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Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
Hippocampal stiffness in mesial temporal lobe epilepsy measured with MR elastography: Preliminary comparison with
Graham R Huesmann1, Hillary Schwarb2, Daniel R Smith3
1Carle Neuroscience Institute, Carle Foundation Hospital, Urbana, IL, United States; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States; Department of Molecular and Integrative Physiology, University of Illinois at Urbana-Champaign, Urbana, IL, United States; Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, United States.
Abstract:
Mesial temporal lobe epilepsy (MTLE) is the most common form of refractory epilepsy. Common imaging biomarkers are often not sensitive enough to identify MTLE sufficiently early to facilitate the greatest benefit from surgical or pharmacological intervention. The objective of this work is to establish hippocampal stiffness measured with magnetic resonance elastography (MRE) as a biomarker for MTLE; we hypothesized that the epileptogenic hippocampus in MTLE is stiffer than the non-epileptogenic hippocampus. MRE was used to measure hippocampal stiffness in a group of patients with unilateral MTLE (n = 12) and a group of healthy comparison participants (n = 13). We calculated the ratio of hippocampal stiffness ipsilateral to epileptogenesis to the contralateral side for both groups. We found a higher hippocampal stiffness ratio in patients with MTLE compared with healthy participants (1.14 v. 0.99; p = 0.004), and that stiffness ratio differentiated MTLE from control groups effectively (AUC = 0.85). Hippocampal stiffness ratio, when added to volume ratio, an established MTLE biomarker, significantly improved the ability to differentiate the two groups (p = 0.038). Stiffness measured with MRE is sensitive to hippocampal pathology in MTLE and the addition of MRE to neuroimaging assessments may improve detection and characterization of the disease.
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