Browsing by Author "Badea, Alexandra"
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Item Open Access A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data.(Cereb Cortex, 2015-11) Calabrese, Evan; Badea, Alexandra; Cofer, Gary; Qi, Yi; Johnson, G AllanInterest in structural brain connectivity has grown with the understanding that abnormal neural connections may play a role in neurologic and psychiatric diseases. Small animal connectivity mapping techniques are particularly important for identifying aberrant connectivity in disease models. Diffusion magnetic resonance imaging tractography can provide nondestructive, 3D, brain-wide connectivity maps, but has historically been limited by low spatial resolution, low signal-to-noise ratio, and the difficulty in estimating multiple fiber orientations within a single image voxel. Small animal diffusion tractography can be substantially improved through the combination of ex vivo MRI with exogenous contrast agents, advanced diffusion acquisition and reconstruction techniques, and probabilistic fiber tracking. Here, we present a comprehensive, probabilistic tractography connectome of the mouse brain at microscopic resolution, and a comparison of these data with a neuronal tracer-based connectivity data from the Allen Brain Atlas. This work serves as a reference database for future tractography studies in the mouse brain, and demonstrates the fundamental differences between tractography and neuronal tracer data.Item Open Access Accelerated Brain Atrophy, Microstructural Decline and Connectopathy in Age-Related Macular Degeneration.(Biomedicines, 2024-01-10) Stout, Jacques A; Mahzarnia, Ali; Dai, Rui; Anderson, Robert J; Cousins, Scott; Zhuang, Jie; Lad, Eleonora M; Whitaker, Diane B; Madden, David J; Potter, Guy G; Whitson, Heather E; Badea, AlexandraAge-related macular degeneration (AMD) has recently been linked to cognitive impairment. We hypothesized that AMD modifies the brain aging trajectory, and we conducted a longitudinal diffusion MRI study on 40 participants (20 with AMD and 20 controls) to reveal the location, extent, and dynamics of AMD-related brain changes. Voxel-based analyses at the first visit identified reduced volume in AMD participants in the cuneate gyrus, associated with vision, and the temporal and bilateral cingulate gyrus, linked to higher cognition and memory. The second visit occurred 2 years after the first and revealed that AMD participants had reduced cingulate and superior frontal gyrus volumes, as well as lower fractional anisotropy (FA) for the bilateral occipital lobe, including the visual and the superior frontal cortex. We detected faster rates of volume and FA reduction in AMD participants in the left temporal cortex. We identified inter-lingual and lingual-cerebellar connections as important differentiators in AMD participants. Bundle analyses revealed that the lingual gyrus had a lower streamline length in the AMD participants at the first visit, indicating a connection between retinal and brain health. FA differences in select inter-lingual and lingual cerebellar bundles at the second visit showed downstream effects of vision loss. Our analyses revealed widespread changes in AMD participants, beyond brain networks directly involved in vision processing.Item Open Access Altered mGluR5-Homer scaffolds and corticostriatal connectivity in a Shank3 complete knockout model of autism.(Nat Commun, 2016-05-10) Wang, Xiaoming; Bey, Alexandra L; Katz, Brittany M; Badea, Alexandra; Kim, Namsoo; David, Lisa K; Duffney, Lara J; Kumar, Sunil; Mague, Stephen D; Hulbert, Samuel W; Dutta, Nisha; Hayrapetyan, Volodya; Yu, Chunxiu; Gaidis, Erin; Zhao, Shengli; Ding, Jin-Dong; Xu, Qiong; Chung, Leeyup; Rodriguiz, Ramona M; Wang, Fan; Weinberg, Richard J; Wetsel, William C; Dzirasa, Kafui; Yin, Henry; Jiang, Yong-HuiHuman neuroimaging studies suggest that aberrant neural connectivity underlies behavioural deficits in autism spectrum disorders (ASDs), but the molecular and neural circuit mechanisms underlying ASDs remain elusive. Here, we describe a complete knockout mouse model of the autism-associated Shank3 gene, with a deletion of exons 4-22 (Δe4-22). Both mGluR5-Homer scaffolds and mGluR5-mediated signalling are selectively altered in striatal neurons. These changes are associated with perturbed function at striatal synapses, abnormal brain morphology, aberrant structural connectivity and ASD-like behaviour. In vivo recording reveals that the cortico-striatal-thalamic circuit is tonically hyperactive in mutants, but becomes hypoactive during social behaviour. Manipulation of mGluR5 activity attenuates excessive grooming and instrumental learning differentially, and rescues impaired striatal synaptic plasticity in Δe4-22(-/-) mice. These findings show that deficiency of Shank3 can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities that underlie deficits in learning and ASD-like behaviours. