Montreal Neurological Institute Research Articles

Automatically targeting the dorsolateral subthalamic nucleus for functional connectivity-guided rTMS therapy

Aim: Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have provided evidence that repetitive transcranial magnetic stimulation (rTMS) exerts treatment effects via functional connectivity (FC) from a superficial stimulation target to a deep effective region. The dorsolateral subthalamic nucleus (DL-STN) is an effective target in deep brain stimulation surgery for Parkinson’s disease (PD), but its targeting highly depends on well-trained neurosurgeons and is not easily used for FC-guided rTMS. We aimed to devise a method for automatically localizing the DL-STN, and further develop a one-stop plug-in of rs-fMRI FC analysis to assist future individualized FC-guided rTMS. Methods: Based on structural and iron-sensitive MRI of 78 participants, two raters defined the DL-STN coordinates with very high reliability. The averaged coordinates in the standard Montreal Neurological Institute (MNI) space were: left DL-STN, x: -11.89 ± 0.82, y: -14.51 ± 1.00, and z: -6.40 ± 1.01 and the right DL-STN, x: 12.53 ± 0.77, y: -13.97 ± 0.86, and z: -6.57 ± 0.99. As the individual distances from the averaged coordinates were less than 3 mm (within one voxel for most rs-fMRI studies) for all 78 participants, we defined the average coordinates as AutoSTN. We then developed a one-stop plug-in named Connectivity and Coordinates Converting Assistant Toolbox (CC-CAT) and performed AutoSTN FC analysis. Results: The AutoSTN seed showed significant FC with the motor cortices in all participants. Conclusion: The AutoSTN-based rs-fMRI FC could guide future rTMS on PD. The one-stop plug-in CC-CAT can be used for any FC-guided rTMS treatment.

Pseudo-resting-state functional MRI derived from dynamic susceptibility contrast perfusion MRI can predict cognitive impairment in glioma.

Resting-state functional MRI (rs-fMRI) can be used to estimate functional connectivity (FC) between different brain regions, which may be of value for identifying cognitive impairment in patients with brain tumors. Unfortunately, neither rs-fMRI nor neurocognitive assessments are routinely assessed clinically, mostly due to limitations in exam time and cost. Since DSC perfusion MRI is often used clinically to assess tumor vascularity and similarly uses a gradient echo-EPI sequence for T2*sensitivity, we theorized a "pseudo-rs-fMRI" signal could be derived from DSC perfusion to simultaneously quantify FC and perfusion metrics, and these metrics can be used to estimate cognitive impairment in patients with brain tumors. N=24 consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, rs-fMRI, and neurocognitive assessment. Voxel-wise modeling of contrast bolus dynamics during DSC acquisition was performed and then subtracted from the original signal to generate a residual "pseudo-rs-fMRI" signal. Following the pre-processing of pseudo-rs-fMRI, full rs-fMRI, and a truncated version of the full rs-fMRI (first 100 timepoints) data, the default mode, motor, and language network maps were generated with atlas-based ROIs. Dice scores were calculated for the resting-state network maps from pseudo-rs-fMRI and truncated rs-fMRI using the full rs-fMRI maps as reference. Seed-to-voxel and ROI-to-ROI analyses were performed to assess FC differences between cognitively impaired and non-impaired patients. Dice scores for the group-level and patient-level (mean±SD) default mode, motor, and language network maps using pseudo-rs-fMRI were 0.905/0.689±0.118 (group/patient), 0.973/0.730±0.124, and 0.935/0.665±0.142, respectively. There was no significant difference in Dice scores between pseudo-rs-fMRI and the truncated rs-fMRI default mode (P=0.97) or language networks (P=0.30), but there was a difference in motor networks (P=0.02). A multiple logistic regression classifier applied to ROI-to-ROI FC networks using pseudo-rs-fMRI could identify cognitively impaired patients (Sensitivity=84.6%, Specificity=63.6%, ROC AUC=0.7762±0.0954 (SE), P=0.0221) and performance was not significantly different than full rs-fMRI predictions (AUC=0.8881±0.0733 (SE), P=0.0013, P=0.29 compared to pseudo-rs-fMRI). DSC perfusion MRI-derived pseudo-rs-fMRI data can be used to perform typical rs-fMRI FC analyses that may identify cognitive decline in patients with brain tumors while still simultaneously performing perfusion analyses.ABBREVIATIONS: AUC = Area under curve; BOLD = Blood oxygenation level dependent; FC = Functional connectivity; MNI = Montreal Neurological Institute; ROC = Receiver operating characteristic; Rs-fMRI = Resting-state functional MRI.

