MNI Space Research Articles

Internally consistent and fully unbiased multimodal MRI brain template construction from UK Biobank: Oxford-MM

Abstract Anatomical magnetic resonance imaging (MRI) templates of the brain are essential to group-level analyses and image processing pipelines, as they provide a reference space for spatial normalisation. While it has become common for studies to acquire multimodal MRI data, many templates are still limited to one type of modality, usually either scalar or tensor based. Aligning each modality in isolation does not take full advantage of the available complementary information, such as strong contrast between tissue types in structural images, or axonal organisation in the white matter in diffusion tensor images. Most existing strategies for multimodal template construction either do not use all modalities of interest to inform the template construction process, or do not use them in a unified framework. Here, we present multimodal, cross-sectional templates constructed from UK Biobank data: the Oxford-MultiModal-1 (OMM-1) template and age-dependent templates for each year of life between 45 and 81 years. All templates are fully unbiased to represent the average shape of the populations they were constructed from, and internally consistent through jointly informing the template construction process with T1-weighted (T1), T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and diffusion tensor imaging (DTI) data. The OMM-1 template was constructed with a multiresolution, iterative approach using 240 individuals in the 50–55-year age range. The age-dependent templates were estimated using a Gaussian process, which describes the change in average brain shape with age in 37,330 individuals. All templates show excellent contrast and alignment within and between modalities. The global brain shape and size are not preconditioned on existing templates, although maximal possible compatibility with MNI-152 space was maintained through rigid alignment. We showed benefits in registration accuracy across two datasets (UK Biobank and HCP), when using the OMM-1 as the template compared with FSL’s MNI-152 template, and found that the use of age-dependent templates further improved accuracy to a small but detectable extent. All templates are publicly available and can be used as a new reference space for uni- or multimodal spatial alignment.

BIOM-27. VOXEL-WISE SURVIVAL ANALYSIS IN GLIOBLASTOMA: TUMOR PROBABILITY MAPS REVEAL CRITICAL REGIONS NEAR WHITE MATTER TRACTS

Abstract BACKGROUND Glioblastoma is the most aggressive primary brain tumor, characterized by rapid growth and poor prognosis. Understanding spatial determinants of survival in GBM is crucial for improving prognostic accuracy and treatment strategies. Our study employs voxel-wise survival analysis (VSA) of tumor probability maps (TPMs) derived from MRI to identify high-risk brain regions. TPMs are generated through radio-pathomic mapping and can predict non-enhancing tumor regions not captured by traditional imaging. We aim to determine if high tumor probability regions are near previously identified critical white matter (WM) tracts and assess their impact on survival outcomes. METHODS We analyzed data from 374 GBM patients from the UCSF-PDGM-v2 dataset. Using a pretrained radio-pathomic model, TPMs were predicted based on T1, T1C, ADC, and FLAIR MRI sequences. All TPMs were rigidly registered to MNI space using ANTs. A Cox proportional hazards model was applied voxel-wise to assess the association between tumor probability and overall survival (OS). A p-value map was generated, thresholded, and cluster corrected (p < 0.05) for further analysis. RESULTS The VSA revealed that high tumor probability regions were significantly associated with poorer OS in GBM. Gray matter (GM) regions near WM tracts with high tumor probability showed markedly reduced survival. GM regions adjacent to the left IFOF (p < 0.05, HR = 1.19, 845 vs. 961 days for high/low TPM), Corpus Callosum Forceps Minor (p = 0.0001, HR = 1, 740 vs. 902 days), Body of the Corpus Callosum (p = 0.005, HR = 0.97, 748 vs. 798 days for high/low TPM) and other WM tracts, such as the left thalamic radiation superior and left reticulospinal tracts had similar trends. CONCLUSIONS Our study demonstrates that regions with high tumor probability, particularly those in the GM near critical WM tracts, are strongly associated with worse overall survival in GBM patients.

