DTI-based response-driven modeling of mTLE laterality

Abstract

PurposeTo develop lateralization models for distinguishing between unilateral and bilateral mesial temporal lobe epilepsy (mTLE) and determining laterality in cases of unilateral mTLE.BackgroundmTLE is the most common form of medically refractory focal epilepsy. Many mTLE patients fail to demonstrate an unambiguous unilateral ictal onset. Intracranial EEG (icEEG) monitoring can be performed to establish whether the ictal origin is unilateral or truly bilateral with independent bitemporal ictal origin. However, because of the expense and risk of intracranial electrode placement, much research has been done to determine if the need for icEEG can be obviated with noninvasive neuroimaging methods, such as diffusion tensor imaging (DTI).MethodsFractional anisotropy (FA) was used to quantify microstructural changes reflected in the diffusivity properties of the corpus callosum, cingulum, and fornix, in a retrospective cohort of 31 patients confirmed to have unilateral (n = 24) or bilateral (n = 7) mTLE. All unilateral mTLE patients underwent resection with an Engel class I outcome. Eleven were reported to have hippocampal sclerosis on pathological analysis; nine had undergone prior icEEG. The bilateral mTLE patients had undergone icEEG demonstrating independent epileptiform activity in both right and left hemispheres. Twenty-three nonepileptic subjects were included as controls.ResultsIn cases of right mTLE, FA showed significant differences from control in all callosal subregions, in both left and right superior cingulate subregions, and in forniceal crura. Comparison of right and left mTLE cases showed significant differences in FA of callosal genu, rostral body, and splenium and the right posteroinferior and superior cingulate subregions. In cases of left mTLE, FA showed significant differences from control only in the callosal isthmus. Significant differences in FA were identified when cases of right mTLE were compared with bilateral mTLE cases in the rostral and midbody callosal subregions and isthmus. Based on 11 FA measurements in the cingulate, callosal and forniceal subregions, a response-driven lateralization model successfully differentiated all cases (n = 54) into groups of unilateral right (n = 12), unilateral left (n = 12), and bilateral mTLE (n = 7), and nonepileptic control (23).ConclusionThe proposed response-driven DTI biomarker is intended to lessen diagnostic ambiguity of laterality in cases of mTLE and help optimize selection of surgical candidates. Application of this model shows promise in reducing the need for invasive icEEG in prospective cases.

MEG Coherence and DTI Connectivity in mTLE

“…Loss of anisotropy has been demonstrated in the arcuate fasciculus (Powell et al, 2007, Govindan et al, 2008), uncinate fasciculus (Rodrigo et al, 2007), external capsule (Gross et al, 2006), inferior longitudinal fasciculus (Govindan et al, 2008), corpus callosum (Chahboune et al, 2009, Nazem-Zadeh et al, 2015), the afferent and efferent tracts of the parahippocampal gyrus (Yogarajah et al, 2008), fornix and cingulum (Concha et al, 2005, Concha et al, 2009, Nazem-Zadeh et al, 2014c, Nazem-Zadeh et al, 2015), thalamic fibers (Bonilha et al, 2012) and widely spread tracts in the temporal lobe ipsilateral to epileptic focus (Concha et al, 2005, Focke et al, 2008). The apparent diffusion coefficient (ADC) is calculated from the trace of the diagonalized diffusion tensor to give the mean bulk mobility of water without directional information.…”

“…Two-way repeated measures analysis of variance (RMANOVA) was used to examine the relationships of the MEG coherence laterality measurements and the DTI nodal degree laterality measurements with the brain regions (i.e., a repeated factor) and the mTLE laterality type (i.e., a fixed factor) (Nazem-Zadeh et al, 2015). Of particular interest were tests for interaction between a region and a laterality type, since a significant interaction would imply that separate one-way ANOVAs are required to assess mTLE laterality type.…”

Application of DTI connectivity in lateralization of mTLE

“…Previous studies suggest that abnormal water diffusion, identified as changes in FA or MD, may be found in identified white matter tracts of epileptic networks in both temporal and extratemporal structures [14, 19]. Investigation of structural connectivity in mTLE using DTI has shown similar promise in lateralizing epileptogenicity [20].…”

“…Two-way repeated measures analysis of variance (RMANOVA) was used to examine the relationships of the ND laterality measurements with the brain regions (i.e., a repeated factor) and the mTLE laterality type (i.e., a fixed factor) [14]. Of particular interest were tests for interaction between a region and a laterality type, since a significant interaction would imply that separate one-way ANOVAs are required to assess mTLE laterality type.…”

Application of MEG coherence in lateralization of mTLE

“…Two-way repeated measures analysis of variance (RMANOVA) was used to examine the relationships of the MEG coherence laterality measurements with the brain regions (i.e., a repeated factor) and the mTLE laterality type (i.e., a fixed factor) [26]. Of particular interest were tests for interaction between a region and a laterality type, since a significant interaction would imply that separate one-way ANOVAs are required to assess mTLE laterality type.…”