Distribution of Silent Cerebral Infarcts in Adults With Sickle Cell Disease.

Previously we demonstrated that 90% of infarcts in children with sickle cell anemia occur in the border zone regions of cerebral blood flow (CBF). We tested the hypothesis that adults with sickle cell disease (SCD) have silent cerebral infarcts (SCIs) in the border zone regions, with a secondary hypothesis that older age and traditional stroke risk factors would be associated with infarct occurrence in regions outside the border zones. Adults with SCD 18-50 years of age were enrolled in a cross-sectional study at 2 centers and completed a 3T brain MRI. Participants with a history of overt stroke were excluded. Infarct masks were manually delineated on T2-fluid-attenuated inversion-recovery MRI and registered to the Montreal Neurological Institute 152 brain atlas to generate an infarct heatmap. Border zone regions between anterior, middle, and posterior cerebral arteries (ACA, MCA, and PCA) were quantified using the Digital 3D Brain MRI Arterial Territories Atlas, and logistic regression was applied to identify relationships between infarct distribution, demographics, and stroke risk factors. Of 113 participants with SCD (median age 26.1 years, interquartile range [IQR] 21.6-31.4 years, 51% male), 56 (49.6%) had SCIs. Participants had a median of 5.5 infarcts (IQR 3.2-13.8). Analysis of infarct distribution showed that 350 of 644 infarcts (54.3%) were in 4 border zones of CBF and 294 (45.6%) were in non-border zone territories. More than 90% of infarcts were in 3 regions: the non-border zone ACA and MCA territories and the ACA-MCA border zone. Logistic regression showed that older participants have an increased chance of infarcts in the MCA territory (odds ratio [OR] 1.08; 95% CI 1.03-1.13; p = 0.001) and a decreased chance of infarcts in the ACA-MCA border zone (OR 0.94; 95% CI 0.90-0.97; p < 0.001). The presence of at least 1 stroke risk factor did not predict SCI location in any model. When compared with children with SCD, in adults with SCD, older age is associated with expanded zones of tissue infarction that stretch beyond the traditional border zones of CBF, with more than 45% of infarcts in non-border zone regions.

Machine learning techniques based on 18F-FDG PET radiomics features of temporal regions for the classification of temporal lobe epilepsy patients from healthy controls.

This study aimed to investigate the clinical application of 18F-FDG PET radiomics features for temporal lobe epilepsy and to create PET radiomics-based machine learning models for differentiating temporal lobe epilepsy (TLE) patients from healthy controls. A total of 347 subjects who underwent 18F-FDG PET scans from March 2014 to January 2020 (234 TLE patients: 25.50 ± 8.89 years, 141 male patients and 93 female patients; and 113 controls: 27.59 ± 6.94 years, 48 male individuals and 65 female individuals) were allocated to the training (n = 248) and test (n = 99) sets. All 3D PET images were registered to the Montreal Neurological Institute template. PyRadiomics was used to extract radiomics features from the temporal regions segmented according to the Automated Anatomical Labeling (AAL) atlas. The least absolute shrinkage and selection operator (LASSO) and Boruta algorithms were applied to select the radiomics features significantly associated with TLE. Eleven machine-learning algorithms were used to establish models and to select the best model in the training set. The final radiomics features (n = 7) used for model training were selected through the combinations of the LASSO and the Boruta algorithms with cross-validation. All data were randomly divided into a training set (n = 248) and a testing set (n = 99). Among 11 machine-learning algorithms, the logistic regression (AUC 0.984, F1-Score 0.959) model performed the best in the training set. Then, we deployed the corresponding online website version (https://wane199.shinyapps.io/TLE_Classification/), showing the details of the LR model for convenience. The AUCs of the tuned logistic regression model in the training and test sets were 0.981 and 0.957, respectively. Furthermore, the calibration curves demonstrated satisfactory alignment (visually assessed) for identifying the TLE patients. The radiomics model from temporal regions can be a potential method for distinguishing TLE. Machine learning-based diagnosis of TLE from preoperative FDG PET images could serve as a useful preoperative diagnostic tool.

