Kelly M. Leyden

White matter microstructure complements morphometry for predicting verbal memory in epilepsy.

Verbal memory is the most commonly impaired cognitive domain in patients with temporal lobe epilepsy (TLE). Although damage to the hippocampus and adjacent temporal lobe structures is known to contribute to memory impairment, little is known of the relative contributions of white versus gray matter structures, or whether microstructural versus morphometric measures of temporal lobe pathology are stronger predictors of impairment. We evaluate whether measures of temporal lobe pathology derived from diffusion tensor imaging (DTI; microstructural) versus structural MRI (sMRI; morphometric) contribute the most to memory performances in TLE, after controlling for hippocampal volume (HCV). DTI and sMRI were performed on 26 patients with TLE and 35 controls. Verbal memory was measured with the Logical Memory (LM) subtest of the Wechsler Memory Scale-III. Hierarchical regression analyses were performed to examine unique contributions of DTI and sMRI measures to verbal memory with HCV entered in block 1. In patients, impaired recall was associated with increased mean diffusivity (MD) of multiple fiber tracts that project through the temporal lobes. In addition, increased MD of the left cortical and bilateral pericortical white matter was associated with impaired recall. After controlling for left HCV, only microstructural measures of white matter pathology contributed to verbal recall. The best predictive model included left HCV and MD of the left inferior longitudinal fasciculus (ILF) and pericortical white matter beneath the left entorhinal cortex. This model explained 60% of the variance in delayed recall and revealed that MD of the left ILF was the strongest predictor. These data reveal that white matter microstructure within the temporal lobe can be used in conjunction with left HCV to enhance the prediction of verbal memory impairment, and speak to the complementary nature of DTI and sMRI for understanding cognitive dysfunction in epilepsy and possibly other memory disorders.

Frontolimbic Brain Networks Predict Depressive Symptoms in Temporal Lobe Epilepsy

Psychiatric co-morbidities in epilepsy are of great concern. The current study investigated the relative contribution of structural and functional connectivity (FC) between medial temporal (MT) and prefrontal regions in predicting levels of depressive symptoms in patients with temporal lobe epilepsy (TLE). Twenty-one patients with TLE [11 left TLE (LTLE); 10 right TLE (RTLE)] and 20 controls participated. Diffusion tensor imaging was performed to obtain fractional anisotropy (FA) of the uncinate fasciculus (UF), and mean diffusivity (MD) of the amygdala (AM) and hippocampus (HC). Functional MRI was performed to obtain FC strengths between the AM and HC and prefrontal regions of interest including anterior prefrontal (APF), orbitofrontal, and inferior frontal regions. Participants self-reported depression symptoms on the Beck Depression Inventory-II. Greater depressive symptoms were associated with stronger FC of ipsilateral HC-APF, lower FA of the bilateral UF, and higher MD of the ipsilateral HC in LTLE, and with lower FA of the contralateral UF in RTLE. Regression analyses indicated that FC of the ipsilateral HC-APF was the strongest contributor to depression in LTLE, explaining 68.7% of the variance in depression scores. Both functional and microstructural measures of frontolimbic dysfunction were associated with depressive symptoms. These connectivity variables may be moderating which patients present with depression symptoms. In particular, FC MRI may provide a more sensitive measure of depression-related dysfunction, at least in patients with LTLE. Employing sensitive measures of frontolimbic network dysfunction in TLE may help provide new insight into mood disorders in epilepsy that could eventually guide treatment planning.

Heterogeneous cortical atrophy patterns in MCI not captured by conventional diagnostic criteria

Objective: We investigated differences in regional cortical thickness between previously identified empirically derived mild cognitive impairment (MCI) subtypes (amnestic MCI, dysnomic MCI, dysexecutive/mixed MCI, and cluster-derived normal) in order to determine whether these cognitive subtypes would show different patterns of cortical atrophy. Methods: Participants were 485 individuals diagnosed with MCI and 178 cognitively normal individuals from the Alzheimers Disease Neuroimaging Initiative. Cortical thickness estimates were computed for 32 regions of interest per hemisphere. Statistical group maps compared each MCI subtype to cognitively normal participants and to one another. Results: The pattern of cortical thinning observed in each MCI subtype corresponded to their cognitive profile. No differences in cortical thickness were found between the cluster-derived normal MCI subtype and the cognitively normal group. Direct comparison between MCI subtypes suggested that the cortical thickness patterns reflect increasing disease severity. Conclusions: There is an ordered pattern of cortical atrophy among patients with MCI that coincides with their profiles of increasing cognitive dysfunction. This heterogeneity is not captured when patients are grouped by conventional diagnostic criteria. Results in the cluster-derived normal group further support the premise that the conventional MCI diagnostic criteria are highly susceptible to false-positive diagnostic errors. Findings suggest a need to (1) improve the diagnostic criteria by reducing reliance on conventional screening measures, rating scales, and a single memory measure in order to avoid false-positive errors; and (2) divide MCI samples into meaningful subgroups based on cognitive and biomarkers profiles—a method that may provide better staging of MCI and inform prognosis.

Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study.

Structural MRI abnormalities are inconsistently reported in epilepsy. In the largest neuroimaging study to date, Whelan et al. report robust structural alterations across and within epilepsy syndromes, including shared volume loss in the thalamus, and widespread cortical thickness differences. The resulting neuroanatomical map will guide prospective studies of disease progression.

