Room: Stars at Night Ballroom 4
Radiation therapy is a complex process involving many sophisticated human-machine interactions, advanced technology, and decision making steps that must be repeated many times per day. Due to this high level of complexity, technological failure or human error can readily occur, resulting in patient injury. It is therefore important that quality assurance (QA) mechanisms are in place to avoid such incidences. Currently, many of these QA tests are manual in nature and require multiple instances of data collection and analysis. With recent advances in modern digital LINAC technology, data management, and machine learning methods these procedures can be autonomously operated through pre-programming. This leads to the possibility of implementing streamlined and automated methods for completing QA tests in a manner that is more accurate, efficient and comprehensive than human workers.
This session will cover recent advances in several areas of QA for radiation therapy. Topics will include autonomous QA for digital LINAC technology, semi-automate electronic chart checking systems, and QA protocol generation and data management.
Learning Objectives:
1. Understand the advantages and feasibility of autonomous QA for digital LINACs and the issues relative to the clinical implementation of autonomous QA.
2. Understand that automated physics software tools can be useful to detect errors, to improve patient safety and to improve workflow efficiency.
3. Understand how peer collaboration can be used for implementing QA protocols that help promote patient safety and data standardization.
Funding Support, Disclosures, and Conflict of Interest: Parts of the presented work have been licensed to Luca Medical Systems of which Rodney D. Wiersma is a founder.
Not Applicable / None Entered.
Not Applicable / None Entered.