Automated detection of hippocampal sclerosis using clinically empirical and radiomics features.

Journal: Epilepsia
PMID: 31769021

Abstract

OBJECTIVE: Temporal lobe epilepsy is a common form of epilepsy that might be amenable to surgery. However, magnetic resonance imaging (MRI)-negative hippocampal sclerosis (HS) can hamper early diagnosis and surgical intervention for patients in clinical practice, resulting in disease progression. Our aim was to automatically detect and evaluate the structural alterations of HS.

Authors

  • Jiajie Mo
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Zhenyu Liu
    School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Kai Sun
    Department of Materials Science and Engineering, Jinan University.
  • Yanshan Ma
    Epilepsy Center, Peking University First Hospital Fengtai Hospital, Beijing, China.
  • Wenhan Hu
    Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Chao Zhang
    School of Information Engineering, Suqian University, Suqian, Jiangsu, China.
  • Yao Wang
    Department of Gastrointestinal Surgery, Zhongshan People's Hospital, Zhongshan, Guangdong, China.
  • Xiu Wang
    Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Chang Liu
    Key Lab of Cell Differentiation and Apoptosis of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Baotian Zhao
    Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
  • Kai Zhang
    Anhui Province Key Laboratory of Respiratory Tumor and Infectious Disease, First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
  • Jianguo Zhang
    College of Automation, Harbin Engineering University, No. 145, Nantong street, Harbin, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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