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González-Arnay E, Pérez-Santos I, Jiménez-Sánchez L, Cid E, Gal B, de la Prida LM, Cavada C. Immunohistochemical field parcellation of the human hippocampus along its antero-posterior axis. Brain Struct Funct 2024; 229:359-385. [PMID: 38180568 PMCID: PMC10917878 DOI: 10.1007/s00429-023-02725-9] [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: 04/15/2023] [Accepted: 10/15/2023] [Indexed: 01/06/2024]
Abstract
The primate hippocampus includes the dentate gyrus, cornu ammonis (CA), and subiculum. CA is subdivided into four fields (CA1-CA3, plus CA3h/hilus of the dentate gyrus) with specific pyramidal cell morphology and connections. Work in non-human mammals has shown that hippocampal connectivity is precisely patterned both in the laminar and longitudinal axes. One of the main handicaps in the study of neuropathological semiology in the human hippocampus is the lack of clear laminar and longitudinal borders. The aim of this study was to explore a histochemical segmentation of the adult human hippocampus, integrating field (medio-lateral), laminar, and anteroposterior longitudinal patterning. We provide criteria for head-body-tail field and subfield parcellation of the human hippocampus based on immunodetection of Rabphilin3a (Rph3a), Purkinje-cell protein 4 (PCP4), Chromogranin A and Regulation of G protein signaling-14 (RGS-14). Notably, Rph3a and PCP4 allow to identify the border between CA3 and CA2, while Chromogranin A and RGS-14 give specific staining of CA2. We also provide novel histological data about the composition of human-specific regions of the anterior and posterior hippocampus. The data are given with stereotaxic coordinates along the longitudinal axis. This study provides novel insights for a detailed region-specific parcellation of the human hippocampus useful for human brain imaging and neuropathology.
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Affiliation(s)
- Emilio González-Arnay
- Department of Anatomy, Histology and Neuroscience, Universidad Autónoma de Madrid, Madrid, Spain
- Department of Basic Medical Science-Division of Human Anatomy, Universidad de La Laguna, Santa Cruz de Tenerife, Canary Islands, Spain
| | - Isabel Pérez-Santos
- Department of Anatomy, Histology and Neuroscience, Universidad Autónoma de Madrid, Madrid, Spain
| | - Lorena Jiménez-Sánchez
- Department of Anatomy, Histology and Neuroscience, Universidad Autónoma de Madrid, Madrid, Spain
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Elena Cid
- Instituto Cajal, CSIC, Madrid, Spain
| | - Beatriz Gal
- Instituto Cajal, CSIC, Madrid, Spain
- Universidad CEU-San Pablo, Madrid, Spain
| | | | - Carmen Cavada
- Department of Anatomy, Histology and Neuroscience, Universidad Autónoma de Madrid, Madrid, Spain.
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2
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Rosenblum EW, Williams EM, Champion SN, Frosch MP, Augustinack JC. The prosubiculum in the human hippocampus: A rostrocaudal, feature-driven, and systematic approach. J Comp Neurol 2024; 532:e25604. [PMID: 38477395 PMCID: PMC11060218 DOI: 10.1002/cne.25604] [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: 08/28/2023] [Revised: 01/12/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024]
Abstract
The hippocampal subfield prosubiculum (ProS), is a conserved neuroanatomic region in mouse, monkey, and human. This area lies between CA1 and subiculum (Sub) and particularly lacks consensus on its boundaries; reports have varied on the description of its features and location. In this report, we review, refine, and evaluate four cytoarchitectural features that differentiate ProS from its neighboring subfields: (1) small neurons, (2) lightly stained neurons, (3) superficial clustered neurons, and (4) a cell sparse zone. ProS was delineated in all cases (n = 10). ProS was examined for its cytoarchitectonic features and location rostrocaudally, from the anterior head through the body in the hippocampus. The most common feature was small pyramidal neurons, which were intermingled with larger pyramidal neurons in ProS. We quantitatively measured ProS pyramidal neurons, which showed (average, width at pyramidal base = 14.31 µm, n = 400 per subfield). CA1 neurons averaged 15.57 µm and Sub neurons averaged 15.63 µm, both were significantly different than ProS (Kruskal-Wallis test, p < .0001). The other three features observed were lightly stained neurons, clustered neurons, and a cell sparse zone. Taken together, these findings suggest that ProS is an independent subfield, likely with distinct functional contributions to the broader interconnected hippocampal network. Our results suggest that ProS is a cytoarchitecturally varied subfield, both for features and among individuals. This diverse architecture in features and individuals for ProS could explain the long-standing complexity regarding the identification of this subfield.
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Affiliation(s)
- Emma W Rosenblum
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Emily M Williams
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Samantha N Champion
- C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Matthew P Frosch
- C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jean C Augustinack
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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3
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Canada K, Mazloum-Farzaghi N, Rådman G, Adams J, Bakker A, Baumeister H, Berron D, Bocchetta M, Carr V, Dalton M, de Flores R, Keresztes A, La Joie R, Mueller S, Raz N, Santini T, Shaw T, Stark C, Tran T, Wang L, Wisse L, Wuestefeld A, Yushkevich P, Olsen R, Daugherty A. A (Sub)field Guide to Quality Control in Hippocampal Subfield Segmentation on Highresolution T 2-weighted MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.29.568895. [PMID: 38076964 PMCID: PMC10705396 DOI: 10.1101/2023.11.29.568895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.
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Affiliation(s)
- K.L. Canada
- Institute of Gerontology, Wayne State University, Detroit, MI 48202
| | - N. Mazloum-Farzaghi
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - G. Rådman
- Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - J.N. Adams
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697
| | - A. Bakker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21287
| | - H. Baumeister
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - D. Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - M. Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- Centre for Cognitive and Clinical Neuroscience, Division of Psychology, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, UK
| | - V. Carr
- Department of Psychology, San Jose State University, San Jose, CA 95192
| | - M.A. Dalton
- School of Psychology, University of Sydney, Sydney, Australia
| | - R. de Flores
- INSERM UMR-S U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - A. Keresztes
- Brain Imaging Centre, Research Centre for Natural Sciences, Eötvös Loránd Research Network (ELKH), Budapest, Hungary
- Institute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - R. La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA 94158
| | - S.G. Mueller
- Department of Radiology, University of California, San Francisco, CA 94143
- Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center, San Francisco, California 94121
| | - N. Raz
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Department of Psychology, Stony Brook University, Stony Brook, NY 11794
| | - T. Santini
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213
| | - T. Shaw
- School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia
| | - C.E.L. Stark
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697
| | - T.T. Tran
- Department of Psychology, Stanford University, Stanford, CA 94305
| | - L. Wang
- Department of Psychiatry and Behavioral Health, The Ohio State University Wexner Medical Center, Columbus, OH 43210
| | - L.E.M. Wisse
- Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - A. Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - P.A. Yushkevich
- Penn Image, Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104
| | - R.K. Olsen
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - A.M. Daugherty
- Institute of Gerontology, Wayne State University, Detroit, MI 48202
- Department of Psychology, Wayne State University, Detroit, MI 48202
- Michigan Alzheimer’s Disease Research Center, Ann Arbor, MI 48105
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4
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Homayouni R, Canada KL, Saifullah S, Foster DJ, Thill C, Raz N, Daugherty AM, Ofen N. Age-related differences in hippocampal subfield volumes across the human lifespan: A meta-analysis. Hippocampus 2023; 33:1292-1315. [PMID: 37881160 PMCID: PMC10841547 DOI: 10.1002/hipo.23582] [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: 02/06/2023] [Revised: 08/31/2023] [Accepted: 09/28/2023] [Indexed: 10/27/2023]
Abstract
The human hippocampus (Hc) is critical for memory function across the lifespan. It is comprised of cytoarchitectonically distinct subfields: dentate gyrus (DG), cornu ammonis sectors (CA) 1-4, and subiculum, each of which may be differentially susceptible to neurodevelopmental and neurodegenerative mechanisms. Identifying age-related differences in Hc subfield volumes can provide insights into neural mechanisms of memory function across the lifespan. Limited evidence suggests that DG and CA3 volumes differ across development while other regions remain relatively stable, and studies of adulthood implicate a downward trend in all subfield volumes with prominent age effects on CA1. Due to differences in methods and limited sampling for any single study, the magnitude of age effects on Hc subfield volumes and their probable lifespan trajectories remain unclear. Here, we conducted a meta-analysis on cross-sectional studies (n = 48,278 participants, ages = 4-94 years) to examine the association between age and Hc subfield volumes in development (n = 11 studies), adulthood (n = 30 studies), and a combined lifespan sample (n = 41 studies) while adjusting estimates for sample sizes. In development, age was positively associated with DG and CA3-4 volumes, whereas in adulthood a negative association was observed with all subfield volumes. Notably, the observed age effects were not different across subfield volumes within each age group. All subfield volumes showed a nonlinear age pattern across the lifespan with DG and CA3-4 volumes showing a more distinct age trajectory as compared to the other subfields. Lastly, among all the study-level variables, only female percentage of the study sample moderated the age effect on CA1 volume: a higher female-to-male ratio in the study sample was linked to the greater negative association between age and CA1 volume. These results document that Hc subfield volumes differ as a function of age offering broader implications for constructing theoretical models of lifespan memory development.
