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Program Information

Automating the Chart Rounds: Features and Functionality of a Software Designed for Peer-Review of Radiotherapy Treatments


E Schreibmann

E Schreibmann*, E Elder, Department of Radiation Oncology and Winship Cancer Institute of Emory University, Atlanta, GA

Presentations

TU-FG-702-4 (Tuesday, August 1, 2017) 1:45 PM - 3:45 PM Room: 702


Purpose: To minimize time for chart reviews during chart rounds, we developed customized software using artificial intelligence to streamline this task.

Methods: The initial design was to create a software having the ability to browse images, contours, and dose without having to wait for them to load from the clinical database. To further speed-up the review process without compromising review accuracy, we have implemented a set of automated verifications of the charts. Plan metrics are checked automatically against the prescription to flag inaccuracies. Segmented contours of critical structures are validated against a statistical shape model learned from approved segmentations. The patient’s segmentatons are also used to predict achievable doses for critical structures. The software uses Eclipse scripting to integrate these algorithms with the clinical planning system as well as an independent tool written in C++ and VTK to visualize the cases during chart review meetings.

Results: The software has been used clinically since November 2016 for chart rounds teleconferences of the main site and 3 satellites at Emory, employing both Elekta and Varian LINAC Systems, and across a wide variety of physician preferences and treatment techniques that are seamlessly integrated with the software. Interaction with the software is designed for understanding treatment features at a glance and minimizing review time with features such as datasets being loaded in parallel with displaying the automated check results.

Conclusion: Our department developed customized software tailored to the needs of reviewing lists of patients in minimal times. The software employs advanced artificial intelligence modules to check the prescription, structures and dosimetric indices against inaccuracies resulting in a quality assurance platform that streamlines the chart rounds reviews process.


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