Surface-based laminar analysis of diffusion abnormalities in cortical and white matter layers in neocortical epilepsy

Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy

The present study investigates the effectiveness of a deep learning neural network for non-invasively localizing the seizure onset zone (SOZ) using multi-modal MRI data that are clinically acquired from children with drug-resistant epilepsy. A cortical parcellation was applied to localize the SOZ in cortical nodes of the epileptogenic hemisphere. At each node, the laminar surface analysis was followed to sample 1) the relative intensity of gray matter and white matter in multi-modal MRI and 2) the neighboring white matter connectivity using diffusion tractography edge strengths. A cross-validation was employed to train and test all layers of a multi-scale residual neural network (msResNet) that can classify SOZ node in an end-to-end fashion. A prediction probability of a given node belonging to the SOZ class was proposed as a non-invasive MRI marker of seizure onset likelihood. In an independent validation cohort, the proposed MRI marker provided a very large effect size of Cohen's d = 1.21 between SOZ and non-SOZ, and classified SOZ with a balanced accuracy of 0.75 in lesional and 0.67 in non-lesional MRI groups. The subsequent multi-variate logistic regression found the incorporation of the proposed MRI marker into interictal intracranial EEG (iEEG) markers further improves the differentiation between the epileptogenic focus (defined as SOZ resected during surgery) and non-epileptogenic sites (i.e., non-SOZ sites preserved during surgery) up to 15 % in non-lesional MRI group, suggesting that the proposed MRI marker could improve the localization of epileptogenic foci for successful pediatric epilepsy surgery.

Surface-based tracking for short association fibre tractography

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.

Do aggregate, multimodal structural neuroimaging measures replicate regional developmental differences observed in highly cited cellular histological studies?

Influential investigations of postmortem human brain tissue showed regional differences in tissue properties at early phases of development, such as between prefrontal and primary sensory cortical regions. Large-scale neuroimaging studies enable characterization of age-related trajectories with much denser sampling of cortical regions, assessment ages, and demographic variables than postmortem tissue analyses, but no single imaging measure perfectly captures what is measured with histology. Using publicly available data from the Pediatric Imaging, Neurocognition, and Genetics (PING) study, including 951 participants with ages ranging from 3 to 21 years, we characterized cortical regional variability in developmental trajectories of multimodal brain imaging measures. Multivariate analyses integrated morphometric and microstructural cortical surface measures. To replicate foundational histological work showing delayed synapse elimination in middle frontal gyrus relative to primary sensory areas, we tested whether developmental trajectories differ between prefrontal and visual or auditory cortex. We extended this to a whole-cortex analysis of interregional differences, producing cortical parcellations with maximally different developmental trajectories. Consistent with the general conclusions of postmortem analyses, our imaging results suggest that prefrontal regions show a protracted period of greater developmental change; however, they also illustrate the challenges of drawing conclusions about the relative maturational phases of different brain regions.

•

Multimodal, multivariate, nonlinear modeling, integrating morphometric and microstructural measures.

•

Tested regional developmental differences previously found in highly influential cellular histological studies.

•

Produced cortical parcellations with maximally different, multimodal, developmental trajectories.

•

Findings converge with evidence from histological studies showing delayed prefrontal cortical development.

•

Interregional differences vary by measure and illustrate complexities of defining which regions mature first.

Widespread cortical dyslamination in epilepsy patients with malformations of cortical development

PURPOSE

Recent research in epilepsy patients confirms our understanding of epilepsy as a network disorder with widespread cortical compromise. Here, we aimed to investigate the neocortical laminar architecture in patients with focal cortical dysplasia (FCD) and periventricular nodular heterotopia (PNH) using clinically feasible 3 T MRI.

METHODS

Eighteen epilepsy patients (FCD and PNH groups; n = 9 each) and age-matched healthy controls (n = 9) underwent T1 relaxation 3 T MRI, from which component probability T1 maps were utilized to extract sub-voxel composition of 6 T1 cortical layers. Seventy-eight cortical areas of the automated anatomical labeling atlas were divided into 1000 equal-volume sub-areas for better detection of cortical abnormalities, and logistic regressions were performed to compare FCD/PNH patients with healthy controls with the T1 layers composing each sub-area as regressors. Statistical significance (p < 0.05) was determined by a likelihood-ratio test with correction for false discovery rate using Benjamini-Hochberg method.

RESULTS

Widespread cortical abnormalities were observed in the patient groups. Out of 1000 sub-areas, 291 and 256 bilateral hemispheric cortical sub-areas were found to predict FCD and PNH, respectively. For each of these sub-areas, we were able to identify the T1 layer, which contributed the most to the prediction.

CONCLUSION

Our results reveal widespread cortical abnormalities in epilepsy patients with FCD and PNH, which may have a role in epileptogenesis, and likely related to recent studies showing widespread structural (e.g., cortical thinning) and diffusion abnormalities in various human epilepsy populations. Our study provides quantitative information of cortical laminar architecture in epilepsy patients that can be further targeted for study in functional and neuropathological studies.

Aging and central vision loss: Relationship between the cortical macro-structure and micro-structure

Aging and central vision loss are associated with cortical atrophies, but little is known about the relationship between cortical thinning and the underlying cellular structure. We compared the macro- and micro-structure of the cortical gray and superficial white matter of 38 patients with juvenile (JMD) or age-related (AMD) macular degeneration and 38 healthy humans (19-84 years) by multimodal MRI including diffusion-tensor imaging (DTI). A factor analysis showed that cortical thickness, tissue-dependent measures, and DTI-based measures were sensitive to distinct components of brain structure. Age-related cortical thinning and increased diffusion were observed across most of the cortex, but increased T1-weighted intensities (frontal), reduced T2-weighted intensities (occipital), and reduced anisotropy (medial) were limited to confined cortical regions. Vision loss was associated with cortical thinning and enhanced diffusion in the gray matter (less in the white matter) of the occipital central visual field representation. Moreover, AMD (but not JMD) patients showed enhanced diffusion in lateral occipito-temporal cortex and cortical thinning in the posterior cingulum. These findings demonstrate that changes in brain structure are best quantified by multimodal imaging. They further suggest that age-related brain atrophies (cortical thinning) reflect diverse micro-structural etiologies. Moreover, juvenile and age-related macular degeneration are associated with distinct patterns of micro-structural alterations.

