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

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 probability (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.

Tools for large-scale data analytics of an international multi-center study in radiation oncology for cervical cancer.

Purpose: To develop and implement a software that enables centers, treating patients with state-of-the-art radiation oncology, to compare their patient, treatment, and outcome data to a reference cohort, and to assess the quality of their treatment approach.

Materials And Methods: A comprehensive data dashboard was designed, which al- lowed holistic assessment of institutional treatment approaches. The software was tested in the ongoing EMBRACE-II study for locally advanced cervical cancer.

Risk Factors for Local Failure Following Chemoradiation and Magnetic Resonance Image-Guided Brachytherapy in Locally Advanced Cervical Cancer: Results From the EMBRACE-I Study.

Purpose: To report clinical and treatment characteristics, remission and failure patterns, and risk factors for local failure (LF) from the EMBRACE-I study.

Materials And Methods: EMBRACE-I was a prospective, observational, multicenter cohort study on magnetic resonance imaging-based image-guided adaptive brachytherapy (MR-IGABT) in locally advanced cervical cancer. Treatment consisted of external beam radiotherapy, concurrent chemotherapy, and MR-IGABT.

Neural network-assisted automated image registration for MRI-guided adaptive brachytherapy in cervical cancer.

Purpose: In image-guided adaptive brachytherapy (IGABT) a quantitative evaluation of the dosimetric changes between fractions due to anatomical variations, can be implemented via rigid registration of images from subsequent fractions based on the applicator as a reference structure. With available treatment planning systems (TPS), this is a manual and time-consuming process. The aim of this retrospective study was to automate this process.

Evidence-Based Dose Planning Aims and Dose Prescription in Image-Guided Brachytherapy Combined With Radiochemotherapy in Locally Advanced Cervical Cancer.

The last 2 decades have witnessed the development and broad adoption of image-guided adaptive brachytherapy (IGABT) combined with radiochemotherapy in patients with locally advanced cervical cancer. A variety of brachytherapy techniques and dose/fractionation schedules have been applied, and until recently, there was no strong evidence available for preferring one approach to another. However, large volumes of data have now provided high level clinical evidence for dose-effect relations for both disease and morbidity endpoints.

Education and training for image-guided adaptive brachytherapy for cervix cancer-The (GEC)-ESTRO/EMBRACE perspective.

Image-guided adaptive brachytherapy (IGABT) has been shown to improve local/regional control and survival for cervix cancer patients while reducing morbidity. However, the technique is complex involving several conceptual, methodological, and technical innovations compared to conventional brachytherapy. The delivery of high-quality IGABT which will translate into improved outcomes is therefore critically dependent on effective education and training of all health professionals involved in the brachytherapy treatment process.