Lesion Frequency Distribution Maps of Traumatic Axonal Injury on Early Magnetic Resonance Imaging after Moderate and Severe Traumatic Brain Injury and Associations to 12 Months Outcome.

Traumatic axonal injury (TAI) is a common finding on MRI in patients with moderate - severe traumatic brain injury (TBI), and the burden of TAI is associated with outcome in this patient group. Lesion mapping offers a way to combine imaging findings from numerous individual patients into common lesion maps where the findings from a whole patient cohort can be assessed. The aim of this study was to evaluate the spatial distribution of traumatic axonal injury (TAI) lesions on different MRI sequences and its associations to outcome with use of lesion mapping. 269 patients (8-70 years) with moderate or severe TBI traumatic brain injury and magnetic resonance imaging (MRI) within six weeks after injury were prospectively included. TAI lesions were evaluated and manually segmented on fluid-attenuated inversed recovery (FLAIR), diffusion weighted imaging (DWI) and either T2* gradient echo (T2*GRE) or susceptibility weighted imaging (SWI). The segmentations were registered to the Montreal Neurological Institute space and combined to lesion frequency distribution maps. Outcome was assessed with Glasgow Outcome Scale Extended (GOSE) score at 12 months. The frequency and distribution of TAI was assessed qualitatively by evaluated visually reading. Univariable associations to outcome was assessed qualitatively by visual reading evaluated visually and also quantitatively with use of voxel-based lesion-symptom mapping (VLSM). The highest frequency of TAI was found in the posterior half of corpus callosum. The frequency of TAI was higher in the frontal- and temporal lobes than in the parietal- and occipital lobes, and in the upper parts of the brainstem than in the lower. On At the group level, all the voxels in mesencephalon had TAI on FLAIR. The patients with poorest outcome (GOSE scores ≤ 4) had higher frequencies of TAI. On VLSM, poor outcome was associated with TAI lesions univariable associations to outcome was found bilaterally in the splenium, and in the right side of tectum, tegmental mesencephalon and pons. With this study, we present lesion frequency distribution maps of TAI in a large cohort of patients with moderate and severe TBI. In conclusion, we found the highest higher frequency of TAI in posterior corpus callosum, and TAI in splenium, mesencephalon and pons were associated to with poor outcome. In the future, integration into picture archiving systems would enable comparison of individual patient maps with If lesion frequency distribution maps containing outcome information based on imaging findings from numerous patients in the future can be compared to the imaging findings from individual patients, it would offer a new tool in the clinical work-up and outcome prediction of TBI patient. Key Words: Brain injuries, traumatic; Diffuse axonal injury; Neuroimaging; Brain mapping; Artificial intelligence.

The non-decussating and decussating trigeminothalamic tracts in humans: A combination of connectome-based tractography and histological validation.

Functional anatomical research proposed the existence of a bilateral trigeminal ascending system although the anatomy trajectories of the trigeminothalamic connections cranial to the pons remain largely elusive. This study therefore aimed to clarify the anatomical distributions of the trigeminothalamic connections in humans. Advanced deterministic tractography to an averaged template of diffusion tensor imaging data from 1065 subjects from the Human Connectome Project was used. Seedings masks were placed in Montreal Neurological Institute standard space by use of the BigBrain histological dataset. Waypoint masks of the sensory thalamus was obtained from the Brainnetome Atlas. Tractography results were validated by use of the BigBrain histological dataset and Polarized Light Imaging microscopy. The trigeminothalamic tract bifurcated into a decussating ventral and a non-decussating dorsal tract. The ventral and dorsal tracts ascended to the contralateral thalamus and ipsilateral thalamus and reflected the ventral trigeminothalamic tract and the dorsal trigeminothalamic tract, respectively. The projection of the ventral trigeminothalamic tract and the dorsal trigeminothalamic tract to both thalami confirm the existence of a bilateral trigeminothalamic system in humans. Because our study is strictly anatomical, no further conclusions can be drawn with regard to physiological functionality. Future research should explore if the dorsal trigeminothalamic tract and the ventral trigeminothalamic tract actually transmit signals from noxious stimuli, this offers potential in understanding and possibly treating neuropathology in the orofacial region.

