Magnetic Resonance Imaging Template Research Articles

Neuroinflammation Parallels 18F-PI-2620 Positron Emission Tomography Patterns in Primary 4-Repeat Tauopathies.

Preclinical, postmortem, and positron emission tomography (PET) imaging studies have pointed to neuroinflammation as a key pathophysiological hallmark in primary 4-repeat (4R) tauopathies and its role in accelerating disease progression. We tested whether microglial activation (1) progresses in similar spatial patterns as the primary pathology tau spreads across interconnected brain regions, and (2) whether the degree of microglial activation parallels tau pathology spreading. We examined in vivo associations between tau aggregation and microglial activation in 31 patients with clinically diagnosed 4R tauopathies, using 18F-PI-2620 PET and 18F-GE180 (translocator protein [TSPO]) PET. We determined tau epicenters, defined as subcortical brain regions with highest tau PET signal, and assessed the connectivity of tau epicenters to cortical regions of interest using a 3-T resting-state functional magnetic resonance imaging template derived from age-matched healthy elderly controls. In 4R tauopathy patients, we found that higher regional tau PET covaries with elevated TSPO-PET across brain regions that are functionally connected to each other (β = 0.414, P < 0.001). Microglial activation follows similar distribution patterns as tau and distributes primarily across brain regions strongly connected to patient-specific tau epicenters (β = -0.594, P < 0.001). In these regions, microglial activation spatially parallels tau distribution detectable with 18F-PI-2620 PET. Our findings indicate that the spatial expansion of microglial activation parallels tau distribution across brain regions that are functionally connected to each other, suggesting that tau and inflammation are closely interrelated in patients with 4R tauopathies. The combination of in vivo tau and inflammatory biomarkers could therefore support the development of immunomodulatory strategies for disease-modifying treatments in these conditions. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Diffuse glioma-induced structural reorganization in close association with preexisting syntax-related networks

Glioma in the left frontal cortex has been reported to cause agrammatic comprehension and induce global functional connectivity alterations within the syntax-related networks. However, it remains unclear to what extent the structural reorganization is affected by preexisting syntax-related networks. We examined 28 patients with a diffuse glioma in the left hemisphere and 23 healthy participants. Syntactic abilities were assessed by a picture-sentence matching task with various sentence types. The lesion responsible for agrammatic comprehension was identified by region-of-interest-based lesion-symptom mapping (RLSM). Cortical structural alterations were examined by surface-based morphometry (SBM), in which the cortical thickness and fractal dimension were measured with three-dimensional magnetic resonance imaging (MRI). Fiber tracking on the human population-averaged diffusion MRI template was performed to examine whether the cortical structural alterations were associated with the syntax-related networks. The RLSM revealed associations between agrammatic comprehension and a glioma in the posterior limb of the left internal capsule. The SBM demonstrated that decreased cortical thickness and/or increased complexity of the right posterior insula were associated not only with agrammatic comprehension of the patients but also with the syntactic abilities of healthy participants. The fiber tracking revealed that the route between these two regions was anatomically integrated into the preexisting syntax-related networks previously identified. These results suggest a potential association between agrammatic comprehension in patients with diffuse glioma and structural variations in specific tracts and cortical regions, which may be closely related to the syntax-related networks.

Big Field of View MRI T1w and FLAIR Template - NMRI225

Image templates are a common tool for neuroscience research. Often, they are used for spatial normalization of magnetic resonance imaging (MRI) data, which is a necessary procedure for analyzing brain morphology and function via voxel-based analysis. This allows the researcher to reduce individual shape differences across images and make inferences across multiple subjects. Many templates have a small field-of-view typically focussed on the brain, limiting the use for applications requiring detailed information about other extra-cranial structures in the head and neck area. However, there are several applications where such information is important, for example source reconstruction of electroencephalography (EEG) and/or magnetoencephalography (MEG). We have constructed a new template based on 225 T1w and FLAIR images with a big field-of-view that can serve both as target for across subject spatial normalization as well as a basis to build high-resolution head models. This template is based on and iteratively re-registered to the MNI152 space to provide maximal compatibility with the most commonly used brain MRI template.

