Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance.

Journal: Japanese journal of radiology
PMID: 37256470

Abstract

PURPOSE: Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson's disease (PD) by showing reduced signals in the substantia nigra (SN) and locus coeruleus (LC), but requires a long scan time. The aim of this study was to assess the image quality and diagnostic performance of NM-MRI with a shortened scan time using a denoising approach with deep learning-based reconstruction (dDLR).

Authors

  • Sonoko Oshima
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Yasutaka Fushimi
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University.
  • Kanae Kawai Miyake
    Department of Advanced Medical Imaging Research, Graduate School of Medicine, Kyoto University.
  • Satoshi Nakajima
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University.
  • Akihiko Sakata
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku Kyoto 606-8507, Japan.
  • Sachi Okuchi
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Takuya Hinoda
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku Kyoto 606-8507, Japan.
  • Sayo Otani
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Hitomi Numamoto
    Department of Advanced Medical Imaging Research, Graduate School of Medicine, Kyoto University.
  • Koji Fujimoto
    Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Atsushi Shima
    Department of Regenerative Systems Neuroscience, Human Brain Research Center, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Masahito Nambu
    MRI Systems Division, Canon Medical Systems Corporation.
  • Nobukatsu Sawamoto
    Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Ryosuke Takahashi
    Department of Urology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
  • Kentaro Ueno
    Department of Biomedical Statistics and Bioinformatics, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
  • Tsuneo Saga
    Department of Advanced Medical Imaging Research, Graduate School of Medicine, Kyoto University.
  • Yuji Nakamoto
    Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University.

Keywords

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