Magnetoencephalography Atlas Viewer for Dipole Localization and Viewing.

Magnetoencephalography (MEG) is a noninvasive neuroimaging technique widely recognized for epilepsy and tumor mapping. MEG clinical reporting requires a multidisciplinary team, including expert input regarding each dipole's anatomic localization. Here, we introduce a novel tool, the "Magnetoencephalography Atlas Viewer" (MAV), which streamlines this anatomical analysis. The MAV normalizes the patient's Magnetic Resonance Imaging (MRI) to the Montreal Neurological Institute (MNI) space, reverse-normalizes MNI atlases to the native MRI, identifies MEG dipole files, and matches dipoles' coordinates to their spatial location in atlas files. It offers a user-friendly and interactive graphical user interface (GUI) for displaying individual dipoles, groups, coordinates, anatomical labels, and a tri-planar MRI view of the patient with dipole overlays. It evaluated over 273 dipoles obtained in clinical epilepsy subjects. Consensus-based ground truth was established by three neuroradiologists, with a minimum agreement threshold of two. The concordance between the ground truth and MAV labeling ranged from 79% to 84%, depending on the normalization method. Higher concordance rates were observed in subjects with minimal or no structural abnormalities on the MRI, ranging from 80% to 90%. The MAV provides a straightforward MEG dipole anatomic localization method, allowing a nonspecialist to prepopulate a report, thereby facilitating and reducing the time of clinical reporting.

The superior frontal sulcus in the human brain: Morphology and probability maps.

The superior frontal sulcus (SFS) is the major sulcus on the dorsolateral frontal cortex that defines the lateral limit of the superior frontal gyrus. Caudally, it originates near the superior precentral sulcus (SPRS) and, rostrally, it terminates near the frontal pole. The advent of structural neuroimaging has demonstrated significant variability in this sulcus that is not captured by the classic sulcal maps. The present investigation examined the morphological variability of the SFS in 50 individual magnetic resonance imaging (MRI) scans of the human brain that were registered to the Montreal Neurological Institute (MNI) standard stereotaxic space. Two primary morphological patterns were identified: (i) the SFS was classified as a continuous sulcus or (ii) the SFS was a complex of sulcal segments. The SFS showed a high probability of merging with neighbouring sulci on the superior and middle frontal gyri and these patterns were documented. In addition, the morphological variability and spatial extent of the SFS were quantified using volumetric and surface spatial probability maps. The results from the current investigation provide an anatomical framework for understanding the morphology of the SFS, which is critical for the interpretation of structural and functional neuroimaging data in the dorsolateral frontal region, as well as for improving the accuracy of neurosurgical interventions.

Introducing the Concept of Sanctuary Sites in Ischemic Stroke.

The topography of arterial territories has been defined using digital maps of supratentorial infarcts. Regions with a high probability of infarction (Pi) exist in the deep compartment due to a paucity of collaterals. However, less attention has been given to regions with a low Pi. Using published digital maps, patients with cortical stroke and documented vessel occlusion were included. Infarcts from T2-weighted magnetic resonance images were segmented and registered onto a standard brain template (Montreal Neurological Institute 152). Segmented magnetic resonance images were averaged to yield the Pi at a voxel level. The overall Pi for the combined arterial territories was calculated to ensure that Pi was in the range of 0 to 1. Sanctuary sites were identified as regions with Pi <0.1. There were 154 patients (63% men; median age, 69 years; and interquartile range, 57-78 years). The magnetic resonance imaging scan used for segmentation was performed at a median interval of 35 (interquartile range, 3-66) days after stroke onset. Sanctuary sites were present in the frontal (gyrus rectus, the paracentral lobule, and orbitofrontal and precentral gyrus), parietal (postcentral, supramarginal, and angular gyrus, superior and inferior parietal lobule, and precuneus and posterior cingulate), and occipital cortex (cuneus, middle, and superior occipital gyrus). We propose that following vessel occlusion, there are cortical regions with a low Pi, which we termed sanctuary sites. The anatomic basis for this observation is the compensatory capacity of leptomeningeal collaterals.

