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Clinical Validation of An Automated Treatment Error Detection Software for Radiation Therapy

S Yaddanapudi1*, D Wang1 , Y Kim1 , J Xia2 , (1) University of Iowa, Iowa City, IA, (2) Mount Sinai Medical Center, New York, NY

Presentations

(Wednesday, 7/17/2019) 8:30 AM - 9:30 AM

Room: Stars at Night Ballroom 2-3

Purpose: To evaluate the clinical efficacy of utilizing an automated treatment error detection software to perform weekly physics chart checks.

Methods: An in-house developed web-based software tool (ChartAlert) was utilized to detect abnormal treatment events during weekly physics chart check. The software tool analyzes the treatment records to perform checks according to predefined rules, and the results are presented in a color-coded format. Users can review the report and takes appropriate action. ChartAlert utilizes checking rules to check the consistency of different treatment parameters such as MLC leaves positions, dose, couch positions, gantry/collimator override, and prescription change etc. ChartAlert also provides an interface to visually inspect the couch position inconsistencies for a patient. The software also analyzes the couch shifts after imaging and can alert the user of any discrepancies. 4 medical physicists participated in a study for using ChartAlert during the weekly physics chart check and evaluated its clinical efficacy by comparing the manual check results with the automated checks.

Results: Over a 3-month study period, ChartAlert was used for weekly physics chart check. 285 patients for a total of 2161 treated fractions were checked using the software tool. For each patient treatment, 12 different rules were checked and the true positive/negative along with the false positive/negative events were reported. Utilizing the web-based software tool (ChartAlert), we found that the accuracy of detected events was 99.98%.

Conclusion: The web-based software tool (ChartAlert) provides an automated and efficient method to detect and report treatment events.

Funding Support, Disclosures, and Conflict of Interest: Junyi Xia is the co-founder of Infondrian LLC

Keywords

Quality Assurance, Radiation Therapy

Taxonomy

TH- External beam- photons: Development (new technology and techniques)

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