What does diffusion tensor imaging (DTI) tell us about cognitive networks in temporal lobe epilepsy

Diffusion tensor imaging (DTI) has provided considerable insight into our understanding of epilepsy as a network disorder, revealing subtle alterations in white matter microstructure both proximal and distal to the epileptic focus. These white matter changes have been shown to assist with lateralizing the seizure focus, as well as delineating the location/anatomy of key white matter tracts (i.e., optic radiations) for surgical planning. However, only recently have studies emerged describing the utility of DTI for probing cognitive networks in patients with epilepsy and for examining the structural plasticity within these networks both before and after epilepsy surgery. Here, we review the current literature describing the use of DTI for understanding language and memory networks in patients with temporal lobe epilepsy (TLE), as well as the extant literature on networks associated with executive functioning and global intelligence. Studies of memory and language reveal a complex network of frontotemporal fibers that contribute to naming and fluency performance in TLE, and demonstrate that these networks appear to undergo adaptive changes in response to surgical intervention. Although studies of executive functioning and global intelligence have been less conclusive, there is accumulating evidence that aberrant communication between frontoparietal and medial temporal networks may underlie working memory impairment in TLE. More recently, multimodal imaging studies have provided evidence that disruptions within these white matter networks co-localize with functional changes observed on functional MRI. However, structure-function associations are not entirely coherent and may breakdown in patients with TLE, especially those with a left-sided seizure focus. Although the reasons for discordant findings are unclear, small sample sizes, heterogeneity within patient populations and limitations of the current tensor model may account for contradictory and null findings. Improvements in imaging hardware and higher field strengths have now paved the way for the implementation of advanced diffusion techniques, and these advanced models show great promise for improving our understanding of how network dysfunction contributes to cognitive morbidity in TLE.

Restriction spectrum imaging reveals decreased neurite density in patients with temporal lobe epilepsy

Diffusion tensor imaging (DTI) has become a popular tool for delineating the location and extent of white matter injury in temporal lobe epilepsy (TLE). However, DTI yields nonspecific measures that are confounded by changes occurring within both the intracellular and extracellular environments. This study investigated whether an advanced diffusion method, restriction spectrum imaging (RSI) could provide a more robust measure of white matter injury in TLE relative to DTI due to RSIs ability to separate intraaxonal diffusion (i.e., neurite density; ND) from diffusion associated with extraaxonal factors (e.g., inflammation; crossing fibers).

Neuroimaging correlates of language network impairment and reorganization in temporal lobe epilepsy

Advanced, noninvasive imaging has revolutionized our understanding of language networks in the brain and is reshaping our approach to the presurgical evaluation of patients with epilepsy. Functional magnetic resonance imaging (fMRI) has had the greatest impact, unveiling the complexity of language organization and reorganization in patients with epilepsy both pre- and postoperatively, while volumetric MRI and diffusion tensor imaging have led to a greater appreciation of structural and microstructural correlates of language dysfunction in different epilepsy syndromes. In this article, we review recent literature describing how unimodal and multimodal imaging has advanced our knowledge of language networks and their plasticity in epilepsy, with a focus on the most frequently studied epilepsy syndrome in adults, temporal lobe epilepsy (TLE). We also describe how new analytic techniques (i.e., graph theory) are leading to a refined characterization of abnormal brain connectivity, and how subject-specific imaging profiles combined with clinical data may enhance the prediction of both seizure and language outcomes following surgical interventions.

Multimodal imaging of language reorganization in patients with left temporal lobe epilepsy

HighlightsMultimodal imaging can help to localize language networks in LTLE.Interhemispheric language reorganization is associated with alternations to the ARC.Structural and functional shifts mitigate language impairment in LTLE. ABSTRACT This study explored the relationships among multimodal imaging, clinical features, and language impairment in patients with left temporal lobe epilepsy (LTLE). Fourteen patients with LTLE and 26 controls underwent structural MRI, functional MRI, diffusion tensor imaging, and neuropsychological language tasks. Laterality indices were calculated for each imaging modality and a principal component (PC) was derived from language measures. Correlations were performed among imaging measures, as well as to the language PC. In controls, better language performance was associated with stronger left‐lateralized temporo‐parietal and temporo‐occipital activations. In LTLE, better language performance was associated with stronger right‐lateralized inferior frontal, temporo‐parietal, and temporo‐occipital activations. These right‐lateralized activations in LTLE were associated with right‐lateralized arcuate fasciculus fractional anisotropy. These data suggest that interhemispheric language reorganization in LTLE is associated with alterations to perisylvian white matter. These concurrent structural and functional shifts from left to right may help to mitigate language impairment in LTLE.

Verbal episodic memory profiles in HIV-Associated Neurocognitive Disorders (HAND): A comparison with Huntington's disease and mesial temporal lobe epilepsy

ABSTRACT HIV-associated neurocognitive disorders (HAND) commonly feature verbal episodic memory impairment historically characterized by a retrieval deficit, consistent with a classic “subcortical” presentation; however, there are hints of a subtle shift toward a more “cortical” memory profile characterized by a primary encoding deficit. The current study evaluated this possibility by comparing the pattern of HAND-associated verbal episodic memory deficits to those of traditional “subcortical” (i.e., Huntington’s disease; HD) versus “cortical” (i.e., left temporal lobe epilepsy with mesial temporal sclerosis; L-MTLE) profiles. Seventy-seven individuals with HAND, 47 individuals with HD, 21 individuals with L-MTLE, and 45 healthy participants were administered the California Verbal Learning Test - 2nd Edition (CVLT-II). CVLT-II profiles were classified as reflecting a primary encoding deficit, retrieval deficit, or a normal profile. Among participants with a deficit profile, the HAND group showed the highest rates of retrieval versus encoding profiles (71% vs. 29%), followed by HD (59% vs. 41%), L-MTLE (46% vs. 54%), and healthy (50% vs. 50%) groups. While significant profile heterogeneity was observed across clinical groups, findings suggest that HIV-associated verbal episodic memory impairments are most consistent with a traditional “subcortical,” retrieval deficit profile, consistent with the primary frontostriatal neuropathogenesis of HIV disease.