A Multiinstitutional Study on Wasted CT Scans for Over 60,000 Patients
AJR Am J Roentgenol . 2020 Nov;215(5):1123-1129. doi: 10.2214/AJR.19.22604. Epub 2020 Sep 22.
Sean Rose, Ben Viggiano, Robert Bour, Carrie Bartels, Timothy Szczykutowicz
OBJECTIVE. Repeated imaging is an unnecessary source of patient radiation exposure, a detriment to patient satisfaction, and a waste of time and money. Although analysis of rates of repeated and rejected images is mandated in mammography and recommended in radiography, the available data on these rates for CT are limited.
MATERIALS AND METHODS. In this retrospective study, an automated repeat-reject rate analysis algorithm was used to quantify repeat rates from 61,102 patient examinations obtained between 2015 and 2018. The algorithm used DICOM metadata to identify repeat acquisitions. We quantified rates for one academic site and one rural site. The method allows scanner-, technologist-, protocol-, and indication-specific rates to be determined. Positive predictive values and sensitivity were estimated for correctly identifying and classifying repeat acquisitions. Repeat rates were compared between sites to identify areas for targeted technologist training.
RESULTS. Of 61,102 examinations, 4676 instances of repeat scanning contributed excess radiation dose to patients. Estimated helical overlap repeat rates were 1.4% (95% CI, 1.2-1.6%) for the rural site and 1.1% (95% CI, 1.0-1.2%) for the academic site. Significant differences in rates of repeat imaging required because of bolus tracking (11.6% vs 4.3%; p < 0.001) and helical extension (3.3% vs 1.8%; p < 0.001) were observed between sites. Positive predictive values ranged from 91% to 99% depending on the reason for repeat imaging and site location. Sensitivity of the algorithm was 92% (95% CI, 87-96%). Rates tended to be highest for emergent imaging procedures and exceeded 9% for certain protocols.
CONCLUSION. Our multiinstitutional automated quantification of repeat rates for CT provided a useful metric for unnecessary radiation exposure and identification of technologists in need of training.
Read Full Article Here: https://doi.org/10.2214/ajr.19.22604