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. 2023 Dec 22;107(1):100.
doi: 10.5334/jbsr.3259. eCollection 2023.

Reject Analysis in Digital Radiography and Computed Tomography: A Belgian Imaging Department Case Study

Laura Haddad  1 , Hanna Saleme  2 , Nigel Howarth  3 , Denis Tack  2
Affiliations

Reject Analysis in Digital Radiography and Computed Tomography: A Belgian Imaging Department Case Study

Laura Haddad et al. J Belg Soc Radiol. .

Abstract

Objective: Reject analysis is usually performed in digital radiography (DR) for quality assurance. Data for computed tomography (CT) rejects remains sparse. The aim of this study is to help provide a straightforward benchmark for reject analysis of both DR and CT.

Materials and methods: This retrospective observational study included 107,277 DR and 20,659 CT during 18 months in a tertiary care center. Rejected acquisitions were retrieved by Dose Archiving and Communication System (DACS). The DR and CT reject analysis included reject rates, reasons for rejection and supplementary radiation dose associated with these rejects.

Results: 8,904 rejected DR and 514 rejected CT were retrieved. The DR reject rate was 8.3% whereas the CT reject rate was 2.5%. The cumulative effective dose (ED) of DR rejects was 377.3 mSv while the cumulative ED of CT rejects was 1267.4 mSv. The major reason for rejects was positioning for both DR (61%) and CT (44%).

Conclusion: This study helps constitute a simple reproducible method to analyze both DR and CT rejects simultaneously. Although CT rejects are less often monitored than DR rejects, the radiation dose associated with CT rejects is much higher, which emphasizes the need to systematically monitor both DR and CT rejects. Investigating the reasons and the most frequently rejected examinations gives an opportunity for improvement of imaging techniques in cooperation with technologists.

Keywords: Computed Tomography; Digital; Dose optimization; Dose-Length-Product; Dose-area-product; Effective dose; Protocol optimization; Radiography.

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Conflict of interest statement

The authors have no competing interests to declare.

References

    1. McCollough CH, Primak AN, Braun N, Kofler J, Yu L, Christner J. Strategies for reducing radiation dose in CT. Radiol Clin North Am. 2009; 47(1): 27–40. DOI: 10.1016/j.rcl.2008.10.006 - DOI - PMC - PubMed
    1. Jones AK, Heintz P, Geiser W, Goldman L, Jerjian K, Martin M. Ongoing quality control in digital radiography: Report of AAPM imaging physics committee task group 151. Med Phys. 2015; 42(11): 6658–6670. DOI: 10.1118/1.4932623 - DOI - PubMed
    1. Little KJ, Reiser I, Liu L, Kinsey T, Sánchez AA, Haas K. Unified Database for Rejected Image Analysis Across Multiple Vendors in Radiography. J Am Coll Radiol. 2017; 14(2): 208–216. DOI: 10.1016/j.jacr.2016.07.011 - DOI - PubMed
    1. Foos DH, Sehnert WJ, Reiner B, Siegel EL, Segal A, Waldman DL. Digital radiography reject analysis: Data collection methodology, results, and recommendations from an in-depth investigation at two hospitals. J Digit Imaging. 2009; 22(1): 89–98. DOI: 10.1007/s10278-008-9112-5 - DOI - PMC - PubMed
    1. Taylor N. The art of rejection: Comparative analysis between Computed Radiography (CR) and Digital Radiography (DR) workstations in the Accident & Emergency and General radiology departments at a district general hospital using customised and standardised reject criteria over a three year period. Radiography. 2015; 21(3): 236–241. DOI: 10.1016/j.radi.2014.12.003 - DOI

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