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Updated: Mar 25, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
Multidimensional Profiling of MRI-Negative Temporal Lobe Epilepsy Uncovers Distinct Phenotypes
Alice Ballerini1, Alessia Casarini1, Niccolò Biagioli1
1Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.
Objective:
Although hippocampal sclerosis (TLE-HS) represents the most frequent cause of temporal lobe epilepsy (TLE), up to 30% of patients show no lesion on visual MRI inspection (TLE-MRIneg). These cases pose diagnostic and therapeutic challenges and are underrepresented in surgical series. We investigated whether TLE-MRIneg constitutes a distinct clinical and neuroanatomical entity compared to TLE-HS and aimed to identify subtypes within the TLE-MRIneg group.
Methods:
We analyzed MRI and clinical data from 209 patients with TLE and 102 healthy controls from the multicenter "3TLE project". Based on expert radiological review, 96 patients were classified as TLE-MRIneg and 76 as TLE-HS; the remaining 37 were excluded due to other focal lesions. We compared clinical characteristics and brain morphometry between TLE-MRIneg and TLE-HS and applied clustering techniques to detect TLE-MRIneg subtypes.
Results:
Compared with TLE-HS, TLE-MRIneg was associated with later onset, shorter disease duration, and milder clinical presentation. TLE-HS patients exhibited widespread cortical and subcortical atrophy, while TLE-MRIneg showed only subtle cortical thinning. Cluster analysis revealed two subtypes of TLE-MRIneg: one characterized by ipsilateral amygdala enlargement (AE) and the other by diffuse cortical atrophy.
Interpretation:
These findings demonstrate that TLE-MRIneg represents a distinct clinical-imaging entity from TLE-HS. The identification of morphologically defined subtypes, particularly AE, highlights the heterogeneity of TLE-MRIneg and its potential clinical relevance. This work supports the use of advanced imaging and data-driven methods to improve diagnosis and guide individualized management in non-lesional epilepsies.
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