Exhibit Hall | Forum 8
Purpose: Adjusting a CT scanner’s protocols is not a trivial task. Properly tuned CT protocols can have issues with providing uniform diagnostic quality images over indication and patient size needs. This study looks at the function of a site’s automatic exposure control(AEC) before and after a team of medical physicists optimized the protocols for better AEC function. The goal was to provide radiologists with images that did not suffer from issues of tube current(mA) values minning out or maxxing out which correspond to image quality being better or worse than desired respectively.
Methods: From two time periods we analyzed 678 exams pre protocol optimization(2007-2008) and 746 post protocol optimization(2021-2022). For each time period we extracted data from routine chest and routine abdominal exams. All scanners were manufactured by General Electric. To assess the proper function of the AEC for each examination, the percentages of images with mA at the maximum(%img_max_mA) and minimum(%img_min_mA) were measured. All examinations with %img_max_mA or %img_min_mA greater than 20% were classified as suboptimal.
Results: The mean %img_max_mA for the chest exams decreased from 31.3±32.5% to 10.3± 8.0%(p<0.001) from the pre to post optimized protocol periods. Similarly, the mean %img_max_mA for the abdomen exams decreased from 33.4±34.2% to 14.3±16.6%(p<0.001). The mean %min _mA for the chest exams decreased from 18.9±31.9% to 3.6±4.2%(p<0.001).Similarly, the mean %img_min_mA for the abdomen exams decreased from 18.7± 33.2% to 3.7±13.4%(p<0.001). The percent of suboptimal chest exams for %img_max_mA(%img_min_mA) decreased from 45.6(21.9)% to 8.2(1.1)%. The percent of suboptimal abdominal exams for %img_max_mA(%img_min_mA), decreased from 42.3(22.3)% to 12.1(3.2)%.
Conclusion: This demonstrates the value of medical physicists in the optimization of clinical protocols. The intervention resulted in a large reduction of the incidence of suboptimal chest and abdominal examinations as measured by the percentage of images at the extremes of exam mA range.
Funding Support, Disclosures, and Conflict of Interest: Timothy P. Szczykutowicz, Ph.D., DABR has the following conflicts of interest: Consultant: GE, Imalogix, AstoCT, AIDoc, ALARA Medical, and FlowHow.ai. On medical advisor board for GE and Imalogix. Research support by GE, and Canon USA. Patent royalties with Qaelum and FlowHow.ai. Joseph Meier and Jordan Krebs have no conflicts