• DocumentCode
    11670
  • Title

    Automated Characterization of Breast Lesions Imaged With an Ultrafast DCE-MR Protocol

  • Author

    Platel, Bram ; Mus, Roel ; Welte, Tessa ; Karssemeijer, Nico ; Mann, R.

  • Author_Institution
    Dept. of Radiol., Radboud Univ. Nijmegen Med. Centre, Nijmegen, Netherlands
  • Volume
    33
  • Issue
    2
  • fYear
    2014
  • fDate
    Feb. 2014
  • Firstpage
    225
  • Lastpage
    232
  • Abstract
    Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast has become an invaluable tool in the clinical work-up of patients suspected of having breast carcinoma. The purpose of this study is to introduce novel features extracted from the kinetics of contrast agent uptake imaged by a short (100 s) view-sharing MRI protocol, and to investigate how these features measure up to commonly used features for regular DCE-MRI of the breast. Performance is measured with a computer aided diagnosis (CADx) system aimed at distinguishing benign from malignant lesions. A bi-temporal breast MRI protocol was used. This protocol produces five regular, high spatial-resolution T1-weighted acquisitions interleaved with a series of 20 ultrafast view-sharing acquisitions during contrast agent uptake. We measure and compare the performances of morphological and kinetic features derived from both the regular DCE-MRI sequence and the ultrafast view-sharing sequence with four different classifiers. The classification performance of kinetics derived from the short (100 s) ultrafast acquisition starting with contrast agent administration, is significantly higher than the performance of kinetics derived from a much lengthier (510 s), commonly used 3-D gradient echo acquisition. When combined with morphology information all classifiers show a higher performance for the ultrafast acquisition (two out of four results are significantly better).
  • Keywords
    biomedical MRI; cancer; data acquisition; diagnostic radiography; feature extraction; image classification; image enhancement; image resolution; image sequences; mammography; medical image processing; tumours; 3D gradient echo acquisition; automated breast lesion imaging characterization; benign lesions; bitemporal breast MRI protocol; breast carcinoma; classification performance; computer aided diagnosis system; contrast agent administration; contrast agent uptake imaging kinetics; dynamic contrast-enhanced magnetic resonance imaging; feature extraction; high spatial-resolution T1-weighted acquisitions; kinetic features; malignant lesions; morphological features; morphology information; short view-sharing MRI protocol; time 100 s; ultrafast DCE-MRI protocol; ultrafast view-sharing acquisitions; ultrafast view-sharing sequence; Breast; Feature extraction; Kinetic theory; Lesions; Magnetic resonance imaging; Protocols; Spatial resolution; Breast; computer-aided detection and diagnosis; magnetic resonance imaging (MRI); pattern recognition and classification;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2013.2281984
  • Filename
    6601003