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Affiliation(s)
- Roya Homayouni
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
- Department of Psychology, Wayne State University, Detroit, Michigan, USA
| | - Kelsey L Canada
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | - Samaah Saifullah
- School of Medicine, Wayne State University, Detroit, Michigan, USA
| | - Da' Jonae Foster
- Department of Psychology, Wayne State University, Detroit, Michigan, USA
| | - Charlotte Thill
- School of Medicine, Wayne State University, Detroit, Michigan, USA
| | - Naftali Raz
- Department of Psychology, Stony Brook University, Stony Brook, New York, USA
- Max Planck Institute for Human Development, Berlin, Germany
| | - Ana M Daugherty
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
- Department of Psychology, Wayne State University, Detroit, Michigan, USA
| | - Noa Ofen
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
- Department of Psychology, Wayne State University, Detroit, Michigan, USA
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Modo M, Sparling K, Novotny J, Perry N, Foley LM, Hitchens TK. Mapping mesoscale connectivity within the human hippocampus. Neuroimage 2023; 282:120406. [PMID: 37827206 PMCID: PMC10623761 DOI: 10.1016/j.neuroimage.2023.120406] [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: 07/07/2023] [Revised: 09/28/2023] [Accepted: 10/10/2023] [Indexed: 10/14/2023] Open
Abstract
The connectivity of the hippocampus is essential to its functions. To gain a whole system view of intrahippocampal connectivity, ex vivo mesoscale (100 μm isotropic resolution) multi-shell diffusion MRI (11.7T) and tractography were performed on entire post-mortem human right hippocampi. Volumetric measurements indicated that the head region was largest followed by the body and tail regions. A unique anatomical organization in the head region reflected a complex organization of the granule cell layer (GCL) of the dentate gyrus. Tractography revealed the volumetric distribution of the perforant path, including both the tri-synaptic and temporoammonic pathways, as well as other well-established canonical connections, such as Schaffer collaterals. Visualization of the perforant path provided a means to verify the borders between the pro-subiculum and CA1, as well as between CA1/CA2. A specific angularity of different layers of fibers in the alveus was evident across the whole sample and allowed a separation of afferent and efferent connections based on their origin (i.e. entorhinal cortex) or destination (i.e. fimbria) using a cluster analysis of streamlines. Non-canonical translamellar connections running along the anterior-posterior axis were also discerned in the hilus. In line with "dentations" of the GCL, mossy fibers were bunching together in the sagittal plane revealing a unique lamellar organization and connections between these. In the head region, mossy fibers projected to the origin of the fimbria, which was distinct from the body and tail region. Mesoscale tractography provides an unprecedented systems view of intrahippocampal connections that underpin cognitive and emotional processing.
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Affiliation(s)
- Michel Modo
- Department of Radiology; Department of BioEngineering; McGowan Institute for Regenerative Medicine; Centre for Neuroscience University of Pittsburgh (CNUP); Centre for the Neural Basis of Cognition (CNBC).
| | | | | | | | | | - T Kevin Hitchens
- Small Animal Imaging Center; Departmnet of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15203, USA
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6
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André C, Kuhn E, Rehel S, Ourry V, Demeilliez-Servouin S, Palix C, Felisatti F, Champetier P, Dautricourt S, Yushkevich P, Vivien D, de La Sayette V, Chételat G, de Flores R, Rauchs G. Association of Sleep-Disordered Breathing and Medial Temporal Lobe Atrophy in Cognitively Unimpaired Amyloid-Positive Older Adults. Neurology 2023; 101:e370-e385. [PMID: 37258299 PMCID: PMC10435067 DOI: 10.1212/wnl.0000000000207421] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 04/03/2023] [Indexed: 06/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Sleep disordered breathing (SDB) has been related to amyloid deposition and an increased dementia risk. However, how SDB relates to medial temporal lobe neurodegeneration and subsequent episodic memory impairment is unclear. Our objective was to investigate the impact of amyloid positivity on the associations between SDB severity, medial temporal lobe subregions, and episodic memory performance in cognitively unimpaired older adults. METHODS Data were acquired between 2016 and 2020 in the context of the Age-Well randomized controlled trial of the Medit-Aging European project. Participants older than 65 years who were free of neurologic, psychiatric, or chronic medical diseases were recruited from the community. They completed a neuropsychological evaluation, in-home polysomnography, a Florbetapir PET, and an MRI, including a specific high-resolution assessment of the medial temporal lobe and hippocampal subfields. Multiple linear regressions were conducted to test interactions between amyloid status and SDB severity on the volume of MTL subregions, controlling for age, sex, education, and the ApoE4 status. Secondary analyses aimed at investigating the links between SDB, MTL subregional atrophy, and episodic memory performance at baseline and at a mean follow-up of 20.66 months in the whole cohort and in subgroups stratified according to amyloid status. RESULTS We included 122 cognitively intact community-dwelling older adults (mean age ± SD: 69.40 ± 3.85 years, 77 women, 26 Aβ+ individuals) in baseline analyses and 111 at follow-up. The apnea-hypopnea index interacted with entorhinal (β = -0.81, p < 0.001, pη2 = 0.19), whole hippocampal (β = -0.61, p < 0.001, pη2 = 0.10), subiculum (β = -0.56, p = 0.002, pη2 = 0.08), CA1 (β = -0.55, p = 0.002, pη2 = 0.08), and DG (β = -0.53, p = 0.003, pη2 = 0.08) volumes such that a higher sleep apnea severity was related to lower MTL subregion volumes in amyloid-positive individuals, but not in those who were amyloid negative. In the whole cohort, lower whole hippocampal (r = 0.27, p = 0.005) and CA1 (r = 0.28, p = 0.003) volumes at baseline were associated with worse episodic memory performance at follow-up. DISCUSSION Overall, we showed that SDB was associated with MTL atrophy in cognitively asymptomatic older adults engaged in the Alzheimer continuum, which may increase the risk of developing memory impairment over time. TRIAL REGISTRATION INFORMATION ClinicalTrials.gov Identifier: NCT02977819.
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Affiliation(s)
- Claire André
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Elizabeth Kuhn
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Stéphane Rehel
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Valentin Ourry
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Solène Demeilliez-Servouin
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Cassandre Palix
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Francesca Felisatti
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Pierre Champetier
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Sophie Dautricourt
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Paul Yushkevich
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Denis Vivien
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Vincent de La Sayette
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Gaël Chételat
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Robin de Flores
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France
| | - Géraldine Rauchs
- From the Normandie Univ (C.A., E.K., S.R., V.O., S.D.-S., C.P., F.F., P.C., S.D., D.V., G.C., R.F., G.R.), UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders" NEUROPRESAGE Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, France; Normandie Univ (C.A., S.R., V.O., P.C., V.L.S.), UNICAEN, PSL Université, EPHE, INSERM, CHU de Caen, GIP Cyceron, NIMH, France; Penn Image Computing and Science Laboratory (PICSL) (P.Y.), University of Pennsylvania, Philadelphia; Département de Recherche Clinique (D.V.), CHU Caen-Normandie, France; and Service de Neurologie (V.L.S.), CHU de Caen, France.
