Focal cortical dysplasia detection by artificial intelligence using MRI: A systematic review and meta-analysis
Document Type
Journal Article
Publication Date
3-29-2025
Journal
Epilepsy & behavior : E&B
Volume
167
DOI
10.1016/j.yebeh.2025.110403
Keywords
Deep learning; Drug-Resistant Epilepsy; Focal Cortical Dysplasia; Machine Learning; Magnetic Resonance Imaging
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. METHODS: A systematic search was conducted in four databases (Embase, PubMed, Scopus, and Web of Science). The quality of the studies was assessed using QUADAS-AI, and a bivariate random-effects model was used for analysis. The main outcome analyzed was the sensitivity and specificity of patient-wise outcomes. Heterogeneity among studies was assessed using I. RESULTS: A total of 41 studies met the inclusion criteria, including 24 ANN-based studies and 17 machine learning studies. Meta-analysis of internal validation datasets showed a pooled sensitivity of 0.81 and specificity of 0.92 for AI-based models in detecting FCD lesions. Meta-analysis of external validation datasets yielded a pooled sensitivity of 0.73 and specificity of 0.66. There was moderate heterogeneity among studies in the external validation dataset, but no significant publication bias was found. CONCLUSION: Although there is an increasing number of machine learning and ANN-based models for FCD detection, their clinical applicability remains limited. Further refinement and optimization, along with longitudinal studies, are needed to ensure their integration into clinical practice. Addressing the identified limitations and intensifying research efforts will improve their relevance and reliability in real medical scenarios.
APA Citation
Dashtkoohi, Mohammad; Ghadimi, Delaram J.; Moodi, Farzan; Behrang, Nima; Khormali, Ehsan; Salari, Hanieh Mobarak; Cohen, Nathan T.; Gholipour, Taha; and Saligheh Rad, Hamidreza, "Focal cortical dysplasia detection by artificial intelligence using MRI: A systematic review and meta-analysis" (2025). GW Authored Works. Paper 6741.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/6741
Department
Neurology