1
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Khandelwal P, Duong MT, Sadaghiani S, Lim S, Denning AE, Chung E, Ravikumar S, Arezoumandan S, Peterson C, Bedard M, Capp N, Ittyerah R, Migdal E, Choi G, Kopp E, Loja B, Hasan E, Li J, Bahena A, Prabhakaran K, Mizsei G, Gabrielyan M, Schuck T, Trotman W, Robinson J, Ohm DT, Lee EB, Trojanowski JQ, McMillan C, Grossman M, Irwin DJ, Detre JA, Tisdall MD, Das SR, Wisse LEM, Wolk DA, Yushkevich PA. Automated deep learning segmentation of high-resolution 7 Tesla postmortem MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2024; 2:1-30. [PMID: 39301426 PMCID: PMC11409836 DOI: 10.1162/imag_a_00171] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 04/01/2024] [Accepted: 04/15/2024] [Indexed: 09/22/2024]
Abstract
Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automated segmentation methods for brain mapping in postmortem MRI are not well developed, primarily due to limited availability of labeled datasets, and heterogeneity in scanner hardware and acquisition protocols. In this work, we present a high-resolution dataset of 135 postmortem human brain tissue specimens imaged at 0.3 mm3 isotropic using a T2w sequence on a 7T whole-body MRI scanner. We developed a deep learning pipeline to segment the cortical mantle by benchmarking the performance of nine deep neural architectures, followed by post-hoc topological correction. We evaluate the reliability of this pipeline via overlap metrics with manual segmentation in 6 specimens, and intra-class correlation between cortical thickness measures extracted from the automatic segmentation and expert-generated reference measures in 36 specimens. We also segment four subcortical structures (caudate, putamen, globus pallidus, and thalamus), white matter hyperintensities, and the normal appearing white matter, providing a limited evaluation of accuracy. We show generalizing capabilities across whole-brain hemispheres in different specimens, and also on unseen images acquired at 0.28 mm3 and 0.16 mm3 isotropic T2*w fast low angle shot (FLASH) sequence at 7T. We report associations between localized cortical thickness and volumetric measurements across key regions, and semi-quantitative neuropathological ratings in a subset of 82 individuals with Alzheimer's disease (AD) continuum diagnoses. Our code, Jupyter notebooks, and the containerized executables are publicly available at the project webpage (https://pulkit-khandelwal.github.io/exvivo-brain-upenn/).
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Affiliation(s)
- Pulkit Khandelwal
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
| | - Michael Tran Duong
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States
| | - Shokufeh Sadaghiani
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Sydney Lim
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Amanda E. Denning
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Eunice Chung
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Sadhana Ravikumar
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Sanaz Arezoumandan
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Claire Peterson
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Madigan Bedard
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Noah Capp
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Elyse Migdal
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Grace Choi
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Emily Kopp
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Bridget Loja
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Eusha Hasan
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Jiacheng Li
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Alejandra Bahena
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Karthik Prabhakaran
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Gabor Mizsei
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Marianna Gabrielyan
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Theresa Schuck
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Winifred Trotman
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - John Robinson
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Daniel T. Ohm
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Edward B. Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Corey McMillan
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - David J. Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - John A. Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - M. Dylan Tisdall
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Sandhitsu R. Das
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | | | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, United States
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
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2
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Wuestefeld A, Baumeister H, Adams JN, de Flores R, Hodgetts CJ, Mazloum-Farzaghi N, Olsen RK, Puliyadi V, Tran TT, Bakker A, Canada KL, Dalton MA, Daugherty AM, La Joie R, Wang L, Bedard ML, Buendia E, Chung E, Denning A, Del Mar Arroyo-Jiménez M, Artacho-Pérula E, Irwin DJ, Ittyerah R, Lee EB, Lim S, Del Pilar Marcos-Rabal M, Iñiguez de Onzoño Martin MM, Lopez MM, de la Rosa Prieto C, Schuck T, Trotman W, Vela A, Yushkevich P, Amunts K, Augustinack JC, Ding SL, Insausti R, Kedo O, Berron D, Wisse LEM. Comparison of histological delineations of medial temporal lobe cortices by four independent neuroanatomy laboratories. Hippocampus 2024; 34:241-260. [PMID: 38415962 PMCID: PMC11039382 DOI: 10.1002/hipo.23602] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 01/25/2024] [Accepted: 02/04/2024] [Indexed: 02/29/2024]
