A holistic approach for consistent image quality and dose in digital radiography in a large imaging enterprise

Although radiography is individually low dose, the population dose is a concern; therefore, it is important to achieve consistent dose and image quality. A large institution has significant challenges of verification; vast data collection, timely data auditing, and effective intervention across diverse imaging centers, equipment, and anatomy. This study presents a novel, decade-long approach addressing these challenges in high-volume digital radiography (DR) and the clinical impact.

Reject rate and average EI per user/protocol were chosen as performance metrics. An in-house, semiautomated system - utilizing remote software, shared network drives, and manual extraction - was developed to streamline exposure record collection from 68 DR systems from five major manufacturers at multiple facilities. Custom scripts automated dataset aggregation for monthly analysis and review of metrics, incorporating root-cause analysis for individual technologist reject rates exceeding 7% or EI + 100 relative to EI_target 225.

50,000 DR exposures were analyzed monthly to determine average reject rates and EI for 200 technologists. Since 2011, the mean reject rate was lowered from 14% to 2.5% and the median EI from 350 to 220. Median EI for specific high-impact torso protocols decreased by 50-60%. Interventions reduced the technologists' alert recurrence; in 2023, 7% of technologist performance metrics exceeded alert levels, but 66% of those were in compliance the following month.

A semi-automated remote data collection and analysis of reject rates and EI has allowed a sustainable review of high-volume DR resulting in significant improvement in consistent exposure levels and image quality.