Literature DB >> 22850934

Investigation of the variability in the assessment of digital chest X-ray image quality.

Jacquelyn S Whaley1, Barry D Pressman, Jonathan R Wilson, Lionel Bravo, William J Sehnert, David H Foos.   

Abstract

A large database of digital chest radiographs was developed over a 14-month period. Ten radiographic technologists and five radiologists independently evaluated a stratified subset of images from the database for quality deficiencies and decided whether each image should be rejected. The evaluation results showed that the radiographic technologists and radiologists agreed only moderately in their assessments. When compared against each other, radiologist and technologist reader groups were found to have even less agreement than the inter-reader agreement within each group. Radiologists were found to be more accepting of limited-quality studies than technologists. Evidence from the study suggests that the technologists weighted their reject decisions more heavily on objective technical attributes, while the radiologists weighted their decisions more heavily on diagnostic interpretability relative to the image indication. A suite of reject-detection algorithms was independently run on the images in the database. The algorithms detected 4 % of postero-anterior chest exams that were accepted by the technologist who originally captured the image but which would have been rejected by the technologist peer group. When algorithm results were made available to the technologists during the study, there was no improvement in inter-reader agreement in deciding whether to reject an image. The algorithm results do, however, provide new quality information that could be captured within a site-wide, reject-tracking database and leveraged as part of a site-wide QA program.

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Mesh:

Year:  2013        PMID: 22850934      PMCID: PMC3597969          DOI: 10.1007/s10278-012-9515-1

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  12 in total

1.  Continuing challenges in defining image quality.

Authors:  Narendra Shet; Joseph Chen; Eliot L Siegel
Journal:  Pediatr Radiol       Date:  2011-04-14

2.  Maintaining quality control using a radiological digital X-ray dashboard.

Authors:  Todd R Minnigh; Jacqueline Gallet
Journal:  J Digit Imaging       Date:  2008-02-13       Impact factor: 4.056

3.  Image retake analysis in digital radiography using DICOM header information.

Authors:  C Prieto; E Vano; J I Ten; J M Fernandez; A I Iñiguez; N Arevalo; A Litcheva; E Crespo; A Floriano; D Martinez
Journal:  J Digit Imaging       Date:  2008-07-01       Impact factor: 4.056

4.  Digital radiography reject analysis: data collection methodology, results, and recommendations from an in-depth investigation at two hospitals.

Authors:  David H Foos; W James Sehnert; Bruce Reiner; Eliot L Siegel; Arthur Segal; David L Waldman
Journal:  J Digit Imaging       Date:  2008-04-30       Impact factor: 4.056

5.  Quality control management and communication between radiologists and technologists.

Authors:  Paul G Nagy; Benjamin Pierce; Misty Otto; Nabile M Safdar
Journal:  J Am Coll Radiol       Date:  2008-06       Impact factor: 5.532

Review 6.  Image rejects/retakes--radiographic challenges.

Authors:  D Waaler; B Hofmann
Journal:  Radiat Prot Dosimetry       Date:  2010-02-16       Impact factor: 0.972

Review 7.  Artificial neural networks: opening the black box.

Authors:  J E Dayhoff; J M DeLeo
Journal:  Cancer       Date:  2001-04-15       Impact factor: 6.860

8.  The measurement of observer agreement for categorical data.

Authors:  J R Landis; G G Koch
Journal:  Biometrics       Date:  1977-03       Impact factor: 2.571

9.  Managing repeat digital radiography images-a systematic approach and improvement.

Authors:  Wen-Sheng Tzeng; Kuang-Ming Kuo; Chung-Feng Liu; Huan-Chung Yao; Chin-Yu Chen; Huang-Wei Lin
Journal:  J Med Syst       Date:  2011-05-31       Impact factor: 4.460

10.  One year's results from a server-based system for performing reject analysis and exposure analysis in computed radiography.

Authors:  A Kyle Jones; Raimund Polman; Charles E Willis; S Jeff Shepard
Journal:  J Digit Imaging       Date:  2011-04       Impact factor: 4.056

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  2 in total

1.  Reject rate analysis in digital radiography: an Australian emergency imaging department case study.

Authors:  Samantha Atkinson; Michael Neep; Deborah Starkey
Journal:  J Med Radiat Sci       Date:  2019-07-18

2.  The assessment of image quality and diagnostic value in X-ray images: a survey on radiographers' reasons for rejecting images.

Authors:  Elin Kjelle; Catherine Chilanga
Journal:  Insights Imaging       Date:  2022-03-04
  2 in total

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