Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction
Background The associations of density measures from the publicly available Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software with breast cancer have primarily focused on estimates from the contralateral breast at the time of diagnosis. Purpose To evaluate LIBRA measures...
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creator | Gastounioti, Aimilia Kasi, Christine Damases Scott, Christopher G Brandt, Kathleen R Jensen, Matthew R Hruska, Carrie B Wu, Fang F Norman, Aaron D Conant, Emily F Winham, Stacey J Kerlikowske, Karla Kontos, Despina Vachon, Celine M |
description | Background The associations of density measures from the publicly available Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software with breast cancer have primarily focused on estimates from the contralateral breast at the time of diagnosis. Purpose To evaluate LIBRA measures on mammograms obtained before breast cancer diagnosis and compare their performance to established density measures. Materials and Methods For this retrospective case-control study, full-field digital mammograms in for-processing (raw) and for-presentation (processed) formats were obtained (March 2008 to December 2011) in women who developed breast cancer an average of 2 years later and in age-matched control patients. LIBRA measures included absolute dense area and area percent density (PD) from both image formats. For comparison, dense area and PD were assessed by using the research software (Cumulus), and volumetric PD (VPD) and absolute dense volume were estimated with a commercially available software (Volpara). Density measures were compared by using Spearman correlation coefficients (
), and conditional logistic regression (odds ratios [ORs] and 95% confidence intervals [CIs]) was performed to examine the associations of density measures with breast cancer by adjusting for age and body mass index. Results Evaluated were 437 women diagnosed with breast cancer (median age, 62 years ± 17 [standard deviation]) and 1225 matched control patients (median age, 61 years ± 16). LIBRA PD showed strong correlations with Cumulus PD (
= 0.77-0.84) and Volpara VPD (
= 0.85-0.90) (
< .001 for both). For LIBRA, the strongest breast cancer association was observed for PD from processed images (OR, 1.3; 95% CI: 1.1, 1.5), although the PD association from raw images was not significantly different (OR, 1.2; 95% CI: 1.1, 1.4;
= .25). Slightly stronger breast cancer associations were seen for Cumulus PD (OR, 1.5; 95% CI: 1.3, 1.8; processed images;
= .01) and Volpara VPD (OR, 1.4; 95% CI: 1.2, 1.7; raw images;
= .004) compared with LIBRA measures. Conclusion Automated density measures provided by the Laboratory for Individualized Breast Radiodensity Assessment from raw and processed mammograms correlated with established area and volumetric density measures and showed comparable breast cancer associations. © RSNA, 2020 |
doi_str_mv | 10.1148/radiol.2020192509 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7325699</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2401813482</sourcerecordid><originalsourceid>FETCH-LOGICAL-c465t-e055c2538c4cf557a04b4a1d3b7a00b08b96132cd32fbf0f36c17fd68c1c0e363</originalsourceid><addsrcrecordid>eNpVUUlP3DAUtqqiMtD-gF4qH3sJvOclywVpGFZpqla0PVuOY4NLEg-2A-LfN2hY2tN70rdKHyGfEQ4QRX0YdedDf8CAATZMQvOOLFCyqkCO8j1ZAHBe1AKbXbKX0h8AFLKuPpBdznhTgsAFuTu91_2ksw8jDY6uL4-vlvRncPlBR0tdiPRs6vtHupxyGHS2Hf2mhyFcR7258Yae2DH5PMMp2ZQGO2bqR3ocrU6ZrvRobKRXPt3SH9F23jzFfCQ7TvfJfnq---T32emv1UWx_n5-uVquCyNKmQsLUhomeW2EcVJWGkQrNHa8nV9ooW6bEjkzHWeudeB4abByXVkbNGB5yffJ0dZ3M7WD7czcLepebaIfdHxUQXv1PzL6G3Ud7lXFmSybZjb4-mwQw91kU1aDT8b2vR5tmJJiArBGLmo2U3FLNTGkFK17jUFQT1Op7VTqbapZ8-Xffq-Kl234X7eIktg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2401813482</pqid></control><display><type>article</type><title>Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction</title><source>MEDLINE</source><source>Radiological