CNSC-05. MAPPING LANGUAGE PROCESSING IN SURGICAL GLIOMA PATIENTS

Abstract Previous work from our group has shown that the resection of white matter tracts localized by transcranial magnetic stimulation (TMS) predicts postoperative neurological deficits. Here we use advanced preoperative brain mapping along with formal language evaluations to localize the neuroanatomical underpinnings of language processing in surgical glioma patients. In patients who had TMS tracts resected, the resected portions (“tract-cavity segmentations”) were classified according to the functional outcome (“true positives”-corresponding deficit; “false positives”-no deficit) and normalized to MNI space. For patients who sustained long-term deficits, TMS tracts were segmented according to spatial overlap with normative tracts to create ROIs. Each normalized resection cavity (n=79) was analyzed for overlap with each ROI associated with postoperative deficits (n=8). The percentage of patients who had positive ROI resections that included TMS tracts versus patients who had positive ROI resections irrespective of TMS tracts were analyzed according to the percent who sustained deficits in each group. ROIs from all patients were summed to create a probabilistic atlas of functional white matter. “True positive” tract-cavity segmentations localized into dual anterior/posterior “hubs” and demonstrated significantly higher spatial association with normative tracts across three different measures (p<.05). 92% of patients who underwent ROI resections that included TMS tracts sustained long-term deficits while 34% of patients who underwent ROI resections irrespective of individualized mapping sustained deficits (p<.05). The probabilistic atlas of functional white matter demonstrated significantly higher voxel intensities within the white matter deep to the temporoparietal junction defined by the same posterior “hub” ROI from Figure 1 (p<.001). This study demonstrates that essential language processing localizes to ROIs within normative white matter tracts that require individualized mapping for surgical preservation. The white matter deep to the temporoparietal junction serves as a crucial hub for language-processing circuitry in glioma patients.

Reduced neurovascular coupling of the visual network in migraine patients with aura as revealed with arterial spin labeling MRI: is there a demand-supply mismatch behind the scenes?

BackgroundAlthough neuroimaging investigations have consistently demonstrated that “hyperresponsive” and “hyperconnected” visual cortices may represent the functional substrate of cortical spreading depolarization in patients with migraine with aura, the mechanisms which underpin the brain “tendency” to ignite the cortical spreading depolarization and, consequently, aura phenomenon are still matter of debate. Considering that triggers able to induce aura phenomenon constrain brain to increase global (such as physical activity, stressors and sleep abnormalities) or local (such as bright light visual stimulations) energy demand, a vascular supply unable to satisfy the increased energy requirement could be hypothesized in these patients.MethodsTwenty-three patients with migraine with aura, 25 patients with migraine without aura and 20 healthy controls underwent a 3-Tesla MRI study. Cerebral blood flow and local functional connectivity (regional homogeneity) maps were obtained and registered to the MNI space where 100 cortical regions were derived using a functional local-global normative parcellation. A surrogate estimate of the regional neurovascular coupling for each subject was obtained at each parcel from the correlation coefficient between the z-scored ReHo map and the z-scored cerebral blood flow maps.ResultsA significantly higher regional cerebral blood flow across the visual cortex of both hemispheres (i.e. fusiform and lingual gyri) was detected in migraine with aura patients when compared to patients with migraine without aura (p < 0.05, corrected for multiple comparisons). Concomitantly, a significantly reduced neurovascular coupling (p < 0.05, false discovery rate corrected) in the primary visual cortex parcel (VIS-4) of the large-scale visual network was observed in the left hemisphere of patients with migraine with aura (0.23±0.03), compared to both patients with migraine without aura (0.32±0.05) and healthy controls (0.29±0.05).ConclusionsVisual cortex neurovascular “decoupling” might represent the “link” between the exposure to trigger factors and aura phenomenon ignition. While physiological vascular oversupply may compensate neurovascular demand-supply at rest, it becomes inadequate in case of increased energy demand (e.g. when patients face with trigger factors) paving the way to the aura phenomenon ignition in patients with migraine with aura. Whether preventive treatments may exert their therapeutic activity on migraine with aura restoring the energy demands and cerebral blood flow trade-off within the visual network should be further investigated.

Poor sleep quality is associated with decreased regional brain glucose metabolism in healthy middle-aged adults

Sleep disturbance is associated with the development of neurodegenerative disease. We aimed to address the effects of sleep quality on brain glucose metabolism measured by 18F-Fl uorodeoxyglucose (18F-FDG) positron emission tomography (PET) in healthy middle-aged adults. A total of 378 healthy men (mean age: 42.8±3.6 years) were included in this study. Participants underwent brain 18F-FDG PET and completed the Korean version of the Pittsburgh Sleep Quality Index (PSQI-K). Additionally, anthropometric measurements were obtained. PETs were spatially normalized to MNI space using PET templates from SPM5 with PMOD. The Automated Anatomical Labeling 2 atlas was used to define regions of interest (ROIs). The mean uptake of each ROI was scaled to the mean of the global cortical uptake of each individual and defined as the standardized uptake value ratio (SUVR). After the logarithmic transformation of the regional SUVR, the effects of the PSQI-K on the regional SUVR were investigated using Bayesian hierarchical modeling. Brain glucose metabolism of the posterior cingulate, precuneus, and thalamus showed a negative association with total PSQI-K scores in the Bayesian model ROI-based analysis. Voxel-based analysis using statistical parametric mapping revealed a negative association between the total PSQI-K scores and brain glucose metabolism of the precuneus, postcentral gyrus, posterior cingulate, and thalamus. Poor sleep quality is negatively associated with brain glucose metabolism in the precuneus, posterior cingulate, and thalamus. Therefore, the importance of sleep should not be overlooked, even in healthy middle-aged adults.

Peaglet: A user-friendly probabilistic Kernel density estimation of intracranial cortical and subcortical stimulation sites

BackgroundData on human brain function obtained with direct electrical stimulation (DES) in neurosurgical patients have been recently integrated and combined with modern neuroimaging techniques, allowing a connectome-based approach fed by intraoperative DES data. Within this framework is crucial to develop reliable methods for spatial localization of DES-derived information to be integrated within the neuroimaging workflow. New methodTo this aim, we applied the Kernel Density Estimation for modelling the distribution of DES sites from different patients into the MNI space. The algorithm has been embedded in a MATLAB-based User Interface, Peaglet. It allows an accurate probabilistic weighted and unweighted estimation of DES sites location both at cortical level, by using shortest path calculation along the brain 3D geometric topology, and subcortical level, by using a volume-based approach. ResultsWe applied Peaglet to investigate spatial estimation of cortical and subcortical stimulation sites provided by recent brain tumour studies. The resulting NIfTI maps have been anatomically investigated with neuroimaging open-source tools. Comparison with existing methodsPeaglet processes differently cortical and subcortical data following their distinguishing geometrical features, increasing anatomical specificity of DES-related results and their reliability within neuroimaging environments. ConclusionsPeaglet provides a robust probabilistic estimation of the cortical and subcortical distribution of DES sites going beyond a region of interest approach, respecting cortical and subcortical intrinsic geometrical features. Results can be easily integrated within the neuroimaging workflow to drive connectomic analysis.

A large normative connectome for exploring the tractographic correlates of focal brain interventions

Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics – the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts – have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.

354 Feasibility and Clinical Imaging of Pain States Based on Multi-Delay Arterial Spin Labeling in Chronic Low Back Pain Patients Implanted With Thoracic Spinal Cord Stimulation

INTRODUCTION: Multi-delay, pseudo-continuous arterial spin labelling (PCASL) is a novel technique capable of perfusion imaging without contrast. It overcomes the limitation of a low signal-to-noise ratio of pulsed-ASL, and multiple post-label delays allow it to account for and measure arterial transit time (ATT). This makes it a suitable tool for the perfusion assessment. To date, there have been no studies to assess changes in ASL-measured perfusion in chronic low-back pain (cLBP) patients treated with thoracic spinal cord stimulation (tSCS). METHODS: PCASL data was acquired in five patients post-tSCS and five healthy subjects. ATT was estimated using weighted delays from multiple delay times, and it was used to calculate cerebral blood flow (CBF) and cerebral blood volume (CBV). Maps were normalized into MNI space and smoothed. Averaged values of ATT, CBF and CBV from pain ROI atlas were extracted and compared between cLBP and healthy control groups. Statistics comparing perfusion changes between patients and healthy subjects were conducted after Box-Cox transformation of data using Wilcoxon rank sum. RESULTS: Our results demonstrated the feasibility of MRI scanning with ASL sequence in patients with SCS. Specific absorption rates ranged from 0.031–0.042W/kg. Wilcoxon test indicated that ATT was significantly greater in cLBP patients within the supplementary motor area, posterior short gyrus, and the orbitofrontal cortex. There were no significant differences in patients and controls in CBF or CBV. CONCLUSIONS: Rate of perfusion as indexed by PCASL-derived ATT is reduced in cLBP treated with SCS patients in regions associated with pain processing, cognition, and motor planning. Insignificant results in CBF and CBV measures are likely due to low sample size of patients.