Synthesizing human brain CT images from MRI with deep learning

Rapid development of artificial intelligence techniques significantly promotes important medical imaging applications such as disease diagnosis, medical image analysis and cross-modality synthesis. It is valuable to synthesize Computed Tomography (CT) scans of human brains from Magnetic Resonance Imaging (MRI) scans because CT images contain particular information for diseases such as malignant tumors, cerebrovascular malformations and aneurysms. Although there has been many studies trying to apply machine learning methods (e.g., fully convolutional neural networks and generative adversarial networks) to predict CT images based on MRI, there are still opportunities to increase the quality of synthesized CT images using the latest machine learning algorithms. In this study, we aim to synthesize high-credibility human brain CT images from MRI images using machine learning approaches. We build a dataset of both CT and MRI images of 41 patients from The Cancer Imaging Archive. A data pre-processing pipeline is designed to guarantee that the processed images are suitable as inputs to machine learning algorithms. The pipeline includes (1) pairing MRI and CT scans according to a certain time interval between CT and MRI exams of the same patient, (2) registering all MRI images to a standard MRI template, (3) registering all CT images to paired MRI images, (4) intensity normalization and (5) extracting 2D slices from 3D CT and MRI volumes. Three deep neural networks with encoder–decoder structure are selected and implemented including U-Net, U-Net++ and pix2pix to synthesize human brain CT images from MRI images. Experimental results illustrate that U-Net++ shows better performance than U-Net and pix2pix in synthesizing CT images from MRI by achieving a Mean Squared Error of 0.025, a Mean Absolute Error of 0.082 and a Peak Signal-to-Noise Ratio of 67.90, respectively. The trained machine learning models from this work can be applied in future human brain CT image prediction where CT images are absent and MRI images are available for specific patients, thereby supporting disease diagnosis based on CT images.

Multimodal 3D Mouse Brain Atlas Framework with the Skull-Derived Coordinate System.

Magnetic resonance imaging (MRI) and light-sheet fluorescence microscopy (LSFM) are technologies that enable non-disruptive 3-dimensional imaging of whole mouse brains. A combination of complementary information from both modalities is desirable for studying neuroscience in general, disease progression and drug efficacy. Although both technologies rely on atlas mapping for quantitative analyses, the translation of LSFM recorded data to MRI templates has been complicated by the morphological changes inflicted by tissue clearing and the enormous size of the raw data sets. Consequently, there is an unmet need for tools that will facilitate fast and accurate translation of LSFM recorded brains to in vivo, non-distorted templates. In this study, we have developed a bidirectional multimodal atlas framework that includes brain templates based on both imaging modalities, region delineations from the Allen's Common Coordinate Framework, and a skull-derived stereotaxic coordinate system. The framework also provides algorithms for bidirectional transformation of results obtained using either MR or LSFM (iDISCO cleared) mouse brain imaging while the coordinate system enables users to easily assign in vivo coordinates across the different brain templates.

EEG functional connectivity analysis in the source space

There is a growing interest in using electroencephalography (EEG) and source modeling to investigate functional interactions among cortical processes, particularly when dealing with pediatric populations. This paper introduces two pipelines that have been recently used to conduct EEG FC analysis in the cortical source space. The analytic streams of these pipelines can be summarized into the following steps: 1) cortical source reconstruction of high-density EEG data using realistic magnetic resonance imaging (MRI) models created with age-appropriate MRI templates; 2) segmentation of reconstructed source activities into brain regions of interest; and 3) estimation of FC in age-related frequency bands using robust EEG FC measures, such as weighted phase lag index and orthogonalized power envelope correlation. In this paper we demonstrate the two pipelines with resting-state EEG data collected from children at 12 and 36 months of age. We also discuss the advantages and limitations of the methods/techniques integrated into the pipelines. Given there is a need in the research community for open-access analytic toolkits that can be used for pediatric EEG data, programs and codes used for the current analysis are made available to the public.

In vivo symmetric multi-contrast MRI brain templates and atlas for spontaneously hypertensive rats.

Spontaneously hypertensive rats (SHRs) are a valuable animal model of essential hypertension. The increasing use of SHRs in neuroimaging has generated an urgent demand for a template set that provides a reference for advanced data analysis. Structural T2-weighted magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and functional MRI scans that were used to build the template set were obtained from 8 SHRs longitudinally scanned in vivo at 10, 24 and 52weeks of age. These symmetric multi-contrast templates were constructed by iterative registration and averaging. The cortical atlas was derived from the Tohoku atlas, and the subcortical regions were manually delineated based on the templates. A set of SHR brain images named the Hebei Medical University rat brain template set (HRT) comprised 3D symmetric T2WI, raw T2-weighted signal with no added diffusion weighting (B0), fractional anisotropy (FA), mean diffusivity (MD) and blood oxygen level-dependent (BOLD) templates; tissue probability maps (TPMs) of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF); and a whole-brain atlas with 163 labels. We quantitatively validated the template and characterized the longitudinal changes in brain morphology in different brain tissues as SHRs aged. To our knowledge, the HRT is the first MRI template set for SHRs. We believe that the HRT can serve as a beneficial tool for precise analysis of the SHR brain using structural and functional MRI, which can promote neuroimaging studies on essential hypertension.

Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking

Finite element (FE) modeling is becoming an increasingly popular method for analyzing knee joint mechanics and biomechanical mechanisms leading to osteoarthritis (OA). The most common and widely available imaging method for knee OA diagnostics is planar X-ray imaging, while more sophisticated imaging methods, e.g., magnetic resonance imaging (MRI) and computed tomography (CT), are seldom used. Hence, the capability to produce accurate biomechanical knee joint models directly from X-ray imaging would bring FE modeling closer to clinical use. Here, we extend our atlas-based framework by generating FE knee models from X-ray images (N = 28). Based on measured anatomical landmarks from X-ray and MRI, knee joint templates were selected from the atlas library. The cartilage stresses and strains of the X-ray-based model were then compared with the MRI-based model during the stance phase of the gait. The biomechanical responses were statistically not different between MRI- vs. X-ray-based models when the template obtained from X-ray imaging was the same as the MRI template. However, if this was not the case, the peak values of biomechanical responses were statistically different between X-ray and MRI models. The developed X-ray-based framework may pave the way for a clinically feasible approach for knee joint FE modeling.

Deep Brain Stimulation of Caudal Zona Incerta for Parkinson's Disease: One-Year Follow-Up and Electric Field Simulations

ObjectiveTo evaluate the effects of bilateral caudal zona incerta (cZi) deep brain stimulation (DBS) for Parkinson's disease (PD) one year after surgery and to create anatomical improvement maps based on patient-specific simulation of the electric field. Materials and MethodsWe report the one-year results of bilateral cZi-DBS in 15 patients with PD. Patients were evaluated on/off medication and stimulation using the Unified Parkinson's Disease Rating Scale (UPDRS). Main outcomes were changes in motor symptoms (UPDRS-III) and quality of life according to Parkinson's Disease Questionnaire-39 (PDQ-39). Secondary outcomes included efficacy profile according to sub-items of UPDRS-III and simulation of the electric field distribution around the DBS lead using the finite element method. Simulations from all patients were transformed to one common magnetic resonance imaging template space for the creation of improvement maps and anatomical evaluation. ResultsMedian UPDRS-III score off medication improved from 40 at baseline to 21 on stimulation at one-year follow-up (48%, p < 0.0005). PDQ-39 summary index did not change, but the subdomain activities of daily living (ADL) and stigma improved (25%, p < 0.03 and 75%, p < 0.01), whereas communication worsened (p < 0.03). For UPDRS-III sub-items, stimulation alone reduced median tremor score by 9 points, akinesia by 3, and rigidity by 2 points at one-year follow-up in comparison to baseline (90%, 25%, and 29%, respectively, p < 0.01). Visual analysis of the anatomical improvement maps based on simulated electrical fields showed no evident relation with the degree of symptom improvement and neither did statistical analysis show any significant correlation. ConclusionsBilateral cZi-DBS alleviates motor symptoms, especially tremor, and improves ADL and stigma in PD patients one year after surgery. Improvement maps may be a useful tool for visualizing the spread of the electric field. However, there was no clear-cut relation between anatomical location of the electric field and the degree of symptom relief.

Automatic detection of neuromelanin and iron in the midbrain nuclei using a magnetic resonance imaging-based brain template.

