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Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI.

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Title: Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI.
Authors: Borde, Tabea1 (AUTHOR) tabea.borde@tum.de, Wu, Mingming1 (AUTHOR), Ruschke, Stefan1 (AUTHOR), Boehm, Christof1 (AUTHOR), Stelter, Jonathan1 (AUTHOR), Weiss, Kilian2 (AUTHOR), Metz, Stephan1 (AUTHOR), Makowski, Marcus Richard1 (AUTHOR), Karampinos, Dimitrios C.1 (AUTHOR), Fallenberg, Eva Maria1 (AUTHOR)
Source: European Radiology. Jun2023, Vol. 33 Issue 6, p3810-3818. 9p. 1 Color Photograph, 1 Black and White Photograph, 1 Diagram, 2 Charts, 2 Graphs.
Subjects: American College of Radiology, Adipose tissues, Magnetic resonance imaging, Breast exams, Density, Protons
Abstract: Objectives: There is a clinical need for a non-ionizing, quantitative assessment of breast density, as one of the strongest independent risk factors for breast cancer. This study aims to establish proton density fat fraction (PDFF) as a quantitative biomarker for fat tissue concentration in breast MRI and correlate mean breast PDFF to mammography. Methods: In this retrospective study, 193 women were routinely subjected to 3-T MRI using a six-echo chemical shift encoding-based water-fat sequence. Water-fat separation was based on a signal model accounting for a single T2* decay and a pre-calibrated 7-peak fat spectrum resulting in volumetric fat-only, water-only images, PDFF- and T2*-values. After semi-automated breast segmentation, PDFF and T2* values were determined for the entire breast and fibroglandular tissue. The mammographic and MRI-based breast density was classified by visual estimation using the American College of Radiology Breast Imaging Reporting and Data System categories (ACR A-D). Results: The PDFF negatively correlated with mammographic and MRI breast density measurements (Spearman rho: −0.74, p <.001) and revealed a significant distinction between all four ACR categories. Mean T2* of the fibroglandular tissue correlated with increasing ACR categories (Spearman rho: 0.34, p <.001). The PDFF of the fibroglandular tissue showed a correlation with age (Pearson rho: 0.56, p =.03). Conclusion: The proposed breast PDFF as an automated tissue fat concentration measurement is comparable with mammographic breast density estimations. Therefore, it is a promising approach to an accurate, user-independent, and non-ionizing breast density assessment that could be easily incorporated into clinical routine breast MRI exams. Key Points: • The proposed PDFF strongly negatively correlates with visually determined mammographic and MRI-based breast density estimations and therefore allows for an accurate, non-ionizing, and user-independent breast density measurement. • In combination with T2*, the PDFF can be used to track structural alterations in the composition of breast tissue for an individualized risk assessment for breast cancer. [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.)
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  Data: Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI.
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22European+Radiology%22&quot;&gt;European Radiology&lt;/searchLink&gt;. Jun2023, Vol. 33 Issue 6, p3810-3818. 9p. 1 Color Photograph, 1 Black and White Photograph, 1 Diagram, 2 Charts, 2 Graphs.
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  Label: Abstract
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  Data: Objectives: There is a clinical need for a non-ionizing, quantitative assessment of breast density, as one of the strongest independent risk factors for breast cancer. This study aims to establish proton density fat fraction (PDFF) as a quantitative biomarker for fat tissue concentration in breast MRI and correlate mean breast PDFF to mammography. Methods: In this retrospective study, 193 women were routinely subjected to 3-T MRI using a six-echo chemical shift encoding-based water-fat sequence. Water-fat separation was based on a signal model accounting for a single T2* decay and a pre-calibrated 7-peak fat spectrum resulting in volumetric fat-only, water-only images, PDFF- and T2*-values. After semi-automated breast segmentation, PDFF and T2* values were determined for the entire breast and fibroglandular tissue. The mammographic and MRI-based breast density was classified by visual estimation using the American College of Radiology Breast Imaging Reporting and Data System categories (ACR A-D). Results: The PDFF negatively correlated with mammographic and MRI breast density measurements (Spearman rho: −0.74, p &lt;.001) and revealed a significant distinction between all four ACR categories. Mean T2* of the fibroglandular tissue correlated with increasing ACR categories (Spearman rho: 0.34, p &lt;.001). The PDFF of the fibroglandular tissue showed a correlation with age (Pearson rho: 0.56, p =.03). Conclusion: The proposed breast PDFF as an automated tissue fat concentration measurement is comparable with mammographic breast density estimations. Therefore, it is a promising approach to an accurate, user-independent, and non-ionizing breast density assessment that could be easily incorporated into clinical routine breast MRI exams. Key Points: • The proposed PDFF strongly negatively correlates with visually determined mammographic and MRI-based breast density estimations and therefore allows for an accurate, non-ionizing, and user-independent breast density measurement. • In combination with T2*, the PDFF can be used to track structural alterations in the composition of breast tissue for an individualized risk assessment for breast cancer. [ABSTRACT FROM AUTHOR]
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  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.)
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        Value: 10.1007/s00330-022-09341-x
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        Text: English
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    Subjects:
      – SubjectFull: American College of Radiology
        Type: general
      – SubjectFull: Adipose tissues
        Type: general
      – SubjectFull: Magnetic resonance imaging
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      – SubjectFull: Breast exams
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      – SubjectFull: Density
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      – SubjectFull: Protons
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      – TitleFull: Assessing breast density using the chemical-shift encoding-based proton density fat fraction in 3-T MRI.
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              Text: Jun2023
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