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DeKraker J, Haast RAM, Yousif MD, Karat B, Lau JC, Köhler S, Khan AR. Automated hippocampal unfolding for morphometry and subfield segmentation with HippUnfold. eLife 2022; 11:77945. [PMID: 36519725 PMCID: PMC9831605 DOI: 10.7554/elife.77945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 12/13/2022] [Indexed: 12/16/2022] Open
Abstract
Like neocortical structures, the archicortical hippocampus differs in its folding patterns across individuals. Here, we present an automated and robust BIDS-App, HippUnfold, for defining and indexing individual-specific hippocampal folding in MRI, analogous to popular tools used in neocortical reconstruction. Such tailoring is critical for inter-individual alignment, with topology serving as the basis for homology. This topological framework enables qualitatively new analyses of morphological and laminar structure in the hippocampus or its subfields. It is critical for refining current neuroimaging analyses at a meso- as well as micro-scale. HippUnfold uses state-of-the-art deep learning combined with previously developed topological constraints to generate uniquely folded surfaces to fit a given subject's hippocampal conformation. It is designed to work with commonly employed sub-millimetric MRI acquisitions, with possible extension to microscopic resolution. In this paper, we describe the power of HippUnfold in feature extraction, and highlight its unique value compared to several extant hippocampal subfield analysis methods.
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Affiliation(s)
- Jordan DeKraker
- Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western OntarioLondonCanada,Western Institute for Neuroscience, The University of Western OntarioLondonCanada
| | - Roy AM Haast
- Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western OntarioLondonCanada
| | - Mohamed D Yousif
- Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western OntarioLondonCanada
| | - Bradley Karat
- Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western OntarioLondonCanada
| | - Jonathan C Lau
- Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western OntarioLondonCanada,Department of Clinical Neurological Sciences, Division of Neurosurgery, Schulich School of Medicine & Dentistry, The University of Western OntarioLondonCanada,School of Biomedical Engineering, The University of Western OntarioLondonCanada
| | - Stefan Köhler
- Western Institute for Neuroscience, The University of Western OntarioLondonCanada,Department of Psychology, Faculty of Social Science, The University of Western OntarioLondonCanada
| | - Ali R Khan
- Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western OntarioLondonCanada,Western Institute for Neuroscience, The University of Western OntarioLondonCanada,School of Biomedical Engineering, The University of Western OntarioLondonCanada,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, The University of Western OntarioLondonCanada
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2
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Ke J, Foley LM, Hitchens TK, Richardson RM, Modo M. Ex vivo mesoscopic diffusion MRI correlates with seizure frequency in patients with uncontrolled mesial temporal lobe epilepsy. Hum Brain Mapp 2020; 41:4529-4548. [PMID: 32691978 PMCID: PMC7555080 DOI: 10.1002/hbm.25139] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/08/2020] [Accepted: 07/05/2020] [Indexed: 12/28/2022] Open
Abstract
The role of hippocampal connectivity in mesial temporal lobe epilepsy (mTLE) remains poorly understood. The use of ex vivo hippocampal samples excised from patients with mTLE affords mesoscale diffusion magnetic resonance imaging (MRI) to identify individual cell layers, such as the pyramidal (PCL) and granule cell layers (GCL), which are thought to be impacted by seizure activity. Diffusion tensor imaging (DTI) of control (n = 3) and mTLE (n = 7) hippocampi on an 11.7 T MRI scanner allowed us to reveal intra‐hippocampal connectivity and evaluate how epilepsy affected mean (MD), axial (AD), and radial diffusivity (RD), as well as fractional anisotropy (FA). Regional measurements indicated a volume loss in the PCL of the cornu ammonis (CA) 1 subfield in mTLE patients compared to controls, which provided anatomical context. Diffusion measurements, as well as streamline density, were generally higher in mTLE patients compared to controls, potentially reflecting differences due to tissue fixation. mTLE measurements were more variable than controls. This variability was associated with disease severity, as indicated by a strong correlation (r = 0.87) between FA in the stratum radiatum and the frequency of seizures in patients. MD and RD of the PCL in subfields CA3 and CA4 also correlated strongly with disease severity. No correlation of MR measures with disease duration was evident. These results reveal the potential of mesoscale diffusion MRI to examine layer‐specific diffusion changes and connectivity to determine how these relate to clinical measures. Improving the visualization of intra‐hippocampal connectivity will advance the development of novel hypotheses about seizure networks.
