Keywords:
Pelvis, Digital radiography, Diagnostic procedure
Authors:
K. S. Alzyoud1, A. England2, B. Snaith3, K. Flintham, P. Hogg2; 1salford/UK, 2Manchester/UK, 3Wakefield/UK
DOI:
10.1594/ecr2018/C-0425
Aims and objectives
Obesity is an international problem affecting all ages and genders [1,
2].
In relation to imaging,
patient size variation creates a challenge in practice and subsequent inconsistency in technique [3],
positioning,
communication and health care [4].
Therefore,
it is vital that radiology departments consider the impact of obesity,
particularly to overcome the challenges such as the need for repeat projections [2].
Modification to routine imaging practice is required to optimise medical diagnosis and visualisation of structures.
If not,
this will reduce image quality with a subsequent negative impact on diagnosis.
Many methods have been used to define image quality,
including physical and visual grading measurements.
Signal to noise ratio (SNR) and contrast to noise ratio (CNR) are the most frequently described physical methods.
SNR is determined by the relationship between contrast and noise in the image.
It is calculated from the ratio between the mean signal and the standard deviation of the background signal.
CNR is determined by the visibility of the region of interest (ROI) area from the surrounding tissue.
CNR is obtained from the differences of mean signal of the ROI and the mean signal from the background (noise) divided by standard deviation of the background [5].
Visual grading analysis (VGA) is another approach to evaluate image quality.
This is dependent on the visualisation of specified anatomical structures using clinical criteria.
VGA is helpful as it represents clinically relevant decisions and can have a strong correlation between the visibility of normal anatomy and the detectability of pathology structures [6].
The aim of this experiment is to assess the impact of increasing soft tissue thickness (as a proxy for obesity) on image quality (IQ) and effective dose (E) to identify optimal exposure parameters for different patient body habitus.