Society of North America</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Gastounioti, Aimilia ; Kasi, Christine Damases ; Scott, Christopher G ; Brandt, Kathleen R ; Jensen, Matthew R ; Hruska, Carrie B ; Wu, Fang F ; Norman, Aaron D ; Conant, Emily F ; Winham, Stacey J ; Kerlikowske, Karla ; Kontos, Despina ; Vachon, Celine M</creator><creatorcontrib>Gastounioti, Aimilia ; Kasi, Christine Damases ; Scott, Christopher G ; Brandt, Kathleen R ; Jensen, Matthew R ; Hruska, Carrie B ; Wu, Fang F ; Norman, Aaron D ; Conant, Emily F ; Winham, Stacey J ; Kerlikowske, Karla ; Kontos, Despina ; Vachon, Celine M</creatorcontrib><description>Background The associations of density measures from the publicly available Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software with breast cancer have primarily focused on estimates from the contralateral breast at the time of diagnosis. Purpose To evaluate LIBRA measures on mammograms obtained before breast cancer diagnosis and compare their performance to established density measures. Materials and Methods For this retrospective case-control study, full-field digital mammograms in for-processing (raw) and for-presentation (processed) formats were obtained (March 2008 to December 2011) in women who developed breast cancer an average of 2 years later and in age-matched control patients. LIBRA measures included absolute dense area and area percent density (PD) from both image formats. For comparison, dense area and PD were assessed by using the research software (Cumulus), and volumetric PD (VPD) and absolute dense volume were estimated with a commercially available software (Volpara). Density measures were compared by using Spearman correlation coefficients (
), and conditional logistic regression (odds ratios [ORs] and 95% confidence intervals [CIs]) was performed to examine the associations of density measures with breast cancer by adjusting for age and body mass index. Results Evaluated were 437 women diagnosed with breast cancer (median age, 62 years ± 17 [standard deviation]) and 1225 matched control patients (median age, 61 years ± 16). LIBRA PD showed strong correlations with Cumulus PD (
= 0.77-0.84) and Volpara VPD (
= 0.85-0.90) (
< .001 for both). For LIBRA, the strongest breast cancer association was observed for PD from processed images (OR, 1.3; 95% CI: 1.1, 1.5), although the PD association from raw images was not significantly different (OR, 1.2; 95% CI: 1.1, 1.4;
= .25). Slightly stronger breast cancer associations were seen for Cumulus PD (OR, 1.5; 95% CI: 1.3, 1.8; processed images;
= .01) and Volpara VPD (OR, 1.4; 95% CI: 1.2, 1.7; raw images;
= .004) compared with LIBRA measures. Conclusion Automated density measures provided by the Laboratory for Individualized Breast Radiodensity Assessment from raw and processed mammograms correlated with established area and volumetric density measures and showed comparable breast cancer associations. © RSNA, 2020</description><identifier>ISSN: 0033-8419</identifier><identifier>EISSN: 1527-1315</identifier><identifier>DOI: 10.1148/radiol.2020192509</identifier><identifier>PMID: 32396041</identifier><language>eng</language><publisher>United States: Radiological Society of North America</publisher><subject>Aged ; Breast - diagnostic imaging ; Breast Density ; Breast Neoplasms - diagnostic imaging ; Case-Control Studies ; Female ; Humans ; Mammography - methods ; Middle Aged ; Original Research ; Radiographic Image Interpretation, Computer-Assisted - methods ; Retrospective Studies ; Risk Factors ; Software</subject><ispartof>Radiology, 2020-07, Vol.296 (1), p.24-31</ispartof><rights>2020 by the Radiological Society of North America, Inc. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c465t-e055c2538c4cf557a04b4a1d3b7a00b08b96132cd32fbf0f36c17fd68c1c0e363</citedby><cites>FETCH-LOGICAL-c465t-e055c2538c4cf557a04b4a1d3b7a00b08b96132cd32fbf0f36c17fd68c1c0e363</cites><orcidid>0000-0003-1340-0647 ; 0000-0002-1962-9322 ; 0000-0002-8492-9102 ; 0000-0001-8793-8779 ; 0000-0001-9031-5126 ; 0000-0003-0626-7219 ; 0000-0002-3359-7195 ; 0000-0003-2144-261X ; 0000-0002-6195-5201 ; 0000-0002-4208-2708</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,4013,27922,27923</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32396041$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gastounioti, Aimilia</creatorcontrib><creatorcontrib>Kasi, Christine Damases</creatorcontrib><creatorcontrib>Scott, Christopher G</creatorcontrib><creatorcontrib>Brandt, Kathleen R</creatorcontrib><creatorcontrib>Jensen, Matthew R</creatorcontrib><creatorcontrib>Hruska, Carrie B</creatorcontrib><creatorcontrib>Wu, Fang F</creatorcontrib><creatorcontrib>Norman, Aaron D</creatorcontrib><creatorcontrib>Conant, Emily F</creatorcontrib><creatorcontrib>Winham, Stacey J</creatorcontrib><creatorcontrib>Kerlikowske, Karla</creatorcontrib><creatorcontrib>Kontos, Despina</creatorcontrib><creatorcontrib>Vachon, Celine M</creatorcontrib><title>Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction</title><title>Radiology</title><addtitle>Radiology</addtitle><description>Background The associations of density measures from the publicly available Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software with breast cancer have primarily focused on estimates from the contralateral breast at the time of diagnosis. Purpose To evaluate LIBRA measures on mammograms obtained before breast cancer diagnosis and compare their performance to established density measures. Materials and Methods For this retrospective case-control study, full-field digital mammograms in for-processing (raw) and for-presentation (processed) formats were obtained (March 2008 to December 2011) in women who developed breast cancer an average of 2 years later and in age-matched control patients. LIBRA measures included absolute dense area and area percent density (PD) from both image formats. For comparison, dense area and PD were assessed by using the research software (Cumulus), and volumetric PD (VPD) and absolute dense volume were estimated with a commercially available software (Volpara). Density measures were compared by using Spearman correlation coefficients (
), and conditional logistic regression (odds ratios [ORs] and 95% confidence intervals [CIs]) was performed to examine the associations of density measures with breast cancer by adjusting for age and body mass index. Results Evaluated were 437 women diagnosed with breast cancer (median age, 62 years ± 17 [standard deviation]) and 1225 matched control patients (median age, 61 years ± 16). LIBRA PD showed strong correlations with Cumulus PD (
= 0.77-0.84) and Volpara VPD (
= 0.85-0.90) (
< .001 for both). For LIBRA, the strongest breast cancer association was observed for PD from processed images (OR, 1.3; 95% CI: 1.1, 1.5), although the PD association from raw images was not significantly different (OR, 1.2; 95% CI: 1.1, 1.4;
= .25). Slightly stronger breast cancer associations were seen for Cumulus PD (OR, 1.5; 95% CI: 1.3, 1.8; processed images;
= .01) and Volpara VPD (OR, 1.4; 95% CI: 1.2, 1.7; raw images;
= .004) compared with LIBRA measures. Conclusion Automated density measures provided by the Laboratory for Individualized Breast Radiodensity Assessment from raw and processed mammograms correlated with established area and volumetric density measures and showed comparable breast cancer associations. © RSNA, 2020</description><subject>Aged</subject><subject>Breast - diagnostic imaging</subject><subject>Breast Density</subject><subject>Breast Neoplasms - diagnostic imaging</subject><subject>Case-Control Studies</subject><subject>Female</subject><subject>Humans</subject><subject>Mammography - methods</subject><subject>Middle Aged</subject><subject>Original Research</subject><subject>Radiographic Image Interpretation, Computer-Assisted - methods</subject><subject>Retrospective Studies</subject><subject>Risk Factors</subject><subject>Software</subject><issn>0033-8419</issn><issn>1527-1315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpVUUlP3DAUtqqiMtD-gF4qH3sJvOclywVpGFZpqla0PVuOY4NLEg-2A-LfN2hY2tN70rdKHyGfEQ4QRX0YdedDf8CAATZMQvOOLFCyqkCO8j1ZAHBe1AKbXbKX0h8AFLKuPpBdznhTgsAFuTu91_2ksw8jDY6uL4-vlvRncPlBR0tdiPRs6vtHupxyGHS2Hf2mhyFcR7258Yae2DH5PMMp2ZQGO2bqR3ocrU6ZrvRobKRXPt3SH9F23jzFfCQ7TvfJfnq---T32emv1UWx_n5-uVquCyNKmQsLUhomeW2EcVJWGkQrNHa8nV9ooW6bEjkzHWeudeB4abByXVkbNGB5yffJ0dZ3M7WD7czcLepebaIfdHxUQXv1PzL6G3Ud7lXFmSybZjb4-mwQw91kU1aDT8b2vR5tmJJiArBGLmo2U3FLNTGkFK17jUFQT1Op7VTqbapZ8-Xffq-Kl234X7eIktg</recordid><startdate>20200701</startdate><enddate>20200701</enddate><creator>Gastounioti, Aimilia</creator><creator>Kasi, Christine Damases</creator><creator>Scott, Christopher G</creator><creator>Brandt, Kathleen R</creator><creator>Jensen, Matthew R</creator><creator>Hruska, Carrie B</creator><creator>Wu, Fang F</creator><creator>Norman, Aaron D</creator><creator>Conant, Emily F</creator><creator>Winham, Stacey J</creator><creator>Kerlikowske, Karla</creator><creator>Kontos, Despina</creator><creator>Vachon, Celine M</creator><general>Radiological Society of North America</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-1340-0647</orcidid><orcidid>https://orcid.org/0000-0002-1962-9322</orcidid><orcidid>https://orcid.org/0000-0002-8492-9102</orcidid><orcidid>https://orcid.org/0000-0001-8793-8779</orcidid><orcidid>https://orcid.org/0000-0001-9031-5126</orcidid><orcidid>https://orcid.org/0000-0003-0626-7219</orcidid><orcidid>https://orcid.org/0000-0002-3359-7195</orcidid><orcidid>https://orcid.org/0000-0003-2144-261X</orcidid><orcidid>https://orcid.org/0000-0002-6195-5201</orcidid><orcidid>https://orcid.org/0000-0002-4208-2708</orcidid></search><sort><creationdate>20200701</creationdate><title>Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction</title><author>Gastounioti, Aimilia ; Kasi, Christine Damases ; Scott, Christopher G ; Brandt, Kathleen R ; Jensen, Matthew R ; Hruska, Carrie B ; Wu, Fang F ; Norman, Aaron D ; Conant, Emily F ; Winham, Stacey J ; Kerlikowske, Karla ; Kontos, Despina ; Vachon, Celine M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c465t-e055c2538c4cf557a04b4a1d3b7a00b08b96132cd32fbf0f36c17fd68c1c0e363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aged</topic><topic>Breast - diagnostic imaging</topic><topic>Breast Density</topic><topic>Breast Neoplasms - diagnostic imaging</topic><topic>Case-Control Studies</topic><topic>Female</topic><topic>Humans</topic><topic>Mammography - methods</topic><topic>Middle Aged</topic><topic>Original Research</topic><topic>Radiographic Image Interpretation, Computer-Assisted - methods</topic><topic>Retrospective Studies</topic><topic>Risk Factors</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gastounioti, Aimilia</creatorcontrib><creatorcontrib>Kasi, Christine Damases</creatorcontrib><creatorcontrib>Scott, Christopher G</creatorcontrib><creatorcontrib>Brandt, Kathleen R</creatorcontrib><creatorcontrib>Jensen, Matthew R</creatorcontrib><creatorcontrib>Hruska, Carrie B</creatorcontrib><creatorcontrib>Wu, Fang F</creatorcontrib><creatorcontrib>Norman, Aaron D</creatorcontrib><creatorcontrib>Conant, Emily F</creatorcontrib><creatorcontrib>Winham, Stacey J</creatorcontrib><creatorcontrib>Kerlikowske, Karla</creatorcontrib><creatorcontrib>Kontos, Despina</creatorcontrib><creatorcontrib>Vachon, Celine M</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gastounioti, Aimilia</au><au>Kasi, Christine Damases</au><au>Scott, Christopher G</au><au>Brandt, Kathleen R</au><au>Jensen, Matthew R</au><au>Hruska, Carrie B</au><au>Wu, Fang F</au><au>Norman, Aaron D</au><au>Conant, Emily