Stephanie M. de Boer | Searcharxiv

arXiv2026

End-user validation of BRIGHT with custom-developed graphical user interface applied to cervical cancer brachytherapy

Multi-objective optimisation using BRIGHT has proven insightful and effective in prostate cancer brachytherapy treatment planning. BRachytherapy via artificially Intelligent GOMEA-Heuristic based Treatment planning (BRIGHT) generates multiple treatment plans, each with a different trade-off between tumour coverage and organs-at-risk sparing. BRIGHT was recently extended to cervical cancer brachytherapy. In this study, we present a novel, custom-developed graphical user interface (GUI) that enables plan navigation, pairwise comparisons, dose distribution visualisation, and possibility for adjustments - essential for efficient clinical use of BRIGHT. End-user validation of BRIGHT with the dedicated GUI was conducted for cervical cancer brachytherapy by emulating clinical practice in ten previously treated patients. A multidisciplinary brachytherapy team used BRIGHT to create new treatment plans. GUI usability was assessed using the System Usability Scale (SUS). BRIGHT plan quality was compared to clinical practice via blinded one-on-one comparisons. The GUI offered helpful features for plan navigation and evaluation, giving users quick insight into whether planning aims are achievable and what treatment options are available. The overall SUS score was 83.3, indicating an 'excellent' system. BRIGHT outperformed clinical practice in five out of ten patients regarding the coverage-sparing trade-off and performed equally well in the remaining five. The BRIGHT plan was preferred over the clinical plan in eight out of ten patients, four of which showed clinically relevant differences. The clinical plan was preferred in two patients, neither with clinically relevant differences. In conclusion, BRIGHT, with its dedicated GUI, is a clinically viable and user-friendly tool for treatment planning in cervical cancer brachytherapy.

cs.NE↗

arXiv2023

Bi-objective optimization of organ properties for the simulation of intracavitary brachytherapy applicator placement in cervical cancer

Validation of deformable image registration techniques is extremely important, but hard, especially when complex deformations or content mismatch are involved. These complex deformations and content mismatch, for example, occur after the placement of an applicator for brachytherapy for cervical cancer. Virtual phantoms could enable the creation of validation data sets with ground truth deformations that simulate the large deformations that occur between image acquisitions. However, the quality of the multi-organ Finite Element Method (FEM)-based simulations is dependent on the patient-specific external forces and mechanical properties assigned to the organs. A common approach to calibrate these simulation parameters is through optimization, finding the parameter settings that optimize the match between the outcome of the simulation and reality. When considering inherently simplified organ models, we hypothesize that the optimal deformations of one organ cannot be achieved with a single parameter setting without compromising the optimality of the deformation of the surrounding organs. This means that there will be a trade-off between the optimal deformations of adjacent organs, such as the vagina-uterus and bladder. This work therefore proposes and evaluates a multi-objective optimization approach where the trade-off between organ deformations can be assessed after optimization. We showcase what the extent of the trade-off looks like when bi-objectively optimizing the patient-specific mechanical properties and external forces of the vagina-uterus and bladder for FEM-based simulations.

physics.med-ph↗