Epilepsy under the scope of ultra-high field MRI

Ultra-high field magnetic resonance imaging (UHF-MRI) is capable of unraveling anatomical structures in a submillimeter range. In addition, its high resonance regime allows the quantification of constitutive molecules in a spatially sensitive manner, a crucial capability for determining the extent and localization of a probable epileptogenic region or the severity of the epilepsy. The main technical challenges for data acquisition under UHF are to produce a strong, homogeneous transverse field, while keeping the tissue power deposition within the safe regulatory guidelines. The nonuniformities caused by destructive and constructive interferences at UHFs required new technologies to accelerate and increase yield regarding time spent and quality achieved. Image quality is the paramount contribution of UHF high-resolution imaging, which is capable to disclose fine details of the hippocampal formation and its surroundings and their changes in the course of epilepsy. Other sequences like diffusion tensor imaging (DTI) and multiecho susceptibility imaging at 7 T in vivo can assist the creation of normative atlases of the hippocampal subfields or the reconstruction of the highly arborized cerebral blood vessels. In our review, we specify the impact of these advanced relevant techniques onto the study of epilepsy. In this context, we focused onto high field high-resolution scanners and clinically-enriched decision-making. Studies on focal dysplasias correlating ex vivo high-resolution imaging with specific histological and ultrastructural patterns showed that white matter hyperintensities were related to a demyelination process and other alterations. Preliminary results correlating thick serial sections through bioptic epileptogenic tissue could extend the strategy to localize degenerated tissue sectors, correlate nature and extent of tissue loss with preoperative diagnosis and postoperative outcome. Finally, this protocol will provide the neurosurgeon with a detailed depiction of the removed pathologic tissue and possible adverse effects by the pathologic tissue left in situ. This article is part of the special issue "NEWroscience 2018".

Semantic verbal fluency brain network: delineating a physiological basis for the functional hubs using dual-echo ASL and graph theory approach

Objective. Semantic verbal fluency (SFV) is a cognitive process that engages and modulates specific brain areas related to language comprehension and production, decision making, response inhibition, and memory retrieval. The impairment of the brain network responsible for these functions is related to various neurological conditions, and different strategies have been proposed to assess SVF-related deficits in such diseases. In the present study, the concomitant changes of brain perfusion and functional connectivity were investigated during the resting state and SVF task performance.Approach. Arterial spin labeling (ASL), a perfusion-based magnetic resonance imaging (MRI) method, was used with a pseudocontinuous labeling approach and dual-echo readout in 28 healthy right-handed Brazilian Portuguese speakers. The acquisition was performed in a resting state condition and during the performance of a SVF task.Main results. During task performance, a significant increase in cerebral blood flow (CBF) was observed in language-related regions of the frontal lobe, including Brodmann's areas 6, 9, 45, and 47, associated with semantic processing, word retrieval, and speech motor programming. Such regions, along with the posterior cingulate, showed a crucial role in the SVF functional network, assessed by seed-to-voxel and graph analysis. Our approach successfully overcame the generalization problem regarding functional MRI (fMRI) graph analysis with cognitive, task-based paradigms. Moreover, the CBF maps enabled the functional assessment of orbital frontal and temporal regions commonly affected by magnetic susceptibility artifacts in conventional T2*-weighted fMRI approaches.Significance. Our results demonstrated the capability of ASL to evaluate perfusion alterations and functional patterns simultaneously regarding the SVF network providing a quantitative physiological basis to functional hubs in this network, which may support future clinical studies.

Non-classical behavior of the default mode network regions during an information processing task

The default mode network (DMN) efficient deactivation and suppressed functional connectivity (FC) during goal-directed tasks, which require attentional resources, have been considered essential to healthy brain cognition. However, recent studies have shown that DMN regions do not always show the expected behavior. Then, we aimed to investigate the functional activation and connectivity of DMN nodes in young, healthy controls during a goal-directed task. We used an adaptation of the symbol digit modalities test (SDMT) to evaluate the information processing speed (IPS). Twenty-four subjects (10 women, age: 29 ± 7 years) underwent two functional Magnetic Resonance Imaging experiments: one during resting-state and one during a block-designed SDMT paradigm. We superimposed the templates of the DMN on the group activation map and observed the reorganization of the network. For the posterior cingulate cortex (PCC) node of the DMN, which is spatially extensive, comprising the precuneus (dorsal portion) and the posterior cingulate gyrus (PCG, ventral portion), the extent of each region was different between conditions, suggesting different functional roles for them. Therefore, for the functional connectivity (FC) analysis, we split the DMN-PCC region into two regions: left precuneus (BA 7) and PCG. The left precuneus (BA 7) was positively correlated with the left lingual gyrus (BA 17), a task-positive region, and negatively associated with the DMN nodes when comparing task performance with the resting-state condition. The other DMN regions presented the classical antagonistic role during the attentional task. In conclusion, we found that the activation and functional connectivity of the DMN is, in general, suppressed during the information processing. However, the left precuneus BA 7 presented a context-dependent modulatory behavior, working as a transient in-between hub connecting the DMN to task-positive areas. Such findings support studies that show increased activation and excitatory functional connectivity of DMN portions during goal-directed tasks. Moreover, our results may contribute to defining more precise functional correlates of IPS deficits in a wide range of clinical and neurological diseases.