Parkinson disease (PD) is a chronic progressive neurodegenerative disorder characterized pathologically by early loss of neuromelanin (NM) in the substantia nigra pars compacta (SNpc) and increased iron deposition in the substantia nigra (SN). Degeneration of the SN presents as a 50 to 70% loss of pigmented neurons in the ventral lateral tier of the SNpc at the onset of symptoms. Also, using magnetic resonance imaging (MRI), iron deposition and volume changes of the red nucleus (RN), and subthalamic nucleus (STN) have been reported to be associated with disease status and rate of progression. Further, the STN serves as an important target for deep brain stimulation treatment in advanced PD patients. Therefore, an accurate in‐vivo delineation of the SN, its subregions and other midbrain structures such as the RN and STN could be useful to better study iron and NM changes in PD. Our goal was to use an MRI template to create an automatic midbrain deep gray matter nuclei segmentation approach based on iron and NM contrast derived from a single, multiecho magnetization transfer contrast gradient echo (MTC‐GRE) imaging sequence. The short echo TE = 7.5 ms data from a 3D MTC‐GRE sequence was used to find the NM‐rich region, while the second echo TE = 15 ms was used to calculate the quantitative susceptibility map for 87 healthy subjects (mean age ± SD: 63.4 ± 6.2 years old, range: 45–81 years). From these data, we created both NM and iron templates and calculated the boundaries of each midbrain nucleus in template space, mapped these boundaries back to the original space and then fine‐tuned the boundaries in the original space using a dynamic programming algorithm to match the details of each individual's NM and iron features. A dual mapping approach was used to improve the performance of the morphological mapping of the midbrain of any given individual to the template space. A threshold approach was used in the NM‐rich region and susceptibility maps to optimize the DICE similarity coefficients and the volume ratios. The results for the NM of the SN as well as the iron containing SN, STN, and RN all indicate a strong agreement with manually drawn structures. The DICE similarity coefficients and volume ratios for these structures were 0.85, 0.87, 0.75, and 0.92 and 0.93, 0.95, 0.89, 1.05, respectively, before applying any threshold on the data. Using this fully automatic template‐based deep gray matter mapping approach, it is possible to accurately measure the tissue properties such as volumes, iron content, and NM content of the midbrain nuclei.

Pre-Operative Magnetic Resonance Imaging (MRI) and Surgical Management of Endometriosis

Study Objective To demonstrate how interdisciplinary collaboration between Radiology and Minimally Invasive Gynecologic Surgery departments can address pre-operative challenges in patients undergoing surgical management of endometriosis. Design Radiology review of imaging pre-operatively and subsequent retrospective review of completed surgical cases by surgeons with intra-operative photography and video. Setting Bimonthly conferences with members of both departments present. Patients or Participants De-identified patients with complex endometriosis on MRI who were planned for surgical management Interventions Review of MRI using separation by compartments and detailed description and measurements of lesions prior to surgery to improve patient counseling and recruitment of appropriate surgical services. Measurements and Main Results Surgical videos demonstrate planned removal of lesions. Contribution of MRI conference to individual patient cases is discussed along with how this helps address specific pre-operative challenges in endometriosis patients. Development of standardized MRI templates is ongoing. Conclusion Interdisciplinary collaboration is an important aspect of patient care when managing complex endometriosis with excisional fertility-sparing surgery. Patient counseling on planned surgery and risks can be improved with precise detection and standardized reporting using pre-operative imaging such as MRI. Scheduled pre-operative review of MRI provides the ability to address these clinical concerns. By correlating imaging, clinical, and intra-operative findings, we hope to improve patient outcomes. To demonstrate how interdisciplinary collaboration between Radiology and Minimally Invasive Gynecologic Surgery departments can address pre-operative challenges in patients undergoing surgical management of endometriosis. Radiology review of imaging pre-operatively and subsequent retrospective review of completed surgical cases by surgeons with intra-operative photography and video. Bimonthly conferences with members of both departments present. De-identified patients with complex endometriosis on MRI who were planned for surgical management Review of MRI using separation by compartments and detailed description and measurements of lesions prior to surgery to improve patient counseling and recruitment of appropriate surgical services. Surgical videos demonstrate planned removal of lesions. Contribution of MRI conference to individual patient cases is discussed along with how this helps address specific pre-operative challenges in endometriosis patients. Development of standardized MRI templates is ongoing. Interdisciplinary collaboration is an important aspect of patient care when managing complex endometriosis with excisional fertility-sparing surgery. Patient counseling on planned surgery and risks can be improved with precise detection and standardized reporting using pre-operative imaging such as MRI. Scheduled pre-operative review of MRI provides the ability to address these clinical concerns. By correlating imaging, clinical, and intra-operative findings, we hope to improve patient outcomes.

Population-Average Brain Templates and Application to Automated Voxel-Wise Analysis Pipelines for Cynomolgus Macaque.

The growing number of neuroimaging studies of cynomolgus macaques require extending existing templates to facilitate species-specific application of voxel-wise neuroimaging methodologies. This study aimed to create population-averaged structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) templates for the cynomolgus macaques and apply the templates in fully automated voxel-wise analyses. We presented the development of symmetric and asymmetric MRI and DTI templates from a sample of 63 young male cynomolgus monkeys with the use of optimized template creation approaches. We also generated the associated average tissue probability maps and Diffeomorphic Anatomical Registration using Exponentiated Lie Algebra templates for use with the Statistical Parametric Mapping (SPM), as well as the average fractional anisotropy/skeleton targets for incorporation into tract-based spatial statistics (TBSS) framework. Both asymmetric and symmetric templates in a standardized coordinate space demonstrated low bias and high contrast. Fully automated processing using SPM was accomplished for all native MRI datasets and demonstrated outstanding performance regarding skull-stripping, segmentation, and normalization when using the MRI templates. Automated normalization to the DTI template was excellently achieved for all native DTI images using the TBSS pipeline. The cynomolgus MRI and DTI templates are anticipated to provide a common platform for precise single-subject data analysis and facilitate comparison of neuroimaging findings in cynomolgus monkeys across studies and sites. It is also hoped that the procedures of template creation and fully-automated voxel-wise frameworks will provide a straightforward avenue for investigating brain function, development, and neuro-psychopathological disorders in non-human primate models.

IE-Map: a novel in-vivo atlas and template of the human inner ear

Brain atlases and templates are core tools in scientific research with increasing importance also in clinical applications. Advances in neuroimaging now allowed us to expand the atlas domain to the vestibular and auditory organ, the inner ear. In this study, we present IE-Map, an in-vivo template and atlas of the human labyrinth derived from multi-modal high-resolution magnetic resonance imaging (MRI) data, in a fully non-invasive manner without any contrast agent or radiation. We reconstructed a common template from 126 inner ears (63 normal subjects) and annotated it with 94 established landmarks and semi-automatic segmentations of all relevant macroscopic vestibular and auditory substructures. We validated the atlas by comparing MRI templates to a novel CT/micro-CT atlas, which we reconstructed from 21 publicly available post-mortem images of the bony labyrinth. Templates in MRI and micro-CT have a high overlap, and several key anatomical measures of the bony labyrinth in IE-Map are in line with micro-CT literature of the inner ear. A quantitative substructural analysis based on the new template, revealed a correlation of labyrinth parameters with total intracranial volume. No effects of gender or laterality were found. We provide the validated templates, atlas segmentations, surface meshes and landmark annotations as open-access material, to provide neuroscience researchers and clinicians in neurology, neurosurgery, and otorhinolaryngology with a widely applicable tool for computational neuro-otology.

Electrical Source Imaging in Freely Moving Rats: Evaluation of a 12-Electrode Cortical Electroencephalography System.

This work presents and evaluates a 12-electrode intracranial electroencephalography system developed at the National Institute of Mental Health (Klecany, Czech Republic) in terms of an electrical source imaging (ESI) technique in rats. The electrode system was originally designed for translational research purposes. This study demonstrates that it is also possible to use this well-established system for ESI, and estimates its precision, accuracy, and limitations. Furthermore, this paper sets a methodological basis for future implants. Source localization quality is evaluated using three approaches based on surrogate data, physical phantom measurements, and in vivo experiments. The forward model for source localization is obtained from the FieldTrip-SimBio pipeline using the finite-element method. Rat brain tissue extracted from a magnetic resonance imaging template is approximated by a single-compartment homogeneous tetrahedral head model. Four inverse solvers were tested: standardized low-resolution brain electromagnetic tomography, exact low-resolution brain electromagnetic tomography (eLORETA), linear constrained minimum variance (LCMV), and dynamic imaging of coherent sources. Based on surrogate data, this paper evaluates the accuracy and precision of all solvers within the brain volume using error distance and reliability maps. The mean error distance over the whole brain was found to be the lowest in the eLORETA solution through signal to noise ratios (SNRs) (0.2 mm for 25 dB SNR). The LCMV outperformed eLORETA under higher SNR conditions, and exhibiting higher spatial precision. Both of these inverse solvers provided accurate results in a phantom experiment (1.6 mm mean error distance across shallow and 2.6 mm across subcortical testing dipoles). Utilizing the developed technique in freely moving rats, an auditory steady-state response experiment provided results in line with previously reported findings. The obtained results support the idea of utilizing a 12-electrode system for ESI and using it as a solid basis for the development of future ESI dedicated implants.

Identification of neural networks preferentially engaged by epileptogenic mass lesions through lesion network mapping analysis

Lesion network mapping (LNM) has been applied to true lesions (e.g., cerebrovascular lesions in stroke) to identify functionally connected brain networks. No previous studies have utilized LNM for analysis of intra-axial mass lesions. Here, we implemented LNM for identification of potentially vulnerable epileptogenic networks in mass lesions causing medically-refractory epilepsy (MRE). Intra-axial brain lesions were manually segmented in patients with MRE seen at our institution (EL_INST). These lesions were then normalized to standard space and used as seeds in a high-resolution normative resting state functional magnetic resonance imaging template. The resulting connectivity maps were first thresholded (pBonferroni_cor < 0.05) and binarized; the thresholded binarized connectivity maps were subsequently summed to produce overall group connectivity maps, which were compared with established resting-state networks to identify potential networks prone to epileptogenicity. To validate our data, this approach was also applied to an external dataset of epileptogenic lesions identified from the literature (EL_LIT). As an additional exploratory analysis, we also segmented and computed the connectivity of institutional non-epileptogenic lesions (NEL_INST), calculating voxel-wise odds ratios (VORs) to identify voxels more likely to be functionally-connected with EL_INST versus NEL_INST. To ensure connectivity results were not driven by anatomical overlap, the extent of lesion overlap between EL_INST, and EL_LIT and NEL_INST was assessed using the Dice Similarity Coefficient (DSC, lower index ~ less overlap). Twenty-eight patients from our institution were included (EL_INST: 17 patients, 17 lesions, 10 low-grade glioma, 3 cavernoma, 4 focal cortical dysplasia; NEL_INST: 11 patients, 33 lesions, all brain metastases). An additional 23 cases (25 lesions) with similar characteristics to the EL_INST data were identified from the literature (EL_LIT). Despite minimal anatomical overlap of lesions, both EL_INST and EL_LIT showed greatest functional connectivity overlap with structures in the Default Mode Network, Frontoparietal Network, Ventral Attention Network, and the Limbic Network—with percentage volume overlap of 19.5%, 19.1%, 19.1%, and 12.5%, respectively—suggesting them as networks consistently engaged by epileptogenic mass lesions. Our exploratory analysis moreover showed that the mesial frontal lobes, parahippocampal gyrus, and lateral temporal neocortex were at least twice as likely to be functionally connected with the EL_INST compared to the NEL_INST group (i.e. Peak VOR > 2.0); canonical resting-state networks preferentially engaged by EL_INSTs were the Limbic and the Frontoparietal Networks (Mean VOR > 1.5). In this proof of concept study, we demonstrate the feasibility of LNM for intra-axial mass lesions by showing that ELs have discrete functional connections and may preferentially engage in discrete resting-state networks. Thus, the underlying normative neural circuitry may, in part, explain the propensity of particular lesions toward the development of MRE. If prospectively validated, this has ramifications for patient counseling along with both approach and timing of surgery for lesions in locations prone to development of MRE.

Lobule-Specific Dosage Considerations for Cerebellar Transcranial Direct Current Stimulation During Healthy Aging: A Computational Modeling Study Using Age-Specific Magnetic Resonance Imaging Templates

Aging is associated with a decline in cognitive and motor performances, which are a part of geriatric syndromes. Since aging is associated with morphological changes in the cerebellum and cerebellar morphology is a good predictor of cognitive and motor performances, so the study of cerebellar role in age-related decline in performance is necessary. Cerebellar transcranial direct current stimulation (ctDCS) has been proposed to study and facilitate the cerebellar function. However, lobule-specific dosing has not been investigated in healthy aging. This is important because the same electrode montage across different individuals for ctDCS (called the "one-size-fits-all" approach) can lead to inter-individual differences in the lobule-specific dosing of the electric field (EF). These differences can be due to the inter-individual variability and age-related changes in the cerebellar structure. To investigate such lobule-specific dosing differences in healthy aging, we modeled the lobular EF distribution across groups of 18 to 89 years for a commonly used "one-size-fits-all" ctDCS montage. A fully automated open-source pipeline performed age-group specific computational modeling of EF using 18 age-appropriate human brain magnetic resonance imaging (MRI) templates. The 18 age-appropriate human brain MRI templates were obtained from a database found online at https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/. We extracted the EF magnitude (called EF strength) across the 28 cerebellar lobules based on a spatially unbiased cerebellar atlas. We investigated the aging effects on various measures of specificity including the ratio of the mean lobular EF at the lobules beneath the active electrode (ipsilateral [right] lobules VIIIa, VIIIb, IX) divided by the mean EF across both the targeted (ipsi) and the contralateral (contra) cerebellar hemisphere. Two-way ANOVA showed that the lobules as well as the age group (and their interaction term) had a significant effect (p < 0.01) on the EF strength. Specifically, EF strength increased significantly at the neighboring cerebellar lobules (e.g., ipsilateral [right] lobules VIIb, Crus I and Crus II) of the targeted cerebellar hemisphere at an old age (70-74, 75-79, and 85-89 years) that reduced the specificity of ctDCS at the ipsilateral (right) lobules VIIIa, VIIIb, IX beneath the active electrode. We also found that the maximum EF strength in the cerebellar hemispheres decreased with an increase in the volume of the cerebrospinal fluid (CSF) and a decrease in the cerebellar volume with aging in a linear manner. We found that cerebellar shrinkage and increasing thickness of the highly conductive CSF during healthy aging can lead to the dispersion of the current away from the lobules underlying the active electrode. We concluded that an individualized ctDCS approach for dosimetry is critical when ctDCS is used as an adjuvant treatment for active aging to address age-related lobule-specific cerebellar geriatric syndromes effectively. Future work is necessary to investigate age-related effects of lobule-specific ctDCS on the large-scale cognitive and motor networks using functional neuroimaging that is expected due to the cerebellum's extensive reciprocal connectivity with the cerebral cortex.