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7
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Poiret C, Bouyeure A, Patil S, Grigis A, Duchesnay E, Faillot M, Bottlaender M, Lemaitre F, Noulhiane M. A fast and robust hippocampal subfields segmentation: HSF revealing lifespan volumetric dynamics. Front Neuroinform 2023; 17:1130845. [PMID: 37396459 PMCID: PMC10308024 DOI: 10.3389/fninf.2023.1130845] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 05/22/2023] [Indexed: 07/04/2023] Open
Abstract
The hippocampal subfields, pivotal to episodic memory, are distinct both in terms of cyto- and myeloarchitectony. Studying the structure of hippocampal subfields in vivo is crucial to understand volumetric trajectories across the lifespan, from the emergence of episodic memory during early childhood to memory impairments found in older adults. However, segmenting hippocampal subfields on conventional MRI sequences is challenging because of their small size. Furthermore, there is to date no unified segmentation protocol for the hippocampal subfields, which limits comparisons between studies. Therefore, we introduced a novel segmentation tool called HSF short for hippocampal segmentation factory, which leverages an end-to-end deep learning pipeline. First, we validated HSF against currently used tools (ASHS, HIPS, and HippUnfold). Then, we used HSF on 3,750 subjects from the HCP development, young adults, and aging datasets to study the effect of age and sex on hippocampal subfields volumes. Firstly, we showed HSF to be closer to manual segmentation than other currently used tools (p < 0.001), regarding the Dice Coefficient, Hausdorff Distance, and Volumetric Similarity. Then, we showed differential maturation and aging across subfields, with the dentate gyrus being the most affected by age. We also found faster growth and decay in men than in women for most hippocampal subfields. Thus, while we introduced a new, fast and robust end-to-end segmentation tool, our neuroanatomical results concerning the lifespan trajectories of the hippocampal subfields reconcile previous conflicting results.
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Affiliation(s)
- Clement Poiret
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Antoine Bouyeure
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Sandesh Patil
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Antoine Grigis
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Edouard Duchesnay
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
| | - Matthieu Faillot
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- BioMaps, Service Hospitalier Frédéric Joliot, CNRS, Inserm, Université Paris-Saclay, Orsay, France
| | - Michel Bottlaender
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- BioMaps, Service Hospitalier Frédéric Joliot, CNRS, Inserm, Université Paris-Saclay, Orsay, France
| | - Frederic Lemaitre
- CETAPS EA 3832, Université de Rouen, Rouen, France
- CRIOBE, UAR 3278, CNRS-EPHE-UPVD, Mooréa, France
| | - Marion Noulhiane
- UNIACT, NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- NeuroSpin, CEA Paris-Saclay, Frederic Joliot Institute, Gif-sur-Yvette, France
- InDEV, NeuroDiderot, Université Paris Cité, Inserm, Paris, France
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8
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de Flores R, Demeilliez-Servouin S, Kuhn E, Chauveau L, Landeau B, Delcroix N, Gonneaud J, Vivien D, Chételat G. Respective influence of beta-amyloid and APOE ε4 genotype on medial temporal lobe subregions in cognitively unimpaired older adults. Neurobiol Dis 2023; 181:106127. [PMID: 37061167 DOI: 10.1016/j.nbd.2023.106127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 04/17/2023] Open
Abstract
Medial temporal lobe (MTL) subregions are differentially affected in Alzheimer's disease (AD), with a specific involvement of the entorhinal cortex (ERC), perirhinal cortex and hippocampal cornu ammonis (CA)1. While amyloid (Aβ) and APOEε4 are respectively the first molecular change and the main genetic risk factor in AD, their links with MTL atrophy remain relatively unclear. Our aim was to uncover these effects using baseline data from 130 participants included in the Age-Well study, for whom ultra-high-resolution structural MRI, amyloid-PET and APOEε4 genotype were available. No volume differences were observed between Aβ + (n = 24) and Aβ- (n = 103), nor between APOE4+ (n = 35) and APOE4- (n = 95) participants. However, our analyses showed that both Aβ and APOEε4 status interacted with age on CA1, which is known to be specifically atrophied in early AD. In addition, APOEε4 status moderated the effects of age on other subregions (subiculum, ERC), suggesting a more important contribution of APOEε4 than Aβ to MTL atrophy in cognitively unimpaired population. These results are crucial to develop MRI-based biomarkers to detect early AD.
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Affiliation(s)
- Robin de Flores
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France.
| | - Solène Demeilliez-Servouin
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Elizabeth Kuhn
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Léa Chauveau
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Brigitte Landeau
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | | | - Julie Gonneaud
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Denis Vivien
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
| | - Gaël Chételat
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Caen-Normandie University, GIP Cyceron, France
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9
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Oltmer J, Rosenblum EW, Williams EM, Roy J, Llamas-Rodriguez J, Perosa V, Champion SN, Frosch MP, Augustinack JC. Stereology neuron counts correlate with deep learning estimates in the human hippocampal subregions. Sci Rep 2023; 13:5884. [PMID: 37041300 PMCID: PMC10090178 DOI: 10.1038/s41598-023-32903-y] [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: 10/11/2022] [Accepted: 04/04/2023] [Indexed: 04/13/2023] Open
Abstract
Hippocampal subregions differ in specialization and vulnerability to cell death. Neuron death and hippocampal atrophy have been a marker for the progression of Alzheimer's disease. Relatively few studies have examined neuronal loss in the human brain using stereology. We characterize an automated high-throughput deep learning pipeline to segment hippocampal pyramidal neurons, generate pyramidal neuron estimates within the human hippocampal subfields, and relate our results to stereology neuron counts. Based on seven cases and 168 partitions, we vet deep learning parameters to segment hippocampal pyramidal neurons from the background using the open-source CellPose algorithm, and show the automated removal of false-positive segmentations. There was no difference in Dice scores between neurons segmented by the deep learning pipeline and manual segmentations (Independent Samples t-Test: t(28) = 0.33, p = 0.742). Deep-learning neuron estimates strongly correlate with manual stereological counts per subregion (Spearman's correlation (n = 9): r(7) = 0.97, p < 0.001), and for each partition individually (Spearman's correlation (n = 168): r(166) = 0.90, p <0 .001). The high-throughput deep-learning pipeline provides validation to existing standards. This deep learning approach may benefit future studies in tracking baseline and resilient healthy aging to the earliest disease progression.
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Affiliation(s)
- Jan Oltmer
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Emma W Rosenblum
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Emily M Williams
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Jessica Roy
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Josué Llamas-Rodriguez
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Valentina Perosa
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, J. Philip Kistler Stroke Research Center, Cambridge Str. 175, Suite 300, Boston, MA, 02114, USA
- Department of Neurology, Otto-Von-Guericke University, Magdeburg, Germany
| | - Samantha N Champion
- Department of Neuropathology, Massachusetts General Hospital, Boston, MA, USA
| | - Matthew P Frosch
- Department of Neuropathology, Massachusetts General Hospital, Boston, MA, USA
| | - Jean C Augustinack
- Department of Radiology, Athinoula A. Martinos Center, Massachusetts General Hospital, Charlestown, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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10
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Insausti R, Insausti AM, Muñoz López M, Medina Lorenzo I, Arroyo-Jiménez MDM, Marcos Rabal MP, de la Rosa-Prieto C, Delgado-González JC, Montón Etxeberria J, Cebada-Sánchez S, Raspeño-García JF, Iñiguez de Onzoño MM, Molina Romero FJ, Benavides-Piccione R, Tapia-González S, Wisse LEM, Ravikumar S, Wolk DA, DeFelipe J, Yushkevich P, Artacho-Pérula E. Ex vivo, in situ perfusion protocol for human brain fixation compatible with microscopy, MRI techniques, and anatomical studies. Front Neuroanat 2023; 17:1149674. [PMID: 37034833 PMCID: PMC10076536 DOI: 10.3389/fnana.2023.1149674] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 02/28/2023] [Indexed: 04/11/2023] Open
Abstract
We present a method for human brain fixation based on simultaneous perfusion of 4% paraformaldehyde through carotids after a flush with saline. The left carotid cannula is used to perfuse the body with 10% formalin, to allow further use of the body for anatomical research or teaching. The aim of our method is to develop a vascular fixation protocol for the human brain, by adapting protocols that are commonly used in experimental animal studies. We show that a variety of histological procedures can be carried out (cyto- and myeloarchitectonics, histochemistry, immunohistochemistry, intracellular cell injection, and electron microscopy). In addition, ex vivo, ex situ high-resolution MRI (9.4T) can be obtained in the same specimens. This procedure resulted in similar morphological features to those obtained by intravascular perfusion in experimental animals, provided that the postmortem interval was under 10 h for several of the techniques used and under 4 h in the case of intracellular injections and electron microscopy. The use of intravascular fixation of the brain inside the skull provides a fixed whole human brain, perfectly fitted to the skull, with negligible deformation compared to conventional techniques. Given this characteristic of ex vivo, in situ fixation, this procedure can probably be considered the most suitable one available for ex vivo MRI scans of the brain. We describe the compatibility of the method proposed for intravascular fixation of the human brain and fixation of the donor's body for anatomical purposes. Thus, body donor programs can provide human brain tissue, while the remainder of the body can also be fixed for anatomical studies. Therefore, this method of human brain fixation through the carotid system optimizes the procurement of human brain tissue, allowing a greater understanding of human neurological diseases, while benefiting anatomy departments by making the remainder of the body available for teaching purposes.
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Affiliation(s)
- Ricardo Insausti
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Ana María Insausti
- Department of Health, School of Medicine, Public University of Navarra, Pamplona, Spain
| | - Mónica Muñoz López
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Isidro Medina Lorenzo
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Maria del Mar Arroyo-Jiménez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - María Pilar Marcos Rabal
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Carlos de la Rosa-Prieto
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - José Carlos Delgado-González
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Javier Montón Etxeberria
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Sandra Cebada-Sánchez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Juan Francisco Raspeño-García
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - María Mercedes Iñiguez de Onzoño
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Francisco Javier Molina Romero
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
| | - Ruth Benavides-Piccione
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, and Instituto Cajal, CSIC, Madrid, Spain
| | - Silvia Tapia-González
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, and Instituto Cajal, CSIC, Madrid, Spain
| | | | - Sadhana Ravikumar
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Javier DeFelipe
- Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, and Instituto Cajal, CSIC, Madrid, Spain
| | - Paul Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Emilio Artacho-Pérula
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, Medical Sciences Department, School of Medicine and CRIB, University of Castilla La Mancha, Albacete, Spain
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11
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Yildirim Z, Delen F, Berron D, Baumeister H, Ziegler G, Schütze H, Glanz W, Dobisch L, Peters O, Freiesleben SD, Schneider LS, Priller J, Spruth EJ, Schneider A, Fliessbach K, Wiltfang J, Schott BH, Meiberth D, Buerger K, Janowitz D, Perneczky R, Rauchmann BS, Teipel S, Kilimann I, Laske C, Munk MH, Spottke A, Roy N, Heneka M, Brosseron F, Wagner M, Roeske S, Ramirez A, Ewers M, Dechent P, Hetzer S, Scheffler K, Kleineidam L, Wolfsgruber S, Yakupov R, Schmid M, Berger M, Gurvit H, Jessen F, Duzel E. Brain reserve contributes to distinguishing preclinical Alzheimer's stages 1 and 2. Alzheimers Res Ther 2023; 15:43. [PMID: 36855049 PMCID: PMC9972621 DOI: 10.1186/s13195-023-01187-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 02/08/2023] [Indexed: 03/02/2023]
Abstract
BACKGROUND In preclinical Alzheimer's disease, it is unclear why some individuals with amyloid pathologic change are asymptomatic (stage 1), whereas others experience subjective cognitive decline (SCD, stage 2). Here, we examined the association of stage 1 vs. stage 2 with structural brain reserve in memory-related brain regions. METHODS We tested whether the volumes of hippocampal subfields and parahippocampal regions were larger in individuals at stage 1 compared to asymptomatic amyloid-negative older adults (healthy controls, HCs). We also tested whether individuals with stage 2 would show the opposite pattern, namely smaller brain volumes than in amyloid-negative individuals with SCD. Participants with cerebrospinal fluid (CSF) biomarker data and bilateral volumetric MRI data from the observational, multi-centric DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study were included. The sample comprised 95 amyloid-negative and 26 amyloid-positive asymptomatic participants as well as 104 amyloid-negative and 47 amyloid-positive individuals with SCD. Volumes were based on high-resolution T2-weighted images and automatic segmentation with manual correction according to a recently established high-resolution segmentation protocol. RESULTS In asymptomatic individuals, brain volumes of hippocampal subfields and of the parahippocampal cortex were numerically larger in stage 1 compared to HCs, whereas the opposite was the case in individuals with SCD. MANOVAs with volumes as dependent data and age, sex, years of education, and DELCODE site as covariates showed a significant interaction between diagnosis (asymptomatic versus SCD) and amyloid status (Aß42/40 negative versus positive) for hippocampal subfields. Post hoc paired comparisons taking into account the same covariates showed that dentate gyrus and CA1 volumes in SCD were significantly smaller in amyloid-positive than negative individuals. In contrast, CA1 volumes were significantly (p = 0.014) larger in stage 1 compared with HCs. CONCLUSIONS These data indicate that HCs and stages 1 and 2 do not correspond to linear brain volume reduction. Instead, stage 1 is associated with larger than expected volumes of hippocampal subfields in the face of amyloid pathology. This indicates a brain reserve mechanism in stage 1 that enables individuals with amyloid pathologic change to be cognitively normal and asymptomatic without subjective cognitive decline.
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Affiliation(s)
- Zerrin Yildirim
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Vakif Gureba Cad., Capa Kampusu Sehremini, Fatih, 34093, Istanbul, Turkey.
- Department of Neurology, Bagcilar Training and Research Hospital, University of Health Sciences, 34200, Istanbul, Turkey.
