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AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes
INTRODUCTION: While Cumulus – a semi-automated method for measuring breast density – is utilised extensively in research, it is labour-intensive and unsuitable for screening programmes that require an efficient and valid measure on which to base screening recommendations. We develop an automated met...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978575/ https://www.ncbi.nlm.nih.gov/pubmed/24020331 http://dx.doi.org/10.1186/bcr3474 |
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author | Nickson, Carolyn Arzhaeva, Yulia Aitken, Zoe Elgindy, Tarek Buckley, Mitchell Li, Min English, Dallas R Kavanagh, Anne M |
author_facet | Nickson, Carolyn Arzhaeva, Yulia Aitken, Zoe Elgindy, Tarek Buckley, Mitchell Li, Min English, Dallas R Kavanagh, Anne M |
author_sort | Nickson, Carolyn |
collection | PubMed |
description | INTRODUCTION: While Cumulus – a semi-automated method for measuring breast density – is utilised extensively in research, it is labour-intensive and unsuitable for screening programmes that require an efficient and valid measure on which to base screening recommendations. We develop an automated method to measure breast density (AutoDensity) and compare it to Cumulus in terms of association with breast cancer risk and breast cancer screening outcomes. METHODS: AutoDensity automatically identifies the breast area in the mammogram and classifies breast density in a similar way to Cumulus, through a fast, stand-alone Windows or Linux program. Our sample comprised 985 women with screen-detected cancers, 367 women with interval cancers and 4,975 controls (women who did not have cancer), sampled from first and subsequent screening rounds of a film mammography screening programme. To test the validity of AutoDensity, we compared the effect estimates using AutoDensity with those using Cumulus from logistic regression models that tested the association between breast density and breast cancer risk, risk of small and large screen-detected cancers and interval cancers, and screening programme sensitivity (the proportion of cancers that are screen-detected). As a secondary analysis, we report on correlation between AutoDensity and Cumulus measures. RESULTS: AutoDensity performed similarly to Cumulus in all associations tested. For example, using AutoDensity, the odds ratios for women in the highest decile of breast density compared to women in the lowest quintile for invasive breast cancer, interval cancers, large and small screen-detected cancers were 3.2 (95% CI 2.5 to 4.1), 4.7 (95% CI 3.0 to 7.4), 6.4 (95% CI 3.7 to 11.1) and 2.2 (95% CI 1.6 to 3.0) respectively. For Cumulus the corresponding odds ratios were: 2.4 (95% CI 1.9 to 3.1), 4.1 (95% CI 2.6 to 6.3), 6.6 (95% CI 3.7 to 11.7) and 1.3 (95% CI 0.9 to 1.8). Correlation between Cumulus and AutoDensity measures was 0.63 (P < 0.001). CONCLUSIONS: Based on the similarity of the effect estimates for AutoDensity and Cumulus in models of breast density and breast cancer risk and screening outcomes, we conclude that AutoDensity is a valid automated method for measuring breast density from digitised film mammograms. |
format | Online Article Text |
id | pubmed-3978575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-39785752014-04-08 AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes Nickson, Carolyn Arzhaeva, Yulia Aitken, Zoe Elgindy, Tarek Buckley, Mitchell Li, Min English, Dallas R Kavanagh, Anne M Breast Cancer Res Research Article INTRODUCTION: While Cumulus – a semi-automated method for measuring breast density – is utilised extensively in research, it is labour-intensive and unsuitable for screening programmes that require an efficient and valid measure on which to base screening recommendations. We develop an automated method to measure breast density (AutoDensity) and compare it to Cumulus in terms of association with breast cancer risk and breast cancer screening outcomes. METHODS: AutoDensity automatically identifies the breast area in the mammogram and classifies breast density in a similar way to Cumulus, through a fast, stand-alone Windows or Linux program. Our sample comprised 985 women with screen-detected cancers, 367 women with interval cancers and 4,975 controls (women who did not have cancer), sampled from first and subsequent screening rounds of a film mammography screening programme. To test the validity of AutoDensity, we compared the effect estimates using AutoDensity with those using Cumulus from logistic regression models that tested the association between breast density and breast cancer risk, risk of small and large screen-detected cancers and interval cancers, and screening programme sensitivity (the proportion of cancers that are screen-detected). As a secondary analysis, we report on correlation between AutoDensity and Cumulus measures. RESULTS: AutoDensity performed similarly to Cumulus in all associations tested. For example, using AutoDensity, the odds ratios for women in the highest decile of breast density compared to women in the lowest quintile for invasive breast cancer, interval cancers, large and small screen-detected cancers were 3.2 (95% CI 2.5 to 4.1), 4.7 (95% CI 3.0 to 7.4), 6.4 (95% CI 3.7 to 11.1) and 2.2 (95% CI 1.6 to 3.0) respectively. For Cumulus the corresponding odds ratios were: 2.4 (95% CI 1.9 to 3.1), 4.1 (95% CI 2.6 to 6.3), 6.6 (95% CI 3.7 to 11.7) and 1.3 (95% CI 0.9 to 1.8). Correlation between Cumulus and AutoDensity measures was 0.63 (P < 0.001). CONCLUSIONS: Based on the similarity of the effect estimates for AutoDensity and Cumulus in models of breast density and breast cancer risk and screening outcomes, we conclude that AutoDensity is a valid automated method for measuring breast density from digitised film mammograms. BioMed Central 2013 2013-09-11 /pmc/articles/PMC3978575/ /pubmed/24020331 http://dx.doi.org/10.1186/bcr3474 Text en Copyright © 2013 Nickson et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Nickson, Carolyn Arzhaeva, Yulia Aitken, Zoe Elgindy, Tarek Buckley, Mitchell Li, Min English, Dallas R Kavanagh, Anne M AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes |
title | AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes |
title_full | AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes |
title_fullStr | AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes |
title_full_unstemmed | AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes |
title_short | AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes |
title_sort | autodensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978575/ https://www.ncbi.nlm.nih.gov/pubmed/24020331 http://dx.doi.org/10.1186/bcr3474 |
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