EviGUIDE-a tool for evidence-based decision making in image-guided adaptive brachytherapy for cervical cancer

被引:3
作者
Ecker, Stefan [1 ,5 ]
Kirisits, Christian [1 ]
Schmid, Maximilian [1 ]
Knoth, Johannes [1 ]
Heilemann, Gerd [1 ]
De Leeuw, Astrid [2 ]
Sturdza, Alina [1 ]
Kirchheiner, Kathrin [1 ]
Jensen, Nina [3 ]
Nout, Remi [4 ]
Juergenliemk-Schulz, Ina [2 ]
Poetter, Richard [1 ]
Spampinato, Sofia [3 ]
Tanderup, Kari [3 ]
Eder-Nesvacil, Nicole [1 ]
机构
[1] Med Univ Vienna, Vienna, Austria
[2] Univ Med Ctr Utrecht, Dept Radiat Oncol, Utrecht, Netherlands
[3] Aarhus Univ Hosp, Dept Oncol, Aarhus, Denmark
[4] Univ Med Ctr Rotterdam, Erasmus MC Canc Inst, Dept Radiotherapy, Rotterdam, Netherlands
[5] Med Univ Vienna, Dept Radiat Oncol, Wahringer Gurtel 18-20, A-1090 Vienna, Austria
基金
奥地利科学基金会;
关键词
Cervical cancer; IGABT; Decision support; Outcome prediction; WORKING GROUP; RISK-FACTORS; RADIOTHERAPY; RECOMMENDATIONS; PARAMETERS; PHYSICS; TERMS;
D O I
10.1016/j.radonc.2023.109748
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose: To develop a novel decision-support system for radiation oncology that incorporates clinical, treatment and outcome data, as well as outcome models from a large clinical trial on magnetic resonance image-guided adaptive brachytherapy (MR-IGABT) for locally advanced cervical cancer (LACC).Methods: A system, called EviGUIDE, was developed that combines dosimetric information from the treatment planning system, patient and treatment characteristics, and established tumor control proba-bility (TCP), and normal tissue complication probability (NTCP) models, to predict clinical outcome of radiotherapy treatment of LACC. Six Cox Proportional Hazards models based on data from 1341 patients of the EMBRACE-I study have been integrated. One TCP model for local tumor control, and five NTCP mod-els for OAR morbidities.Results: EviGUIDE incorporates TCP-NTCP graphs to help users visualize the clinical impact of different treatment plans and provides feedback on achievable doses based on a large reference population. It enables holistic assessment of the interplay between multiple clinical endpoints and tumour and treat-ment variables. Retrospective analysis of 45 patients treated with MR-IGABT showed that there exists a sub-cohort of patients (20%) with increased risk factors, that could greatly benefit from the quantitative and visual feedback.Conclusion: A novel digital concept was developed that can enhance clinical decision-making and facil-itate personalized treatment. It serves as a proof of concept for a new generation of decision support sys-tems in radiation oncology, which incorporate outcome models and high-quality reference data, and aids the dissemination of evidence-based knowledge about optimal treatment and serve as a blueprint for other sites in radiation oncology.& COPY; 2023 The Authors. Published by Elsevier B.V. Radiotherapy and Oncology 186 (2023) 109748 This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
引用
收藏
页数:9
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