Curtin University Homepage
  • Library
  • Help
    • Admin

    espace - Curtin’s institutional repository

    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item
    • espace Home
    • espace
    • Curtin Research Publications
    • View Item

    Analysing breast tissue composition with MRI using currently available short, simple sequences

    Access Status
    Fulltext not available
    Authors
    Chau, Anson
    Hua, J.
    Taylor, D.
    Date
    2016
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Chau, A. and Hua, J. and Taylor, D. 2016. Analysing breast tissue composition with MRI using currently available short, simple sequences. Clinical Radiology. 71 (3): pp. 287-292.
    Source Title
    Clinical Radiology
    DOI
    10.1016/j.crad.2015.11.020
    ISSN
    0009-9260
    School
    Department of Medical Radiation Sciences
    URI
    http://hdl.handle.net/20.500.11937/50785
    Collection
    • Curtin Research Publications
    Abstract

    © 2015 The Royal College of Radiologists. Aim: To determine the most robust commonly available magnetic resonance imaging (MRI) sequence to quantify breast tissue composition at 1.5 T. Materials and methods: Two-dimensional (2D) T1-weighted, Dixon fat, Dixon water and SPAIR images were obtained from five participants and a breast phantom using a 1.5 T Siemens Aera MRI system. Manual segmentation of the breasts was performed, and an in-house computer program was used to generate signal intensity histograms. Relative trough depth and relative peak separation were used to determine the robustness of the images for quantifying the two breast tissues. Total breast volumes and percentage breast densities calculated using the four sequences were compared. Results: Dixon fat histograms had consistently low relative trough depth and relative peak separation compared to those obtained using other sequences. There was no significant difference in total breast volumes and percentage breast densities of the participants or breast phantom using Dixon fat and 2D T1-weighted histograms. Dixon water and SPAIR histograms were not suitable for quantifying breast tissue composition. Conclusion: Dixon fat images are the most robust for the quantification of breast tissue composition using a signal intensity histogram.

    Related items

    Showing items related by title, author, creator and subject.

    • Quantitative Measurement of Breast Density Using Personalized 3D-Printed Breast Model for Magnetic Resonance Imaging
      Sindi, Rooa ; Wong, Y.H.; Yeong, C.H.; Sun, Zhonghua (2020)
      Despite the development and implementation of several MRI techniques for breast density assessments, there is no consensus on the optimal protocol in this regard. This study aimed to determine the most appropriate MRI ...
    • Quantitative Measurements of Breast Density Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis
      Sindi, Rooa; Sa dos Reis, Claudia; Bennett, Colleen; Stevenson, G.; Sun, Zhonghua (2019)
      Breast density, a measure of dense fibroglandular tissue relative to non-dense fatty tissue, is confirmed as an independent risk factor of breast cancer. Although there has been an increasing interest in the quantitative ...
    • Breastfeeding and perceptions of breast shape changes in Australian and Japanese women
      Inoue, Madoka (2012)
      This thesis examines infant feeding practices, including knowledge and attitudes towards breastfeeding, factors that influence the duration of breastfeeding, and breastfeeding outcomes in relation to postpartum women’s ...
    Advanced search

    Browse

    Communities & CollectionsIssue DateAuthorTitleSubjectDocument TypeThis CollectionIssue DateAuthorTitleSubjectDocument Type

    My Account

    Admin

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Follow Curtin

    • 
    • 
    • 
    • 
    • 

    CRICOS Provider Code: 00301JABN: 99 143 842 569TEQSA: PRV12158

    Copyright | Disclaimer | Privacy statement | Accessibility

    Curtin would like to pay respect to the Aboriginal and Torres Strait Islander members of our community by acknowledging the traditional owners of the land on which the Perth campus is located, the Whadjuk people of the Nyungar Nation; and on our Kalgoorlie campus, the Wongutha people of the North-Eastern Goldfields.