Impact of body part thickness on AP pelvis radiographic image quality and effective dose

Alzyoud, K, Hogg, P ORCID: https://orcid.org/0000-0002-6506-0827 and England, A ORCID: https://orcid.org/0000-0001-6333-7776 2018, 'Impact of body part thickness on AP pelvis radiographic image quality and effective dose' , Radiography, 25 (1) , e11-e17.

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Abstract

Introduction: Within medical imaging variations in patient size can generate challenges, especially when selecting appropriate acquisition parameters. This experiment sought to evaluate the impact of increasing body part thickness on image quality (IQ) and effective dose (E) and identify optimum exposure parameters.
Methods: An anthropomorphic pelvis phantom was imaged with additional layers (1 to 15 cm) of animal fat as a proxy for increasing body thickness. Acquisitions used the automatic exposure control (AEC), 100 cm source to image distance (SID) and a range of tube potentials (70 to 110 kVp). IQ was evaluated physically and perceptually. E was estimated using PCXMC software.
Results: For all tube potentials, signal to noise ratio (SNR) and contrast to noise ratio (CNR) deceased as body part thickness increased. 70 kVp produced the highest SNR (46.6 to 22.6); CNR (42.8 to 17.6). Visual grading showed that the highest IQ scores were achieved using 70 and 75 kVp. As thickness increases, E increased exponentially (r=0.96; p<0.001). Correlations were found between visual and physical IQ (SNR r= 0.97, p<0.001; CNR r=0.98, p<0.001).
Conclusion: To achieve an optimal IQ across the range of thicknesses, lower kVp settings were most effective. This is at variance with professional practice as there is a tendency for radiographers to increase kVp as thickness increases. Dose reductions were experienced at higher kVp settings and are a valid method for optimisation when imaging larger patients.

Item Type: Article
Schools: Schools > School of Health and Society > Centre for Health Sciences Research
Journal or Publication Title: Radiography
Publisher: Elsevier
ISSN: 1078-8174
Related URLs:
Depositing User: Dr Andrew England
Date Deposited: 07 Sep 2018 07:36
Last Modified: 10 Jan 2019 05:30
URI: http://usir.salford.ac.uk/id/eprint/48256

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