Evidence of regional associations between age-related inter-individual differences in resting-state functional connectivity and cortical thinning revealed through a multi-level analysis

Normal aging incurs functional and anatomical alterations in the brain. Cortical thinning, age-related alterations in resting-state functional connectivity (RSFC) and reductions in fractional amplitude of low frequency fluctuations (fALFF) are key components of brain aging that can be studied by neuroimaging. However, the level of association between these processes has not been fully established. We performed an analysis at multiple-levels, i.e. region or connection and modality, to investigate whether the evidence for the effect of aging on fALFF, RSFC and cortical thickness are associated in a large cohort. Our results show that there is a positive association between the level of evidence of age-related effects in all three in the brain. We also demonstrate that on a regional basis the association between RSFC alterations and cortical atrophy may be either positive or negative, which may relate to compensatory mechanisms predicted by the Scaffolding Theory of Aging and Cognition (STAC).

Prospective motion correction of fMRI: Improving the quality of resting state data affected by large head motion

The quality of functional MRI (fMRI) data is affected by head motion. It has been shown that fMRI data quality can be improved by prospectively updating the gradients and radio-frequency pulses in response to head motion during image acquisition by using an MR-compatible optical tracking system (prospective motion correction, or PMC). Recent studies showed that PMC improves the temporal Signal to Noise Ratio (tSNR) of resting state fMRI data (rs-fMRI) acquired from subjects not moving intentionally. Besides that, the time courses of Independent Components (ICs), resulting from Independent Component Analysis (ICA), were found to present significant temporal correlation with the motion parameters recorded by the camera. However, the benefits of applying PMC for improving the quality of rs-fMRI acquired under large head movements and its effects on resting state networks (RSN) and connectivity matrices are still unknown. In this study, subjects were instructed to cross their legs at will while rs-fMRI data with and without PMC were acquired, which generated head motion velocities ranging from 4 to 30 ​mm/s. We also acquired fMRI data without intentional motion. Independent component analysis of rs-fMRI was performed to evaluate IC maps and time courses of RSNs. We also calculated the temporal correlation among different brain regions and generated connectivity matrices for the different motion and PMC conditions. In our results we verified that the crossing leg movements reduced the tSNR of sessions without and with PMC by 45 and 20%, respectively, when compared to sessions without intentional movements. We have verified an interaction between head motion speed and PMC status, showing stronger attenuation of tSNR for acquisitions without PMC than for those with PMC. Additionally, the spatial definition of major RSNs, such as default mode, visual, left and right central executive networks, was improved when PMC was enabled. Furthermore, motion altered IC-time courses by decreasing power at low frequencies and increasing power at higher frequencies (typically associated with artefacts). PMC partially reversed these alterations of the power spectra. Finally, we showed that PMC provides temporal correlation matrices for data acquired under motion conditions more comparable to those obtained by fMRI sessions where subjects were instructed not to move.

Fractional Anisotropy of Thalamic Nuclei Is Associated With Verticality Misperception After Extra-Thalamic Stroke

Verticality misperception after stroke is a frequent neurological deficit that leads to postural imbalance and a higher risk of falls. The posterior thalamic nuclei are described to be involved with verticality perception, but it is unknown if extra-thalamic lesions can have the same effect via diaschisis and degeneration of thalamic nuclei. We investigated the relationship between thalamic fractional anisotropy (FA, a proxy of structural integrity), and verticality perception, in patients after stroke with diverse encephalic extra-thalamic lesions. We included 11 first time post-stroke patients with extra-thalamic primary lesions, and compared their region-based FA to a group of 25 age-matched healthy controls. For the patient sample, correlation and regression analyses evaluated the relationship between thalamic nuclei FA and error of postural vertical (PV) and haptic vertical (HV) in the roll (PVroll/HVroll) and pitch planes (PVpitch/HVpitch). Relative to controls, patients showed decreased FA of anterior, ventral anterior, ventral posterior lateral, dorsal, and pulvinar thalamic nuclei, despite the primary lesions being extra-thalamic. We found a significant correlation between HVroll, and FA in the anterior and dorsal nuclei, and PVroll with FA in the anterior nucleus. FA in the anterior, ventral anterior, ventral posterior lateral, dorsal and pulvinar nuclei predicted PV, and FA in the ventral anterior, ventral posterior lateral and dorsal nuclei predicted HV. While prior studies indicate that primary lesions of the thalamus can result in verticality misperception, here we present evidence supporting that secondary degeneration of thalamic nuclei via diaschisis can also be associated with verticality misperception after stroke.