The collaboration of Francis Forster and Wilder Penfield in the management of a girl with ‘reflex epilepsy’

ABSTRACT In the era after World War II, Francis (Frank) Forster (1912–2006) became a preeminent American neurologist and epileptologist, with international prominence in the study of reflex epilepsy. Forster’s interest in reflex epilepsy began with a chance observation of the condition, in 1946, in a four-year-old girl. When medical measures failed to control her somatosensory-evoked seizures, Forster recommended surgery, and then facilitated transfer to Canadian neurosurgeon Wilder Penfield (1891–1976) at the Montreal Neurological Institute. Forster traveled to Montreal for the child’s surgery. The surgery on February 27, 1948, proved to be curative for the child, and Forster’s interactions with Penfield and epileptologist Herbert Jasper (1906–1999) made a lasting impression. This study reviews the medical and surgical history of this case, which strongly influenced Forster’s career.

Quantifying 3D MR fingerprinting (3D-MRF) reproducibility across subjects, sessions, and scanners automatically using MNI atlases.

Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling. We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions. Voxel values within MRF-derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor-reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images. MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities.

Specific-CT brain template construction and retrospective dosimetric comparison study in brain for nasopharyngeal carcinoma patients treated with IMRT or VMAT.

The current Radiotherapy (RT) technology still inevitably irradiated normal brain tissue, causing implicit radiation-induced injury. This study investigates the precise localization and the corresponding radiation dosage of brain regions susceptible to damage in nasopharyngeal carcinoma (NPC) patients following RT. Utilizing the Advanced Normalization Tools (ANTs) package, a computed tomography (CT) brain template was created in the standard Montreal Neurological Institute (MNI) space, based on 803 Chinese NPC patients (T0~T4) who underwent RT. With this template, all patients' CT and RTdose data were registered to the MNI space, and the RTdose distribution characteristics in normal brain tissues were compared for NPC patients treated with Intensity-modulated radiotherapy (IMRT) or Volumetric Modulated Arc Therapy (VMAT), with patients' age and gender as covariates. Analysis of the average dosages indicated that certain areas within the Limbic, Temporal, and Posterior Lobes, the Brainstem, and the Cerebellum Posterior Lobe were exposed to doses exceeding 50 Gy. Inter-group analysis revealed that IMRT delivered higher doses than VMAT to brain regions anterior to the nasopharyngeal tumor, whereas VMAT affected the posterior regions more. Interestingly, VMAT showed a drawback in preserving the normal brain tissues for T4-stage patients. This revealed that the two treatment modalities have unique characteristics in preserving normal brain tissue, each with advantages. With better localization precision, the created CT brain template in MNI space may be beneficial for NPC patients' toxicity and dosimetric analyses.

Neuroanatomical mapping of inhibitory attention and working memory with functional magnetic resonance imaging in healthy children

The objective is to produce an average brain activation mapping template in healthy children using functional magnetic resonance imaging (fMRI), with specific paradigms for activating inhibitory attention and working memory functions. A nutritional and neuropsychological evaluation was performed on 87 right-handed children. The inclusion criteria were met by 30 children (15 boys and 15 girls) between 9 and 11 years old, who were studied with fMRI in two inhibitory attention tests (Go/No Go), with food cues, a working memory test (Continuous Performance Test Identical Pairs) and measurement of anatomical volumes. These data were subsequently processed with the FSL-v5 program, with a threshold of p < 0.05 (cluster-wise). The brain areas activated were located using a standard Montreal Neurological Institute brain template and the Harvard-Oxford structural cortical atlas. The inhibitory attention tests showed activation frontal areas predominantly on the right, and the cingulate, parietal and occipital areas, with preponderance in occipital areas in the food cues test. In the Continuous Performance Test-Identical Pairs test, activation was obtained predominantly in the occipital, frontal and parietal areas. Brain activity mapping templates are obtained in healthy children with tests for inhibitory attention, food cues and working memory. The activation areas are mostly those reported in the literature. This provides baseline brain activation patterns for studying pathologies related to inhibitory attention, impulsivity and working memory.

Speech and lexico-semantic errors during direct cortical stimulation mapping of the language-dominant hemisphere: effects of object and action naming.

