Literature DB >> 20159914

Image rejects/retakes--radiographic challenges.

D Waaler1, B Hofmann.   

Abstract

A general held position among radiological personnel prior to digitalisation was that the problem of image rejects/retakes should more or less vanish. However, rejects/retakes still impose several challenges within radiographic imaging; they occupy unnecessary resources, expose patients to unnecessary ionizing radiation and may also indicate suboptimal quality management. The latter is the main objective of this paper, which is based on a survey of international papers published both for screen/film and digital technology. The digital revolution in imaging seems to have reduced the percentage of image rejects/retakes from 10-15 to 3-5 %. The major contribution to the decrease appears to be the dramatic reduction of incorrect exposures. At the same time, rejects/retakes due to lack of operator competence (positioning, etc.) are almost unchanged, or perhaps slightly increased (due to lack of proper technical competence, incorrect organ coding, etc.). However, the causes of rejects/retakes are in many cases defined and reported with reference to radiographers' subjective evaluations. Thus, unless radiographers share common views on image quality and acceptance criteria, objective measurements and assessments of reject/retake rates are challenging tasks. Interestingly, none of the investigated papers employs image quality parameters such as 'too much noise' as categories for rejects/retakes. Surprisingly, no reject/retake analysis seems yet to have been conducted for direct digital radiography departments. An increased percentage of rejects/retakes is related to 'digital skills' of radiographers and therefore points to areas for extended education and training. Furthermore, there is a need to investigate the inter-subjectivity of radiographers' perception of, and attitude towards, both technical and clinical image quality criteria. Finally, there may be a need to validate whether reject/retake rate analysis is such an effective quality indicator as has been asserted.

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Mesh:

Year:  2010        PMID: 20159914     DOI: 10.1093/rpd/ncq032

Source DB:  PubMed          Journal:  Radiat Prot Dosimetry        ISSN: 0144-8420            Impact factor:   0.972


  11 in total

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

Authors:  Jacquelyn S Whaley; Barry D Pressman; Jonathan R Wilson; Lionel Bravo; William J Sehnert; David H Foos
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

2.  Clinical utility of ultra-low-dose pre-test exposure to avoid unnecessary patient exposure due to positioning errors: a simulation study.

Authors:  Hideo Nose; Junji Shiraishi
Journal:  Radiol Phys Technol       Date:  2017-09-11

3.  Application of off-line image processing for optimization in chest computed radiography using a low cost system.

Authors:  Wilbroad E Muhogora; Peter Msaki; Renato Padovani
Journal:  J Appl Clin Med Phys       Date:  2015-03-08       Impact factor: 2.102

4.  Educational Module Intervention for Radiographers to Reduce Repetition Rate of Routine Digital Chest Radiography in Makkah Region of Saudi Arabia Tertiary Hospitals: Protocol of a Quasi-Experimental Study.

Authors:  Rosliza Abdul Manaf; Abdullah A Almalki; Muhamad Hanafiah Juni; Hayati Kadir Shahar; Noramaliza Mohd Noor; Abdelsafi Gabbad
Journal:  JMIR Res Protoc       Date:  2017-09-26

5.  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

6.  Digital radiograph rejection analysis during "Coronavirus disease 2019 (COVID-19) pandemic" in a tertiary care public sector hospital in Khyber Pakhtunkhwa Province of Pakistan.

Authors:  Amir Ali; Muhammad Yaseen
Journal:  Chin J Acad Radiol       Date:  2021-06-07

7.  Image rejects in general direct digital radiography.

Authors:  Bjørn Hofmann; Tine Blomberg Rosanowsky; Camilla Jensen; Kenneth Hong Ching Wah
Journal:  Acta Radiol Open       Date:  2015-10-08

8.  Repeat analysis of intraoral digital imaging performed by undergraduate students using a complementary metal oxide semiconductor sensor: An institutional case study.

Authors:  Mohd Yusmiaidil Putera Mohd Yusof; Nur Liyana Abdul Rahman; Amiza Aqiela Ahmad Asri; Noor Ilyani Othman; Ilham Wan Mokhtar
Journal:  Imaging Sci Dent       Date:  2017-12-12

9.  Geometric validation of a computer simulator used in radiography education.

Authors:  Philip Cosson; Zenghai Lu
Journal:  BJR Open       Date:  2020-02-03

10.  Visualizing the Invisible: Invisible Waste in Diagnostic Imaging.

Authors:  Bjørn Hofmann; Eivind Richter Andersen; Elin Kjelle
Journal:  Healthcare (Basel)       Date:  2021-12-07
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