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Affiliation(s)
- Justin Ke
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Lesley M Foley
- Animal Imaging Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - T Kevin Hitchens
- Animal Imaging Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - R Mark Richardson
- Centre for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Neurological Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Michel Modo
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Centre for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,McGowan Institute for Regenerative Medicine, Pittsburgh, Pennsylvania, USA
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3
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Bennett IJ, Stark SM, Stark CEL. Recognition Memory Dysfunction Relates to Hippocampal Subfield Volume: A Study of Cognitively Normal and Mildly Impaired Older Adults. J Gerontol B Psychol Sci Soc Sci 2020; 74:1132-1141. [PMID: 29401233 DOI: 10.1093/geronb/gbx181] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 01/02/2018] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVES The current study examined recognition memory dysfunction and its neuroanatomical substrates in cognitively normal older adults and those diagnosed with mild cognitive impairment (MCI). METHODS Participants completed the Mnemonic Similarity Task, which provides simultaneous measures of recognition memory and mnemonic discrimination. They also underwent structural neuroimaging to assess volume of medial temporal cortex and hippocampal subfields. RESULTS As expected, individuals diagnosed with MCI had significantly worse recognition memory performance and reduced volume across medial temporal cortex and hippocampal subfields relative to cognitively normal older adults. After controlling for diagnostic group differences, however, recognition memory was significantly related to whole hippocampus volume, and to volume of the dentate gyrus/CA3 subfield in particular. Recognition memory was also related to mnemonic discrimination, a fundamental component of episodic memory that has previously been linked to dentate gyrus/CA3 structure and function. DISCUSSION Results reveal that hippocampal subfield volume is sensitive to individual differences in recognition memory in older adults independent of clinical diagnosis. This supports the notion that episodic memory declines along a continuum within this age group, not just between diagnostic groups.
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Affiliation(s)
- Ilana J Bennett
- Department of Psychology, University of California, Riverside
| | - Shauna M Stark
- Department of Neurobiology and Behavior, University of California, Irvine
| | - Craig E L Stark
- Department of Neurobiology and Behavior, University of California, Irvine.,Center for the Neurobiology of Learning and Memory, University of California, Irvine
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Olsen RK, Carr VA, Daugherty AM, La Joie R, Amaral RS, Amunts K, Augustinack JC, Bakker A, Bender AR, Berron D, Boccardi M, Bocchetta M, Burggren AC, Chakravarty MM, Chételat G, de Flores R, DeKraker J, Ding SL, Geerlings MI, Huang Y, Insausti R, Johnson EG, Kanel P, Kedo O, Kennedy KM, Keresztes A, Lee JK, Lindenberger U, Mueller SG, Mulligan EM, Ofen N, Palombo DJ, Pasquini L, Pluta J, Raz N, Rodrigue KM, Schlichting ML, Lee Shing Y, Stark CE, Steve TA, Suthana NA, Wang L, Werkle-Bergner M, Yushkevich PA, Yu Q, Wisse LE. Progress update from the hippocampal subfields group. Alzheimers Dement (Amst) 2019; 11:439-449. [PMID: 31245529 PMCID: PMC6581847 DOI: 10.1016/j.dadm.2019.04.001] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Heterogeneity of segmentation protocols for medial temporal lobe regions and hippocampal subfields on in vivo magnetic resonance imaging hinders the ability to integrate findings across studies. We aim to develop a harmonized protocol based on expert consensus and histological evidence. METHODS Our international working group, funded by the EU Joint Programme-Neurodegenerative Disease Research (JPND), is working toward the production of a reliable, validated, harmonized protocol for segmentation of medial temporal lobe regions. The working group uses a novel postmortem data set and online consensus procedures to ensure validity and facilitate adoption. RESULTS This progress report describes the initial results and milestones that we have achieved to date, including the development of a draft protocol and results from the initial reliability tests and consensus procedures. DISCUSSION A harmonized protocol will enable the standardization of segmentation methods across laboratories interested in medial temporal lobe research worldwide.