349 Brain Functional Imaging of Pain States Using Resting-State fMRI and Multi-Delay PCASL in Chronic Low-Back Pain Patients Implanted With Thoracic Spinal Cord Stimulation

INTRODUCTION: A treatment of chronic low-back pain is implantation of a thoracic spinal cord stimulator (tSCS), which has been shown to reduce pain. The functional changes in pain processing regions of the brain as assessed by resting-state fMRI and multi-delay pseudocontinuous arterial spin labeling (PCASL) have never been studied. METHODS: PCASL data based on 5 post-label delays (0.5–2.5s) as well as rsfMRI were acquired in five patients (1F) post-tSCS with cLBP and five healthy subjects (2F). Patient MRI scans were taken post-implantation with the SCS device turned off. Three PCASL measures and four rsfMRI measures were derived and normalized into MNI space and smoothed. Averaged values for each measure from the pain ROI atlas were extracted and compared between patients and controls. Statistics were conducted following Box-Cox transformation of data. RESULTS: Arterial transit time derived from PCASL showed a significant difference in the OFC, SMA, and PSG of patients, but other ASL measures showed no effect. Several regions across the rs-fMRI measures showed significant differences, including those involved in cognition (DLPFC, PCC), and pain processing (PSG) and sensation (S2). CONCLUSIONS: Functional imaging showed that cLBP patients treated with SCS display differences in resting-state function and brain perfusion across several pain regions of the brain. These areas are mainly part of the cognitive and behavioral components of the pain circuitry.

360 Diffusion Imaging-Derived Structural Changes in Cerebral Pain Regions of Chronic Low-Back Pain Patients Implanted With Thoracic Spinal Cord Stimulation

INTRODUCTION: Thoracic spinal cord stimulation (tSCS) is an effective treatment of chronic low-back pain (cLBP). Although diffusion imaging has been conducted in this group of patients, the study of diffusion-derived structural imaging of regions involved in pain processing has not been conducted. METHODS: Diffusion-weighted imaging scans were acquired in five patients (1 female) post-tSCS with cLBP and five healthy subjects (2 female). Patient MRI scans were taken post-implantation with the SCS device turned off during the MRI session. Four DTI maps and four MAP maps were derived and normalized into MNI space and smoothed. DTI and MAP values for each measure from the pain ROI atlas were extracted and compared between patients and controls. RESULTS: Statistically significant differences were found in regions involved with sensory processing of pain (ASG, PSG) as well as affective pain experience (ACC) across the DTI measures. MAP measures showed significance across five ROIs involved with sensory processing of pain, affective pain experience, and fear response (AMYG). CONCLUSIONS: Diffusion-derived structural imaging of pain regions suggests that cLBP patients receiving SCS have differences in diffusion imaging-derived structural parameters involved with pain processing, cognition, and fear response.

Choroid plexus volume in multiple sclerosis can be estimated on structural MRI avoiding contrast injection

We compared choroid plexus (ChP) manual segmentation on non-contrast-enhanced (non-CE) sequences and reference standard CE T1- weighted (T1w) sequences in 61 multiple sclerosis patients prospectively included. ChP was separately segmented on T1w, T2-weighted (T2w) fluid-attenuated inversion-recovery (FLAIR), and CE-T1w sequences. Inter-rater variability assessed on 10 subjects showed high reproducibility between sequences measured by intraclass correlation coefficient (T1w 0.93, FLAIR 0.93, CE-T1w 0.99). CE-T1w showed higher signal-to-noise ratio and contrast-to-noise ratio (CE-T1w 23.77 and 18.49, T1w 13.73 and 7.44, FLAIR 13.09 and 10.77, respectively). Manual segmentation of ChP resulted 3.073 ± 0.563 mL (mean ± standard deviation) on T1w, 3.787 ± 0.679 mL on FLAIR, and 2.984 ± 0.506 mL on CE-T1w images, with an error of 28.02 ± 19.02% for FLAIR and 3.52 ± 12.61% for T1w. FLAIR overestimated ChP volume compared to CE-T1w (p < 0.001). The Dice similarity coefficient of CE-T1w versus T1w and FLAIR was 0.67 ± 0.05 and 0.68 ± 0.05, respectively. Spatial error distribution per slice was calculated after nonlinear coregistration to the standard MNI152 space and showed a heterogeneous profile along the ChP especially near the fornix and the hippocampus. Quantitative analyses suggest T1w as a surrogate of CE-T1w to estimate ChP volume.Relevance statement To estimate the ChP volume, CE-T1w can be replaced by non-CE T1w sequences because the error is acceptable, while FLAIR overestimates the ChP volume. This encourages the development of automatic tools for ChP segmentation, also improving the understanding of the role of the ChP volume in multiple sclerosis, promoting longitudinal studies.Key points • CE-T1w sequences are considered the reference standard for ChP manual segmentation.• FLAIR sequences showed a higher CNR than T1w sequences but overestimated the ChP volume.• Non-CE T1w sequences can be a surrogate of CE-T1w sequences for manual segmentation of ChP.Graphical

Qualitative and Visual Along-Tract Analysis of Diffusion-Based Parameters in Patients with Diffuse Gliomas.

