A Robust Residual Three-dimensional Convolutional Neural Networks Model for Prediction of Amyloid-β Positivity by Using FDG-PET.

Journal: Clinical nuclear medicine
Published Date: Jun 17, 2025

Abstract

BACKGROUND: Widely used in oncology PET, 2-deoxy-2- 18 F-FDG PET is more accessible and affordable than amyloid PET, which is a crucial tool to determine amyloid positivity in diagnosis of Alzheimer disease (AD). This study aimed to leverage deep learning with residual 3D convolutional neural networks (3DCNN) to develop a robust model that predicts amyloid-β positivity by using FDG-PET.

Authors

  • Ilya Ardakani
  • Takahiro Yamada
    Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osaka, Japan.
  • Sayaka Iwano
    Splink Inc, Minato-ku, Tokyo, Japan.
  • Sunil Kumar Maurya
    Department of Research and Development, Splink, Inc., Akasaka, Minato, Tokyo, Japan.
  • Kazunari Ishii
    Division of Positron Emission Tomography, Institute of Advanced Clinical Medicine, Kindai University, Osaka, Japan.

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