Heterogeneity of focal breast lesions and surrounding tissue assessed by mammographic texture analysis: Preliminary evidence of an association with tumour invasion and oestrogen receptor status

Ganeshan, Balaji, Strukowska, Olga, Skogen, Karoline, Young, Rupert, Chatwin, Chris and Miles, Kenneth A. (2011) Heterogeneity of focal breast lesions and surrounding tissue assessed by mammographic texture analysis: Preliminary evidence of an association with tumour invasion and oestrogen receptor status. Journal of Digital Imaging, 1 (33). ISSN 0897-1889

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Abstract

Aim: This pilot study investigates whether heterogeneity in focal breast lesions and surrounding tissue assessed on mammography is potentially related to cancer invasion and hormone receptor status. Materials and Methods: Texture analysis (TA) assessed the heterogeneity of focal lesions and their surrounding tissues in digitized mammograms from 11 patients randomly selected from an imaging archive [ductal carcinoma in situ (DCIS) only, n = 4; invasive carcinoma (IC) with DCIS, n = 3; IC only, n = 4]. TA utilized band-pass image filtration to highlight image features at different spatial frequencies (filter values: 1.0–2.5) from fine to coarse texture. The distribution of features in the derived images was quantified using uniformity. Results: Significant differences in uniformity were observed between patient groups for all filter values. With medium scale filtration (filter value = 1.5) pure DCIS was more uniform (median = 0.281) than either DCIS with IC (median = 0.246, p = 0.0102) or IC (median = 0.249, p = 0.0021). Lesions with high levels of estrogen receptor expression were more uniform, most notably with coarse filtration (filter values 2.0 and 2.5, rs = 0.812, p = 0.002). Comparison of uniformity values in focal lesions and surrounding tissue showed significant differences between DCIS with or without IC versus IC (p = 0.0009). Conclusion: This pilot study shows the potential for computer-based assessments of heterogeneity within focal mammographic lesions and surrounding tissue to identify adverse pathological features in mammographic lesions. The technique warrants further investigation as a possible adjunct to existing computer aided diagnosis systems.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
School of Mathematical and Physical Sciences > Mathematics
Brighton and Sussex Medical School > Clinical and Experimental Medicine
Subjects: R Medicine > R Medicine (General) > R856 Biomedical engineering. Electronics. Instrumentation
R Medicine > R Medicine (General) > R895 Medical physics. Medical radiology. Nuclear medicine
Depositing User: Grecia GarciaGarcia
Date Deposited: 03 Apr 2012 10:04
Last Modified: 05 Oct 2017 18:26
URI: http://sro.sussex.ac.uk/id/eprint/7184
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