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Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning

Overview of attention for article published in Radiation and Environmental Biophysics, March 2023
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Title
Improving normal tissue sparing using scripting in endometrial cancer radiation therapy planning
Published in
Radiation and Environmental Biophysics, March 2023
DOI 10.1007/s00411-023-01019-2
Pubmed ID
Authors

Yagiz Yedekci, Melis Gültekin, Sezin Yuce Sari, Ferah Yildiz

Abstract

The aim of this study was to improve the protection of organs at risk (OARs), decrease the total planning time and maintain sufficient target doses using scripting endometrial cancer external beam radiation therapy (EBRT) planning. Computed tomography (CT) data of 14 endometrial cancer patients were included in this study. Manual and automatic planning with scripting were performed for each CT. Scripts were created in the RayStation™ (RaySearch Laboratories AB, Stockholm, Sweden) planning system using a Python code. In scripting, seven additional contours were automatically created to reduce the OAR doses. The scripted and manual plans were compared to each other in terms of planning time, dose-volume histogram (DVH) parameters, and total monitor unit (MU) values. While the mean total planning time for manual planning was 368 ± 8 s, it was only 55 ± 2 s for the automatic planning with scripting (p < 0.001). The mean doses of OARs decreased with automatic planning (p < 0.001). In addition, the maximum doses (D2% and D1%) for bilateral femoral heads and the rectum were significantly reduced. It was observed that the total MU value increased from 1146 ± 126 (manual planning) to 1369 ± 95 (scripted planning). It is concluded that scripted planning has significant time and dosimetric advantages over manual planning for endometrial cancer EBRT planning.

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Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 1 50%
Unknown 1 50%
Readers by discipline Count As %
Medicine and Dentistry 1 50%
Unknown 1 50%