| | - Firuze Delen
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Vakif Gureba Cad., Capa Kampusu Sehremini, Fatih, 34093, Istanbul, Turkey
- Department of Neurology, Basaksehir Cam and Sakura City Hospital, 34480, Istanbul, Turkey
| | - David Berron
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Hartmut Schütze
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Silka Dawn Freiesleben
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Luisa-Sophie Schneider
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Charitéplatz 1, 10117, Berlin, Germany
- Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany
- University of Edinburgh and UK DRI, Edinburgh, UK
| | - Eike Jakob Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Charitéplatz 1, 10117, Berlin, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Jens Wiltfang
- Department of Medical Sciences, Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Von-Siebold-Str. 5, 37075, Goettingen, Germany
| | - Björn-Hendrik Schott
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Von-Siebold-Str. 5, 37075, Goettingen, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Dix Meiberth
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Psychiatry, University of Cologne, Medical Faculty, Kerpener Strasse 62, 50924, Cologne, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE, Munich), Feodor-Lynen-Strasse 17, 81377, Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Feodor-Lynen-Strasse 17, 81377, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Feodor-Lynen-Strasse 17, 81377, Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE, Munich), Feodor-Lynen-Strasse 17, 81377, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
- Department of Neuroradiology, University Hospital LMU, Munich, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurology, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
| | - Michael Heneka
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
| | - Frederic Brosseron
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
| | - Michael Wagner
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Sandra Roeske
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
| | - Alfredo Ramirez
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Joseph-Stelzmann-Strasse 26, 50931, Cologne, Germany
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE, Munich), Feodor-Lynen-Strasse 17, 81377, Munich, Germany
| | - Peter Dechent
- Department of Cognitive Neurology, MR-Research in Neurosciences, Georg-August-University Goettingen, Göttingen, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, 72076, Tübingen, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Institute for Medical Biometry Informatics, and Epidemiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Moritz Berger
- Institute for Medical Biometry Informatics, and Epidemiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Hakan Gurvit
- Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul Faculty of Medicine, Istanbul University, 34093, Istanbul, Turkey
- Neuroimaging Unit, Istanbul University, Hulusi Behcet Life Sciences Research Center, 34093, Istanbul, Turkey
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Psychiatry, University of Cologne, Medical Faculty, Kerpener Strasse 62, 50924, Cologne, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Joseph-Stelzmann-Strasse 26, 50931, Cologne, Germany
| | - Emrah Duzel
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
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12
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Williams EM, Rosenblum EW, Pihlstrom N, Llamas-Rodríguez J, Champion S, Frosch MP, Augustinack JC. Pentad: A reproducible cytoarchitectonic protocol and its application to parcellation of the human hippocampus. Front Neuroanat 2023; 17:1114757. [PMID: 36843959 PMCID: PMC9947247 DOI: 10.3389/fnana.2023.1114757] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/13/2023] [Indexed: 02/11/2023] Open
Abstract
Introduction The hippocampus is integral for learning and memory and is targeted by multiple diseases. Neuroimaging approaches frequently use hippocampal subfield volumes as a standard measure of neurodegeneration, thus making them an essential biomarker to study. Collectively, histologic parcellation studies contain various disagreements, discrepancies, and omissions. The present study aimed to advance the hippocampal subfield segmentation field by establishing the first histology based parcellation protocol, applied to n = 22 human hippocampal samples. Methods The protocol focuses on five cellular traits observed in the pyramidal layer of the human hippocampus. We coin this approach the pentad protocol. The traits were: chromophilia, neuron size, packing density, clustering, and collinearity. Subfields included were CA1, CA2, CA3, CA4, prosubiculum, subiculum, presubiculum, parasubiculum, as well as the medial (uncal) subfields Subu, CA1u, CA2u, CA3u, and CA4u. We also establish nine distinct anterior-posterior levels of the hippocampus in the coronal plane to document rostrocaudal differences. Results Applying the pentad protocol, we parcellated 13 subfields at nine levels in 22 samples. We found that CA1 had the smallest neurons, CA2 showed high neuronal clustering, and CA3 displayed the most collinear neurons of the CA fields. The border between presubiculum and subiculum was staircase shaped, and parasubiculum had larger neurons than presubiculum. We also demonstrate cytoarchitectural evidence that CA4 and prosubiculum exist as individual subfields. Discussion This protocol is comprehensive, regimented and supplies a high number of samples, hippocampal subfields, and anterior-posterior coronal levels. The pentad protocol utilizes the gold standard approach for the human hippocampus subfield parcellation.
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Affiliation(s)
- Emily M. Williams
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Emma W. Rosenblum
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Nicole Pihlstrom
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Josué Llamas-Rodríguez
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Samantha Champion
- Department of Neuropathology, Massachusetts General Hospital, Boston, MA, United States
| | - Matthew P. Frosch
- Department of Neuropathology, Massachusetts General Hospital, Boston, MA, United States
| | - Jean C. Augustinack
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
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13
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Li H, Zu T, Hsu YC, Zhao Z, Liu R, Zheng T, Li Q, Sun Y, Liu D, Zhang J, Zhang Y, Wu D. Inversion-Recovery-Prepared Oscillating Gradient Sequence Improves Diffusion-Time Dependency Measurements in the Human Brain. J Magn Reson Imaging 2023; 57:446-453. [PMID: 35723048 DOI: 10.1002/jmri.28311] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 06/06/2022] [Accepted: 06/06/2022] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Oscillating gradient diffusion MRI (dMRI) enables measurements at a short diffusion-time (td ), but it is challenging for clinical systems. Particularly, the low b-value and low resolution may give rise to cerebrospinal fluid (CSF) contamination. PURPOSE To assess the effect of CSF partial volume on td -dMRI measurements and efficacy of inversion-recovery (IR) prepared oscillating and pulsed gradient dMRI sequence to improve td -dMRI measurements in the human brain. STUDY TYPE Prospective. SUBJECTS Ten normal volunteers and six glioma patients. FIELD STRENGTH/SEQUENCE A 3 T; three-dimensional (3D) IR-prepared oscillating gradient-prepared gradient spin-echo (GRASE) and two-dimensional (2D) IR-prepared oscillating gradient echo-planar imaging (EPI) sequences. ASSESSMENT We assessed the td -dependent patterns of apparent diffusion coefficient (ADC) in several gray and white matter structures, including the hippocampal subfields (head, body, and tail), cortical gray matter, thalamus, and posterior white matter in normal volunteers. Pulsed gradient (0 Hz) and oscillating gradients at frequencies of 20 Hz, 40 Hz, and 60 Hz dMRI were acquired with GRASE and EPI sequences with or without the IR module. We also tested the td -dependency patterns in glioma patients using the EPI sequence with or without the IR module. STATISTICAL TESTS The differences in ADC across the different td s were compared by one-way ANOVA followed by post hoc pairwise t-tests with Bonferroni correction. RESULTS In the healthy subjects, brain regions that were possibly contaminated by CSF signals, such as the hippocampus (head, body, and tail) and cortical gray matter, td -dependent ADC changes were only significant with the IR-prepared 2D and 3D sequences but not with the non-IR sequences. In brain glioblastomas patients, significantly higher td -dependence was observed in the tumor region with the IR module than that without IR (slope = 0.0196 μm2 /msec2 vs. 0.0034 μm2 /msec2 ). CONCLUSION The IR-prepared sequence effectively suppressed the CSF partial volume effect and significantly improved the td -dependent measurements in the human brain. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Haotian Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tao Zu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare China, Shanghai, China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Ruibin Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tianshu Zheng
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qing Li
- MR Collaboration, Siemens Healthcare China, Shanghai, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare China, Shanghai, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
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14
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Zhao Z, Zhang L, Luo W, Cao Z, Zhu Q, Kong X, Zhu K, Zhang J, Wu D. Layer-specific microstructural patterns of anterior hippocampus in Alzheimer's disease with ex vivo diffusion MRI at 14.1 T. Hum Brain Mapp 2022; 44:458-471. [PMID: 36053237 PMCID: PMC9842914 DOI: 10.1002/hbm.26062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/20/2022] [Accepted: 08/16/2022] [Indexed: 01/25/2023] Open
Abstract
High-resolution ex vivo diffusion MRI (dMRI) can provide exquisite mesoscopic details and microstructural information of the human brain. Microstructural pattern of the anterior part of human hippocampus, however, has not been well elucidated with ex vivo dMRI, either in normal or disease conditions. The present study collected high-resolution (0.1 mm isotropic) dMRI of post-mortem anterior hippocampal tissues from four Alzheimer's diseases (AD), three primary age-related tauopathy (PART), and three healthy control (HC) brains on a 14.1 T spectrometer. We evaluated how AD affected dMRI-based microstructural features in different layers and subfields of anterior hippocampus. In the HC samples, we found higher anisotropy, lower diffusivity, and more streamlines in the layers within cornu ammonis (CA) than those within dentate gyrus (DG). Comparisons between disease groups showed that (1) anisotropy measurements in the CA layers of AD, especially stratum lacunosum (SL) and stratum radiatum (SR), had higher regional variability than the other two groups; (2) streamline density in the DG layers showed a gradually increased variance from HC to PART to AD; (3) AD also showed the higher variability in terms of inter-layer connectivity than HC or PART. Moreover, voxelwise correlation analysis between the coregistered dMRI and histopathology images revealed significant correlations between dMRI measurements and the contents of amyloid beta (Aβ)/tau protein in specific layers of AD samples. These findings may reflect layer-specific microstructural characteristics in different hippocampal subfields at the mesoscopic resolution, which were associated with protein deposition in the anterior hippocampus of AD patients.