Grade 2-3 diffuse gliomas (DGs) show extensive infiltration through white matter (WM) tracts. Along-tract analysis of WM tracts based on diffusion tensor tractography (DTI) can been performed to assess the microstructural integrity of WM tracts. The clinical implication of these DTI-related findings is still under debate, especially in tumor patients. The aim of this study was to analyze and compare diffusion-based parameters along WM tracts and variables specific to WM -tumor interactions in DGs and correlate them with preoperative neuropsychological assessment. Fourteen patients with IDH-mutated grade 2-3 DGs were included. Tumor volumes were manually segmented on 3D-FLAIR images after spatial normalisation to MNI space. DTI was acquired using a single-shot echo-planar sequence on a 3T with 48 sampling directions. DTI data were reconstructed within the MNI space using q-space diffeomorphic reconstruction (QSDR) in DSI studio. Five bilateral sets of WM tracts were reconstructed based on the HCP-1065 template. All WM tracts were stretched to the same length of 100 indices, and for each index diffusion-based parameters fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), mean diffusivity (MD) and quantitative anisotropy (QA) were sampled. Tumor-related parameters (TRP); tumor volume (Tv), maximum tumor presence (MTP) and the number of sequential indices in which a tumor is present (Te) were derived based on the along-tract analysis. Normal data were constructed by calculating the average and standard deviations of contralateral and not-affected WM tracts for each diffusion-based parameter, respectively. Affected WM tracts were individually compared to normal data using a z-test. Preoperative neuropsychological assessment was performed in all subjects and correlated to results from the along-tract analysis using correlation and logistic regression models. Abnormalities in diffusion-based parameters were detected in WM tracts. Topographical and quantitative information were presented within the same graph. AD and MD displayed the highest linear correlation with the TRPs. Abnormal QA showed a linear correlation with Tv per WM tract. Neuropsychological impairment was correlated with all the TRPs and with abnormal FA (p < 0.05) and abnormal QA (p < 0.01). Abnormal QA was the only independent variable able to predict the presence of neuropsychological impairment in the patients based on the linear regression analysis. Graphical presentation of the along-tract analysis presented in this study shows that it may be a sensitive and robust method to acquire and display topographical and qualitative information regarding WM tracts in close proximity to DGs. Further studies and refinements to the methods presented herein may advance current clinical methods for evaluating displacement and infiltrations and further aid the efforts of pre-planning surgical interventions with the goal to maximise EOR and tailor oncological treatment.

Abstract TMP34: Lower Limb Motor Performance is Proportional to Corticospinal Tract Integrity in Chronic Stroke

Introduction: Gait is a complex behavior characterized by an array of measures, each contributing to our understanding of gait performance. To improve gait recovery after stroke, we need to connect complex clinical function and brain structure. Here, our purpose is to evaluate the relationship between lower limb performance and structural integrity of corticospinal tract (CST) in ambulatory chronic stroke survivors. Methods: Diffusion weighted images (DWIs) and lower limb performance measures were acquired from 36 chronic (&gt;6 months) stroke survivors with lower limb deficits. Clinical measures included Fugl-Meyer(FM), Gait Assessment and Intervention Tool (GAIT), timed-up-and-go (TUG) and fastest gait speed (GS). Lesions were manually outlined on the MRIs, and left hemisphere lesions were flipped. DWIs were preprocessed using standard denoising techniques before calculating fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD). Tract-based spatial statistics (TBSS) was used to normalize all data to MNI space and project it onto a skeleton of white matter tracts. CSTs were isolated. Voxel-wise analysis was performed with permutation testing (5000 permutations). A regression model was created for each clinical variable using lesion masks as a regressor. Results: Participants were 64±8.9 y/o, 83% male and 53% left hemisphere lesion. FM was 24.1±4.1. Mild correlations were present for FM with GAIT (Pearson, r = -0.33, p = 0.045) and GS (r = 0.34, p = 0.038), and GS with GAIT (r = -0.35, p = 0.036). TUG was highly correlated with GS (r = -0.93, p = 0.000). In exploratory analysis, findings for ipsilesional CST were as follows: 1) better FM was associated with higher FA, MD and RD, p = 0.001, 0.002 and 0.006 respectively; 2) better GS with higher FA, p = 0.034,3) better TUG scores with lower RD, p = 0.041 and 4) a trend of GAIT with RD, p=0.054. Location of statistically significant voxels varied for different clinical measures. No associations were found for contralesional CST. Conclusion: Structural correlates of lower limb performance can be detected using diffusion weighted tractography. FM, an impairment measure of paretic limb, has a stronger association with CST integrity than the measures of global gait function (TUG and GS).