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs.Item Open Access An Online Repository for Pre-Clinical Imaging Protocols (PIPs).(Tomography (Ann Arbor, Mich.), 2023-03) Gammon, Seth T; Cohen, Allison S; Lehnert, Adrienne L; Sullivan, Daniel C; Malyarenko, Dariya; Manning, Henry Charles; Hormuth, David A; Daldrup-Link, Heike E; An, Hongyu; Quirk, James D; Shoghi, Kooresh; Pagel, Mark David; Kinahan, Paul E; Miyaoka, Robert S; Houghton, A McGarry; Lewis, Michael T; Larson, Peder; Sriram, Renuka; Blocker, Stephanie J; Pickup, Stephen; Badea, Alexandra; Badea, Cristian T; Yankeelov, Thomas E; Chenevert, Thomas LProviding method descriptions that are more detailed than currently available in typical peer reviewed journals has been identified as an actionable area for improvement. In the biochemical and cell biology space, this need has been met through the creation of new journals focused on detailed protocols and materials sourcing. However, this format is not well suited for capturing instrument validation, detailed imaging protocols, and extensive statistical analysis. Furthermore, the need for additional information must be counterbalanced by the additional time burden placed upon researchers who may be already overtasked. To address these competing issues, this white paper describes protocol templates for positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) that can be leveraged by the broad community of quantitative imaging experts to write and self-publish protocols in protocols.io. Similar to the Structured Transparent Accessible Reproducible (STAR) or Journal of Visualized Experiments (JoVE) articles, authors are encouraged to publish peer reviewed papers and then to submit more detailed experimental protocols using this template to the online resource. Such protocols should be easy to use, readily accessible, readily searchable, considered open access, enable community feedback, editable, and citable by the author.Item Open Access Automated multimodal segmentation of acute ischemic stroke lesions on clinical MR images.(Magnetic resonance imaging, 2022-10) Moon, Hae Sol; Heffron, Lindsay; Mahzarnia, Ali; Obeng-Gyasi, Barnabas; Holbrook, Matthew; Badea, Cristian T; Feng, Wuwei; Badea, AlexandraMagnetic resonance (MR) imaging (MRI) is commonly used to diagnose, assess and monitor stroke. Accurate and timely segmentation of stroke lesions provides the anatomico-structural information that can aid physicians in predicting prognosis, as well as in decision making and triaging for various rehabilitation strategies. To segment stroke lesions, MR protocols, including diffusion-weighted imaging (DWI) and T2-weighted fluid attenuated inversion recovery (FLAIR) are often utilized. These imaging sequences are usually acquired with different spatial resolutions due to time constraints. Within the same image, voxels may be anisotropic, with reduced resolution along slice direction for diffusion scans in particular. In this study, we evaluate the ability of 2D and 3D U-Net Convolutional Neural Network (CNN) architectures to segment ischemic stroke lesions using single contrast (DWI) and dual contrast images (T2w FLAIR and DWI). The predicted segmentations correlate with post-stroke motor outcome measured by the National Institutes of Health Stroke Scale (NIHSS) and Fugl-Meyer Upper Extremity (FM-UE) index based on the lesion loads overlapping the corticospinal tracts (CST), which is a neural substrate for motor movement and function. Although the four methods performed similarly, the 2D multimodal U-Net achieved the best results with a mean Dice of 0.737 (95% CI: 0.705, 0.769) and a relatively high correlation between the weighted lesion load and the NIHSS scores (both at baseline and at 90 days). A monotonically constrained quintic polynomial regression yielded R2 = 0.784 and 0.875 for weighted lesion load versus baseline and 90-Days NIHSS respectively, and better corrected Akaike information criterion (AICc) scores than those of the linear regression. In addition, using the quintic polynomial regression model to regress the weighted lesion load to the 90-Days FM-UE score results in an R2 of 0.570 with a better AICc score than that of the linear regression. Our results suggest that the multi-contrast information enhanced the accuracy of the segmentation and the prediction accuracy for upper extremity motor outcomes. Expanding the training dataset to include different types of stroke lesions and more data points will help add a temporal longitudinal aspect and increase the accuracy. Furthermore, adding patient-specific data may improve the inference about the relationship between imaging metrics and functional outcomes.Item Open Access Cerebral white matter connectivity, cognition, and age-related macular degeneration.