ESTRO 2024 - Abstract Book

S361

Beachytherapy - Physics

ESTRO 2024

Keywords: Automated treatment planning, Cervical cancer

References:

[1] A. Bouter, T. Alderliesten, B.R. Pieters, A. Bel, Y. Niatsetski, and P.A.N. Bosman. GPU-accelerated bi-objective treatment planning for prostate high-dose-rate brachytherapy . Medical Physics 46(9), 3776–3787 (2019).

[2] D.L. Barten, B.R. Pieters, A. Bouter, M.C. van der Meer, S.C. Maree, K. Hinnen, H.G. Westerveld, P.A.N. Bosman, T. Alderliesten, N. van Wieringen, and A. Bel. Towards artificial intelligence-based automated treatment planning in clinical practice: A prospective study of the first clinical experience in high-dose-rate prostate brachytherapy . Brachytherapy 22(2), 279-289 (2023). [3] L.R.M. Dickhoff, E.M. Kerkhof, H.H. Deuzeman, C.L. Creutzberg, T. Alderliesten, and P.A.N. Bosman. Adaptive Objective Configuration in Bi-Objective Evolutionary Optimization for Cervical Cancer Brachytherapy Treatment Planning . In Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’22. Boston, MA, USA: ACM; 2022:1173-1181.

1695

Proffered Paper

Time-resolved analysis of clinical dose metrics for HDR brachytherapy error detection

Teun van Wagenberg, Gabriel P Fonseca, Robert Voncken, Maaike Berbee, Evert van Limbergen, Frank Verhaegen

Maastricht University Medical Center+, Department of Radiation Oncology (Maastro), GROW School for Oncology and Reproduction, Maastricht, Netherlands

Purpose/Objective:

Despite good clinical outcomes of high-dose rate brachytherapy treatments (HDRBT), there is currently no widespread solution to detect errors and verify the dose delivered to the patient. To solve this problem, new systems are being developed to track the source with submillimeter precision over the course of a treatment. Source tracking results are mostly reported as deviations from the planned source position (in millimeters) and dwell time (in seconds), however clinical impact is hard to quantify using just these metrics. For example, the dose difference caused by a catheter shift depends not just on the magnitude of the shift, but also on its location relative to the tumour and OARs, and the shape of these structures for a specific patient. This makes it difficult to set thresholds for intervention using distance and time as metric. Therefore, a dose calculation tool was implemented to calculate the delivered dose from the source tracking data in real-time. By calculating the dose after each dwell position, time-resolved information of the treatment progress is generated, making it possible to assess the contribution of each dwell towards the clinical parameters. The resulting data can be used to decide whether a delivered treatment is acceptable, and can predict if a treatment error will lead to an underdosage in the tumor before the treatment is fully finished.

Material/Methods: