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Patel J, Schöttner M, Tarun A, Tourbier S, Alemán-Gómez Y, Hagmann P, Bolton TAW. Modeling the impact of MRI acquisition bias on structural connectomes: Harmonizing structural connectomes. Netw Neurosci 2024; 8:623-652. [PMID: 39355442 PMCID: PMC11340995 DOI: 10.1162/netn_a_00368] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 02/26/2024] [Indexed: 10/03/2024] Open
Abstract
One way to increase the statistical power and generalizability of neuroimaging studies is to collect data at multiple sites or merge multiple cohorts. However, this usually comes with site-related biases due to the heterogeneity of scanners and acquisition parameters, negatively impacting sensitivity. Brain structural connectomes are not an exception: Being derived from T1-weighted and diffusion-weighted magnetic resonance images, structural connectivity is impacted by differences in imaging protocol. Beyond minimizing acquisition parameter differences, removing bias with postprocessing is essential. In this work we create, from the exhaustive Human Connectome Project Young Adult dataset, a resampled dataset of different b-values and spatial resolutions, modeling a cohort scanned across multiple sites. After demonstrating the statistical impact of acquisition parameters on connectivity, we propose a linear regression with explicit modeling of b-value and spatial resolution, and validate its performance on separate datasets. We show that b-value and spatial resolution affect connectivity in different ways and that acquisition bias can be reduced using a linear regression informed by the acquisition parameters while retaining interindividual differences and hence boosting fingerprinting performance. We also demonstrate the generative potential of our model, and its generalization capability in an independent dataset reflective of typical acquisition practices in clinical settings.
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Affiliation(s)
- Jagruti Patel
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Mikkel Schöttner
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Anjali Tarun
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Sebastien Tourbier
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Yasser Alemán-Gómez
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
| | - Thomas A W Bolton
- Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
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2
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Armstrong RC, Sullivan GM, Perl DP, Rosarda JD, Radomski KL. White matter damage and degeneration in traumatic brain injury. Trends Neurosci 2024; 47:677-692. [PMID: 39127568 DOI: 10.1016/j.tins.2024.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 06/17/2024] [Accepted: 07/19/2024] [Indexed: 08/12/2024]
Abstract
Traumatic brain injury (TBI) is a complex condition that can resolve over time but all too often leads to persistent symptoms, and the risk of poor patient outcomes increases with aging. TBI damages neurons and long axons within white matter tracts that are critical for communication between brain regions; this causes slowed information processing and neuronal circuit dysfunction. This review focuses on white matter injury after TBI and the multifactorial processes that underlie white matter damage, potential for recovery, and progression of degeneration. A multiscale perspective across clinical and preclinical advances is presented to encourage interdisciplinary insights from whole-brain neuroimaging of white matter tracts down to cellular and molecular responses of axons, myelin, and glial cells within white matter tissue.
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Affiliation(s)
- Regina C Armstrong
- Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA; Military Traumatic Brain Injury Initiative (MTBI(2)), Bethesda, MD, USA.
| | - Genevieve M Sullivan
- Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA; Military Traumatic Brain Injury Initiative (MTBI(2)), Bethesda, MD, USA; Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA
| | - Daniel P Perl
- Pathology, School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA; Department of Defense - Uniformed Services University Brain Tissue Repository, Bethesda, MD, USA
| | - Jessica D Rosarda
- Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Kryslaine L Radomski
- Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
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3
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Cottam NC, Ofori K, Bryant M, Rogge JR, Hekmatyar K, Sun J, Charvet CJ. From circuits to lifespan: translating mouse and human timelines with neuroimaging based tractography. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.28.605528. [PMID: 39131378 PMCID: PMC11312435 DOI: 10.1101/2024.07.28.605528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Age is a major predictor of developmental processes and disease risk, but humans and model systems (e.g., mice) differ substantially in the pace of development and aging. The timeline of human developmental circuits is well known. It is unclear how such timelines compare to those in mice. We lack age alignments across the lifespan of mice and humans. Here, we build upon our Translating Time resource, which is a tool that equates corresponding ages during development. We collected 477 time points (n=1,132 observations) from age-related changes in body, bone, dental, and brain processes to equate corresponding ages across humans and mice. We acquired high-resolution diffusion MR scans of mouse brains (n=12) at sequential stages of postnatal development (postnatal day 3, 4, 12, 21, 60) to trace the timeline of brain circuit maturation (e.g., olfactory association pathway, corpus callosum). We found heterogeneity in white matter pathway growth. The corpus callosum largely ceases to grow days after birth while the olfactory association pathway grows through P60. We found that a P3 mouse equates to a human at roughly GW24, and a P60 mouse equates to a human in teenage years. Therefore, white matter pathway maturation is extended in mice as it is in humans, but there are species-specific adaptations. For example, olfactory-related wiring is protracted in mice, which is linked to their reliance on olfaction. Our findings underscore the importance of translational tools to map common and species-specific biological processes from model systems to humans.
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Affiliation(s)
- Nicholas C. Cottam
- Department of Biological Sciences, Delaware State University, Dover, DE, USA
| | - Kwadwo Ofori
- Department of Biological Sciences, Delaware State University, Dover, DE, USA
| | - Madison Bryant
- College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Jessica R. Rogge
- College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Khan Hekmatyar
- Center for Biomedical and Brain Imaging Center, University of Delaware, Wilmington, DE, USA
- Advanced Translational Imaging Facility, Georgia State University, Atlanta, GA
| | - Jianli Sun
- Department of Biological Sciences, Delaware State University, Dover, DE, USA
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4
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Mansour H, Azrak R, Cook JJ, Hornburg KJ, Qi Y, Tian Y, Williams RW, Yeh FC, White LE, Johnson GA. An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.28.587246. [PMID: 38586051 PMCID: PMC10996689 DOI: 10.1101/2024.03.28.587246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
We have combined MR histology and light sheet microscopy (LSM) of five postmortem C57BL/6J mouse brains in a stereotaxic space based on micro-CT yielding a multimodal 3D atlas with the highest spatial and contrast resolution yet reported. Brains were imaged in situ with multi gradient echo (mGRE) and diffusion tensor imaging (DTI) at 15 μm resolution (∼ 2.4 million times that of clinical MRI). Scalar images derived from the average DTI and mGRE provide unprecedented contrast in 14 complementary 3D volumes, each highlighting distinct histologic features. The same tissues scanned with LSM and registered into the stereotaxic space provide 17 different molecular cell type stains. The common coordinate framework labels (CCFv3) complete the multimodal atlas. The atlas has been used to correct distortions in the Allen Brain Atlas and harmonize it with Franklin Paxinos. It provides a unique resource for stereotaxic labeling of mouse brain images from many sources.
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Cerdán Cerdá A, Toschi N, Treaba CA, Barletta V, Herranz E, Mehndiratta A, Gomez-Sanchez JA, Mainero C, De Santis S. A translational MRI approach to validate acute axonal damage detection as an early event in multiple sclerosis. eLife 2024; 13:e79169. [PMID: 38192199 PMCID: PMC10776086 DOI: 10.7554/elife.79169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 12/05/2023] [Indexed: 01/10/2024] Open
Abstract
Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls. AxCaliber is sensitive to acute axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the targeted tract, which correlated with neurofilament staining. Electron microscopy confirmed that increased mean axonal diameter is associated with acute axonal pathology. In humans with multiple sclerosis, we uncovered a diffuse increase in mean axonal caliber in most areas of the normal-appearing white matter, preferentially affecting patients with short disease duration. Our results demonstrate that MRI-based axonal diameter mapping is a sensitive and specific imaging biomarker that links noninvasive imaging contrasts with the underlying biological substrate, uncovering generalized axonal damage in multiple sclerosis as an early event.