(NeuroImage. Clinical, 2021-02-23) Zhuang, Jie; Madden, David J; Cunha, Priscila; Badea, Alexandra; Davis, Simon W; Potter, Guy G; Lad, Eleonora M; Cousins, Scott W; Chen, Nan-Kuei; Allen, Kala; Maciejewski, Abigail J; Fernandez, Xuan Duong; Diaz, Michele T; Whitson, Heather EAge-related macular degeneration (AMD) is a common retina disease associated with cognitive impairment in older adults. The mechanism(s) that account for the link between AMD and cognitive decline remain unclear. Here we aim to shed light on this issue by investigating whether relationships between cognition and white matter in the brain differ by AMD status. In a direct group comparison of brain connectometry maps from diffusion weighted images, AMD patients showed significantly weaker quantitative anisotropy (QA) than healthy controls, predominantly in the splenium and left optic radiation. The QA of these tracts, however, did not correlate with the visual acuity measure, indicating that this group effect is not directly driven by visual loss. The AMD and control groups did not differ significantly in cognitive performance.Across all participants, better cognitive performance (e.g. verbal fluency) is associated with stronger connectivity strength in white matter tracts including the splenium and the left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. However, there were significant interactions between group and cognitive performance (verbal fluency, memory), suggesting that the relation between QA and cognitive performance was weaker in AMD patients than in controls.This may be explained by unmeasured determinants of performance that are more common or impactful in AMD or by a recruitment bias whereby the AMD group had higher cognitive reserve. In general, our findings suggest that neural degeneration in the brain might occur in parallel to AMD in the eyes, although the participants studied here do not (yet) exhibit overt cognitive declines per standard assessments.Item Open Access High-resolution hybrid micro-CT imaging pipeline for mouse brain region segmentation and volumetric morphometry.(PloS one, 2024-01) Nadkarni, Rohan; Han, Zay Yar; Anderson, Robert J; Allphin, Alex J; Clark, Darin P; Badea, Alexandra; Badea, Cristian TBackground
Brain region segmentation and morphometry in humanized apolipoprotein E (APOE) mouse models with a human NOS2 background (HN) contribute to Alzheimer's disease (AD) research by demonstrating how various risk factors affect the brain. Photon-counting detector (PCD) micro-CT provides faster scan times than MRI, with superior contrast and spatial resolution to energy-integrating detector (EID) micro-CT. This paper presents a pipeline for mouse brain imaging, segmentation, and morphometry from PCD micro-CT.Methods
We used brains of 26 mice from 3 genotypes (APOE22HN, APOE33HN, APOE44HN). The pipeline included PCD and EID micro-CT scanning, hybrid (PCD and EID) iterative reconstruction, and brain region segmentation using the Small Animal Multivariate Brain Analysis (SAMBA) tool. We applied SAMBA to transfer brain region labels from our new PCD CT atlas to individual PCD brains via diffeomorphic registration. Region-based and voxel-based analyses were used for comparisons by genotype and sex.Results
Together, PCD and EID scanning take ~5 hours to produce images with a voxel size of 22 μm, which is faster than MRI protocols for mouse brain morphometry with voxel size above 40 μm. Hybrid iterative reconstruction generates PCD images with minimal artifacts and higher spatial resolution and contrast than EID images. Our PCD atlas is qualitatively and quantitatively similar to the prior MRI atlas and successfully transfers labels to PCD brains in SAMBA. Male and female mice had significant volume differences in 26 regions, including parts of the entorhinal cortex and cingulate cortex. APOE22HN brains were larger than APOE44HN brains in clusters from the hippocampus, a region where atrophy is associated with AD.Conclusions
This work establishes a pipeline for mouse brain analysis using PCD CT, from staining to imaging and labeling brain images. Our results validate the effectiveness of the approach, setting a foundation for research on AD mouse models while reducing scanning durations.Item Open Access Localization of Metal Electrodes in the Intact Rat Brain Using Registration of 3D Microcomputed Tomography Images to a Magnetic Resonance Histology Atlas.(eNeuro, 2015-07) Borg, Jana Schaich; Vu, Mai-Anh; Badea, Cristian; Badea, Alexandra; Johnson, G Allan; Dzirasa, KafuiSimultaneous neural recordings taken from multiple areas of the rodent brain are garnering growing interest due to the insight they can provide about spatially distributed neural circuitry. The promise of such recordings has inspired great progress in methods for surgically implanting large numbers of metal electrodes into intact rodent brains. However, methods for localizing the precise location of these electrodes have remained severely lacking. Traditional histological techniques that require slicing and staining of physical brain tissue are cumbersome, and become increasingly impractical as the number of implanted electrodes