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
Full text not available from this repository.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 |
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Schools and Departments: | Brighton and Sussex Medical School > Clinical and Experimental Medicine School of Engineering and Informatics > Engineering and Design School of Mathematical and Physical Sciences > Mathematics |
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: | 23 Mar 2019 13:51 |
URI: | http://sro.sussex.ac.uk/id/eprint/7184 |