari
AU - Chopra, Supriya
N1 - Publisher Copyright: © 2024 Elsevier B.V.
PY - 2025/3
Y1 - 2025/3
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85215552416&partnerID=8YFLogxK
U2 - 10.1016/j.radonc.2024.110694
DO - 10.1016/j.radonc.2024.110694
M3 - Article
C2 - 39709028
AN - SCOPUS:85215552416
SN - 0167-8140
VL - 204
JO - Radiotherapy and Oncology
JF - Radiotherapy and Oncology
M1 - 110694
ER -