A deep learning framework for F-FDG PET imaging diagnosis in pediatric patients with temporal lobe epilepsy.

Journal: European journal of nuclear medicine and molecular imaging
Published Date: Jul 1, 2021

Abstract

PURPOSE: Epilepsy is one of the most disabling neurological disorders, which affects all age groups and often results in severe consequences. Since misdiagnoses are common, many pediatric patients fail to receive the correct treatment. Recently, F-fluorodeoxyglucose positron emission tomography (F-FDG PET) imaging has been used for the evaluation of pediatric epilepsy. However, the epileptic focus is very difficult to be identified by visual assessment since it may present either hypo- or hyper-metabolic abnormality with unclear boundary. This study aimed to develop a novel symmetricity-driven deep learning framework of PET imaging for the identification of epileptic foci in pediatric patients with temporal lobe epilepsy (TLE).

Authors

  • Qinming Zhang
    Department of Nuclear Medicine and PET-CT Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Yi Liao
    Department of Radiology, West China Second Hospital of Sichuan University, Chengdu, Sichuan, China.
  • Xiawan Wang
    Department of Nuclear Medicine and PET-CT Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Teng Zhang
    College of Veterinary Medicine, Hebei Agricultural University, Baoding, Hebei 071000, China.
  • Jianhua Feng
    Department of Pediatrics, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Jianing Deng
    College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
  • Kexin Shi
    Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China.
  • Lin Chen
    College of Sports, Nanjing Tech University, Nanjing, China.
  • Liu Feng
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Mindi Ma
    Department of Nuclear Medicine and PET-CT Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Le Xue
    Department of Nuclear Medicine and PET-CT Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Haifeng Hou
    Department of Nuclear Medicine and PET-CT Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Xiaofeng Dou
    Department of Nuclear Medicine and PET-CT Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Congcong Yu
    Department of Nuclear Medicine and PET-CT Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Lei Ren
    Department of Biomaterials, College of Materials, Xiamen University, Xiamen 361005, P.R. China.
  • Yao Ding
    Department of Neurology, Epilepsy Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Yufei Chen
    College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China. Electronic address: yufeichen@tongji.edu.cn.
  • Shuang Wu
  • Zexin Chen
    Center of Clinical Epidemiology & Biostatistics, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Hong Zhang
    Department of Anesthesiology and Operation, The First Hospital of Lanzhou University, Lanzhou, Gansu, China.
  • Cheng Zhuo
    College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China. czhuo@zju.edu.cn.
  • Mei Tian
    Huashan Hospital and Human Phenome Institute, Fudan University, Shanghai, China; tianmei@fudan.edu.cn hzhang21@zju.edu.cn.

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