A deep learning model for brain age prediction using minimally preprocessed T1w images as input.

In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (CNN)-based biological brain age prediction model that uses one T1w MRI preprocessing step when applying the model to external datasets to simplify implementation and increase accessibility in research settings. Our model only requires rigid image registration to the MNI space, which is an advantage compared to previous methods that require more preprocessing steps, such as feature extraction. We used a multicohort dataset of cognitively healthy individuals (age range = 32.0-95.7 years) comprising 17,296 MRIs for training and evaluation. We compared our model using hold-out (CNN1) and cross-validation (CNN2-4) approaches. To verify generalisability, we used two external datasets with different populations and MRI scan characteristics to evaluate the model. To demonstrate its usability, we included the external dataset's images in the cross-validation training (CNN3). To ensure that our model used only the brain signal on the image, we also predicted brain age using skull-stripped images (CNN4). The trained models achieved a mean absolute error of 2.99, 2.67, 2.67, and 3.08 years for CNN1-4, respectively. The model's performance in the external dataset was in the typical range of mean absolute error (MAE) found in the literature for testing sets. Adding the external dataset to the training set (CNN3), overall, MAE is unaffected, but individual cohort MAE improves (5.63-2.25 years). Salience maps of predictions reveal that periventricular, temporal, and insular regions are the most important for age prediction. We provide indicators for using biological (predicted) brain age as a metric for age correction in neuroimaging studies as an alternative to the traditional chronological age. In conclusion, using different approaches, our CNN-based model showed good performance using one T1w brain MRI preprocessing step. The proposed CNN model is made publicly available for the research community to be easily implemented and used to study ageing and age-related disorders.

Microstructural alterations of major thalamic nuclei in the chronic pediatric spinal cord injured population

BackgroundThe brain undergoes reorganization following spinal cord injury (SCI), but little is known about how the thalamus is affected in pediatric SCIs. PurposeTo characterize microstructural alterations in the thalamus after SCI with diffusion tensor imaging (DTI) metrics. Methods18 pediatric participants with chronic SCI (8–20 years) were stratified using the American Spinal Injury Association Impairment Scale (AIS) into groups: A, B, and C/D. DTI of the brain used a 3 T Siemens Verio MRI using the parameters: 20 directions, number of averages = 3, b = 1000 s/mm2, voxel size = 1.8 mm × 1.8 mm, slice thickness = 5 mm, TE = 95 ms, TR = 4300 ms, 30 slices, FOV = 230 × 230 mm2, matrix = 128 × 128, acquisition time = 4:45 min. Diffusion data was processed to generate DTI metrics FA, MD, AD, and RD. Data analysisDTI metrics were acquired by superimposing the AAL3 thalamic atlas onto participant diffusion images registered to MNI152 space. We utilized a multiple Mann–Whitney U-test to compare between AIS groups, considering values of p ≤ 0.05 as significant. ResultsFA, AD, RD, and MD significantly differed in thalamic nuclei between AIS groups A vs B and B vs C/D. Significant nuclei include the right ventral anterior, left intralaminar, bilateral lateral pulvinar, and right lateral geniculate. ConclusionOur findings suggest the presence of microstructural alterations based on SCI severity in pediatric patients. These results are encouraging and warrant further study.

Should I stay or should I go? The cerebral bases of street-crossing decision.

An observer willing to cross a street must first estimate if the approaching cars offer enough time to safely complete the task. The brain areas supporting this perception, known as Time-To-Contact (TTC) perception, have been mainly studied through noninvasive correlational approaches. We carried out an experiment in which patients were tested during an awake brain surgery electrostimulation mapping to examine the causal implication of various brain areas in the street-crossing decision process. Forty patients were tested in a gap acceptance task before their surgery to establish a baseline performance. The task was individually adapted upon this baseline level and carried out during their surgery. We acquired and normalized to MNI space the coordinates of the functional areas that influenced task performance. A total of 103 stimulation sites were tested, allowing to establish a large map of the areas involved in the street-crossing decision. Multiple sites were found to impact the gap acceptance decision. A direct implication was however found mostly for sites within the right parietal lobe, while indirect implication was found for sites within the language, motor, or attentional networks. The right parietal lobe can be considered as causally influencing the gap acceptance decision. Other positive sites were all accompanied with dysfunction in other cognitive functions, and therefore should probably not be considered as the site of TTC estimation.

Associations between glymphatic function and BBB water exchange rate and perfusion in a Latinx cohort

AbstractBackgroundThe glymphatic system is thought to clear waste products from the brain by facilitating the exchange of interstitial fluid (ISF) with cerebrospinal fluid (CSF) through aquaporin‐4 (AQP4) water channels present in astrocyte endfeet. A recent non‐invasive MRI method, diffusion tensor image analysis along the perivascular space (DTI‐ALPS), has been proposed for evaluating brain clearance function and has shown reduced glymphatic function in various neurological disorders such as Alzheimer’s disease. However, the role of microvascular perfusion and blood‐brain barrier (BBB) permeability in the glymphatic system remains unclear. In this study, we used a novel diffusion‐prepared arterial spin labeling (DP‐ASL) MRI technique to measure BBB water exchange rate (kw) and cerebral blood flow (CBF) and studied their relationships with the DTI‐ALPS score.Method44 Latinx subjects (20 male; age = 65.6±5.6 years) were recruited from the USC MarkVCID study. Imaging parameters for DP‐ASL were: resolution = 3.5×3.5×8mm3, 10 slices, scan time 10 mins. kw was calculated from the ratio of intra‐ and extra‐vascular perfusion signals with total‐general‐variation (TGV) regularized single‐pass approximation (SPA) modeling and CBF was calculated from PLD = 1800ms data using one‐compartment Kety model. kw and CBF maps were normalized into the MNI space and regional analysis was performed in the frontal/temporal/parietal lobe, and subcortical regions. Association between ALPS score and CBF/kw values were studied by linear regressions. P&lt;0.05 was considered as significant.ResultFig.1 shows kw and CBF maps from three representative subjects with increasing ALPS scores (top to bottom). ALPS was significantly correlated with kw in MTL (β = 1.7e‐3,P = 0.04) and a positive trend was observed between ALPS and whole brain average kw (P = 0.11). While significant correlations were found between ALPS and CBF in multiple brain regions including frontal lobe (β = 7e‐3,P = 0.009), temporal lobe (β = 7e‐3,P = 0.002), parietal lobe (β = 4e‐3,P = 0.03), MTL (β = 8e‐3,P = 0.03), ACC (β = 6e‐3,P = 0.005), PCC (β = 4e‐3,P = 0.02), precuneus (β = 4e‐3,P = 0.04) and whole brain (β = 8e‐3,P = 0.01). Fig.2 shows scatter plots of ALPS versus kw (A) and CBF in MTL and whole brain, respectively.ConclusionThis is the first study in Latinx population demonstrating positive correlations between ALPS score and both CBF and kw, suggesting a possible involvement of blood flow and BBB water exchange rate in the glymphatic system.

Dysfunctional cerebral glucose transport in Alzheimer’s Disease

AbstractBackgroundGlucose is the primary energy source required for the homeostatic function of the brain. Glucose transporter 1 (GLUT1) present at the blood‐brain barrier is a key regulator of glucose transport into the brain. Reduced GLUT1 expression is shown to exacerbate Alzheimer’s pathology in rodent models. Here we aimed to establish whether there are regional differences in ineffective glucose transport amongst people living with Alzheimer’s disease.Method125 participants diagnosed with Alzheimer’s dementia, with an [18F]FDG scan with atrial input were enrolled. All participants underwent 3‐tesla magnetic resonance imaging and [18F]FDG scan with continuous and discrete arterial sampling. Spectral analysis was performed to create 1‐minute input‐response function parametric maps. To produce glucose transfer maps we applied the following equation; K1 ⁎ Ca / τ (K1 = 1‐minute IRF map, Ca = Plasma glucose concentration, τ = 1.48 a lumped constant). Glucose transfer maps were then coregistered to the participants’ structural MRI and normalised to MNI space. Regional mean glucose transfer was then calculated for the anterior cingulate cortex, frontal lobe, hippocampus, parahippocampus, occipital lobe, parietal lobe, posterior cingulate cortex, striatum, temporal lobe, and thalamus. A within‐subject ANOVA was then performed to evaluate the regional differences in cerebral glucose transport.ResultThe parahippocampus exhibited the lowest rate of glucose transfer in comparison to all other regions (p &lt; 0.001), followed by the hippocampus. The striatum and occipital lobe demonstrated the regions of the highest mean glucose transportation from blood to the brain. In terms of brain lobes, the temporal lobe showed the lowest rates of glucose transfer, followed by the parietal lobe, then frontal and occipital (p &lt; 0.001).ConclusionWe demonstrate dysfunctional BBB glucose transport in Alzheimer’s disease, with prominent glucose transport abnormalities localised in the parahippocampus. Impaired glucose transport was most apparent within temporal lobe structures. Targeting glucose transfer may be an effective way of treating Alzheimer’s disease.