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Affiliation(s)
- Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument ScienceZhejiang UniversityHangzhouChina
| | - Lei Zhang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of NeurobiologyZhejiang University School of MedicineHangzhouChina
| | - Wanrong Luo
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument ScienceZhejiang UniversityHangzhouChina
| | - Zuozhen Cao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument ScienceZhejiang UniversityHangzhouChina
| | - Qinfeng Zhu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument ScienceZhejiang UniversityHangzhouChina
| | - Xueqian Kong
- Department of ChemistryZhejiang UniversityHangzhouChina
| | - Keqing Zhu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of NeurobiologyZhejiang University School of MedicineHangzhouChina
| | - Jing Zhang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of NeurobiologyZhejiang University School of MedicineHangzhouChina,Department of Pathology, The First Affiliated Hospital and School of MedicineZhejiang UniversityHangzhouChina
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument ScienceZhejiang UniversityHangzhouChina
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15
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Leaver AM, Espinoza R, Wade B, Narr KL. Parsing the Network Mechanisms of Electroconvulsive Therapy. Biol Psychiatry 2022; 92:193-203. [PMID: 35120710 PMCID: PMC9196257 DOI: 10.1016/j.biopsych.2021.11.016] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/03/2021] [Accepted: 11/19/2021] [Indexed: 12/17/2022]
Abstract
Electroconvulsive therapy (ECT) is one of the oldest and most effective forms of neurostimulation, wherein electrical current is used to elicit brief, generalized seizures under general anesthesia. When electrodes are positioned to target frontotemporal cortex, ECT is arguably the most effective treatment for severe major depression, with response rates and times superior to other available antidepressant therapies. Neuroimaging research has been pivotal in improving the field's mechanistic understanding of ECT, with a growing number of magnetic resonance imaging studies demonstrating hippocampal plasticity after ECT, in line with evidence of upregulated neurotrophic processes in the hippocampus in animal models. However, the precise roles of the hippocampus and other brain regions in antidepressant response to ECT remain unclear. Seizure physiology may also play a role in antidepressant response to ECT, as indicated by early positron emission tomography, single-photon emission computed tomography, and electroencephalography research and corroborated by recent magnetic resonance imaging studies. In this review, we discuss the evidence supporting neuroplasticity in the hippocampus and other brain regions during and after ECT, and their associations with antidepressant response. We also offer a mechanistic, circuit-level model that proposes that core mechanisms of antidepressant response to ECT involve thalamocortical and cerebellar networks that are active during seizure generalization and termination over repeated ECT sessions, and their interactions with corticolimbic circuits that are dysfunctional prior to treatment and targeted with the electrical stimulus.
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Affiliation(s)
- Amber M Leaver
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Evanston, Illinois.
| | - Randall Espinoza
- Department of Psychiatry and Behavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Benjamin Wade
- Department of Neurology, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Katherine L Narr
- Department of Neurology, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California; Department of Psychiatry and Behavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
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16
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Düzel E, Costagli M, Donatelli G, Speck O, Cosottini M. Studying Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis with 7-T magnetic resonance. Eur Radiol Exp 2021; 5:36. [PMID: 34435242 PMCID: PMC8387546 DOI: 10.1186/s41747-021-00221-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 04/07/2021] [Indexed: 12/18/2022] Open
Abstract
Ultra-high-field (UHF) magnetic resonance (MR) scanners, that is, equipment operating at static magnetic field of 7 tesla (7 T) and above, enable the acquisition of data with greatly improved signal-to-noise ratio with respect to conventional MR systems (e.g., scanners operating at 1.5 T and 3 T). The change in tissue relaxation times at UHF offers the opportunity to improve tissue contrast and depict features that were previously inaccessible. These potential advantages come, however, at a cost: in the majority of UHF-MR clinical protocols, potential drawbacks may include signal inhomogeneity, geometrical distortions, artifacts introduced by patient respiration, cardiac cycle, and motion. This article reviews the 7 T MR literature reporting the recent studies on the most widespread neurodegenerative diseases: Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.
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Affiliation(s)
- Emrah Düzel
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany. .,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. .,University College London, London, UK.
| | - Mauro Costagli
- IRCCS Stella Maris, Pisa, Italy.,University of Genoa, Genova, Italy
| | - Graziella Donatelli
- Fondazione Imago 7, Pisa, Italy.,Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - Oliver Speck
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Mirco Cosottini
- Azienda Ospedaliero Universitaria Pisana, Pisa, Italy.,University of Pisa, Pisa, Italy
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17
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Wisse LEM, Ravikumar S, Ittyerah R, Lim S, Lane J, Bedard ML, Xie L, Das SR, Schuck T, Grossman M, Lee EB, Tisdall MD, Prabhakaran K, Detre JA, Mizsei G, Trojanowski JQ, Artacho-Pérula E, de Iñiguez de Onzono Martin MM, M Arroyo-Jiménez M, Muñoz Lopez M, Molina Romero FJ, P Marcos Rabal M, Cebada Sánchez S, Delgado González JC, de la Rosa Prieto C, Córcoles Parada M, Wolk DA, Irwin DJ, Insausti R, Yushkevich PA. Downstream effects of polypathology on neurodegeneration of medial temporal lobe subregions. Acta Neuropathol Commun 2021; 9:128. [PMID: 34289895 PMCID: PMC8293481 DOI: 10.1186/s40478-021-01225-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 07/06/2021] [Indexed: 12/14/2022] Open
Abstract
The medial temporal lobe (MTL) is a nidus for neurodegenerative pathologies and therefore an important region in which to study polypathology. We investigated associations between neurodegenerative pathologies and the thickness of different MTL subregions measured using high-resolution post-mortem MRI. Tau, TAR DNA-binding protein 43 (TDP-43), amyloid-β and α-synuclein pathology were rated on a scale of 0 (absent)-3 (severe) in the hippocampus and entorhinal cortex (ERC) of 58 individuals with and without neurodegenerative diseases (median age 75.0 years, 60.3% male). Thickness measurements in ERC, Brodmann Area (BA) 35 and 36, parahippocampal cortex, subiculum, cornu ammonis (CA)1 and the stratum radiatum lacunosum moleculare (SRLM) were derived from 0.2 × 0.2 × 0.2 mm3 post-mortem MRI scans of excised MTL specimens from the contralateral hemisphere using a semi-automated approach. Spearman's rank correlations were performed between neurodegenerative pathologies and thickness, correcting for age, sex and hemisphere, including all four proteinopathies in the model. We found significant associations of (1) TDP-43 with thickness in all subregions (r = - 0.27 to r = - 0.46), and (2) tau with BA35 (r = - 0.31) and SRLM thickness (r = - 0.33). In amyloid-β and TDP-43 negative cases, we found strong significant associations of tau with ERC (r = - 0.40), BA35 (r = - 0.55), subiculum (r = - 0.42) and CA1 thickness (r = - 0.47). This unique dataset shows widespread MTL atrophy in relation to TDP-43 pathology and atrophy in regions affected early in Braak stageing and tau pathology. Moreover, the strong association of tau with thickness in early Braak regions in the absence of amyloid-β suggests a role of Primary Age-Related Tauopathy in neurodegeneration.
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Affiliation(s)
- L E M Wisse
- Department of Diagnostic Radiology, Lund University, Klinikgatan 13b, Lund, Sweden.
- Department of Radiology, University of Pennsylvania, Philadelphia, USA.
| | - S Ravikumar
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - R Ittyerah
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - S Lim
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - J Lane
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - M L Bedard
- Department of Pharmacology, University of North Carolina At Chapel Hill, Chapel Hill, USA
| | - L Xie
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - S R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - T Schuck
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - M Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - E B Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - M D Tisdall
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - K Prabhakaran
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - J A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - G Mizsei
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - J Q Trojanowski
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - E Artacho-Pérula
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | | | - M M Arroyo-Jiménez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - M Muñoz Lopez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - F J Molina Romero
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - M P Marcos Rabal
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - S Cebada Sánchez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - J C Delgado González
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - C de la Rosa Prieto
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - M Córcoles Parada
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - D A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - D J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, USA
| | - R Insausti
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla La Mancha, Albacete, Spain
| | - P A Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
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18
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DeKraker J, Köhler S, Khan AR. Surface-based hippocampal subfield segmentation. Trends Neurosci 2021; 44:856-863. [PMID: 34304910 DOI: 10.1016/j.tins.2021.06.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 05/25/2021] [Accepted: 06/15/2021] [Indexed: 10/20/2022]
Abstract
Though it is often termed 'subcortical,' the hippocampus is composed of a folded 'archicortical' sheet contiguous with the neocortex. The human hippocampus varies considerably in its internal folding configuration, creating major challenges in interindividual alignment and parcellation into subfields. In this opinion article, we discuss surface-based methods that aim to explicitly model hippocampal folding, similar to methods used in the neocortex, allowing interindividual alignment in an unfolded or flat-mapped 2D space. Such an approach enables detailed morphological characterization, constrains the problem of subfield segmentation, and provides a way to visualize data without occlusions. We argue that, when applied to magnetic resonance imaging (MRI) data, such methods overcome pitfalls of more conventional manual or registration-based subfield segmentation approaches.
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Affiliation(s)
- Jordan DeKraker
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada; Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada.
| | - Stefan Köhler
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada; Department of Psychology, University of Western Ontario, London, ON, Canada.
| | - Ali R Khan
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada; Robarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada; School of Biomedical Engineering, University of Western Ontario, London, ON, Canada; Department of Medical Biophysics, University of Western Ontario, London, ON, Canada.
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19
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Vockert N, Perosa V, Ziegler G, Schreiber F, Priester A, Spallazzi M, Garcia-Garcia B, Aruci M, Mattern H, Haghikia A, Düzel E, Schreiber S, Maass A. Hippocampal vascularization patterns exert local and distant effects on brain structure but not vascular pathology in old age. Brain Commun 2021; 3:fcab127. [PMID: 34222874 PMCID: PMC8249103 DOI: 10.1093/braincomms/fcab127] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Revised: 04/25/2021] [Accepted: 06/03/2021] [Indexed: 12/29/2022] Open
Abstract
The hippocampus within the medial temporal lobe is highly vulnerable to age-related pathology such as vascular disease. We examined hippocampal vascularization patterns by harnessing the ultra-high resolution of 7 Tesla magnetic resonance angiography. Dual-supply hemispheres with a contribution of the anterior choroidal artery to hippocampal blood supply were distinguished from single-supply ones with a sole dependence on the posterior cerebral artery. A recent study indicated that a dual vascular supply is related to preserved cognition and structural hippocampal integrity in old age and vascular disease. Here, we examined the regional specificity of these structural benefits at the level of medial temporal lobe sub-regions and hemispheres. In a cross-sectional study with an older cohort of 17 patients with cerebral small vessel disease (70.7 ± 9.0 years, 35.5% female) and 27 controls (71.1 ± 8.2 years, 44.4% female), we demonstrate that differences in grey matter volumes related to the hippocampal vascularization pattern were specifically observed in the anterior hippocampus and entorhinal cortex. These regions were especially bigger in dual-supply hemispheres, but also seemed to benefit from a contralateral dual supply. We further show that total grey matter volumes were greater in people with at least one dual-supply hemisphere, indicating that the hippocampal vascularization pattern has more far-reaching structural implications beyond the medial temporal lobe. A mediation analysis identified total grey matter as a mediator of differences in global cognition. However, our analyses on multiple neuroimaging markers for cerebral small vessel disease did not reveal any evidence that an augmented hippocampal vascularization conveys resistance nor resilience against vascular pathology. We propose that an augmented hippocampal vascularization might contribute to maintaining structural integrity in the brain and preserving cognition despite age-related degeneration. As such, the binary hippocampal vascularization pattern could have major implications for brain structure and function in ageing and dementia independent of vascular pathology, while presenting a simple framework with potential applicability to the clinical setting.
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Affiliation(s)
- Niklas Vockert
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
| | - Valentina Perosa
- Department of Neurology, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Gabriel Ziegler
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, 39120 Magdeburg, Germany
| | - Frank Schreiber
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Department of Neurology, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
| | - Anastasia Priester
- Department of Neuroradiology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Marco Spallazzi
- Department of Medicine and Surgery, Unit of Neurology, Azienda Ospedaliero- Universitaria, 43126 Parma, Italy
| | - Berta Garcia-Garcia
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Department of Neurology, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
| | - Merita Aruci
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
| | - Hendrik Mattern
- Biomedical Magnetic Resonance, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
| | - Aiden Haghikia
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Department of Neurology, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Department of Neurology, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, 39120 Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
- Center for Behavioral Brain Sciences (CBBS), 39106 Magdeburg, Germany
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
- Department of Neurology, Otto von Guericke University Magdeburg, 39120 Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), 39106 Magdeburg, Germany
| | - Anne Maass
- German Center for Neurodegenerative Diseases, 39120 Magdeburg, Germany
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20
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Santini T, Koo M, Farhat N, Campos VP, Alkhateeb S, Vieira MAC, Butters MA, Rosano C, Aizenstein HJ, Mettenburg J, Novelli EM, Ibrahim TS. Analysis of hippocampal subfields in sickle cell disease using ultrahigh field MRI. Neuroimage Clin 2021; 30:102655. [PMID: 34215139 PMCID: PMC8102634 DOI: 10.1016/j.nicl.2021.102655] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 03/28/2021] [Accepted: 03/29/2021] [Indexed: 12/05/2022]
Abstract
Sickle cell disease (SCD) is an inherited hemoglobinopathy that causes organ dysfunction, including cerebral vasculopathy and neurological complications. Hippocampal segmentation with newer and advanced 7 Tesla (7T) MRI protocols has revealed atrophy in specific subregions in other neurodegenerative and neuroinflammatory diseases, however, there is limited evidence of hippocampal involvement in SCD. Thus, we explored whether SCD may be also associated with abnormalities in hippocampal subregions. We conducted 7T MRI imaging in individuals with SCD, including the HbSS, HbSC and HbS/beta thalassemia genotypes (n = 53), and healthy race and age-matched controls (n = 47), using a customized head coil. Both T1- and T2-weighted images were used for automatic segmentation of the hippocampal subfields. Individuals with SCD had, on average, significantly smaller volume of the region including the Dentate Gyrus and Cornu Ammonis (CA) 2 and 3 as compared to the control group. Other hippocampal subregions also showed a trend towards smaller volumes in the SCD group. These findings support and extend previous reports of reduced volume in the temporal lobe in SCD patients. Further studies are necessary to investigate the mechanisms that lead to structural changes in the hippocampus subfields and their relationship with cognitive performance in SCD patients.
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Affiliation(s)
- Tales Santini
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Minseok Koo
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Nadim Farhat
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Vinicius P Campos
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Salem Alkhateeb
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Marcelo A C Vieira
- Department of Electrical and Computer Engineering, University of São Paulo, São Carlos, SP, Brazil
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Caterina Rosano
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Howard J Aizenstein
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
| | - Joseph Mettenburg
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Enrico M Novelli
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, PA, United States.
| | - Tamer S Ibrahim
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Department of Radiology, University of Pittsburgh, Pittsburgh, PA, United States.
