Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published Date: Mar 10, 2021

Abstract

BACKGROUND: The purpose of this study was to develop a voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and 3,4-dihydroxy-6-[F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) images using an unsupervised, two-level clustering approach followed by support vector machine in order to classify the isocitrate dehydrogenase (IDH) status of gliomas.

Authors

  • Hiroyuki Tatekawa
    Department of Diagnostic and Interventional Radiology, Graduate School of Medicine, Osaka Metropolitan University, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan.
  • Akifumi Hagiwara
    Department of Radiology, Juntendo University School of Medicine.
  • Hiroyuki Uetani
    Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto 860-8556, Japan (T.N., N.Y., N.K., Y.N., H.U., M.K., S.O., T.H.).
  • Shadfar Bahri
    Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
  • Catalina Raymond
    UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
  • Albert Lai
    Institute for Informatics Washington University School of Medicine St. Louis Missouri USA.
  • Timothy F Cloughesy
    UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
  • Phioanh L Nghiemphu
    UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
  • Linda M Liau
    UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
  • Whitney B Pope
    Department of Radiological Science, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA.
  • Noriko Salamon
    Department of Radiology, University of California, Los Angeles, Los Angeles, CA, USA.
  • Benjamin M Ellingson
    UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.

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