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Affiliation(s)
| | - Nicola Toschi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
- Department of Biomedicine and Prevention, University of Rome Tor VergataRomeItaly
| | - Constantina A Treaba
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Valeria Barletta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Elena Herranz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Ambica Mehndiratta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Jose A Gomez-Sanchez
- Instituto de Neurociencias de Alicante, CSIC-UMHSan Juan de AlicanteSpain
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL)AlicanteSpain
- Millennium Nucleus for the Study of Pain (MiNuSPain)SantiagoChile
| | - Caterina Mainero
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Silvia De Santis
- Instituto de Neurociencias de Alicante, CSIC-UMHSan Juan de AlicanteSpain
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Chakhoyan A, Shkrkova K, Sizdahkhani S, Huuskonen MT, Lamorie-Foote K, Diaz A, Chen S, Liu Q, D'Agostino C, Zhang H, Mack WJ, Sioutas C, Finch CE, Zlokovic B, Mack WJ. Magnetic resonance imaging of white matter response to diesel exhaust particles. RESEARCH SQUARE 2023:rs.3.rs-3087503. [PMID: 37503159 PMCID: PMC10371072 DOI: 10.21203/rs.3.rs-3087503/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Air pollution is associated with risks of dementia and accelerated cognitive decline. Rodent air pollution models have shown white matter vulnerability. This study uses diffusion tensor imaging (DTI) to quantify changes to white matter microstructure and tractography in multiple myelinated regions after exposure to diesel exhaust particulate (DEP). Adult C57BL/6 male mice were exposed to re-aerosolized DEP (NIST SRM 2975) at a concentration of 100 ug/m3 for 200 hours. Ex-vivo MRI analysis and fractional anisotropy (FA)-aided white matter tractography were conducted to study the effect of DEP exposure on the brain white matter tracts. Immunohistochemistry was used to assess myelin and axonal structure. DEP exposure for 8 weeks altered myelin composition in multiple regions. Diffusion tensor imaging (DTI) showed decreased FA in the corpus callosum (30%), external capsule (15%), internal capsule (15%), and cingulum (31 %). Separate immunohistochemistry analyses confirmed prior findings. Myelin basic protein (MBP) was decreased (corpus callosum: 28%, external capsule: 29%), and degraded MPB increased (corpus callosum: 32%, external capsule: 53%) in the DEP group. White matter is highly susceptible to chronic DEP exposure. This study demonstrates the utility of DTI as a neuroanatomical tool in the context of air pollution and white matter myelin vulnerability.
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Affiliation(s)
- Ararat Chakhoyan
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Kristina Shkrkova
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Saman Sizdahkhani
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Mikko T Huuskonen
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Krista Lamorie-Foote
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Arnold Diaz
- Leonard Davis School of Gerontology, University of Southern California
| | - Selena Chen
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Qinghai Liu
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - Carla D'Agostino
- Leonard Davis School of Gerontology, University of Southern California
| | - Hongqiao Zhang
- Leonard Davis School of Gerontology, University of Southern California
| | - Wendy J Mack
- Department of Population and Public Health Sciences, Keck School of Medicine
| | | | - Caleb E Finch
- Leonard Davis School of Gerontology, University of Southern California
| | - Berislav Zlokovic
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
| | - William J Mack
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California
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7
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Merenstein JL, Zhao J, Mullin HA, Rudolph MD, Song AW, Madden DJ. High-resolution multi-shot diffusion imaging of structural networks in healthy neurocognitive aging. Neuroimage 2023; 275:120191. [PMID: 37244322 PMCID: PMC10482115 DOI: 10.1016/j.neuroimage.2023.120191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 05/10/2023] [Accepted: 05/24/2023] [Indexed: 05/29/2023] Open
Abstract
