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Breast Cancer Research
Published in: Breast Cancer Research 1/2019

Open Access 01-12-2019 | Breast Cancer | Research article

Sensitivity of screening mammography by density and texture: a cohort study from a population-based screening program in Denmark

Authors: My von Euler-Chelpin, Martin Lillholm, Ilse Vejborg, Mads Nielsen, Elsebeth Lynge

Published in: Breast Cancer Research | Issue 1/2019

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Abstract

Background

Screening mammography works better in fatty than in dense breast tissue. Computerized assessment of parenchymal texture is a non-subjective method to obtain a refined description of breast tissue, potentially valuable in addition to breast density scoring for the identification of women in need of supplementary imaging. We studied the sensitivity of screening mammography by a combination of radiologist-assessed Breast Imaging Reporting and Data System (BI-RADS) density score and computer-assessed parenchymal texture marker, mammography texture resemblance (MTR), in a population-based screening program.

Methods

Breast density was coded according to the fourth edition of the BI-RADS density code, and MTR marker was divided into quartiles from 1 to 4. Screening data were followed up for the identification of screen-detected and interval cancers. We calculated sensitivity and specificity with 95% confidence intervals (CI) by BI-RADS density score, MTR marker, and combination hereof.

Results

Density and texture were strongly correlated, but the combination led to the identification of subgroups with different sensitivity. Sensitivity was high, about 80%, in women with BI-RADS density score 1 and MTR markers 1 or 2. Sensitivity was low, 67%, in women with BI-RADS density score 2 and MTR marker 4. For women with BI-RADS density scores 3 and 4, the already low sensitivity was further decreased for women with MTR marker 4. Specificity was 97–99% in all subgroups.

Conclusion

Our study showed that women with low density constituted a heterogenous group. Classifying women for extra imaging based on density only might be a too crude approach. Screening sensitivity was systematically high in women with fatty and homogenous breast tissue.
Literature
1.
2.
European Commission. European guidelines for quality assurance in breast cancer screening and diagnosis. 4th ed. European Communities: Luxembourg; 2006.
3.
Marmot MG, Altman DG, Cameron DA, et al. The benefits and harms of breast cancer screening: an independent review. Br J Cancer. 2013;108(11):2205–40.CrossRefPubMedPubMedCentral
4.
The IARC Working Group. IARC Handbooks of Cancer Prevention: Breast cancer screening. Volume 15, 2015.
5.
Leconte I, Feger C, Galant C, et al. Mammography and subsequent whole-breast sonography of nonpalpable breast cancers: the importance of radiologic breast density. AJR Am J Roentgenol. 2003;180(6):1675–9.CrossRefPubMed
6.
7.
8.
Ray KM, Price ER, Joe BN. Breast density legislation: mandatory disclosure to patients, alternative screening, billing, reimbursement. AJR Am J Roentgenol. 2015;204(2):257–60.CrossRefPubMed
9.
Raj SD, Fein-Zachary V, Slanetz PJ. Deciphering the breast density inform law movement: implications for practice. Semin Ultrasound CT MR. 2018;39(1):16–24.CrossRefPubMed
10.
Whitman GJ, Woodtichartpreecha P. Breast density legislation: more evidence is needed. Breast J. 2016;22(5):491–2.CrossRefPubMed
11.
Gastounioti A, Conant EF, Kontos D. Beyond breast density: a review on the advancing role of parenchymal texture analysis in breast cancer risk assessment. Breast Cancer Res. 2016;18(1):91.CrossRefPubMedPubMedCentral
12.
13.
Kallenberg M, Petersen K, Nielsen M, et al. Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring. IEEE Trans Med Imaging. 2016;35(5):1322–31.CrossRefPubMed
14.
Wanders JOP, van Gils CH, Karssemeijer N, et al. The combined effect of mammographic texture and density on breast cancer risk: a cohort study. Breast Cancer Res. 2018;20(1):36.CrossRefPubMedPubMedCentral
15.
Bjerregaard B, Larsen O. The Danish Pathology Register. Scand J Public Health. 2011;39(7 Suppl):72–4.CrossRefPubMed
16.
Highnam R, Brady M, Yaffe M, Karssemeijer N, Harvey J. Robust breast composition measurement - Volpara (TM). Lect Notes Comput Sci. 2010;6136:342–9.CrossRef
17.
Wang C, Brentnall AR, Cuzick J, et al. A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studies. Breast Cancer Res. 2017;19(1):114.CrossRefPubMedPubMedCentral
18.
Kemp JK, O’Meara ES, Key D, et al. Comparing sensitivity and specificity of screening mammography in the United States and Denmark. Int J Cancer. 2015;137(9):2198–207.CrossRef
19.
Domingo L, Hofvind S, Hubbard RA, et al. Cross-national comparison of screening mammography accuracy measures in U.S., Norway, and Spain. Eur Radiol. 2016;26(8):2520–8.CrossRefPubMed
20.
Hofvind S, Geller BM, Skelly J, Vacek PM. Sensitivity and specificity of mammographic screening as practised in Vermont and Norway. Br J Radiol. 2012;85(1020):e1226–32.CrossRefPubMedPubMedCentral
21.
Kerlikowske K, Zhu W, Tosteson AN, et al. Identifying women with dense breasts at high risk for interval cancer: a cohort study. Ann Intern Med. 2015;162(10):673–81.CrossRefPubMedPubMedCentral
22.
Mainprize JG, Alonso-Proulx O, Alshafeiy, et al. Prediction of cancer masking in screening mammography using density and textural features. Acad Radiol. 2019;26(5):608–19.CrossRefPubMed
23.
Winkel RR, von Euler-Chelpin M, Nielsen M, et al. Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer. BMC Cancer. 2015;15:274.CrossRefPubMedPubMedCentral
Metadata
Title
Sensitivity of screening mammography by density and texture: a cohort study from a population-based screening program in Denmark
Authors
My von Euler-Chelpin
Martin Lillholm
Ilse Vejborg
Mads Nielsen
Elsebeth Lynge
Publication date
01-12-2019
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2019
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-019-1203-3

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