Deep Cerebellar Transcranial Direct Current Stimulation of the Dentate Nucleus to Facilitate Standing Balance in Chronic Stroke Survivors-A Pilot Study.

Objective: Cerebrovascular accidents are the second leading cause of death and the third leading cause of disability worldwide. We hypothesized that cerebellar transcranial direct current stimulation (ctDCS) of the dentate nuclei and the lower-limb representations in the cerebellum can improve functional reach during standing balance in chronic (>6 months’ post-stroke) stroke survivors. Materials and Methods: Magnetic resonance imaging (MRI) based subject-specific electric field was computed across a convenience sample of 10 male chronic (>6 months) stroke survivors and one healthy MRI template to find an optimal bipolar bilateral ctDCS montage to target dentate nuclei and lower-limb representations (lobules VII–IX). Then, in a repeated-measure crossover study on a subset of 5 stroke survivors, we compared 15 min of 2 mA ctDCS based on the effects on successful functional reach (%) during standing balance task. Three-way ANOVA investigated the factors of interest– brain regions, montages, stroke participants, and their interactions. Results: “One-size-fits-all” bipolar ctDCS montage for the clinical study was found to be PO9h–PO10h for dentate nuclei and Exx7–Exx8 for lobules VII–IX with the contralesional anode. PO9h–PO10h ctDCS performed significantly (alpha = 0.05) better in facilitating successful functional reach (%) when compared to Exx7–Exx8 ctDCS. Furthermore, a linear relationship between successful functional reach (%) and electric field strength was found where PO9h–PO10h montage resulted in a significantly (alpha = 0.05) higher electric field strength when compared to Exx7–Exx8 montage for the same 2 mA current. Conclusion: We presented a rational neuroimaging based approach to optimize deep ctDCS of the dentate nuclei and lower limb representations in the cerebellum for post-stroke balance rehabilitation. However, this promising pilot study was limited by “one-size-fits-all” bipolar ctDCS montage as well as a small sample size.

Effects of Maturation on Striatal Dopamine Transporter Availability in Rats.

We investigated the effects of maturation on dopamine transporter (DAT) availability in the rat via longitudinal monitoring with positron emission tomography (PET). Eight 5-week-old male Sprague-Dawley rats (113-186 g) were used. Four 18F-FP-CIT PET scans were taken at 5, 10, 15, and 20 weeks. Baseline PET images were manually fused with the built-in magnetic resonance imaging template; volumes of interest (VOIs) were manually defined by placing a spherical region around the hot spot with the maximum count rate. VOIs were placed on bilateral caudate and putamen (CPu), nucleus accumbens (NAc), and cerebellum. Specific binding ratios (SBRs) were calculated as follows: (mean uptake of bilateral targets-mean uptake of bilateral cerebellum)/(mean uptake of bilateral cerebellum). In CPu, SBRs at 5 weeks (3.25 ± 0.66) were lower than those at 10 weeks (4.59 ± 0.78, p = 0.1151) and at 15 weeks (5.56 ± 0.92, p = 0.0182). In NAc, SBRs at 5 weeks (1.41 ± 0.47) were lower than those at 10 weeks (2.03 ± 0.36, p = 0.1960) and at 15 weeks (2.43 ± 0.50, p = 0.0427). SBRs in CPu and NAc significantly increased with maturation until 15 weeks. However, differences in SBR between 15 and 20 weeks were not significant. Striatal DAT availability increases until 15 weeks postnatally, then remains stable, reflecting maturation of the dopaminergic system in rats.

