Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.

Journal: Neuroradiology
Published Date: Jul 1, 2023

Abstract

PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (I-FP-CIT) single-photon emission computerized tomography (SPECT) can evaluate Parkinsonism. Nigral hyperintensity from nigrosome-1 and striatal dopamine transporter uptake are reduced in Parkinsonism; however, quantification is only possible with SPECT. Here, we aimed to develop a deep-learning-based regressor model that can predict striatal I-FP-CIT uptake on nigrosome magnetic resonance imaging (MRI) as a biomarker for Parkinsonism.

Authors

  • Yun Jung Bae
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Byung Se Choi
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.
  • Jong-Min Kim
    Department of Clinical Pharmacology and Toxicology, Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
  • Walid Abdullah Ai
    Division of Computer Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea.
  • Ildong Yun
    Division of Computer Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea.
  • Yoo Sung Song
    Departments of Nuclear Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea.
  • Yoonho Nam
    Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, Catholic University of Korea, Seoul, Republic of Korea.
  • Se Jin Cho
    Department of Radiology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Gyeonggi, Republic of Korea.
  • Jae Hyoung Kim
    Department of Radiology, Seoul National University Bundang Hospital, Seongnam.

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