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Volumetric Breast Density and Radiographic Parameters

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Breast Imaging (IWDM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8539))

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Abstract

The detection of breast cancer relies on high-quality images from digital mammography. Optimal levels of compression force are unknown, and UK national guidelines recommend forces of less than 200N. However, large variations in compression forces exist and may be influenced by the mammography practitioner and the breast size and pain threshold of the patient. This study examined the relationship between breast density and compression force. Women attending for routine breast screening and who had a mammogram taken by the same practitioner on the same equipment were included in the study (n=211). Volumetric density measurements were obtained using VolparaTM and details on imaging parameters were obtained from the DICOM headers. There was a strong, positive correlation between compression force and fibroglandular tissue. There was also evidence of a significant positive association between compression force and breast volume which was independent of the volume of fibroglandular tissue present.

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Author information

Authors and Affiliations

  1. Manchester Medical School, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK

    Jennifer Khan-Perez

  2. Centre for Imaging Sciences, Institute of Population Health, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK

    Elaine Harkness, Jamie Sergeant, Anthony Maxwell & Susan M. Astley

  3. Genesis Breast Cancer Prevention Centre, University Hospital of South Manchester NHS Trust, Wythenshawe, Manchester, M23 9LT, UK

    Elaine Harkness, Clare Mercer, Megan Bydder, Anthony Maxwell, Catherine Rylance & Susan M. Astley

  4. Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, The University of Manchester, Wythenshawe, Manchester, M23 9LT, UK

    Elaine Harkness, Julie Morris, Anthony Maxwell & Susan M. Astley

  5. Arthritis Research UK Centre for Epidemiology, Institute of Inflammation and Repair, Faculty of Medical and Human Sciences, Manchester Academic Health Science Centre, University of Manchester, Oxford Road, Manchester, M13 9PT, UK

    Jamie Sergeant

  6. NIHR Manchester Musculoskeletal Biomedical Research Unit, Central Manchester NHS Foundation Trust, Manchester Academic Health Science Centre, UK

    Jamie Sergeant

  7. Centre for Biostatistics, Institute of Population Health, University of Manchester, Oxford Road, Manchester, M13 9PT, UK

    Julie Morris

  8. Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Christie Hospital, Withington, Manchester, M20 4BX, UK

    Anthony Maxwell & Susan M. Astley

Authors
  1. Jennifer Khan-Perez
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  2. Elaine Harkness
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  3. Clare Mercer
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  4. Megan Bydder
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  5. Jamie Sergeant
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  6. Julie Morris
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  7. Anthony Maxwell
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  8. Catherine Rylance
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  9. Susan M. Astley
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Editor information

Editors and Affiliations

  1. Department of Intelligent Image Information, Gifu University Graduate School of Medicine, 1-1 Yanagido, 501-1194, Gifu, Gifu, Japan

    Hiroshi Fujita , Takeshi Hara  & Chisako Muramatsu ,  & 

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© 2014 Springer International Publishing Switzerland

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Khan-Perez, J. et al. (2014). Volumetric Breast Density and Radiographic Parameters. In: Fujita, H., Hara, T., Muramatsu, C. (eds) Breast Imaging. IWDM 2014. Lecture Notes in Computer Science, vol 8539. Springer, Cham. https://doi.org/10.1007/978-3-319-07887-8_38

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  • DOI: https://doi.org/10.1007/978-3-319-07887-8_38

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07886-1

  • Online ISBN: 978-3-319-07887-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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