Related Experiment Video
Updated: Jan 7, 2026
Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
Published on: October 6, 2023
Streamlined data extraction and visualization utilizing third-party verification software for online adaptive
Sean Tanny1, Alexander Podgorsak1, Nicholas Sperling2
1Department of Radiation Oncology, University of Rochester Medical Center, New York, New York, USA.
Purpose:
Online adaptive radiation therapy (oART) has generated a significant influx of daily treatment planning data. Present oART platforms have leveraged automation for decreased planning times at the expense of end-user access, making longitudinal oART data assessment time consuming. We have developed modified software that extracts oART data from the secondary calculation software associated with one of the oART platforms.
Methods:
A Python program was developed to query oART data from a web-based secondary dose calculation software. Structure, plan, and dosimetric data were collected for all generated oART plans over the course of 3 years. This software stores data in a Pandas dataframe to allow for comparisons and advanced visualization. The software includes some pre-defined visualization and analysis methods, as well as tools to de-identify and share cohorts of oART data.
Results:
Twelve hundred oART sessions were pulled from our secondary dose verification software. Various visualization methods were implemented and are demonstrated in this technical note. This software demonstrated significant time savings in data extraction compared to manual session exports, but does not pull raw DICOM information, such as CT scans, structure sets, or dose files.
Conclusion:
Our extraction software presents a streamlined way to collect, analyze, and visualize oART data using a dedicated oART platform. Further tools are needed to improve access and analysis of oART data.