Healthy neurocognitive aging has been associated with the microstructural degradation of white matter pathways that connect distributed gray matter regions, assessed by diffusion-weighted imaging (DWI). However, the relatively low spatial resolution of standard DWI has limited the examination of age-related differences in the properties of smaller, tightly curved white matter fibers, as well as the relatively more complex microstructure of gray matter. Here, we capitalize on high-resolution multi-shot DWI, which allows spatial resolutions < 1 mm3 to be achieved on clinical 3T MRI scanners. We assessed whether traditional diffusion tensor-based measures of gray matter microstructure and graph theoretical measures of white matter structural connectivity assessed by standard (1.5 mm3 voxels, 3.375 μl volume) and high-resolution (1 mm3 voxels, 1μl volume) DWI were differentially related to age and cognitive performance in 61 healthy adults 18-78 years of age. Cognitive performance was assessed using an extensive battery comprising 12 separate tests of fluid (speed-dependent) cognition. Results indicated that the high-resolution data had larger correlations between age and gray matter mean diffusivity, but smaller correlations between age and structural connectivity. Moreover, parallel mediation models including both standard and high-resolution measures revealed that only the high-resolution measures mediated age-related differences in fluid cognition. These results lay the groundwork for future studies planning to apply high-resolution DWI methodology to further assess the mechanisms of both healthy aging and cognitive impairment.
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Affiliation(s)
- Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA.
| | - Jiayi Zhao
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA
| | - Hollie A Mullin
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA
| | - Marc D Rudolph
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
| | - Allen W Song
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA
| | - David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, 27710, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA
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8
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Arefin TM, Lee CH, Liang Z, Rallapalli H, Wadghiri YZ, Turnbull DH, Zhang J. Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI. Neuroimage 2023; 273:120111. [PMID: 37060936 PMCID: PMC10149621 DOI: 10.1016/j.neuroimage.2023.120111] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/29/2023] [Accepted: 04/12/2023] [Indexed: 04/17/2023] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography has yielded intriguing insights into brain circuits and their relationship to behavior in response to gene mutations or neurological diseases across a number of species. Still, existing tractography approaches suffer from limited sensitivity and specificity, leading to uncertain interpretation of the reconstructed connections. Hence, in this study, we aimed to optimize the imaging and computational pipeline to achieve the best possible spatial overlaps between the tractography and tracer-based axonal projection maps within the mouse brain corticothalamic network. We developed a dMRI-based atlas of the mouse forebrain with structural labels imported from the Allen Mouse Brain Atlas (AMBA). Using the atlas and dMRI tractography, we first reconstructed detailed node-to-node mouse brain corticothalamic structural connectivity matrices using different imaging and tractography parameters. We then investigated the effects of each condition for accurate reconstruction of the corticothalamic projections by quantifying the similarities between the tractography and the tracer data from the Allen Mouse Brain Connectivity Atlas (AMBCA). Our results suggest that these parameters significantly affect tractography outcomes and our atlas can be used to investigate macroscopic structural connectivity in the mouse brain. Furthermore, tractography in mouse brain gray matter still face challenges and need improved imaging and tractography methods.
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Affiliation(s)
- Tanzil Mahmud Arefin
- Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States; Center for Neurotechnology in Mental Health Research, Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, United States
| | - Choong Heon Lee
- Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States
| | - Zifei Liang
- Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States
| | - Harikrishna Rallapalli
- Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States
| | - Youssef Z Wadghiri
- Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States
| | - Daniel H Turnbull
- Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States
| | - Jiangyang Zhang
- Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, 660 First Ave., New York City, NY, United States.
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9
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Johnson GA, Tian Y, Ashbrook DG, Cofer GP, Cook JJ, Gee JC, Hall A, Hornburg K, Qi Y, Yeh FC, Wang N, White LE, Williams RW. Merged magnetic resonance and light sheet microscopy of the whole mouse brain. Proc Natl Acad Sci U S A 2023; 120:e2218617120. [PMID: 37068254 PMCID: PMC10151475 DOI: 10.1073/pnas.2218617120] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/10/2023] [Indexed: 04/19/2023] Open
Abstract
We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 μm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 μm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 μm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a high-dimensional integrated volume with registration (HiDiver) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.
