- Poster presentation
- Open Access
Mammographic image unsharpness: a predictable phenomenon?
© Coltart et al. 2011
- Published: 4 November 2011
- Logistic Regression
- Exposure Time
- Selection Criterion
- Predictor Model
In 2009, the South West of Scotland Breast Screening Unit (SWSBSU) had to repeat 236 examinations due to mammographic image unsharpness. Such recalls were undesirable because of radiation safety issues, anxiety caused and cost. The aim of this study was to model predictors of recall that could be used in clinical practise to help reduce the numbers of repeat examinations required due to blurring.
This retrospective study compared two sample groups (n = 118), randomly selected from a cohort of women who attended the SWSBSU in 2009 (n = 16,194). Tests of significance were used to compare a range of variables in each group and logistic regression was employed to produce four predictor models for recall. Statistical analysis was carried out by the authors using SPSS version 18.
A 12 mm increase in compressed breast thickness (CBT), a 50 mAs increase in exposure or a 350 ms increase in exposure time will double the odds of recall due to unsharpness. Also, an increase of 2 kVp, when imaging a breast with a CBT of 60 mm, will reduce the odds of recall by approximately 39%.
CBT is a major determinant of recall due to unsharpness. Within the context of the reported increase in average CBT  and rising national obesity, reconsideration of kVp selection criteria may be necessary to minimise the incidence of recall due to unsharpness.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.