Patient-specific neurosurgical phantom: assessment of visual quality, accuracy, and scaling effects

BACKGROUND

Training in medical education depends on the availability of standardized materials that can reliably mimic the human anatomy and physiology. One alternative to using cadavers or animal bodies is to employ phantoms or mimicking devices. Styrene-ethylene/butylene-styrene (SEBS) gels are biologically inert and present tunable properties, including mechanical properties that resemble the soft tissue. Therefore, SEBS is an alternative to develop a patient-specific phantom, that provides real visual and morphological experience during simulation-based neurosurgical training.

RESULTS

A 3D model was reconstructed and printed based on patient-specific magnetic resonance images. The fused deposition of polyactic acid (PLA) filament and selective laser sintering of polyamid were used for 3D printing. Silicone and SEBS materials were employed to mimic soft tissues. A neuronavigation protocol was performed on the 3D-printed models scaled to three different sizes, 100%, 50%, and 25% of the original dimensions. A neurosurgery team (17 individuals) evaluated the phantom realism as "very good" and "perfect" in 49% and 31% of the cases, respectively, and rated phantom utility as "very good" and "perfect" in 61% and 32% of the cases, respectively. Models in original size (100%) and scaled to 50% provided a quantitative and realistic visual analysis of the patient's cortical anatomy without distortion. However, reduction to one quarter of the original size (25%) hindered visualization of surface details and identification of anatomical landmarks.

CONCLUSIONS

A patient-specific phantom was developed with anatomically and spatially accurate shapes, that can be used as an alternative for surgical planning. Printed models scaled to sizes that avoided quality loss might save time and reduce medical training costs.

Cortical and functional responses to an early protocol of sensory re-education of the hand using audio–tactile interaction

Introduction

Early sensory re-education techniques are important strategies associated with cortical hand area preservation. The aim of this study was to investigate early cortical responses, sensory function outcomes and disability in patients treated with an early protocol of sensory re-education of the hand using an audio-tactile interaction device with a sensor glove model.

Methods

After surgical repair of median and/or ulnar nerves, participants received either early sensory re-education twice a week with the sensor glove during three months or no specific sensory training. Both groups underwent standard rehabilitation. Patients were assessed at one, three and six months after surgery on training-related cortical responses by functional magnetic resonance imaging, sensory thresholds, discriminative touch and disability using the Disabilities of the Arm, Shoulder and Hand patient-reported questionnaire.

Results

At six-months, there were no statistically significant differences in sensory function between groups. During functional magnetic resonance imaging, trained patients presented complex cortical responses to auditory stimulation indicating an effective connectivity between the cortical hand map and associative areas.

Conclusion

Training with the sensor glove model seems to provide some type of early cortical audio-tactile interaction in patients with sensory impairment at the hand after nerve injury. Although no differences were observed between groups related to sensory function and disability at the intermediate phase of peripheral reinnervation, this study suggests that an early sensory intervention by sensory substitution could be an option to enhance the response on cortical reorganization after nerve repair in the hand. Longer follow-up and an adequately powered trial is needed to confirm our findings.

Neuro-degeneration profile of Alzheimer's patients: A brain morphometry study

INTRODUCTION

Alzheimer's disease (AD) is a primary and progressive neurodegenerative disorder, which is marked by cognitive deterioration and memory impairment. Atrophy of hippocampus and other basal brain regions is one of the most predominant structural imaging findings related to AD. Most studies have evaluated the pre-clinical and initial stages of AD through clinical trials using Magnetic Resonance Imaging. Structural biomarkers for advanced AD stages have not been evaluated yet, being considered only hypothetically.

OBJECTIVE

To evaluate the brain morphometry of AD patients at all disease stages, identifying the structural neuro-degeneration profile associated with AD severity.