increases. Here we solve these problems by describing a method that registers 3-D computerized tomography (CT) images of intact rat brains implanted with metal electrode bundles to a Magnetic Resonance Imaging Histology (MRH) Atlas. Our method allows accurate visualization of each electrode bundle's trajectory and location without removing the electrodes from the brain or surgically implanting external markers. In addition, unlike physical brain slices, once the 3D images of the electrode bundles and the MRH atlas are registered, it is possible to verify electrode placements from many angles by "re-slicing" the images along different planes of view. Further, our method can be fully automated and easily scaled to applications with large numbers of specimens. Our digital imaging approach to efficiently localizing metal electrodes offers a substantial addition to currently available methods, which, in turn, may help accelerate the rate at which insights are gleaned from rodent network neuroscience.Item Open Access Magnetic resonance microscopy.(Anal Cell Pathol (Amst), 2012) Badea, Alexandra; Johnson, G AllanItem Open Access Quantitative mapping of trimethyltin injury in the rat brain using magnetic resonance histology.(Neurotoxicology, 2014-05) Johnson, G Allan; Calabrese, Evan; Little, Peter B; Hedlund, Laurence; Qi, Yi; Badea, AlexandraThe growing exposure to chemicals in our environment and the increasing concern over their impact on health have elevated the need for new methods for surveying the detrimental effects of these compounds. Today's gold standard for assessing the effects of toxicants on the brain is based on hematoxylin and eosin (H&E)-stained histology, sometimes accompanied by special stains or immunohistochemistry for neural processes and myelin. This approach is time-consuming and is usually limited to a fraction of the total brain volume. We demonstrate that magnetic resonance histology (MRH) can be used for quantitatively assessing the effects of central nervous system toxicants in rat models. We show that subtle and sparse changes to brain structure can be detected using magnetic resonance histology, and correspond to some of the locations in which lesions are found by traditional pathological examination. We report for the first time diffusion tensor image-based detection of changes in white matter regions, including fimbria and corpus callosum, in the brains of rats exposed to 8 mg/kg and 12 mg/kg trimethyltin. Besides detecting brain-wide changes, magnetic resonance histology provides a quantitative assessment of dose-dependent effects. These effects can be found in different magnetic resonance contrast mechanisms, providing multivariate biomarkers for the same spatial location. In this study, deformation-based morphometry detected areas where previous studies have detected cell loss, while voxel-wise analyses of diffusion tensor parameters revealed microstructural changes due to such things as cellular swelling, apoptosis, and inflammation. Magnetic resonance histology brings a valuable addition to pathology with the ability to generate brain-wide quantitative parametric maps for markers of toxic insults in the rodent brain.Item Open Access Spatial Correlates Integrating Image and Behavioral Biomarkers of Cognitive Dysfunction in Mouse Models of AD(2017) Delpratt, NatalieAlzheimer’s disease (AD) is a disorder that is the 6th leading cause of death in the United States. Although physicians and researchers are aware of the pathologies that come with the disease such as the presence of amyloid plaques, neurofibrillary tangles, and neuronal degeneration - the actual onset and progression of the disease is unknown. Currently, there is no known cure for Alzheimer’s. Therefore, it is critical to identify early biomarkers, to help better understand the disease in its early stages and monitor possible treatments given to patients. In this study, mouse models of AD and age matched controls are utilized in a multivariate approach using several magnetic resonance imaging protocols to identify potential image based biomarkers attributed to AD. We used predictive-based methods of imaging and behavior metrics to identify relevant anatomical networks by means of sparse regression. Another method to determine generalizable regions of interest based solely on imaging data was obtained from eigenanatomy. This knowledge of associative regions by either method was used for predictive modeling of behavioral characteristics in AD and control mice. Several regions, cerebellum, hippocampus, and motor cortex, showed significant changes in each of the three imaging contrasts and were also identified as linked to memory impairment. Successful predictions were produced for behavior assessment using the Morris Water Maze. All things considered, predictive analysis via imaging and behavior could be used to determine regions associated with AD that also match up with imaging markers of the disease.