ESTRO 2024 - Abstract Book

S2903

Interdiscplinary - Other

ESTRO 2024

This study showed how in-silico biological models allow us to study the impact of varying thermal conditions on the HT+RT treatment outcome. This can be used to optimize HT treatments, design clinical trials, and help interpret of patient data.

Keywords: TCP, Hyperthermia, Biological Modeling

References:

[1] van Leeuwen CM, Oei AL, ten Cate R, et al. Measurement and analysis of the impact of time-interval, temperature and radiation dose on tumour cell survival and its application in thermoradiotherapy plan evaluation. Int J Hyperth. 2018;34:30–38. https://doi.org/10.1080/02656736.2017.1320812.

1308

Digital Poster

Custom-made dose management system for planning CTs in radiotherapy - a tool for defining local DRLs

Anna Sophie Duque, Zaira Katsilieri, Judit Alvarez, Christian Gröger, Barbara Dobler

University Hospital Regensburg, Radiotherapy, Regensburg, Germany

Purpose/Objective:

Article 122 of the German Radiation Protection Ordinance [1] states that every patient exposition to ionising radiation must be recorded and evaluated, on the basis of dose reference levels (DRLs). Whilst there are national diagnostic DRLs (dDRLs) for CT in Germany, this is not the case for planning CT acquisitions in radiotherapy. It is recommended to establish local DRLs for individual institutions using a dose management system (DMS). At the radiotherapy department of the Universitätsklinikum Regensburg (UKR) a DMS was created, and local DRLs were defined.

Material/Methods:

All CT acquisitions were performed at the Aquilion large-bore CT scanner by Canon used for treatment planning at the department of radiotherapy at the UKR. For dosimetric evaluation, the custom-made software PyCT was developed. The software reads Radiation Dose Structured Reports (RDSRs) generated by the CT scanner and extracts patient-specific data such as patient ID, name, etc. as well as dosimetric data such as scanning protocol, Computed Tomography Dose Index (CTDI), scan length etc. The data is stored in an SQLite database and can be viewed in a table (see fig. 1), filtered, analysed and displayed in graphs and charts (see fig.2).