Prediction of breast cancer risk by automated volumetric breast density measurement
Purpose Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women. Materials and methods We r...
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| Veröffentlicht in: | Japanese journal of radiology 2023-01, Vol.41 (1), p.54-62 |
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| container_title | Japanese journal of radiology |
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| creator | Nara, Miyako Fujioka, Tomoyuki Mori, Mio Aruga, Tomoyuki Tateishi, Ukihide |
| description | Purpose
Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women.
Materials and methods
We retrospectively analyzed 635 BC patients and 999 controls who received a mammography at our hospital between February 2019 and March 2021. Volumetric breast density percentage (VBD%), breast volume (BV), and fibroglandular volume (FGV) were measured using Volpara
™
, an automated, three-dimensional image analysis program. A VBD% of 7.5% or higher was classified as DB. The association between the VBD%, BV, and FGV, and BC risk were assessed using logistic regression.
Results
Of the BC group and the control group, 77% and 79% had DB. The stratified FGV was positively associated with BC risk (odds ratio: 2.84; 95% confidence interval 1.58–5.12;
P
|
| doi_str_mv | 10.1007/s11604-022-01320-y |
| format | Article |
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Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women.
Materials and methods
We retrospectively analyzed 635 BC patients and 999 controls who received a mammography at our hospital between February 2019 and March 2021. Volumetric breast density percentage (VBD%), breast volume (BV), and fibroglandular volume (FGV) were measured using Volpara
™
, an automated, three-dimensional image analysis program. A VBD% of 7.5% or higher was classified as DB. The association between the VBD%, BV, and FGV, and BC risk were assessed using logistic regression.
Results
Of the BC group and the control group, 77% and 79% had DB. The stratified FGV was positively associated with BC risk (odds ratio: 2.84; 95% confidence interval 1.58–5.12;
P
< 0.001). No significant association was found between either the VBD% or BV and BC risk.
Conclusion
The proportion of Japanese women with DB was high, suggesting that DB might not be significantly associated with BC risk. However, our results also suggested that the FGV may be related to BC risk in Japanese women.</description><identifier>ISSN: 1867-1071</identifier><identifier>EISSN: 1867-108X</identifier><identifier>DOI: 10.1007/s11604-022-01320-y</identifier><identifier>PMID: 35913644</identifier><language>eng</language><publisher>Singapore: Springer Nature Singapore</publisher><subject>Automation ; Breast - diagnostic imaging ; Breast cancer ; Breast Density ; Breast Neoplasms - diagnostic imaging ; Breast Neoplasms - epidemiology ; Density measurement ; Female ; Health risks ; Humans ; Image analysis ; Image processing ; Imaging ; Mammography ; Mammography - methods ; Medicine ; Medicine & Public Health ; Nuclear Medicine ; Original Article ; Radiology ; Radiotherapy ; Retrospective Studies ; Risk factors ; Statistical analysis ; Three dimensional analysis</subject><ispartof>Japanese journal of radiology, 2023-01, Vol.41 (1), p.54-62</ispartof><rights>The Author(s) under exclusive licence to Japan Radiological Society 2022. corrected publication 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2022. The Author(s) under exclusive licence to Japan Radiological Society.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c520t-2c69ed74d372c08ff5b7bf42f238bcd9cec36da8c7479d6669b99e02e91800743</citedby><cites>FETCH-LOGICAL-c520t-2c69ed74d372c08ff5b7bf42f238bcd9cec36da8c7479d6669b99e02e91800743</cites><orcidid>0000-0002-7141-8901</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11604-022-01320-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11604-022-01320-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35913644$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Nara, Miyako</creatorcontrib><creatorcontrib>Fujioka, Tomoyuki</creatorcontrib><creatorcontrib>Mori, Mio</creatorcontrib><creatorcontrib>Aruga, Tomoyuki</creatorcontrib><creatorcontrib>Tateishi, Ukihide</creatorcontrib><title>Prediction of breast cancer risk by automated volumetric breast density measurement</title><title>Japanese journal of radiology</title><addtitle>Jpn J Radiol</addtitle><addtitle>Jpn J Radiol</addtitle><description>Purpose
Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women.
Materials and methods
We retrospectively analyzed 635 BC patients and 999 controls who received a mammography at our hospital between February 2019 and March 2021. Volumetric breast density percentage (VBD%), breast volume (BV), and fibroglandular volume (FGV) were measured using Volpara
™
, an automated, three-dimensional image analysis program. A VBD% of 7.5% or higher was classified as DB. The association between the VBD%, BV, and FGV, and BC risk were assessed using logistic regression.
Results
Of the BC group and the control group, 77% and 79% had DB. The stratified FGV was positively associated with BC risk (odds ratio: 2.84; 95% confidence interval 1.58–5.12;
P
< 0.001). No significant association was found between either the VBD% or BV and BC risk.
