Abnormal structural connectivity in patients with epilepsy and focal cortical dysplasia (FCD)

JUAN PABLO PRINCICH; SANTIAGO COLLAVINI; MARIANO FERNÁNDEZ CORAZZA; SILVIA KOCHEN

Buenos Aires

Congreso; Congreso; 2nd FALAN Congress; 2016; 2016

Federation of Latin-American and Caribbean Societies for Neuroscience

INTRODUCTION:Brain anatomical connectivity can be inferred from DTI fiber tractography that links remote cortical regions. This process differs from the MR functional and effective connectivity were the analysis is performed considering the BOLD signal synchronic fluctuation or based on a causal relation between connected regions respectively .METHOD:Our goal is to study the brain anatomical network of epilepsy patients with FCD. For this, the anatomical connection probabilities (ACP) between 80 cortical and subcortical brain gray matter areas were obtained using an algorithm that segment anatomical regions (Freesurfer ? Deskian et al., 2006) on individual high resolution T1 MR images. The ACP measures are estimated based on a deterministic variant of the whole brain tractography (1.5T MR unit, 32 gradients directions , 800 ms B value with final isotropic resolution of 2 mm). The ACP between any two areas gives the probability that those areas are connected at least by a single nervous fiber. Then, the brain is modeled as a non-directed weighted graph with continuous arc weights given by the ACP matrix (See Workflow chart in Fig. 1).Complex networks properties such as small-world attributes, efficiency, characteristic path length , and average clustering coefficient are computed using graph theoretical analysis with BCT toolbox (Rubinov and Sporns, 2010). The analysis was carried out for 21 epilepsy patients with clinical and neuroimaging features of FCD (mean age: 23, S.D.: 11.6) and compared against 20 right-handed healthy subjects (mean age: 27, S.D.: 4.8) .Based on the same adjacency matrices, connectivity analysis was additionally performed using a cluster approach with the network based statistic (NBS) toolbox (Zalesky et al., 2010 ). This tool performs non parametric comparison of connected networks using permutation tests on supra threshold connections.RESULTS:According to the topology results, all networks have small-world characteristics. Patients brain anatomical networks also present bigger relative local efficiency (p. 019). Additionally a tendency to higher global efficiency values (p. 056) and smaller characteristic path length (p. 031) was found in a subgroup of patients (n: 11) with associated white matter anomalies (Fig. 2).Networks statistics demonstrated a connected component comprising 10 nodes and 9 links with reduced connectivity in patients (p. 015) compared with controls (Fig. 3).CONCLUSION:Our findings shows that abnormal structural connectivity detected in patients with epilepsy and FCD are associated with a more random organisation of network?s topology. Anatomical connectivity analysis based on DTI may be a sensitive tool to characterise complex brain systems in epilepsy patients wih cortical malformation.