Deep Learning-Based Prediction of PET Amyloid Status Using MRI.

Journal: AJNR. American journal of neuroradiology
Published Date: Jun 27, 2025

Abstract

BACKGROUND AND PURPOSE: Identifying amyloid-beta (Aβ)-positive patients is essential for Alzheimer's disease (AD) clinical trials and disease-modifying treatments but currently requires PET or cerebrospinal fluid sampling. Previous MRI-based deep learning models, using only T1-weighted (T1w) images, have shown moderate performance.

Authors

  • Donghoon Kim
    The School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea.
  • Jon André Ottesen
    Computational Radiology & Artificial Intelligence (CRAI) Unit, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway. jon.a.ottesen@gmail.com.
  • Ashwin Kumar
    Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd, Stanford, CA 94305.
  • Brandon C Ho
    From the Department of Radiology (D.K., J.A.O., A.K., B.C.H., E.B.,), and the Department of Neurology and Neurological Sciences (C.B.Y., E.M.), Stanford University, Stanford, California, USA, and Computational Radiology and Artificial Intelligence (CRAI) Research Group (J.A.O), Oslo University Hospital, Oslo, Norway.
  • Elsa Bismuth
    From the Department of Radiology (D.K., J.A.O., A.K., B.C.H., E.B.,), and the Department of Neurology and Neurological Sciences (C.B.Y., E.M.), Stanford University, Stanford, California, USA, and Computational Radiology and Artificial Intelligence (CRAI) Research Group (J.A.O), Oslo University Hospital, Oslo, Norway.
  • Christina B Young
    From the Department of Radiology (D.K., J.A.O., A.K., B.C.H., E.B.,), and the Department of Neurology and Neurological Sciences (C.B.Y., E.M.), Stanford University, Stanford, California, USA, and Computational Radiology and Artificial Intelligence (CRAI) Research Group (J.A.O), Oslo University Hospital, Oslo, Norway.
  • Elizabeth Mormino
    From the Departments of Radiology (K.T.C., F.B.d.C.M., S.S., G.Z.), Electrical Engineering (E.G., J.M.P.), and Neurology and Neurological Sciences (A.B., K.L.P., S.J.S., M.D.G., E.M.), Stanford University, 1201 Welch Rd, Stanford, CA 94305; Department of Engineering Physics, Tsinghua University, Beijing, PR China (J.X.); GE Healthcare, Menlo Park, Calif (M.K.); and Subtle Medical, Menlo Park, CA (E.G.).
  • Greg Zaharchuk
    Stanford University, Stanford CA 94305, USA.

Keywords

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