Conclusion
The proportion of Japanese women with DB was high, suggesting that DB might not be significantly associated with BC risk. However, our results also suggested that the FGV may be related to BC risk in Japanese women.</description><subject>Automation</subject><subject>Breast - diagnostic imaging</subject><subject>Breast cancer</subject><subject>Breast Density</subject><subject>Breast Neoplasms - diagnostic imaging</subject><subject>Breast Neoplasms - epidemiology</subject><subject>Density measurement</subject><subject>Female</subject><subject>Health risks</subject><subject>Humans</subject><subject>Image analysis</subject><subject>Image processing</subject><subject>Imaging</subject><subject>Mammography</subject><subject>Mammography - methods</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Nuclear Medicine</subject><subject>Original Article</subject><subject>Radiology</subject><subject>Radiotherapy</subject><subject>Retrospective Studies</subject><subject>Risk factors</subject><subject>Statistical analysis</subject><subject>Three dimensional analysis</subject><issn>1867-1071</issn><issn>1867-108X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1LxDAQhoMofqz-AQ9S8OKlOvnYpDmK-AULCip4C20yleq2XZNU6L83uusKHjxlQp55J_MQckjhlAKos0CpBJEDYzlQziAfN8guLaTKKRTPm-ta0R2yF8IrgBRciG2yw6eacinELnm49-gaG5u-y_o6qzyWIWa27Cz6zDfhLavGrBxi35YRXfbRz4cWo2_sD-qwC00cszbdBo8tdnGfbNXlPODB6pyQp6vLx4ubfHZ3fXtxPsvtlEHMmZUanRKOK2ahqOtppapasJrxorJOW7RcurKwSijtpJS60hqBoaZFWl_wCTlZ5i58_z5giKZtgsX5vOywH4JhUivQDKYsocd_0Nd-8F36nWGFBs4LySBRbElZ34fgsTYL37SlHw0F86XcLJWbpNx8KzdjajpaRQ9Vi27d8uM4AXwJhPTUvaD_nf1P7CfhCozv</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Nara, Miyako</creator><creator>Fujioka, Tomoyuki</creator><creator>Mori, Mio</creator><creator>Aruga, Tomoyuki</creator><creator>Tateishi, Ukihide</creator><general>Springer Nature Singapore</general><general>Springer Nature B.V</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>3V.</scope><scope>7QO</scope><scope>7RV</scope><scope>7TK</scope><scope>7U7</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-7141-8901</orcidid></search><sort><creationdate>20230101</creationdate><title>Prediction of breast cancer risk by automated volumetric breast density measurement</title><author>Nara, Miyako ; Fujioka, Tomoyuki ; Mori, Mio ; Aruga, Tomoyuki ; Tateishi, Ukihide</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c520t-2c69ed74d372c08ff5b7bf42f238bcd9cec36da8c7479d6669b99e02e91800743</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Automation</topic><topic>Breast - diagnostic imaging</topic><topic>Breast cancer</topic><topic>Breast Density</topic><topic>Breast Neoplasms - diagnostic imaging</topic><topic>Breast Neoplasms - epidemiology</topic><topic>Density measurement</topic><topic>Female</topic><topic>Health risks</topic><topic>Humans</topic><topic>Image analysis</topic><topic>Image processing</topic><topic>Imaging</topic><topic>Mammography</topic><topic>Mammography - methods</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Nuclear Medicine</topic><topic>Original Article</topic><topic>Radiology</topic><topic>Radiotherapy</topic><topic>Retrospective Studies</topic><topic>Risk factors</topic><topic>Statistical analysis</topic><topic>Three dimensional analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nara, Miyako</creatorcontrib><creatorcontrib>Fujioka, Tomoyuki</creatorcontrib><creatorcontrib>Mori, Mio</creatorcontrib><creatorcontrib>Aruga, Tomoyuki</creatorcontrib><creatorcontrib>Tateishi, Ukihide</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>Natural Science Collection (ProQuest)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>Japanese journal of radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nara, Miyako</au><au>Fujioka, Tomoyuki</au><au>Mori, Mio</au><au>Aruga, Tomoyuki</au><au>Tateishi, Ukihide</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of breast cancer risk by automated volumetric breast density measurement</atitle><jtitle>Japanese journal of radiology</jtitle><stitle>Jpn J Radiol</stitle><addtitle>Jpn J Radiol</addtitle><date>2023-01-01</date><risdate>2023</risdate><volume>41</volume><issue>1</issue><spage>54</spage><epage>62</epage><pages>54-62</pages><issn>1867-1071</issn><eissn>1867-108X</eissn><abstract>Purpose
Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women.
Materials and methods
We retrospectively analyzed 635 BC patients and 999 controls who received a mammography at our hospital between February 2019 and March 2021. Volumetric breast density percentage (VBD%), breast volume (BV), and fibroglandular volume (FGV) were measured using Volpara
™
, an automated, three-dimensional image analysis program. A VBD% of 7.5% or higher was classified as DB. The association between the VBD%, BV, and FGV, and BC risk were assessed using logistic regression.
Results
Of the BC group and the control group, 77% and 79% had DB. The stratified FGV was positively associated with BC risk (odds ratio: 2.84; 95% confidence interval 1.58–5.12;
P
< 0.001). No significant association was found between either the VBD% or BV and BC risk.
Conclusion
The proportion of Japanese women with DB was high, suggesting that DB might not be significantly associated with BC risk. However, our results also suggested that the FGV may be related to BC risk in Japanese women.</abstract><cop>Singapore</cop><pub>Springer Nature Singapore</pub><pmid>35913644</pmid><doi>10.1007/s11604-022-01320-y</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-7141-8901</orcidid></addata></record> |
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| identifier | ISSN: 1867-1071 |
| ispartof | Japanese journal of radiology, 2023-01, Vol.41 (1), p.54-62 |
| issn | 1867-1071 1867-108X |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2697092052 |
| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | Automation Breast - diagnostic imaging Breast cancer Breast Density Breast Neoplasms - diagnostic imaging Breast Neoplasms - epidemiology Density measurement Female Health risks Humans Image analysis Image processing Imaging Mammography Mammography - methods Medicine Medicine & Public Health Nuclear Medicine Original Article Radiology Radiotherapy Retrospective Studies Risk factors Statistical analysis Three dimensional analysis |
| title | Prediction of breast cancer risk by automated volumetric breast density measurement |
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