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Affiliation(s)
- Rosanna K. Olsen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Valerie A. Carr
- Department of Psychology, San Jose State University, San Jose, CA, USA
| | - Ana M. Daugherty
- Department of Psychology, Wayne State University, Detroit, MI, USA
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Robert S.C. Amaral
- Cerebral Imaging Centre, Douglas Hospital Mental Health University Institute, Verdun, Quebec, Canada
| | - Katrin Amunts
- C. and O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Düsseldorf, Germany
- Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Jean C. Augustinack
- Department of Radiology, Harvard Medical School, Charlestown, MA, USA
- Massachusetts General Hospital, Charlestown, MA, USA
| | - Arnold Bakker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Andrew R. Bender
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, USA
- Department of Neurology and Ophthalmology, Michigan State University, East Lansing, MI, USA
- College of Human Medicine, Michigan State University, East Lansing, MI, USA
| | - David Berron
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Marina Boccardi
- Department of Psychiatry, University of Geneva, Geneva, Switzerland
- IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London, London, United Kingdom
| | - Alison C. Burggren
- Robert and Beverly Lewis Center for Neuroimaging, University of Oregon, Eugene, OR, USA
| | - M. Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Hospital Mental Health University Institute, Verdun, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Gaël Chételat
- Université Normandie, Université de Caen-Normandie, Caen, France
- Institut National de la Santé et de la Recherché Médicale (INSERM), UMR-S U1237, Caen, France
- GIP Cyceron, Caen, France
| | - Robin de Flores
- Université Normandie, Université de Caen-Normandie, Caen, France
- Institut National de la Santé et de la Recherché Médicale (INSERM), UMR-S U1237, Caen, France
| | - Jordan DeKraker
- Robarts Research Institute, Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
| | | | - Mirjam I. Geerlings
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- Utrecht University, Utrecht, The Netherlands
| | - Yushan Huang
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | | | - Prabesh Kanel
- Department of Radiology at the University of Michigan, Ann Arbor, MI, USA
| | - Olga Kedo
- Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Kristen M. Kennedy
- Center for Vital Longevity, Behavioral and Brain Science, The University of Texas at Dallas, Dallas, TX, USA
| | - Attila Keresztes
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
| | - Joshua K. Lee
- Center for Mind and Brain, University of California, Davis, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, Davis, CA, USA
| | - Ulman Lindenberger
- Research Centre for Natural Sciences, Hungarian Academy of Sciences, Budapest, Hungary
- Max Planck – University College London Centre for Computational Psychiatry and Ageing Research, Berlin, Germany and London, United Kingdom
| | - Susanne G. Mueller
- Department of Radiology, University of California, San Francisco, CA, USA
| | | | - Noa Ofen
- Department of Psychology, Wayne State University, Detroit, MI, USA
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
- Neurobiology Department, Weizmann Institute of Science, Rehovot, Israel
| | - Daniela J. Palombo
- Department of Psychology, University of British Columbia, Vancouver, British Colombia, Canada
| | - Lorenzo Pasquini
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - John Pluta
- Division of Translational Medicine and Genomics, University of Pennsylvania, Philadelphia, PA, USA
| | - Naftali Raz
- Department of Psychology, Wayne State University, Detroit, MI, USA
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Karen M. Rodrigue
- Center for Vital Longevity, Behavioral and Brain Science, The University of Texas at Dallas, Dallas, TX, USA
| | | | - Yee Lee Shing
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Institute of Psychology, Goethe University Frankfurt, Frankfurt, Germany
| | - Craig E.L. Stark
- Department of Neurobiology and Behavior, Center for Learning and Memory, University of California, Irvine, CA, USA
| | - Trevor A. Steve
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Nanthia A. Suthana
- Department of Psychiatry and Biobehavioral Sciences, Department of Neurosurgery, University of California, Los Angeles, CA, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences and Department Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Markus Werkle-Bergner
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Paul A. Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Qijing Yu
- Department of Psychology, Wayne State University, Detroit, MI, USA
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Laura E.M. Wisse
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
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5
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de Flores R, Berron D, Ding SL, Ittyerah R, Pluta JB, Xie L, Adler DH, Robinson JL, Schuck T, Trojanowski JQ, Grossman M, Liu W, Pickup S, Das SR, Wolk DA, Yushkevich PA, Wisse LEM. Characterization of hippocampal subfields using ex vivo MRI and histology data: Lessons for in vivo segmentation. Hippocampus 2019; 30:545-564. [PMID: 31675165 DOI: 10.1002/hipo.23172] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 09/30/2019] [Accepted: 10/05/2019] [Indexed: 11/07/2022]
Abstract
