True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Jan 8, 2021

Abstract

PURPOSE: While sampled or short-frame realizations have shown the potential power of deep learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose cases is lacking. Therefore, we evaluated deep learning enhancement using a significantly reduced injected radiotracer protocol for amyloid PET/MRI.

Authors

  • Kevin T Chen
    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.).
  • Tyler N Toueg
    Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
  • Mary Ellen Irene Koran
    Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.
  • Guido Davidzon
    Department of Radiology, Stanford University, Stanford, CA, United States.
  • Michael Zeineh
    Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.
  • Dawn Holley
    Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.
  • Harsh Gandhi
    Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.
  • Kim Halbert
    Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.
  • Athanasia Boumis
    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.).
  • Gabriel Kennedy
    Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
  • 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.).
  • Mehdi Khalighi
    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.

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