In this retrospective study, the authors aimed to establish the stereotactically defined probability distribution for speech (i.e., anarthria, speech arrest) and lexico-semantic errors (i.e., anomia) through direct cortical stimulation (DCS) by using two tasks: action naming and object naming. They also analyzed the patterns of interindividual variability in the localization of the language sites involved, and investigated whether any patient or lesion location factors were associated with greater variability. Eighty-one Italian-speaking patients who underwent awake surgery between 2010 and 2021 for low- and high-grade gliomas in eloquent areas of the language-dominant hemisphere were entered in the analyses. The intraoperative DCS protocol included automatic speech tasks, object naming, and action naming. The position of the tags, as depicted on the intraoperative video or photograph, was transposed into Montreal Neurological Institute space. Subsequently, a 2D scatterplot and cluster analysis were performed. Associations between various clinical and radiological characteristics and the quantity of positive stimulated sites were determined by univariate analyses using binary logistic regression. Associated variables (p < 0.2) were included in stepwise multivariate logistic regression with backward elimination (p < 0.05). A total of 1380 cortical sites were stimulated, with a positive response in 511 cases (37%). Most anarthric errors were triggered when stimulating the left precentral gyrus, and most speech arrest errors were elicited when stimulating the left posterior inferior frontal gyrus. Anomias were found in the left inferior frontal gyrus and in the posterior part of the left temporal lobe for object naming. DCS to the left dorsal premotor cortex elicited anomic errors for action naming. Anomias were also elicited during DCS to the left posterior temporal lobe, with both object and action naming. The distribution of speech and lexico-semantic errors is in line with the current literature. The action-naming results are new and mostly involve the dorsal premotor cortex. These findings stress the importance of maximizing the use of different language tasks during surgery, because even when looking for the same type of errors, different tasks may be better suited to map specific brain regions. DCS with action and object naming identifies more positive sites than object naming alone.

Autism Spectrum Disorder Detection by Hybrid Convolutional Recurrent Neural Networks from Structural and Resting State Functional MRI Images.

This study aims to increase the accuracy of autism spectrum disorder (ASD) diagnosis based on cognitive and behavioral phenotypes through multiple neuroimaging modalities. We apply machine learning (ML) algorithms to classify ASD patients and healthy control (HC) participants using structural magnetic resonance imaging (s-MRI) together with resting state functional MRI (rs-f-MRI and f-MRI) data from the large multisite data repository ABIDE (autism brain imaging data exchange) and identify important brain connectivity features. The 2D f-MRI images were converted into 3D s-MRI images, and datasets were preprocessed using the Montreal Neurological Institute (MNI) atlas. The data were then denoised to remove any confounding factors. We show, by using three fusion strategies such as early fusion, late fusion, and cross fusion, that, in this implementation, hybrid convolutional recurrent neural networks achieve better performance in comparison to either convolutional neural networks (CNNs) or recurrent neural networks (RNNs). The proposed model classifies subjects as autistic or not according to how functional and anatomical connectivity metrics provide an overall diagnosis based on the autism diagnostic observation schedule (ADOS) standard. Our hybrid network achieved an accuracy of 96% by fusing s-MRI and f-MRI together, which outperforms the methods used in previous studies.

10125-GGE-10 EVALUATION OF MGMT PROMOTER METHYLATION STATUS OF GBM CELL LINE CLONAL POPULATION.

Abstract In this study, the epigenetic heterogeneity of GBM was investigated by evaluating the methylation status of the O6-methylguanine methyltransferase (MGMT) promoter in individual clones of a single cell derived from GBM cell lines. Cell lines, U251 and U373, were used for the experiments from the Brain Tumour Research Centre of the Montreal Neurological Institute. To evaluate the methylation status of the MGMT promoter, pyrosequencing and methylation-specific PCR (MSP) were used. A total of 12 U251 and 12 U373 clones were isolated. The methylation status of 83 of 97 CpG sites in the MGMT promoter were evaluated by pyrosequencing, and 11 methylated CpG sites and 13 unmethylated CpG sites were evaluated by MSP. The results demonstrate tumor heterogeneity among individual clones derived from a single GBM cell.

Deep brain stimulation for Tourette syndrome: modulation of the limbic-motor interface network.