Hippocampal subfield segmentation on in vivo MRI is of great interest for cognition, aging, and disease research. Extant subfield segmentation protocols have been based on neuroanatomical references, but these references often give limited information on anatomical variability. Moreover, there is generally a mismatch between the orientation of the histological sections and the often anisotropic coronal sections on in vivo MRI. To address these issues, we provide a detailed description of hippocampal anatomy using a postmortem dataset containing nine specimens of subjects with and without dementia, which underwent a 9.4 T MRI and histological processing. Postmortem MRI matched the typical orientation of in vivo images and segmentations were generated in MRI space, based on the registered annotated histological sections. We focus on the following topics: the order of appearance of subfields, the location of subfields relative to macroanatomical features, the location of subfields in the uncus and tail and the composition of the dark band, a hypointense layer visible in T2-weighted MRI. Our main findings are that: (a) there is a consistent order of appearance of subfields in the hippocampal head, (b) the composition of subfields is not consistent in the anterior uncus, but more consistent in the posterior uncus, (c) the dark band consists only of the CA-stratum lacunosum moleculare, not the strata moleculare of the dentate gyrus, (d) the subiculum/CA1 border is located at the middle of the width of the hippocampus in the body in coronal plane, but moves in a medial direction from anterior to posterior, and (e) the variable location and composition of subfields in the hippocampal tail can be brought back to a body-like appearance when reslicing the MRI scan following the curvature of the tail. Our findings and this publicly available dataset will hopefully improve anatomical accuracy of future hippocampal subfield segmentation protocols.
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Affiliation(s)
- Robin de Flores
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | - David Berron
- Clinical Sciences Malmö, Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Song-Lin Ding
- Allen Institute for Brain Science, Seattle, Washington.,Institute of Neuroscience, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China
| | - Ranjit Ittyerah
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - John B Pluta
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Long Xie
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Daniel H Adler
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - John L Robinson
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Theresa Schuck
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, Pennsylvania
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Weixia Liu
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Stephen Pickup
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Paul A Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Laura E M Wisse
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.,Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.,Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
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6
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Kyle CT, Stokes J, Bennett J, Meltzer J, Permenter MR, Vogt JA, Ekstrom A, Barnes CA. Cytoarchitectonically-driven MRI atlas of nonhuman primate hippocampus: Preservation of subfield volumes in aging. Hippocampus 2019; 29:409-421. [PMID: 29072793 PMCID: PMC5920786 DOI: 10.1002/hipo.22809] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 09/29/2017] [Accepted: 10/24/2017] [Indexed: 11/12/2022]
Abstract
Identification of primate hippocampal subfields in vivo using structural MRI imaging relies on variable anatomical guidelines, signal intensity differences, and heuristics to differentiate between regions (Yushkevich et al., 2015a). Thus, a clear anatomically-driven basis for subfield demarcation is lacking. Recent work, however, has begun to develop methods to use ex vivo histology or ex vivo MRI (Adler et al., 2014; Iglesias et al., 2015) that have the potential to inform subfield demarcations of in vivo images. For optimal results, however, ex vivo and in vivo images should ideally be matched within the same healthy brains, with the goal to develop a neuroanatomically-driven basis for in vivo structural MRI images. Here, we address this issue in young and aging rhesus macaques (young n = 5 and old n = 5) using ex vivo Nissl-stained sections in which we identified the dentate gyrus, CA3, CA2, CA1, subiculum, presubiculum, and parasubiculum guided by morphological cell properties (30 μm thick sections spaced at 240 μm intervals and imaged at 161 nm/pixel). The histologically identified boundaries were merged with in vivo structural MRIs (0.625 × 0.625 × 1 mm) from the same subjects via iterative rigid and diffeomorphic registration resulting in probabilistic atlases of young and old rhesus macaques. Our results indicate stability in hippocampal subfield volumes over an age range of 13 to 32 years, consistent with previous results showing preserved whole hippocampal volume in aged macaques (Shamy et al., 2006). Together, our methods provide a novel approach for identifying hippocampal subfields in non-human primates and a potential 'ground truth' for more accurate identification of hippocampal subfield boundaries on in vivo MRIs. This could, in turn, have applications in humans where accurately identifying hippocampal subfields in vivo is a critical research goal.
