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. 2023 May;24(5):e13938.
doi: 10.1002/acm2.13938. Epub 2023 Mar 30.

AAPM task group report 305: Guidance for standardization of vendor-neutral reject analysis in radiography

Kevin Little  1 , Ingrid Reiser  2 , Bruce Apgar  3 , Poonam Dalal  4 , Jaydev Dave  5 , Ryan Fisher  6 , Katie Hulme  7 , Mary Ellen Jafari  8 , Emily Marshall  2 , Stephen Meyer  9 , Quentin Moore  10 , Nicole Murphy  11 , Thomas Nishino  12 , Katelyn Nye  4 , Kevin O'Donnell  13 , John Sabol  4 , Adrian Sanchez  14 , William Sensakovic  15 , Lawrence Tarbox  16 , Robert Uzenoff  17 , Alisa Walz-Flannigan  18 , Charles Willis  13 , Jie Zhang  19
Affiliations

AAPM task group report 305: Guidance for standardization of vendor-neutral reject analysis in radiography

Kevin Little et al. J Appl Clin Med Phys. 2023 May.

Abstract

Reject rate analysis is considered an integral part of a diagnostic radiography quality control (QC) program. A rejected image is a patient radiograph that was not presented to a radiologist for diagnosis and that contributes unnecessary radiation dose to the patient. Reject rates that are either too high or too low may suggest systemic department shortcomings in QC mechanisms. Due to the lack of standardization, reject data often cannot be easily compared between radiography systems from different vendors. The purpose of this report is to provide guidance to help standardize data elements that are required for comprehensive reject analysis and to propose data reporting and workflows to enable an effective and comprehensive reject rate monitoring program. Essential data elements, a proposed schema for classifying reject reasons, and workflow implementation options are recommended in this task group report.

Keywords: Computed radiography; digital radiography; radiography; reject; reject rate; reject rate analysis; repeat.

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Conflict of interest statement

(1) The members of TG305 listed below attest that they have no potential Conflicts of Interest related to the subject matter or materials presented in this document. Ingrid Reiser, Ryan Fisher, Katie Hulme, Mary Ellen Jafari, Emily Marshall, Quentin Moore, Nicole Murphy, Thomas Nishino, Adrian Sanchez, William Sensakovic, Lawrence Tarbox, Alisa Walz‐Flannigan, and Jie Zhang. (2) The members of TG305 listed below disclose the following potential Conflict(s) of Interest related to subject matter or materials presented in this document. During the time this work was performed, Kevin Little was an employee of Ohio State University, which has research agreements with Qaelum NV and Siemens Healthineers. Bruce Apgar is an employee of AGFA HealthCare. Jaydev Dave has received research support from Philips Healthcare, Lantheus Medical Imaging Inc., and GE Healthcare. Stephen Meyer is an employee of Canon Medical Components USA. Kevin O'Donnell is an employee of Canon Medical Research USA, a subsidiary of Canon Medical Systems Corporation. Katelyn Nye is an employee of GE Healthcare. Dalal Poonam is an employee of GE Healthcare. During part of the time this work was performed, John Sabol was an employee of GE Healthcare, Robert Uzenoff was an employee of Fujifilm Medical Systems U.S.A., and Charles Willis was a member of the GE Medical Advisory Board for Radiography.

Figures

FIGURE 1
FIGURE 1
Generic actions and decisions taken by the radiologic technologist when performing radiographic imaging.
FIGURE 2
FIGURE 2
The diagram depicts a typical radiology information system (RIS)‐driven workflow for a radiology clinic. Typically, after the order has been created in the hospital information system (HIS) and pushed to the RIS, the technologist begins and ends the procedure, as indicated by the dashed arrows. Images are commonly reviewed for image quality at the acquisition workstation by the technologist that acquired the images, and images deemed “unacceptable” for interpretation are rejected and do not get sent to picture archiving and communication system (PACS). Additional technical items may be assessed in PACS during a “QA Review” stage prior to ending the procedure in the RIS. PACS super‐users have the ability to delete images from PACS during “QA Review.” Note that the radiologist has no knowledge or input to the image QA review process in this workflow.
FIGURE 3
FIGURE 3
The proposed DICOM implementation would enable radiologists’ direct involvement in the image quality control (QC) review process. PACS, picture archiving and communication system; RIS, radiology information system.
See this image and copyright information in PMC

References

    1. Gray J. Quality Control in Diagnostic Imaging: A Quality Control Cookbook. University Park Press; 1983.
    1. DeMaio DN, Herrmann T, Noble LB, et al. Best practices in digital radiography. Radiol Technol. 2019;91(2):198‐201. - PubMed
    1. National Council on Radiation Protection and Measurements Report 99 – Quality Assurance for Diagnostic Imaging . U.S. Dept. of Commerce, National Bureau of Standards; 1988.
    1. Shepard SJ, Lin PJP, Boone JM, et al. AAPM Report 74: Quality Control in Diagnostic Radiology. American Association of Physicists in Medicine; 2002.
    1. Jones AK, Heintz P, Geiser W, et al. 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