Deep brain stimulation (DBS) is an effective treatment for medically refractory Tourette syndrome (TS). Several effective targets have been reported, but there is still controversy about the networks involved in the efficacy of DBS for TS. Here, the authors aimed to identify the basal ganglia-thalamo-cortical networks associated with tic and obsessive-compulsive behavior (OCB) improvement and the network link between the two main targets for TS. A retrospective analysis of 21 patients treated with pallidal and thalamic DBS was performed. Tics and OCB scores were recorded before and after DBS. The authors localized the electrodes in standard MNI (Montreal Neurological Institute) space and calculated the volume of tissue activated with the settings at the last follow-up to obtain areas of maximal improvement ("sweet spots") among all patients for the pallidal and thalamic targets. Tractography was used to show the white matter pathways associated with maximal tic and OCB improvement. Ten patients treated with pallidal DBS and 11 patients treated with thalamic DBS were included. Responder rates were 80% in the pallidal and 64% in the thalamic target groups. Sweet spots for tics and OCB clustered in several areas across the basal ganglia and thalamus delineated two main networks. Tic reduction in the pallidal target mapped to a limbic pallidothalamic network and in the thalamic target to the premotor thalamocortical network. Putting these two networks together will form the main output of the so-called limbic-motor interface network. However, OCB reduction mapped a dorsomedial prefrontal cortex/dorsal anterior cingulate (dmPFC/dACC) network. The authors demonstrated the involvement of the limbic-motor interface network during effective DBS for tics in patients with TS. OCB redution was associated with the additional involvement of dmPFC/dACC connections passing dorsal to the head of the globus pallidus pars externa on its way to the thalamus and midbrain.

Voxel‐level of abnormal β‐amyloid accumulation and spatiotemporal distribution patterns in Alzheimer’s Disease

AbstractBackgroundThe spatial patterns of β‐amyloid (Aβ) accumulation are critical for early diagnosis and clinical trials of Alzheimer’s Disease (AD). In this study, we explored a new voxel‐level Aβ index and investigated spatial patterns of voxels with abnormal Aβ deposition in different stages of AD.MethodWe identified 944 ADNI participants with Aβ 18F‐florbetapir positron emission tomography (PET) image. All Aβ PET images were co‐registered with their corresponding magnetic resonance imaging (MRI) scans, intensity‐normalized to the whole cerebellum, and spatial‐normalized to the Montreal Neurological Institute (MNI) space. We defined the threshold of each voxel as the mean+2SD of 18F‐florbetapir PET images of 51 participants who were Aβ PET negative (A‐), CSF p‐Tau181 negative (T‐), hippocampal atrophy negative (N‐), and cognitively unimpaired (CU) at both baseline and follow‐up. The positive voxel number (NoVoxel+) was counted based on the threshold of each voxel. The cross‐sectional and longitudinal correlations between NoVoxel+ and cortical summary Aβ standard uptake value ratio (SUVR) were determined in A‐ and Aβ‐positive (A+) separately. We compared baseline NoVoxel+ among different stages of AD, as well as how it related to longitudinal changes of Aβ SUVR, CSF p‐Tau181, residual hippocampal volume (rHCV), temporal meta‐ROI cortical thickness, and preclinical Alzheimer cognitive composite (PACC) score, and follow‐up tau PET levels, controlling for age, sex and APOE4. Finally, we investigated the spatial patterns of NoVoxel+ in different stages of AD.ResultThe new Aβ index NoVoxel+ was strongly correlated with the cortical summary Aβ SUVR cross‐sectionally and longitudinally regardless of Aβ positivity (Figure 1). Cognitively impaired (MCI and dementia) individuals showed larger (p&lt;0.001) NoVoxel+ than the CU individuals, A+ group had greater NoVoxel+ than the A‐ group (Figure 2). NoVoxel+ was related to faster rates of increases in Aβ SUVR and CSF p‐Tau, decreases in rHCV, temporal meta‐ROI cortical thickness, and PACC. Abnormal Aβ voxels were primarily located in precuneus, medial orbital frontal and anterior/posterior cingulate regions in A‐/CU group (Figure 3).ConclusionThe proposed voxel‐level Aβ deposition NoVoxel+ may be useful to investigate the spatial and temporal patterns of Aβ accumulation in AD, particularly in early amyloidosis stage.

Cerebellum Hyperactivity and its cortical connectivity in Alzheimer’s Disease (AD) utilizing FDG PET and Resting State Functional Magnetic Resonance.