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Affiliation(s)
- Colin T Kyle
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ
| | - Jared Stokes
- Department of Psychology, University of California, Davis, CA
| | - Jeffrey Bennett
- Department of Psychiatry and Behavioral Science and M.I.N.D. Institute, UC Davis, Sacramento, CA
| | - Jeri Meltzer
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Michele R Permenter
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Julie A Vogt
- California National Primate Research Center, University of California, Davis, Davis, CA
| | - Arne Ekstrom
- Department of Psychology, University of California, Davis, CA
- Center for Neuroscience, University of California, Davis, CA
| | - Carol A Barnes
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ
- Division of Neural Systems, Memory and Aging, University of Arizona, Tucson, AZ
- Departments of Psychology, Neurology and Neuroscience, University of Arizona, Tucson, AZ
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Jonkman LE, Graaf YGD, Bulk M, Kaaij E, Pouwels PJW, Barkhof F, Rozemuller AJM, van der Weerd L, Geurts JJG, van de Berg WDJ. Normal Aging Brain Collection Amsterdam (NABCA): A comprehensive collection of postmortem high-field imaging, neuropathological and morphometric datasets of non-neurological controls. Neuroimage Clin 2019; 22:101698. [PMID: 30711684 PMCID: PMC6360607 DOI: 10.1016/j.nicl.2019.101698] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 01/21/2019] [Accepted: 01/27/2019] [Indexed: 12/18/2022]
Abstract
Well-characterized, high-quality brain tissue of non-neurological control subjects is a prerequisite to study the healthy aging brain, and can serve as a control for the study of neurological disorders. The Normal Aging Brain Collection Amsterdam (NABCA) provides a comprehensive collection of post-mortem (ultra-)high-field MRI (3Tesla and 7 Tesla) and neuropathological datasets of non-neurological controls. By providing MRI within the pipeline, NABCA uniquely stimulates translational neurosciences; from molecular and morphometric tissue studies to the clinical setting. We describe our pipeline, including a description of our on-call autopsy team, donor selection, in situ and ex vivo post-mortem MRI protocols, brain dissection and neuropathological diagnosis. A demographic, radiological and pathological overview of five selected cases on all these aspects is provided. Additionally, information is given on data management, data and tissue application procedures, including review by a scientific advisory board, and setting up a material transfer agreement before distribution of tissue. Finally, we focus on future prospects, which includes laying the foundation for a unique platform for neuroanatomical, histopathological and neuro-radiological education, of professionals, students and the general (lay) audience. NABCA provides a collection of correlative post-mortem MRI and pathological datasets. Non-neurological control brains for studies on aging and neurological disorders. Stimulating micro- to macroscale structural exploration within same patient Post-mortem MRI data and tissue available for integrated advanced data analytics
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Affiliation(s)
- Laura E Jonkman
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
| | - Yvon Galis-de Graaf
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Marjolein Bulk
- Department of Radiology, Leiden University Medical Centre, Leiden, the Netherlands; Department of Human Genetics, Leiden University Medical Centre, Leiden, the Netherlands
| | - Eliane Kaaij
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Petra J W Pouwels
- Department of radiology and nuclear medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Department of radiology and nuclear medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Institutes of neurology and healthcare engineering, University College London, London, United Kingdom
| | - Annemieke J M Rozemuller
- Department of pathology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Louise van der Weerd
- Department of Radiology, Leiden University Medical Centre, Leiden, the Netherlands; Department of Human Genetics, Leiden University Medical Centre, Leiden, the Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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8
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Ianov L, De Both M, Chawla MK, Rani A, Kennedy AJ, Piras I, Day JJ, Siniard A, Kumar A, Sweatt JD, Barnes CA, Huentelman MJ, Foster TC. Hippocampal Transcriptomic Profiles: Subfield Vulnerability to Age and Cognitive Impairment. Front Aging Neurosci 2017; 9:383. [PMID: 29276487 PMCID: PMC5727020 DOI: 10.3389/fnagi.2017.00383] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Accepted: 11/07/2017] [Indexed: 01/11/2023] Open
Abstract
The current study employed next-generation RNA sequencing to examine gene expression differences related to brain aging, cognitive decline, and hippocampal subfields. Young and aged rats were trained on a spatial episodic memory task. Hippocampal regions CA1, CA3, and the dentate gyrus were isolated. Poly-A mRNA was examined using two different sequencing platforms, Illumina, and Ion Proton. The Illumina platform was used to generate seed lists of genes that were statistically differentially expressed across regions, ages, or in association with cognitive function. The gene lists were then retested using the data from the Ion Proton platform. The results indicate hippocampal subfield differences in gene expression and point to regional differences in vulnerability to aging. Aging was associated with increased expression of immune response-related genes, particularly in the dentate gyrus. For the memory task, impaired performance of aged animals was linked to the regulation of Ca2+ and synaptic function in region CA1. Finally, we provide a transcriptomic characterization of the three subfields regardless of age or cognitive status, highlighting and confirming a correspondence between cytoarchitectural boundaries and molecular profiling.