MATERIAL AND METHODS

AD patients aged 60 years or over at different AD stages were recruited and grouped into three groups following the Clinical Dementia Rating (CDR) score: CDR1 (n = 16), CDR2 (n = 15), CDR3 (n = 13). Age paired healthy volunteers (n = 16) were also recruited (control group). Brain images were acquired on a 3T magnetic resonance scanner using a conventional Gradient eco 3D T1-w sequence without contrast injection. Volumetric quantitative data and cortical thickness were obtained by automatic segmentation using the Freesurfer software. Volume of each brain region was normalized by the whole brain volume in order to minimize age and body size effects. Volume and cortical thickness variations among groups were compared.

RESULTS

Atrophy was observed in the hippocampus, amygdala, entorhinal cortex, parahippocampal region, temporal pole and temporal lobe of patients suffering from AD at any stage. Cortical thickness was reduced only in the parahippocampal gyrus at all disease stages. Volume and cortical thickness were correlated with the Mini Mental State Examination (MMSE) score in all studied regions, as well as with CDR and disease duration.

DISCUSSION AND CONCLUSION

As previously reported, brain regions affected by AD during its initial stages, such as hippocampus, amygdala, entorhinal cortex, and parahippocampal region, were found to be altered even in individuals with severe AD. In addition, individuals, specifically, with CDR 3, have multiple regions with lower volumes than individuals with a CDR 2. These results indicate that rates of atrophy have not plateaued out at CDR 2-3, and in severe patients there are yet neuronal loss and gliosis. These findings can add important information to the more accepted model in the literature that focuses mainly on early stages. Our findings allow a better understanding on the AD pathophysiologic process and follow-up process of drug treatment even at advanced disease stages.

Using network dynamic fMRI for detection of epileptogenic foci

Background

Epilepsy is one of the most prevalent neurological disorders. It remains medically intractable for about one-third of patients with focal epilepsy, for whom precise localization of the epileptogenic zone responsible for seizure initiation may be critical for successful surgery. Existing fMRI literature points to widespread network disturbances in functional connectivity. Per previous scalp and intracranial EEG studies and consistent with excessive local synchronization during interictal discharges, we hypothesized that, relative to same regions in healthy controls, epileptogenic foci would exhibit less chaotic dynamics, identifiable via entropic analyses of resting state fMRI time series.

Methods

In order to first validate this hypothesis on a cohort of patients with known ground truth, here we test individuals with well-defined epileptogenic foci (left mesial temporal lobe epilepsy). We analyzed voxel-wise resting-state fMRI time-series using the autocorrelation function (ACF), an entropic measure of regulation and feedback, and performed follow-up seed-to-voxel functional connectivity analysis. Disruptions in connectivity of the region exhibiting abnormal dynamics were examined in relation to duration of epilepsy and patients’ cognitive performance using a delayed verbal memory recall task.

Results

ACF analysis revealed constrained (less chaotic) functional dynamics in left temporal lobe epilepsy patients, primarily localized to ipsilateral temporal pole, proximal to presumed focal points. Autocorrelation decay rates differentiated, with 100 % accuracy, between patients and healthy controls on a subject-by-subject basis within a leave-one-subject out classification framework. Regions identified via ACF analysis formed a less efficient network in patients, as compared to controls. Constrained dynamics were linked with locally increased and long-range decreased connectivity that, in turn, correlated significantly with impaired memory (local left temporal connectivity) and epilepsy duration (left temporal – posterior cingulate cortex connectivity).

Conclusions

Our current results suggest that data driven functional MRI methods that target network dynamics hold promise in providing clinically valuable tools for identification of epileptic regions.

Brain activation inhomogeneity highlighted by the Isotropic Anomalous Diffusion filter

The visual appealing nature of the now popular BOLD fMRI may give the false impression of extreme simplicity, as if the the functional maps could be generated with the press of a single button. However, one can only get plausible maps after long and cautious processing, considering that time and noise come into play during acquisition. One of the most popular ways to account for noise and individual variability in fMRI is the use of a Gaussian spatial filter. Although very robust, this filter may introduce excessive blurring, given the strong dependence of results on the central voxel value. Here, we propose the use of the Isotropic Anomalous Diffusion (IAD) approach, aiming to reduce excessive homogeneity while retaining the natural variability of signal across brain space. We found differences between Gaussian and IAD filters in two parameters gathered from Independent Component maps (ICA), identified on brain areas responsible for auditory processing during rest. Analysis of data gathered from 7 control subjects shows that the IAD filter rendered more localized active areas and higher contrast-to-noise ratios, when compared to equivalent Gaussian filtered data (Student t-test, p<0.05). The results seem promising, since the anomalous filter performs satisfactorily in filtering noise with less distortion of individual localized brain responses.

Effect of scanner acoustic background noise on strict resting-state fMRI

Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a 'resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced "silent" pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.