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Proceedings Paper

Using image simulation to test the effect of detector type on breast cancer detection
Author(s): Alistair Mackenzie; Lucy M. Warren; David R. Dance; Dev P. Chakraborty; Julie Cooke; Mark D. Halling-Brown; Padraig T. Looney; Matthew G. Wallis; Rosalind M. Given-Wilson; Gavin G. Alexander; Kenneth C. Young
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Paper Abstract

Introduction: The effect that the image quality associated with different image receptors has on cancer detection in mammography was measured using a novel method for changing the appearance of images. Method: A set of 270 mammography cases (one view, both breasts) was acquired using five Hologic Selenia and two Hologic Dimensions X-ray sets: 160 normal cases, 80 cases with subtle real non-calcification malignant lesions and 30 cases with biopsy proven benign lesions. Simulated calcification clusters were inserted into half of the normal cases. The 270 cases (Arm 1) were converted to appear as if they had been acquired on three other imaging systems: caesium iodide detector (Arm 2), needle image plate computed radiography (CR) (Arm 3) and powder phosphor CR (Arm 4). Five experienced mammography readers marked the location of suspected cancers in the images and classified the degree of visibility of the lesions. Statistical analysis was performed using JAFROC. Results: The differences in the visibility of calcification clusters between all pairs of arms were statistically significant (p<0.05), except between Arms 1 and 2. The difference in the visibility of non-calcification lesions was smaller than for calcification clusters, but the differences were still significant except between Arms 1 and 2 and between Arms 3 and 4. Conclusion: Detector type had a significant impact on the visibility of all types of subtle cancers, with the largest impact being on the visibility of calcification clusters.

Paper Details

Date Published: 11 March 2014
PDF: 14 pages
Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90370I (11 March 2014); doi: 10.1117/12.2043423
Show Author Affiliations
Alistair Mackenzie, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
Lucy M. Warren, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
David R. Dance, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
Dev P. Chakraborty, Univ. of Pittsburgh (United States)
Julie Cooke, Jarvis Breast Screening and Diagnostic Ctr. (United Kingdom)
Mark D. Halling-Brown, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Padraig T. Looney, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Matthew G. Wallis, Cambridge Univ. Hospitals NHS Foundation Trust (United Kingdom)
NIHR Cambridge Biomedical Research Ctr. (United Kingdom)
Rosalind M. Given-Wilson, St. George's Healthcare NHS Trust (United Kingdom)
Gavin G. Alexander, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Kenneth C. Young, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)


Published in SPIE Proceedings Vol. 9037:
Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment
Claudia R. Mello-Thoms; Matthew A. Kupinski, Editor(s)

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