F</au><au>Winham, Stacey J</au><au>Kerlikowske, Karla</au><au>Kontos, Despina</au><au>Vachon, Celine M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction</atitle><jtitle>Radiology</jtitle><addtitle>Radiology</addtitle><date>2020-07-01</date><risdate>2020</risdate><volume>296</volume><issue>1</issue><spage>24</spage><epage>31</epage><pages>24-31</pages><issn>0033-8419</issn><eissn>1527-1315</eissn><abstract>Background The associations of density measures from the publicly available Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software with breast cancer have primarily focused on estimates from the contralateral breast at the time of diagnosis. Purpose To evaluate LIBRA measures on mammograms obtained before breast cancer diagnosis and compare their performance to established density measures. Materials and Methods For this retrospective case-control study, full-field digital mammograms in for-processing (raw) and for-presentation (processed) formats were obtained (March 2008 to December 2011) in women who developed breast cancer an average of 2 years later and in age-matched control patients. LIBRA measures included absolute dense area and area percent density (PD) from both image formats. For comparison, dense area and PD were assessed by using the research software (Cumulus), and volumetric PD (VPD) and absolute dense volume were estimated with a commercially available software (Volpara). Density measures were compared by using Spearman correlation coefficients (
), and conditional logistic regression (odds ratios [ORs] and 95% confidence intervals [CIs]) was performed to examine the associations of density measures with breast cancer by adjusting for age and body mass index. Results Evaluated were 437 women diagnosed with breast cancer (median age, 62 years ± 17 [standard deviation]) and 1225 matched control patients (median age, 61 years ± 16). LIBRA PD showed strong correlations with Cumulus PD (
= 0.77-0.84) and Volpara VPD (
= 0.85-0.90) (
< .001 for both). For LIBRA, the strongest breast cancer association was observed for PD from processed images (OR, 1.3; 95% CI: 1.1, 1.5), although the PD association from raw images was not significantly different (OR, 1.2; 95% CI: 1.1, 1.4;
= .25). Slightly stronger breast cancer associations were seen for Cumulus PD (OR, 1.5; 95% CI: 1.3, 1.8; processed images;
= .01) and Volpara VPD (OR, 1.4; 95% CI: 1.2, 1.7; raw images;
= .004) compared with LIBRA measures. Conclusion Automated density measures provided by the Laboratory for Individualized Breast Radiodensity Assessment from raw and processed mammograms correlated with established area and volumetric density measures and showed comparable breast cancer associations. © RSNA, 2020</abstract><cop>United States</cop><pub>Radiological Society of North America</pub><pmid>32396041</pmid><doi>10.1148/radiol.2020192509</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0003-1340-0647</orcidid><orcidid>https://orcid.org/0000-0002-1962-9322</orcidid><orcidid>https://orcid.org/0000-0002-8492-9102</orcidid><orcidid>https://orcid.org/0000-0001-8793-8779</orcidid><orcidid>https://orcid.org/0000-0001-9031-5126</orcidid><orcidid>https://orcid.org/0000-0003-0626-7219</orcidid><orcidid>https://orcid.org/0000-0002-3359-7195</orcidid><orcidid>https://orcid.org/0000-0003-2144-261X</orcidid><orcidid>https://orcid.org/0000-0002-6195-5201</orcidid><orcidid>https://orcid.org/0000-0002-4208-2708</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aged Breast - diagnostic imaging Breast Density Breast Neoplasms - diagnostic imaging Case-Control Studies Female Humans Mammography - methods Middle Aged Original Research Radiographic Image Interpretation, Computer-Assisted - methods Retrospective Studies Risk Factors Software |
title | Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction |
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