Python-Based Automation Framework for Annual Machine QA Data Archiving In Qatrack+
Abstract
Purpose
Annual water-tank measurements help ensure beam characteristics remain consistent with commissioning baselines. However, the lack of a standardized processing workflow and decentralized data storage makes it difficult to analyze inter-LINAC and intra-LINAC temporal data trends. This project aimed to standardize data handling, centralize annual beam-scan results in QATrack+, and implement automated data entry.
Methods
All PDD and profile data were acquired using a 48×48×48 cm³ IBA blue water phantom and myQA Accept software (version_8.5, IBA, Germany). To standardize the input for QATrack+ (v0.3.0.14), all datasets were preprocessed using predefined normalization, central-axis correction, and data smoothing settings, in myQA Accept and then exported as *.csv files. Numerical parameters, defining beam characteristics, were selected from the list of numerical values reported by myQA Accept. A total of 25 parameters were chosen for 6 MV and 15 MV beams, 57 for 6 FFF, and 30 for each electron energy. A Python (v3.12.5) script was written to parse the *.csv file and calculate the beam characteristic parameters independently and automatically populate the relevant QATrack+ fields. The user is only required to upload the *.csv in QATrack+ and the rest is done by the script.
Results
Automated data entry into QATrack+ provided an efficient and a consolidated platform for reviewing temporal data trends across all linacs. The stored numerical data from QATrack+ can also be exported to enable additional statistical analysis and data visualization options.
Conclusion
This project established a standardized and automated system for processing and recording annual water-tank data. Centralizing beam parameters in QATrack+ improves accessibility, consistency, and the ability to visualize and compare trends across machines. The workflow also supports the development of site-specific tolerance values. Overall, this work enhances the efficiency and reliability of the Annual QA program and contributes to maintaining the safety and quality of radiation treatments.