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21
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Homayouni R, Yu Q, Ramesh S, Tang L, Daugherty AM, Ofen N. Test-retest reliability of hippocampal subfield volumes in a developmental sample: Implications for longitudinal developmental studies. J Neurosci Res 2021; 99:2327-2339. [PMID: 33751637 DOI: 10.1002/jnr.24831] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 03/04/2021] [Indexed: 12/21/2022]
Abstract
The hippocampus (Hc) is composed of cytoarchitectonically distinct subfields: dentate gyrus (DG), cornu ammonis sectors 1-3 (CA1-3), and subiculum. Limited evidence suggests differential maturation rates across the Hc subfields. While longitudinal studies are essential in demonstrating differential development of Hc subfields, a prerequisite for interpreting meaningful longitudinal effects is establishing test-retest consistency of Hc subfield volumes measured in vivo over time. Here, we examined test-retest consistency of Hc subfield volumes measured from structural MR images in two independent developmental samples. Sample One (n = 28, ages 7-20 years, M = 12.64, SD = 3.35) and Sample Two (n = 28, ages 7-17 years, M = 11.72, SD = 2.88) underwent MRI twice with a 1-month and a 2-year delay, respectively. High-resolution PD-TSE-T2 -weighted MR images (0.4 × 0.4 × 2 mm3 ) were collected and manually traced using a longitudinal manual demarcation protocol. In both samples, we found excellent consistency of Hc subfield volumes between the two visits, assessed by two-way mixed intraclass correlation (ICC (3) single measures ≥ 0.87), and no difference between children and adolescents. The results further indicated that discrepancies between repeated measures were not related to Hc subfield volumes, or visit number. In addition to high consistency, with the applied longitudinal protocol, we detected significant variability in Hc subfield volume changes over the 2-year delay, implying high sensitivity of the method in detecting individual differences. Establishing unbiased, high longitudinal consistency of Hc subfield volume measurements optimizes statistical power of a hypothesis test and reduces standard error of the estimate, together improving external validity of the measures in constructing theoretical models of memory development.
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Affiliation(s)
- Roya Homayouni
- Institute of Gerontology, Wayne State University, Detroit, MI, USA.,Department of Psychology, Wayne State University, Detroit, MI, USA
| | - Qijing Yu
- Institute of Gerontology, Wayne State University, Detroit, MI, USA.,Department of Psychology, Wayne State University, Detroit, MI, USA
| | - Sruthi Ramesh
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Lingfei Tang
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Ana M Daugherty
- Institute of Gerontology, Wayne State University, Detroit, MI, USA.,Department of Psychology, Wayne State University, Detroit, MI, USA.,Department of Psychiatry and Behavioral Neurosciences, School of Medicine, Wayne State University, Detroit, MI, USA
| | - Noa Ofen
- Institute of Gerontology, Wayne State University, Detroit, MI, USA.,Department of Psychology, Wayne State University, Detroit, MI, USA.,Merrill Palmer Skillman Institute, Wayne State University, Detroit, MI, USA
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22
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Li L, Pan N, Zhang L, Lui S, Huang X, Xu X, Wang S, Lei D, Li L, Kemp GJ, Gong Q. Hippocampal subfield alterations in pediatric patients with post-traumatic stress disorder. Soc Cogn Affect Neurosci 2021; 16:334-344. [PMID: 33315100 PMCID: PMC7943370 DOI: 10.1093/scan/nsaa162] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 10/15/2020] [Accepted: 12/14/2020] [Indexed: 02/05/2023] Open
Abstract
The hippocampus, a key structure with distinct subfield functions, is strongly implicated in the pathophysiology of post-traumatic stress disorder (PTSD); however, few studies of hippocampus subfields in PTSD have focused on pediatric patients. We therefore investigated the hippocampal subfield volume using an automated segmentation method and explored the subfield-centered functional connectivity aberrations related to the anatomical changes, in a homogenous population of traumatized children with and without PTSD. To investigate the potential diagnostic value in individual patients, we used a machine learning approach to identify features with significant discriminative power for diagnosis of PTSD using random forest classifiers. Compared to controls, we found significant mean volume reductions of 8.4% and 9.7% in the right presubiculum and hippocampal tail in patients, respectively. These two subfields' volumes were the most significant contributors to group discrimination, with a mean classification accuracy of 69% and a specificity of 81%. These anatomical alterations, along with the altered functional connectivity between (pre)subiculum and inferior frontal gyrus, may underlie deficits in fear circuitry leading to dysfunction of fear extinction and episodic memory, causally important in post-traumatic symptoms such as hypervigilance and re-experience. For the first time, we suggest that hippocampal subfield volumes might be useful in discriminating traumatized children with and without PTSD.
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Affiliation(s)
- Lei Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Lianqing Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Xin Xu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Lingjiang Li
- Mental Health Institute, The Second Xiangya Hospital of Central South University, Changsha 410008, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L693BX, UK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
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23
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Paquola C, Benkarim O, DeKraker J, Larivière S, Frässle S, Royer J, Tavakol S, Valk S, Bernasconi A, Bernasconi N, Khan A, Evans AC, Razi A, Smallwood J, Bernhardt BC. Convergence of cortical types and functional motifs in the human mesiotemporal lobe. eLife 2020; 9:e60673. [PMID: 33146610 PMCID: PMC7671688 DOI: 10.7554/elife.60673] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 11/03/2020] [Indexed: 01/24/2023] Open
Abstract
The mesiotemporal lobe (MTL) is implicated in many cognitive processes, is compromised in numerous brain disorders, and exhibits a gradual cytoarchitectural transition from six-layered parahippocampal isocortex to three-layered hippocampal allocortex. Leveraging an ultra-high-resolution histological reconstruction of a human brain, our study showed that the dominant axis of MTL cytoarchitectural differentiation follows the iso-to-allocortical transition and depth-specific variations in neuronal density. Projecting the histology-derived MTL model to in-vivo functional MRI, we furthermore determined how its cytoarchitecture underpins its intrinsic effective connectivity and association to large-scale networks. Here, the cytoarchitectural gradient was found to underpin intrinsic effective connectivity of the MTL, but patterns differed along the anterior-posterior axis. Moreover, while the iso-to-allocortical gradient parametrically represented the multiple-demand relative to task-negative networks, anterior-posterior gradients represented transmodal versus unimodal networks. Our findings establish that the combination of micro- and macrostructural features allow the MTL to represent dominant motifs of whole-brain functional organisation.
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Affiliation(s)
- Casey Paquola
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Oualid Benkarim
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Jordan DeKraker
- Brain and Mind Institute, University of Western OntarioLondonCanada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Stefan Frässle
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & ETH ZurichZurichSwitzerland
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Sofie Valk
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre JülichJülichGermany
- Institute of Systems Neuroscience, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Andrea Bernasconi
- Neuroimaging Of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Neda Bernasconi
- Neuroimaging Of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Ali Khan
- Brain and Mind Institute, University of Western OntarioLondonCanada
| | - Alan C Evans
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
- McGill Centre for Integrative Neuroscience, McGill UniversityMontrealCanada
| | | | | | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
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24
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Snytte J, Elshiekh A, Subramaniapillai S, Manning L, Pasvanis S, Devenyi GA, Olsen RK, Rajah MN. The ratio of posterior–anterior medial temporal lobe volumes predicts source memory performance in healthy young adults. Hippocampus 2020; 30:1209-1227. [DOI: 10.1002/hipo.23251] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 07/02/2020] [Accepted: 07/10/2020] [Indexed: 02/01/2023]
Affiliation(s)
- Jamie Snytte
- Integrated Program in Neuroscience, Faculty of Medicine McGill University Montreal Quebec Canada
| | - Abdelhalim Elshiekh
- Integrated Program in Neuroscience, Faculty of Medicine McGill University Montreal Quebec Canada
| | | | - Lyssa Manning
- Massachusetts General Hospital Boston Massachusetts USA
| | - Stamatoula Pasvanis
- Cerebral Imaging Centre Douglas Mental Health University Institute Montreal Quebec Canada
| | - Gabriel A. Devenyi
- Cerebral Imaging Centre Douglas Mental Health University Institute Montreal Quebec Canada
- Department of Psychiatry McGill University Montreal Quebec Canada
| | - Rosanna K. Olsen
- Department of Psychology University of Toronto Toronto Ontario Canada
- Rotman Research Institute Baycrest Health Sciences Toronto Ontario Canada
| | - Maria Natasha Rajah
- Cerebral Imaging Centre Douglas Mental Health University Institute Montreal Quebec Canada
- Department of Psychiatry McGill University Montreal Quebec Canada
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