AbstractBackgroundThe role of the cerebellum in Alzheimer’s disease (AD) is not fully understood. There are a few studies that have demonstrated impaired cortical – cerebellar connectivity in AD. Additionally, transgenic mouse studies clearly show amyloid‐β (Aβ) deposition in the cerebellum affecting synaptic transmission and plasticity, sometimes before plaque formation. To characterize metabolic activity in the cerebellum, we analyzed 18F‐fluorodeoxyglucose (FDG) positron emission tomography (PET) and resting‐state functional MRI (rs‐fMRI) data in AD, mild‐cognitive impaired (MCI), and age‐matched cognitively normal (CN) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Our focus was on the intrinsic functional connectivity of the cerebellum with three brain networks: the default mode network (DMN), dorsal attention network (DAN), and the primary olfactory cortex (POC) in the medial temporal lobe. We hypothesized that the resting state functional connectivity of cerebellar regions (that showed differential FDG metabolic activity) would exhibit impaired brain‐wide network connectivity.MethodA group of 272 ADNI subjects (CN = 80, MCI = 149, AD = 43) with FDG‐PET scans were analyzed in this study. All 272 subjects did not have consistent rs‐fMRI data therefore, we analyzed 160 subjects (CN = 80, MCI = 84, AD = 29) that had consistent rs‐fMRI data acquisition parameters. The PET preprocessing was performed in SPM12. Partial volume correction was performed using the Van‐Cittert deconvolution technique. The rs‐fMRI data was preprocessed in DPABI; PET and rs‐fMRI data were normalized to the Montreal Neurological Institute template. DMN and DAN masks were downloaded from neurovault.org. The Statistical analyses were performed in DPABI.ResultThe SPM group analysis of PET data identified crus II, right cerebellum 4,5 and vermis lobule 6 as hyperactive (increased glucose metabolism) in AD and MCI compared to CN (Figure 1). Subsequent analyses identified brain regions within the DMN, DAN, and POC that are correlated with hyperactive cerebellar regions. Similarity analyses detected impaired resting state functional connectivity of hyperactive cerebellar regions with the three brain networks (Figure 2).ConclusionThe hyper‐metabolism in the cerebellum may reflect disruption of local and brain‐wide network connectivity due to neurodegeneration. Observed hyper‐metabolism may be related to inhibitory dynamics of the cerebellum — providing a hypothetical mechanism to explain the susceptibility of brain networks in AD.

Cholinergic white matter hyperintensity volume, cognitive decline, and incident dementia in older adults

AbstractBackgroundWhite matter hyperintensities (WMHs) are frequently observed in the elderly and their severity tends to increase with age. Previous studies have revealed that WMHs are closely related to cognitive dysfunction. However, as inter‐individual variations and a clinicoradiological discrepancy exist, not all individuals with severe WMH burden experience worse cognitive performance. Furthermore, the location of WMHs appears to be a critical factor in the relationship between WMHs and cognitive function. Few studies take both volume and location of white matter hyperintensities (WMHs) into account to explore the association between WMH burden and cognitive impairment. We therefore investigated associations of cholinergic WMH volume (WMHV) with global cognitive function, cognitive decline, and incident dementia in older adults.MethodA total of 752 older adults (mean age 60 years, 50% female) from the Taizhou Imaging Study were involved. Brain magnetic resonance imaging data at baseline and repeated measures of cognition over 5 years were collected and analyzed. WMHV in whole brain, the cholinergic pathways, and different tract classes in the Montreal Neurologic Institute standard space was obtained using the Lesion Segmentation Toolbox and tools from FMRIB Software Library. Multivariable linear regression, Cox regression, and partial correlation tests were performed.ResultOver a median 5.67 (IQR: 2.88‐6.84) years of follow‐up, cholinergic WMHV was associated with annual decline of Mini‐Mental State Examination (MMSE) (β = ‐0.206; P = 0.006), and incident dementia (HR = 3.45; 95%CI: 2.08‐5.74). Within the cholinergic pathways, WMHs in commissural fibers were related to incident dementia. However, greater global WMHV only slightly increased the risk of incident dementia (HR = 1.03; 95%CI: 1.01‐1.06). Neither global nor cholinergic WMHV was associated with MMSE in cross‐sectional analysis.ConclusionCholinergic WMHV is associated with longitudinal cognitive decline and incident dementia in older adults. Within the cholinergic pathways, commissural fiber tracts were strategic locations correlated to incident dementia. Our findings suggest cholinergic WMHV might be a potential indicator of cognitive deterioration.