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Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study

BACKGROUND: Mammographic density is a well-established risk factor for breast cancer. We investigated the association between three different methods of measuring density or parenchymal pattern/texture on digitized film-based mammograms, and examined to what extent textural features independently an...

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Autores principales: Winkel, Rikke Rass, von Euler-Chelpin, My, Nielsen, Mads, Petersen, Kersten, Lillholm, Martin, Nielsen, Michael Bachmann, Lynge, Elsebeth, Uldall, Wei Yao, Vejborg, Ilse
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936245/
https://www.ncbi.nlm.nih.gov/pubmed/27387546
http://dx.doi.org/10.1186/s12885-016-2450-7
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author Winkel, Rikke Rass
von Euler-Chelpin, My
Nielsen, Mads
Petersen, Kersten
Lillholm, Martin
Nielsen, Michael Bachmann
Lynge, Elsebeth
Uldall, Wei Yao
Vejborg, Ilse
author_facet Winkel, Rikke Rass
von Euler-Chelpin, My
Nielsen, Mads
Petersen, Kersten
Lillholm, Martin
Nielsen, Michael Bachmann
Lynge, Elsebeth
Uldall, Wei Yao
Vejborg, Ilse
author_sort Winkel, Rikke Rass
collection PubMed
description BACKGROUND: Mammographic density is a well-established risk factor for breast cancer. We investigated the association between three different methods of measuring density or parenchymal pattern/texture on digitized film-based mammograms, and examined to what extent textural features independently and jointly with density can improve the ability to identify screening women at increased risk of breast cancer. METHODS: The study included 121 cases and 259 age- and time matched controls based on a cohort of 14,736 women with negative screening mammograms from a population-based screening programme in Denmark in 2007 (followed until 31 December 2010). Mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, Tabár’s classification on parenchymal patterns and a fully automated texture quantification technique. The individual and combined association with breast cancer was estimated using binary logistic regression to calculate Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs). RESULTS: Cases showed significantly higher BI-RADS and texture scores on average than controls (p < 0.001). All three methods were individually able to segregate women into different risk groups showing significant ORs for BI-RADS D3 and D4 (OR: 2.37; 1.32–4.25 and 3.93; 1.88–8.20), Tabár’s PIII and PIV (OR: 3.23; 1.20–8.75 and 4.40; 2.31–8.38), and the highest quartile of the texture score (3.04; 1.63–5.67). AUCs for BI-RADS, Tabár and the texture scores (continuous) were 0.63 (0.57–0–69), 0.65 (0.59–0–71) and 0.63 (0.57–0–69), respectively. Combining two or more methods increased model fit in all combinations, demonstrating the highest AUC of 0.69 (0.63-0.74) when all three methods were combined (a significant increase from standard BI-RADS alone). CONCLUSION: Our findings suggest that the (relative) amount of fibroglandular tissue (density) and mammographic structural features (texture/parenchymal pattern) jointly can improve risk segregation of screening women, using information already available from normal screening routine, in respect to future personalized screening strategies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-016-2450-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-49362452016-07-07 Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study Winkel, Rikke Rass von Euler-Chelpin, My Nielsen, Mads Petersen, Kersten Lillholm, Martin Nielsen, Michael Bachmann Lynge, Elsebeth Uldall, Wei Yao Vejborg, Ilse BMC Cancer Research Article BACKGROUND: Mammographic density is a well-established risk factor for breast cancer. We investigated the association between three different methods of measuring density or parenchymal pattern/texture on digitized film-based mammograms, and examined to what extent textural features independently and jointly with density can improve the ability to identify screening women at increased risk of breast cancer. METHODS: The study included 121 cases and 259 age- and time matched controls based on a cohort of 14,736 women with negative screening mammograms from a population-based screening programme in Denmark in 2007 (followed until 31 December 2010). Mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, Tabár’s classification on parenchymal patterns and a fully automated texture quantification technique. The individual and combined association with breast cancer was estimated using binary logistic regression to calculate Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs). RESULTS: Cases showed significantly higher BI-RADS and texture scores on average than controls (p < 0.001). All three methods were individually able to segregate women into different risk groups showing significant ORs for BI-RADS D3 and D4 (OR: 2.37; 1.32–4.25 and 3.93; 1.88–8.20), Tabár’s PIII and PIV (OR: 3.23; 1.20–8.75 and 4.40; 2.31–8.38), and the highest quartile of the texture score (3.04; 1.63–5.67). AUCs for BI-RADS, Tabár and the texture scores (continuous) were 0.63 (0.57–0–69), 0.65 (0.59–0–71) and 0.63 (0.57–0–69), respectively. Combining two or more methods increased model fit in all combinations, demonstrating the highest AUC of 0.69 (0.63-0.74) when all three methods were combined (a significant increase from standard BI-RADS alone). CONCLUSION: Our findings suggest that the (relative) amount of fibroglandular tissue (density) and mammographic structural features (texture/parenchymal pattern) jointly can improve risk segregation of screening women, using information already available from normal screening routine, in respect to future personalized screening strategies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-016-2450-7) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-07 /pmc/articles/PMC4936245/ /pubmed/27387546 http://dx.doi.org/10.1186/s12885-016-2450-7 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Winkel, Rikke Rass
von Euler-Chelpin, My
Nielsen, Mads
Petersen, Kersten
Lillholm, Martin
Nielsen, Michael Bachmann
Lynge, Elsebeth
Uldall, Wei Yao
Vejborg, Ilse
Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
title Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
title_full Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
title_fullStr Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
title_full_unstemmed Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
title_short Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
title_sort mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936245/
https://www.ncbi.nlm.nih.gov/pubmed/27387546
http://dx.doi.org/10.1186/s12885-016-2450-7
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