Relationship between APOE risk score and myelin in Alzheimer’s disease

AbstractBackgroundPostmortem brain tissue analysis suggests that apolipoprotein E (APOE) ε4 is associated with lower brain myelination (Blanchard et al. 2022). However, in vivo evidence for this association is lacking. Here, we examined the relationship between APOE genotype and myelin content in the brain using multicomponent relaxometry (mcDESPOT) imaging and an APOE neuropathologic risk score (Deming et al, 2023).Methods121 cognitively unimpaired participants from the Wisconsin Alzheimer’s Disease Research Center and the Wisconsin Registry for Alzheimer’s Prevention completed at least one mcDESPOT MRI scan and were APOE genotyped. Myelin content was quantified using mcDESPOT‐derived myelin water fraction (MWF) maps. Amyloid positivity was determined using CSF Aβ42/Aβ40 or a [C‐11]PiB PET scan. Cutoffs for amyloid positivity was a CSF Aβ42/Aβ40 ratio of &lt;0.046 (Van Hulle et al, 2020) or a global PiB DVR threshold &gt;1.19 (Betthauser et al, 2020). MWF maps were registered to MNI space and smoothed with an 8mm FWHM kernel. We conducted a voxel‐wise regression analysis to determine the relationship between APOE risk and myelin content. Covariates included age, age difference between MRI and amyloid acquisition, gender, race, amyloid status, APOE by amyloid status interaction, and APOE by gender interaction. We followed up these analyses examining specific brain regions implicated in AD. All analyses were corrected for multiple comparisons.ResultsParticipant characteristics are shown in Table 1. Voxel‐wise analysis indicated that MWF was negatively associated with age in the superior longitudinal fasciculus and small regions of the brainstem (Figure 1). MWF was not associated with APOE risk, gender, or race. ROI analysis showed a significant APOE by amyloid status interaction in the left (β = 0.006, p‐value = 0.035) and right cingulum (β = ‐0.013, p‐value = 0.037; Table 2). However, these interactions did not survive FDR correction.ConclusionThese findings suggest that myelin content decreases with age. Although APOE ε4 increases risk for developing AD dementia, it was not associated with brain myelin content in this cohort. In preclinical participants harboring amyloid pathology, APOE risk may impact myelin content although our findings did not survive FDR correction. More research is needed to fully elucidate this relationship.

Sustained connectivity correlates of motor function in Alzheimer’s disease

AbstractBackgroundIn addition to cognitive deficits, issues with motor control are present across the dementia spectrum. Traditional functional connectivity measures synchrony of intrinsic activity between brain regions and is altered in patients with Alzheimer’s disease in regions supporting motor function; however, less is known regarding the temporal stability of that synchrony. Sustained connectivity uses the width of cross correlation curves of BOLD time series to reflect the relative duration of synchronous activity between brain regions. This study investigates sustained connectivity across the dementia spectrum in motor regions.Method109 participants were included in this analysis and included 32 individuals with mild cognitive impairment (MCI) (18 F, 73.84 ± 5.14), 30 with Alzheimer’s disease (AD) (19 F, 77.37 ± 6.45), and 47 control individuals (29 F, mean age 72.13 ± 4.68). All study participants completed MP2RAGE structural imaging and two 15‐minute resting fMRI scans. Preprocessing steps included segmentation, motion realignment, registration to MNI space, and regression of motion parameters. Sustained connectivity values were averaged across both scans and only participants with more than 50% volumes remaining after censoring were included in analysis. A 17 resting‐state network parcellation was used to evaluate sustained connectivity across the brain with each network treated as a single ROI. A linear regression analysis was used to compare sustained connectivity across groups controlling for mean head motion, age, and sex. T statistics and p‐values are reported for across group sustained connectivity values.ResultAcross all three groups, sustained connectivity with the dorsal and ventral somatomotor networks was significantly increased across a number of resting‐state networks including the central visual, anterior ventral attention, and lateral temporal default mode network (DMN; all dorsal) and the somatomotor association, anterior ventral attention, medial frontoparietal, lateral temporal and lateral DMN (all ventral; Figure 1; pFDR &lt; .05).ConclusionThese data suggest sustained connectivity may be a potential metric for assessing progressive cognitive decline in dementia. Our results indicate that sustained connectivity may be used to track changes in the temporal duration of functional connectivity in motor networks in individuals with intact cognition, mild cognitive impairment, and Alzheimer’s disease.