Automatic identification of atherosclerosis subjects in a heterogeneous MR brain imaging data set.

Journal: Magnetic resonance imaging
PMID: 31228556

Abstract

Carotid-artery atherosclerosis (CA) contributes significantly to overall morbidity and mortality in ischemic stroke. We propose a machine learning technique to automatically identify subjects with CA from a heterogeneous cohort of magnetic resonance brain images. The cohort includes 190 subjects with CA, white mater hyperintensites of presumed vascular origin or multiple sclerosis, as well as 211 presumed healthy subjects. We determined a set of handcrafted and convolutional discriminant features to perform this task. A support vector machine (SVM) was used to perform this four-class classification task. Our approach had an accuracy rate of 97.5% (higher than chance accuracy of 52.6% for guessing majority class), sensitivity of 96.4% and specificity of 97.9% in identifying subjects with CA, suggesting that the proposed combination of features may be used as an imaging biomarker for characterizing atherosclerotic disease on brain imaging.

Authors

  • Mariana Bento
    Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Seaman Family MR Research Centre, Foothills Medical Center, Calgary, AB, Canada; Calgary Image Processing and Analysis Center (CIPAC), Foothills Medical Centre, Calgary, AB, Canada. Electronic address: mariana.pinheirobent@ucalgary.ca.
  • Roberto Souza
    Medical Imaging and Computing Laboratory, Department of Computer Engineering and Industrial Automation, University of Campinas, Campinas, São Paulo, Brazil; Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada; Seaman Family Magnetic Resonance Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada. Electronic address: roberto.medeirosdeso@ucalgary.ca.
  • Marina Salluzzi
    Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; Calgary Image Processing and Analysis Center (CIPAC), Foothills Medical Centre, Calgary, AB, Canada.
  • Letícia Rittner
    Medical Imaging and Computing Laboratory, Department of Computer Engineering and Industrial Automation, University of Campinas, Campinas, São Paulo, Brazil.
  • Yunyan Zhang
    Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
  • Richard Frayne
    Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada; Calgary Image Processing and Analysis Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada; Seaman Family Magnetic Resonance Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Alberta, Canada.

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