Implementation of an automated diagnostic display quality assurance program

The diagnostic accuracy of medical imaging is critically dependent on the performance of primary diagnostic displays. However, quality assurance (QA) programs for these displays are often limited by geographic dispersion, manual testing requirements, and inconsistent calibration practices. This study evaluates the implementation of a centralised, automated QA program aligned with AAPM Task Group 270 (TG-270) recommendations across a large health service. A four-stage process was used to assess and improve the performance of 53 diagnostic displays. This included baseline QC evaluation, internal photometer and ambient light sensor accuracy testing, implementation of a cloud-based automated QC system, and post-intervention performance testing. Internal photometers were cross-calibrated using a traceable external photometer. Initial testing revealed that 53% (28/53) of internal photometers exhibited errors >10% relative to a calibrated external photometer. As found, 67% (30/45) of connected displays reported meeting their existing QC tolerances; however, after cross-calibrating the internal photometers and repeating the same tests, only 9% (4/45) actually met those tolerances, indicating that most displays had been falsely reporting compliance. After implementing the automated program with recalibrated sensors and updated TG-270-aligned tolerances, 68% (36/53) of displays met the updated tolerances. Displays failing to meet luminance requirements were found to have high cumulative use hours, highlighting the need for lifecycle management. Automated QA systems significantly improve diagnostic display performance when combined with validated calibration protocols. Internal photometers require periodic cross-calibration to ensure reliable self-assessment. These findings support the adoption of centralised, standards-based QA programs to enhance diagnostic confidence and operational efficiency and highlight the need for defined cross-calibration intervals as part of ongoing program maintenance.