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

Structural and Neuronal Integrity Measures of Fatigue Severity in Multiple Sclerosis

Fatigue is a common and disabling symptom in Multiple Sclerosis (MS). However, consistent neuroimaging correlates of its severity are not fully elucidated. In this article, we study the neuronal correlates of fatigue severity in MS. Forty-three Relapsing Remitting MS (RRMS) patients with MS-related fatigue (Fatigue Severity Scale (FSS) range: 1–7) and Expanded Disability Status Scale (EDSS) ≤ 4, were divided into high fatigue (HF, FSS ≥ 5.1) and low fatigue groups (LF, FSS ≤ 3). We measured T2 lesion load using a semi-automated technique. Cortical thickness, volume of sub-cortical nuclei, and brainstem structures were measured using Freesurfer. Cortical Diffusion Tensor Imaging (DTI) parameters were extracted using a cross modality technique. A correlation analysis was performed between FSS, volumetric, and DTI indices across all patients. HF patients showed significantly lower volume of thalamus, (p = 0.02), pallidum (p = 0.01), and superior cerebellar peduncle ((SCP), p = 0.002). The inverse correlation between the FSS score and the above volumes was significant in the total study population. In the right temporal cortex (RTC), the Radial Diffusivity ((RD), p = 0.01) and Fractional Anisotropy ((FA), p = 0.01) was significantly higher and lower, respectively, in the HF group. After Bonferroni correction, thalamic volume, FA-RTC, and RD-RTC remained statistically significant. Multivariate regression analysis identified FA-RTC as the best predictor of fatigue severity. Our data suggest an association between fatigue severity and volumetric changes of thalamus, pallidum, and SCP. Early neuronal injury in the RTC is implicated in the pathogenesis of MS-related fatigue.

Cortical thickness asymmetries and surgical outcome in neocortical epilepsy

PURPOSE

We evaluated if cortical thickness measures were associated with surgical outcome in patients with non-lesional neocortical epilepsy.

METHODS

Twenty-one young patients (age: 2.4-19.7years) with epilepsy of neocortical origin and normal MRI underwent two-stage epilepsy surgery with subdural EEG monitoring. Cortical thickness was measured on presurgical volumetric MRI using the FreeSurfer software. The prognostic value of hemispheric and lobar/regional cortical thickness measures for 1-year and 2-year post-surgical seizure outcome has been analyzed.

RESULTS

At one-year follow-up, 14 patients (67%) were seizure-free. Hemispheric and frontal lobe cortical thickness showed no/minimal asymmetry in seizure-free patients but thinner cortex ipsilateral to the seizure focus in those with recurrent seizures (p=0.02). More robust differences were found in patients≥6years of age (p=0.006 for frontal asymmetries), whose cortical thickness asymmetries remained prognostic for 2-year post-surgical outcome (p=0.007). By using an optimal cutoff threshold based on a receiver operating characteristic analysis, mean hemispheric asymmetry predicted one-year seizure freedom with 93% sensitivity and 71% specificity in the whole group, and with 100% sensitivity and 92% specificity in patients≥6years of age.

CONCLUSION

In patients with neocortical epilepsy and normal MRI, neocortical thinning in the epileptic hemisphere, particularly in frontal cortex, is associated with poor surgical outcome. Although these results require validation in a larger cohort prospectively, these data suggest that presurgical evaluation of cortical thickness may assist in identification of patients at high risk for surgical failure.

Applications of blood-oxygen-level-dependent functional magnetic resonance imaging and diffusion tensor imaging in epilepsy

The lifetime prevalence of epilepsy ranges from 2.7 to 12.4 per 1000 in Western countries. Around 30% of patients with epilepsy remain refractory to antiepileptic drugs and continue to have seizures. Noninvasive imaging techniques such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) have helped to better understand mechanisms of seizure generation and propagation, and to localize epileptic, eloquent, and cognitive networks. In this review, the clinical applications of fMRI and DTI are discussed, for mapping cognitive and epileptic networks and organization of white matter tracts in individuals with epilepsy.

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.

Epileptic baboons have lower numbers of neurons in specific areas of cortex

Epilepsy is characterized by recurrent seizure activity that can induce pathological reorganization and alter normal function in neocortical networks. In the present study, we determined the numbers of cells and neurons across the complete extent of the cortex for two epileptic baboons with naturally occurring seizures and two baboons without epilepsy. Overall, the two epileptic baboons had a 37% average reduction in the number of cortical neurons compared with the two nonepileptic baboons. The loss of neurons was variable across cortical areas, with the most pronounced loss in the primary motor cortex, especially in lateral primary motor cortex, representing the hand and face. Less-pronounced reductions of neurons were found in other parts of the frontal cortex and in somatosensory cortex, but no reduction was apparent in the primary visual cortex and little in other visual areas. The results provide clear evidence that epilepsy in the baboon is associated with considerable reduction in the numbers of cortical neurons, especially in frontal areas of the cortex related to motor functions. Whether or not the reduction of neurons is a cause or an effect of seizures needs further investigation.