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Affiliation(s)
- Lara Ianov
- Departments of Neuroscience and Genetics and Genomics Program, Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Civitan International Research Center, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Matt De Both
- Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, United States
| | - Monica K Chawla
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Asha Rani
- Departments of Neuroscience and Genetics and Genomics Program, Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Andrew J Kennedy
- Evelyn F. McKnight Brain Institute, University of Alabama, Birmingham, AL, United States
| | - Ignazio Piras
- Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, United States
| | - Jeremy J Day
- Evelyn F. McKnight Brain Institute, University of Alabama, Birmingham, AL, United States
| | - Ashley Siniard
- Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, United States
| | - Ashok Kumar
- Departments of Neuroscience and Genetics and Genomics Program, Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - J David Sweatt
- Evelyn F. McKnight Brain Institute, University of Alabama, Birmingham, AL, United States.,Department of Pharmacology, Vanderbilt University, Nashville, TN, United States
| | - Carol A Barnes
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States.,Departments of Psychology, Neurology and Neuroscience, University of Arizona, Tucson, AZ, United States
| | - Matthew J Huentelman
- Neurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, United States.,Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Thomas C Foster
- Departments of Neuroscience and Genetics and Genomics Program, Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, United States
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Abstract
We consider internal representations of the world in the form of scenes. The anterior medial hippocampus is implicated in scene-based cognition. This region contains the pre/parasubiculum. The pre/parasubiculum is a primary target of a major visuospatial processing system. The pre/parasubiculum may be the hippocampal hub of the scene processing network.
Internal representations of the world in the form of spatially coherent scenes have been linked with cognitive functions including episodic memory, navigation and imagining the future. In human neuroimaging studies, a specific hippocampal subregion, the pre/parasubiculum, is consistently engaged during scene-based cognition. Here we review recent evidence to consider why this might be the case. We note that the pre/parasubiculum is a primary target of the parieto-medial temporal processing pathway, it receives integrated information from foveal and peripheral visual inputs and it is contiguous with the retrosplenial cortex. We discuss why these factors might indicate that the pre/parasubiculum has privileged access to holistic representations of the environment and could be neuroanatomically determined to preferentially process scenes.
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Affiliation(s)
- Marshall A Dalton
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK
| | - Eleanor A Maguire
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, UK
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10
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Berron D, Vieweg P, Hochkeppler A, Pluta JB, Ding SL, Maass A, Luther A, Xie L, Das SR, Wolk DA, Wolbers T, Yushkevich PA, Düzel E, Wisse LEM. A protocol for manual segmentation of medial temporal lobe subregions in 7 Tesla MRI. Neuroimage Clin 2017; 15:466-482. [PMID: 28652965 PMCID: PMC5476466 DOI: 10.1016/j.nicl.2017.05.022] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 05/25/2017] [Indexed: 12/16/2022]
Abstract
Recent advances in MRI and increasing knowledge on the characterization and anatomical variability of medial temporal lobe (MTL) anatomy have paved the way for more specific subdivisions of the MTL in humans. In addition, recent studies suggest that early changes in many neurodegenerative and neuropsychiatric diseases are better detected in smaller subregions of the MTL rather than with whole structure analyses. Here, we developed a new protocol using 7 Tesla (T) MRI incorporating novel anatomical findings for the manual segmentation of entorhinal cortex (ErC), perirhinal cortex (PrC; divided into area 35 and 36), parahippocampal cortex (PhC), and hippocampus; which includes the subfields subiculum (Sub), CA1, CA2, as well as CA3 and dentate gyrus (DG) which are separated by the endfolial pathway covering most of the long axis of the hippocampus. We provide detailed instructions alongside slice-by-slice segmentations to ease learning for the untrained but also more experienced raters. Twenty-two subjects were scanned (19-32 yrs, mean age = 26 years, 12 females) with a turbo spin echo (TSE) T2-weighted MRI sequence with high-resolution oblique coronal slices oriented orthogonal to the long axis of the hippocampus (in-plane resolution 0.44 × 0.44 mm2) and 1.0 mm slice thickness. The scans were manually delineated by two experienced raters, to assess intra- and inter-rater reliability. The Dice Similarity Index (DSI) was above 0.78 for all regions and the Intraclass Correlation Coefficients (ICC) were between 0.76 to 0.99 both for intra- and inter-rater reliability. In conclusion, this study presents a fine-grained and comprehensive segmentation protocol for MTL structures at 7 T MRI that closely follows recent knowledge from anatomical studies. More specific subdivisions (e.g. area 35 and 36 in PrC, and the separation of DG and CA3) may pave the way for more precise delineations thereby enabling the detection of early volumetric changes in dementia and neuropsychiatric diseases.
