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Breast Cancer Research
Published in: Breast Cancer Research 1/2016

Open Access 01-12-2016 | Research article

Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status

Authors: Serghei Malkov, John A. Shepherd, Christopher G. Scott, Rulla M. Tamimi, Lin Ma, Kimberly A. Bertrand, Fergus Couch, Matthew R. Jensen, Amir P. Mahmoudzadeh, Bo Fan, Aaron Norman, Kathleen R. Brandt, V. Shane Pankratz, Celine M. Vachon, Karla Kerlikowske

Published in: Breast Cancer Research | Issue 1/2016

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Abstract

Background

Several studies have shown that mammographic texture features are associated with breast cancer risk independent of the contribution of breast density. Thus, texture features may provide novel information for risk stratification. We examined the association of a set of established texture features with breast cancer risk by tumor type and estrogen receptor (ER) status, accounting for breast density.

Methods

This study combines five case–control studies including 1171 breast cancer cases and 1659 controls matched for age, date of mammogram, and study. Mammographic breast density and 46 breast texture features, including first- and second-order features, Fourier transform, and fractal dimension analysis, were evaluated from digitized film-screen mammograms. Logistic regression models evaluated each normalized feature with breast cancer after adjustment for age, body mass index, first-degree family history, percent density, and study.

Results

Of the mammographic features analyzed, fractal dimension and second-order statistics features were significantly associated (p < 0.05) with breast cancer. Fractal dimensions for the thresholds equal to 10% and 15% (FD_TH_10 and FD_TH_15) were associated with an increased risk of breast cancer while thresholds from 60% to 85% (FD_TH_60 to FD_TH_85) were associated with a decreased risk. Increasing the FD_TH_75 and Energy feature values were associated with a decreased risk of breast cancer while increasing Entropy was associated with a increased risk of breast cancer. For example, 1 standard deviation increase of FD_TH_75 was associated with a 13% reduced risk of breast cancer (odds ratio = 0.87, 95% confidence interval 0.79–0.95). Overall, the direction of associations between features and ductal carcinoma in situ (DCIS) and invasive cancer, and estrogen receptor positive and negative cancer were similar.

Conclusion

Mammographic features derived from film-screen mammograms are associated with breast cancer risk independent of percent mammographic density. Some texture features also demonstrated associations for specific tumor types. For future work, we plan to assess risk prediction combining mammographic density and features assessed on digital images.
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Metadata
Title
Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status
Authors
Serghei Malkov
John A. Shepherd
Christopher G. Scott
Rulla M. Tamimi
Lin Ma
Kimberly A. Bertrand
Fergus Couch
Matthew R. Jensen
Amir P. Mahmoudzadeh
Bo Fan
Aaron Norman
Kathleen R. Brandt
V. Shane Pankratz
Celine M. Vachon
Karla Kerlikowske
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2016
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-016-0778-1

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