The structural MRI markers and cognitive decline in prodromal Alzheimer's disease: a 2-year longitudinal study.

Being clinically diagnosed with a mild cognitive impairment (MCI) due to Alzheimer's disease (AD) is widely studied. Yet, the clinical and structural neuroimaging characteristics for prodromal AD, which are defined as A+T+MCI based on the AT (N) system are still highly desirable. This study evaluates the differences of the cognitive assessments and structural magnetic resonance imaging (MRI) between the early MCI (EMCI) and late MCI (LMCI) participants based on the AT (N) system. The potential clinical value of the structural MRI as a predictor of cognitive decline during follow-up in prodromal AD is further investigated. A total of 406 MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were chosen and dichotomized into EMCI and LMCI groups according to the Second Edition (Logical Memory II) Wechsler Memory Scale. Multiple markers' data was collected, including age, sex, years of education, ApoE4 status, cerebrospinal fluid (CSF) biomarkers, standardized uptake values ratios (SUVR) means of florbetapir-PET-AV45, cognitive measures, and structural MRI. We chose 197 A+T+MCI participants (prodromal AD) with positive biomarkers of Aβ plaques (labeled "A") and fibrillar tau (labeled "T"). We diagnosed Aβ plaques positive by the SUVR means of florbetapir-PET-AV45 (cut-off >1.1) and fibrillar tau positive by CSF phosphorylated-tau at threonine 181 (p-tau) (cut-off >23 pg/mL). The differences of cognitive assessments and regions of interest (ROIs) defined on the MRI template between EMCI and LMCI were compared. Furthermore, the potential clinical utility of the MRI as the predictor of cognitive decline in prodromal AD was evaluated by investigating the relationship between baseline MRI markers and cognition decline at the follow-up period, through a linear regression model. The LMCI participants had a significantly more amyloid burden and CSF levels of total t-tau than the EMCI participants. The LMCI participants scored a lower result than the EMCI group in the global cognition scales and subscales which included tests for memory, delayed recall memory, executive function, language, attention and visuospatial skills. The cognition levels declined faster in the LMCI participants during the 12- and 24-month follow-up. There were significant differences in ROIs on the structural MRI between the two groups, including a bilateral entorhinal, a bilateral hippocampus, a bilateral amygdala, a bilateral lateral ventricle and cingulate, a corpus callosum, and a left temporal. The thickness average of the left entorhinal, the left middle temporal, the left superior temporal, and the right isthmus cingulate was a main contributor to the decreased global cognition levels. The thickness average of the left superior temporal and bilateral entorhinal played a key role in the memory domain decline. The thickness average of the left middle temporal, and the right isthmus cingulate was significantly associated with an executive function decline. Based on the AT (N) system, surely, both the EMCI and LMCI diagnoses presented significant differences in multiple cognition domains. Signature ROIs from the structural MRI tests had correlated a cognitive decline, and could act as one potential predictive marker.

Rhesus Macaque Brain Atlas Regions Aligned to an MRI Template.

To aid in the analysis of rhesus macaque brain images, we aligned digitized anatomical regions from the widely used atlas of Paxinos et al. to a published magnetic resonance imaging (MRI) template based on a large number of subjects. Digitally labelled atlas images were aligned to the template in 2D and then in 3D. The resulting grey matter regions appear qualitatively to be well registered to the template. To quantitatively validate the procedure, MR brain images of 20 rhesus macaques were aligned to the template along with regions drawn by hand in striatal and cortical areas in each subject's MRI. There was good geometric overlap between the hand drawn regions and the template regions. Positron emission tomography (PET) images of the same subjects showing uptake of a dopamine D2 receptor ligand were aligned to the template space, and good agreement was found between tracer binding measures calculated using the hand drawn and template regions. In conclusion, an anatomically defined set of rhesus macaque brain regions has been aligned to an MRI template and has been validated for analysis of PET imaging in a subset of striatal and cortical areas. The entire set of over 200 regions is publicly available at https://www.nitrc.org/ . Graphical Abstract ᅟ.