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Key Words
- AG, Ambient Gyrus
- CA1, Cornu Ammonis 1
- CA2, Cornu Ammonis 2
- CA3, Cornu Ammonis 3
- CS, Collateral Sulcus
- CSF, Cerebrospinal Fluid
- CSa, anterior
- CSp, posterior
- CaS, Calcarine sulcus
- DG, Dentate Gyrus
- ErC, Entorhinal Cortex
- FG, Fusiform Gyrus
- HB, Hippocampal Body
- HH, Hippocampal Head
- HT, Hippocampal Tail
- MTL, Medial Temporal Lobe
- OTS, Occipito-temporal Sulcus
- PhC, Parahippocampal Cortex
- PhG, Parahippocampal Gyrus
- PrC, Perirhinal Cortex
- SRLM, Stratum radiatum lacunosum-moleculare
- SaS, Semiannular Sulcus
- Sub, Subiculum
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Affiliation(s)
- D Berron
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, 39120 Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, 39120 Magdeburg, Germany.
| | - P Vieweg
- German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, 39120 Magdeburg, Germany.
| | - A Hochkeppler
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, 39120 Magdeburg, Germany
| | - J B Pluta
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - S-L Ding
- Allen Institute for Brain Science, Seattle, WA 98109, USA; Institute of Neuroscience, School of Basic Sciences, Guangzhou Medical University, Guangzhou, Guangdong Province 511436, China
| | - A Maass
- German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, 39120 Magdeburg, Germany; Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
| | - A Luther
- German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, 39120 Magdeburg, Germany
| | - L Xie
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - S R Das
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - D A Wolk
- Penn Memory Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - T Wolbers
- German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, 39120 Magdeburg, Germany
| | - P A Yushkevich
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - E Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, 39120 Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, 39120 Magdeburg, Germany; University College London, Institute of Cognitive Neuroscience, London WC1N 3AR, United Kingdom
| | - L E M Wisse
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
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11
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Giuliano A, Donatelli G, Cosottini M, Tosetti M, Retico A, Fantacci ME. Hippocampal subfields at ultra high field MRI: An overview of segmentation and measurement methods. Hippocampus 2017; 27:481-494. [PMID: 28188659 PMCID: PMC5573987 DOI: 10.1002/hipo.22717] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2017] [Indexed: 12/13/2022]
Abstract
The hippocampus is one of the most interesting and studied brain regions because of its involvement in memory functions and its vulnerability in pathological conditions, such as neurodegenerative processes. In the recent years, the increasing availability of Magnetic Resonance Imaging (MRI) scanners that operate at ultra‐high field (UHF), that is, with static magnetic field strength ≥7T, has opened new research perspectives. Compared to conventional high‐field scanners, these systems can provide new contrasts, increased signal‐to‐noise ratio and higher spatial resolution, thus they may improve the visualization of very small structures of the brain, such as the hippocampal subfields. Studying the morphometry of the hippocampus is crucial in neuroimaging research because changes in volume and thickness of hippocampal subregions may be relevant in the early assessment of pathological cognitive decline and Alzheimer's Disease (AD). The present review provides an overview of the manual, semi‐automated and fully automated methods that allow the assessment of hippocampal subfield morphometry at UHF MRI, focusing on the different hippocampal segmentation produced. © 2017 The Authors Hippocampus Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Alessia Giuliano
- Department of Physics, University of Pisa, Pisa, Italy.,National Institute of Nuclear Physics (INFN), Pisa Division, Pisa, Italy
| | - Graziella Donatelli
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Mirco Cosottini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Michela Tosetti
- Laboratory of Medical Physics and Biotechnologies for Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy; Imago7 Foundation, Pisa, Italy
| | - Alessandra Retico
- National Institute of Nuclear Physics (INFN), Pisa Division, Pisa, Italy
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