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Affiliation(s)
| | - Yuqi Tian
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - David G. Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN38162
| | - Gary P. Cofer
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - James J. Cook
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - James C. Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA19104
| | - Adam Hall
- LifeCanvas Technology, Cambridge, MA02141
| | | | - Yi Qi
- Center for In Vivo Microscopy, Duke University, Durham, NC27710
| | - Fang-Cheng Yeh
- Department of Neurologic Surgery, University of Pittsburgh, Pittsburgh, PA15260
| | - Nian Wang
- Department of Radiology, Indiana University, Bloomington, IN47401
| | | | - Robert W. Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN38162
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10
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Hornburg KJ, Slosky LM, Cofer G, Cook J, Qi Y, Porkka F, Clark NB, Pires A, Petrella JR, White LE, Wetsel WC, Barak L, Caron MG, Johnson GA. Prenatal heroin exposure alters brain morphology and connectivity in adolescent mice. NMR IN BIOMEDICINE 2023; 36:e4842. [PMID: 36259728 PMCID: PMC10483958 DOI: 10.1002/nbm.4842] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 09/30/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
The United States is experiencing a dramatic increase in maternal opioid misuse and, consequently, the number of individuals exposed to opioids in utero. Prenatal opioid exposure has both acute and long-lasting effects on health and wellbeing. Effects on the brain, often identified at school age, manifest as cognitive impairment, attention deficit, and reduced scholastic achievement. The neurobiological basis for these effects is poorly understood. Here, we examine how in utero exposure to heroin affects brain development into early adolescence in a mouse model. Pregnant C57BL/6J mice received escalating doses of heroin twice daily on gestational days 4-18. The brains of offspring were assessed on postnatal day 28 using 9.4 T diffusion MRI of postmortem specimens at 36 μm resolution. Whole-brain volumes and the volumes of 166 bilateral regions were compared between heroin-exposed and control offspring. We identified a reduction in whole-brain volume in heroin-exposed offspring and heroin-associated volume changes in 29 regions after standardizing for whole-brain volume. Regions with bilaterally reduced standardized volumes in heroin-exposed offspring relative to controls include the ectorhinal and insular cortices. Regions with bilaterally increased standardized volumes in heroin-exposed offspring relative to controls include the periaqueductal gray, septal region, striatum, and hypothalamus. Leveraging microscopic resolution diffusion tensor imaging and precise regional parcellation, we generated whole-brain structural MRI diffusion connectomes. Using a dimension reduction approach with multivariate analysis of variance to assess group differences in the connectome, we found that in utero heroin exposure altered structure-based connectivity of the left septal region and the region that acts as a hub for limbic regulatory actions. Consistent with clinical evidence, our findings suggest that prenatal opioid exposure may have effects on brain morphology, connectivity, and, consequently, function that persist into adolescence. This work expands our understanding of the risks associated with opioid misuse during pregnancy and identifies biomarkers that may facilitate diagnosis and treatment.
