View in EDS HTML Full Text PDF Full Text

A practical work around for breast density distribution discrepancies between mammographic images from different vendors.

Saved in:
Bibliographic Details
Title: A practical work around for breast density distribution discrepancies between mammographic images from different vendors.
Authors: Wagner, Tobias1 (AUTHOR) tobias.wagner@uzleuven.be, Cockmartin, Lesley2 (AUTHOR), Wang, Yao-Kuan1 (AUTHOR), Marshall, Nicholas1,2 (AUTHOR), Bosmans, Hilde1,2 (AUTHOR) hilde.bosmans@uzleuven.be
Source: European Radiology. Aug2025, Vol. 35 Issue 8, p4885-4892. 8p.
Subjects: Density, Breast cancer, Mammograms, Probability density function, Retrospective studies, Measurement errors, Selection bias (Statistics)
Abstract: Objectives: Investigate the impact of mammography device grouped by vendor on volumetric breast density and propose a method that mitigates biases when determining the proportion of high-density women. Materials and methods: Density grade class and volumetric breast density distributions were obtained from mammographic images from three different vendor devices in different centers using breast density evaluation software in a retrospective study. Density distributions were compared across devices with a Mann–Whitney U test and breast density thresholds corresponding to distribution percentiles calculated. A method of matching density percentiles is proposed to determine women at potentially high risk while mitigating possible bias due to the device used for screening. Results: 2083 (mean age 59 ± 5.4), 531 (mean age 58.8 ± 5.7) and 244 (mean age 60.7 ± 6.0) screened women were evaluated on three vendor devices, respectively. Both the density grade distribution and the volumetric breast density were different between Vendor 1 and Vendor 2 data (p < 0.001) and between Vendor 1 and Vendor 3 data (p < 0.001). Between Vendor 2 and Vendor 3, no significant difference was observed (p = 0.67 for density grade, p = 0.29 for volumetric density). To recruit the top 10% of women with extremely dense breasts required respective density thresholds of 16.1%, 13.6% and 13.8% for the three vendor devices. Conclusion: Density grade class and volumetric breast density distributions differ between devices grouped by vendor and can result in statistically different breast density distributions. Percentile-dependent density thresholds can ensure unbiased selection of high-risk women. Key Points: QuestionDoes the use of x-ray systems from different vendors influence breast density evaluation and the resulting selection of high-risk women during breast cancer screening? FindingsStatistically significant differences were observed between breast density distributions of different vendors; a method of matching via percentiles is proposed to prevent biased density evaluations. Clinical relevanceMeasured breast density distributions differed between X-ray devices. A workaround is proposed that determines density thresholds corresponding to a specified population, allowing the same proportion of women to be selected with a density algorithm. [ABSTRACT FROM AUTHOR]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 186373233
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A practical work around for breast density distribution discrepancies between mammographic images from different vendors.
– Name: Author
  Label: Authors
  Group: Au
  Data: &lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Wagner%2C+Tobias%22&quot;&gt;Wagner, Tobias&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;i&gt; tobias.wagner@uzleuven.be&lt;/i&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Cockmartin%2C+Lesley%22&quot;&gt;Cockmartin, Lesley&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Wang%2C+Yao-Kuan%22&quot;&gt;Wang, Yao-Kuan&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Marshall%2C+Nicholas%22&quot;&gt;Marshall, Nicholas&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Bosmans%2C+Hilde%22&quot;&gt;Bosmans, Hilde&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt; (AUTHOR)&lt;i&gt; hilde.bosmans@uzleuven.be&lt;/i&gt;
– Name: TitleSource
  Label: Source
  Group: Src
  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22European+Radiology%22&quot;&gt;European Radiology&lt;/searchLink&gt;. Aug2025, Vol. 35 Issue 8, p4885-4892. 8p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: &lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Density%22&quot;&gt;Density&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Breast+cancer%22&quot;&gt;Breast cancer&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Mammograms%22&quot;&gt;Mammograms&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Probability+density+function%22&quot;&gt;Probability density function&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Retrospective+studies%22&quot;&gt;Retrospective studies&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Measurement+errors%22&quot;&gt;Measurement errors&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Selection+bias+%28Statistics%29%22&quot;&gt;Selection bias (Statistics)&lt;/searchLink&gt;
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Objectives: Investigate the impact of mammography device grouped by vendor on volumetric breast density and propose a method that mitigates biases when determining the proportion of high-density women. Materials and methods: Density grade class and volumetric breast density distributions were obtained from mammographic images from three different vendor devices in different centers using breast density evaluation software in a retrospective study. Density distributions were compared across devices with a Mann–Whitney U test and breast density thresholds corresponding to distribution percentiles calculated. A method of matching density percentiles is proposed to determine women at potentially high risk while mitigating possible bias due to the device used for screening. Results: 2083 (mean age 59 &#177; 5.4), 531 (mean age 58.8 &#177; 5.7) and 244 (mean age 60.7 &#177; 6.0) screened women were evaluated on three vendor devices, respectively. Both the density grade distribution and the volumetric breast density were different between Vendor 1 and Vendor 2 data (p &lt; 0.001) and between Vendor 1 and Vendor 3 data (p &lt; 0.001). Between Vendor 2 and Vendor 3, no significant difference was observed (p = 0.67 for density grade, p = 0.29 for volumetric density). To recruit the top 10% of women with extremely dense breasts required respective density thresholds of 16.1%, 13.6% and 13.8% for the three vendor devices. Conclusion: Density grade class and volumetric breast density distributions differ between devices grouped by vendor and can result in statistically different breast density distributions. Percentile-dependent density thresholds can ensure unbiased selection of high-risk women. Key Points: QuestionDoes the use of x-ray systems from different vendors influence breast density evaluation and the resulting selection of high-risk women during breast cancer screening? FindingsStatistically significant differences were observed between breast density distributions of different vendors; a method of matching via percentiles is proposed to prevent biased density evaluations. Clinical relevanceMeasured breast density distributions differed between X-ray devices. A workaround is proposed that determines density thresholds corresponding to a specified population, allowing the same proportion of women to be selected with a density algorithm. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: &lt;i&gt;Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=186373233
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00330-025-11383-w
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 8
        StartPage: 4885
    Subjects:
      – SubjectFull: Density
        Type: general
      – SubjectFull: Breast cancer
        Type: general
      – SubjectFull: Mammograms
        Type: general
      – SubjectFull: Probability density function
        Type: general
      – SubjectFull: Retrospective studies
        Type: general
      – SubjectFull: Measurement errors
        Type: general
      – SubjectFull: Selection bias (Statistics)
        Type: general
    Titles:
      – TitleFull: A practical work around for breast density distribution discrepancies between mammographic images from different vendors.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wagner, Tobias
      – PersonEntity:
          Name:
            NameFull: Cockmartin, Lesley
      – PersonEntity:
          Name:
            NameFull: Wang, Yao-Kuan
      – PersonEntity:
          Name:
            NameFull: Marshall, Nicholas
      – PersonEntity:
          Name:
            NameFull: Bosmans, Hilde
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 09387994
          Numbering:
            – Type: volume
              Value: 35
            – Type: issue
              Value: 8
          Titles:
            – TitleFull: European Radiology
              Type: main
ResultId 1