Greyscale Appearance of Film‑screen Radiographic Artefacts in a University Teaching Hospital
Main Article Content
Abstract
Objective: To link the greyscale appearance of radiographic artefacts with their origin, with a view to understanding and minimizing their occurrence.
Materials and Methods: A formula was used to establish a minimum sample size of 400 radiographs out of a population of 5500 radiographs produced between January 2013 and June, 2013. On a daily basis within the study period, all radiographs approved
for reporting by the quality control radiographer with over 10 years’ experience were scrutinized prospectively by the researchers with
the aid of a giant 100 cm × 50 cm viewing box with brightness adjustment, until 400 artefactual radiographs were eventually isolated.
The nature, greyscale appearance and origin of artefacts were arrived at by consensus and documented. Divergence in opinion and
ambiguous artefacts were resolved through observation of radiographers and darkroom assistants at work, as well as darkroom
simulations. The data on subdivision of artefacts was done using simple statistics.
Result: 400 radiographs out of a population of 5500 were sampled for the study. Twelve specific artefacts were isolated and categorized into three distinct appearances of black, white and grey. Preprocessing, processing and postprocessing were established as a broad classification for artefacts. Dispersed dots emanating from preprocessing (grey) and occurring in cassettes had the highest frequency of 140 (35%) while grid lines, n = 3 (0.8%) was the least noted.
Conclusion: All black artefacts arise during the preprocessing stage while processing and postprocessing have the middle-course greyscale appearance of artefacts.
Downloads
Article Details
Section

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
How to Cite
References
1. Kirberger RM, Roos CJ. Radiographic artifacts. J S Afr Vet Assoc 1995;66:85‑94.
2. Hogge JP, Palmer CH, Muller CC, Little ST, Smith DC, Fatouros PP, et al. Quality assurance in mammography: Artifact analysis. Radiographics 1999;19:503‑22.
3. Cesar LJ, Schueler BA, Zink FE, Daly TR, Taubel JP, Jorgenson LL. Artefacts found in computed radiography. Br J Radiol 2001;74:195‑202.
4. Horton KM, Johnson PT, Fishman EK. MDCT of the abdomen: Common misdiagnoses at a busy academic center. AJR Am J Roentgenol 2010;194:660‑7.
5. Chaloeykitti L, Muttarak M, Ng KH. Artifacts in mammography: Ways to identify and overcome them. Singapore Med J 2006;47:634‑40.
6. Eze KC, Omodia N, Okegbunam B, Adewonyi T, Nzotta CC. An audit of rejected repeated x‑ray films as a quality assurance element in a radiology department. Niger J Clin Pract 2008;11:355‑8.
7. Waaler D, Hofmann B. Image rejects/retakes – radiographic challenges. Radiat Prot Dosimetry 2010;139:375‑9.
8. Van Ongeval C, Jacobs J, Bosmans H. Artifacts in digital mammography. JBR‑BTR 2008;91:262‑3.
9. Jiménez DA, Armbrust LJ, O’Brien RT, Biller DS. Artifacts in digital radiography. Vet Radiol Ultrasound 2008;49:321‑32.