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Affiliation(s)
- Kathryn J. Hornburg
- Department of Radiology, School of Medicine, Duke University; 311 Research Drive; Campus Box 3302; Durham, NC 27710 United States
| | - Lauren M. Slosky
- Department of Cell Biology, School of Medicine, Duke University; Campus Box 3709; Durham, NC 27710 United States
- Department of Pharmacology, University of Minnesota; 312 Church Street SE; 3-104 Nils Hasselmo Hall; Minneapolis, MN 55455 United States
| | - Gary Cofer
- Department of Radiology, School of Medicine, Duke University; 311 Research Drive; Campus Box 3302; Durham, NC 27710 United States
| | - James Cook
- Department of Radiology, School of Medicine, Duke University; 311 Research Drive; Campus Box 3302; Durham, NC 27710 United States
| | - Yi Qi
- Department of Radiology, School of Medicine, Duke University; 311 Research Drive; Campus Box 3302; Durham, NC 27710 United States
| | - Fiona Porkka
- Department of Cell Biology, School of Medicine, Duke University; Campus Box 3709; Durham, NC 27710 United States
| | - Nicholas B. Clark
- Department of Cell Biology, School of Medicine, Duke University; Campus Box 3709; Durham, NC 27710 United States
| | - Andrea Pires
- Department of Cell Biology, School of Medicine, Duke University; Campus Box 3709; Durham, NC 27710 United States
| | - Jeffrey R Petrella
- Department of Radiology, School of Medicine, Duke University; 311 Research Drive; Campus Box 3302; Durham, NC 27710 United States
| | - Leonard E. White
- Department of Neurology, School of Medicine, Duke University; Campus Box 2900; Durham, NC 27710 United States
| | - William C. Wetsel
- Department of Cell Biology, School of Medicine, Duke University; Campus Box 3709; Durham, NC 27710 United States
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University; Campus Box 102508; Durham, NC 27710 United States
- Department of Neurology, School of Medicine, Duke University; Campus Box 2900; Durham, NC 27710 United States
| | - Lawrence Barak
- Department of Cell Biology, School of Medicine, Duke University; Campus Box 3709; Durham, NC 27710 United States
| | - Marc G. Caron
- Department of Cell Biology, School of Medicine, Duke University; Campus Box 3709; Durham, NC 27710 United States
- Department of Neurology, School of Medicine, Duke University; Campus Box 2900; Durham, NC 27710 United States
| | - G. Allan Johnson
- Department of Radiology, School of Medicine, Duke University; 311 Research Drive; Campus Box 3302; Durham, NC 27710 United States
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University; Campus Box 90281; Durham, NC 27708-0281 United States
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Maharjan S, Tsai AP, Lin PB, Ingraham C, Jewett MR, Landreth GE, Oblak AL, Wang N. Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging. Front Neurosci 2022; 16:964654. [PMID: 36061588 PMCID: PMC9428354 DOI: 10.3389/fnins.2022.964654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 07/18/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose To evaluate the age-dependent microstructure changes in 5xFAD mice using high-resolution diffusion tensor imaging (DTI). Methods The 5xFAD mice at 4, 7.5, and 12 months and the wild-type controls at 4 months were scanned at 9.4T using a 3D echo-planar imaging (EPI) pulse sequence with the isotropic spatial resolution of 100 μm. The b-value was 3000 s/mm2 for all the diffusion MRI scans. The samples were also acquired with a gradient echo pulse sequence at 50 μm isotropic resolution. The microstructure changes were quantified with DTI metrics, including fractional anisotropy (FA) and mean diffusivity (MD). The conventional histology was performed to validate with MRI findings. Results The FA values (p = 0.028) showed significant differences in the cortex between wild-type (WT) and 5xFAD mice at 4 months, while hippocampus, anterior commissure, corpus callosum, and fornix showed no significant differences for either FA and MD. FA values of 5xFAD mice gradually decreased in cortex (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) and fornix (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) with aging. Both FA (p = 0.029) and MD (p = 0.037) demonstrated significant differences in corpus callosum between 4 and 12 months age old. FA and MD were not significantly different in the hippocampus or anterior commissure. The age-dependent microstructure alterations were better captured by FA when compared to MD. Conclusion FA showed higher sensitivity to monitor amyloid deposition in 5xFAD mice. DTI may be utilized as a sensitive biomarker to monitor beta-amyloid progression for preclinical studies.
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Affiliation(s)
- Surendra Maharjan
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Andy P. Tsai
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Peter B. Lin
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Cynthia Ingraham
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Megan R. Jewett
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Gary E. Landreth
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- Department of Anatomy, Cell Biology and Physiology, Indiana University, Indianapolis, IN, United States
| | - Adrian L. Oblak
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- *Correspondence: Nian Wang,
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