Focal cortical dysplasia detection by artificial intelligence using MRI: A systematic review and meta-analysis.

Journal: Epilepsy & behavior : E&B
PMID: 40158413

Abstract

PURPOSE: Focal cortical dysplasia (FCD) is a common cause of pharmacoresistant epilepsy. However, it can be challenging to detect FCD using MRI alone. This study aimed to review and analyze studies that used machine learning and artificial neural networks (ANN) methods as an additional tool to enhance MRI findings in FCD patients.

Authors

  • Mohammad Dashtkoohi
    Quantitative MR Imaging and Spectroscopy Group (QMISG), Tehran University of Medical Sciences, Tehran, Iran; Interdisciplinary Neuroscience Research Program, Tehran University of Medical Sciences, Tehran, Iran.
  • Delaram J Ghadimi
    Quantitative MR Imaging and Spectroscopy Group (QMISG), Tehran University of Medical Sciences, Tehran, Iran.
  • Farzan Moodi
    Eye Research Center, The Five Senses Institute, Rassoul Akram Hospital, Iran University of Medical Sciences, Sattarkhan-Niaiesh St., Tehran, 11335, Iran.
  • Nima Behrang
    Computer Science Department, Sharif University of Technology, Tehran, Iran.
  • Ehsan Khormali
    Student Research Committee, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran.
  • Hanieh Mobarak Salari
    Quantitative MR Imaging and Spectroscopy Group (QMISG), Tehran University of Medical Sciences, Tehran, Iran.
  • Nathan T Cohen
    Center for Neuroscience Research, Children's National Hospital, The George Washington University School of Medicine, Washington, DC, USA.
  • Taha Gholipour
    Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
  • Hamidreza Saligheh Rad
    Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences - International Campus (TUMS-IC), Tehran, Iran.

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