Abstract
The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and prone to the accumulation of certain neuropathologies such as Alzheimer's disease neurofibrillary tau tangles. The MTL cortex is composed of several subregions which differ in their functional and cytoarchitectonic features. As neuroanatomical schools rely on different cytoarchitectonic definitions of these subregions, it is unclear to what extent their delineations of MTL cortex subregions overlap. Here, we provide an overview of cytoarchitectonic definitions of the entorhinal and parahippocampal cortices as well as Brodmann areas (BA) 35 and 36, as provided by four neuroanatomists from different laboratories, aiming to identify the rationale for overlapping and diverging delineations. Nissl-stained series were acquired from the temporal lobes of three human specimens (two right and one left hemisphere). Slices (50 μm thick) were prepared perpendicular to the long axis of the hippocampus spanning the entire longitudinal extent of the MTL cortex. Four neuroanatomists annotated MTL cortex subregions on digitized slices spaced 5 mm apart (pixel size 0.4 μm at 20× magnification). Parcellations, terminology, and border placement were compared among neuroanatomists. Cytoarchitectonic features of each subregion are described in detail. Qualitative analysis of the annotations showed higher agreement in the definitions of the entorhinal cortex and BA35, while the definitions of BA36 and the parahippocampal cortex exhibited less overlap among neuroanatomists. The degree of overlap of cytoarchitectonic definitions was partially reflected in the neuroanatomists' agreement on the respective delineations. Lower agreement in annotations was observed in transitional zones between structures where seminal cytoarchitectonic features are expressed less saliently. The results highlight that definitions and parcellations of the MTL cortex differ among neuroanatomical schools and thereby increase understanding of why these differences may arise. This work sets a crucial foundation to further advance anatomically-informed neuroimaging research on the human MTL cortex.
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Affiliation(s)
- Anika Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jenna N Adams
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, California, USA
| | - 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
| | | | - Negar Mazloum-Farzaghi
- University of Toronto, Toronto, Ontario, Canada
- Rotman Research Institute, Toronto, Ontario, Canada
| | - Rosanna K Olsen
- University of Toronto, Toronto, Ontario, Canada
- Rotman Research Institute, Toronto, Ontario, Canada
| | - Vyash Puliyadi
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Tammy T Tran
- Department of Psychology, Stanford University, Stanford, California, USA
| | - Arnold Bakker
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, Maryland, USA
| | - Kelsey L Canada
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | | | - Ana M Daugherty
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
- Department of Psychology, Wayne State University, Detroit, Michigan, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
| | - Lei Wang
- The Ohio State University, Columbus, Ohio, USA
| | - Madigan L Bedard
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Esther Buendia
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | - Eunice Chung
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Amanda Denning
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | | | - David J Irwin
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Edward B Lee
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sydney Lim
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | | | - Monica Munoz Lopez
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | | | - Theresa Schuck
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Alicia Vela
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | | | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- C. & O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
| | | | - Song-Lin Ding
- Allen Institute for Brain Science, Seattle, Washington, USA
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, University of Castilla-La Mancha, Albacete, Spain
| | - Olga Kedo
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Laura E M Wisse
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
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3
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Wuestefeld A, Baumeister H, Adams JN, de Flores R, Hodgetts C, Mazloum-Farzaghi N, Olsen RK, Puliyadi V, Tran TT, Bakker A, Canada KL, Dalton MA, Daugherty AM, Joie RL, Wang L, Bedard M, Buendia E, Chung E, Denning A, Arroyo-Jiménez MDM, Artacho-Pérula E, Irwin DJ, Ittyerah R, Lee EB, Lim S, Marcos-Rabal MDP, Martin MMIDO, Lopez MM, Prieto CDLR, Schuck T, Trotman W, Vela A, Yushkevich P, Amunts K, Augustinack JC, Ding SL, Insausti R, Kedo O, Berron D, Wisse LEM. Comparison of histological delineations of medial temporal lobe cortices by four independent neuroanatomy laboratories. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.24.542054. [PMID: 37292729 PMCID: PMC10245880 DOI: 10.1101/2023.05.24.542054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and prone to the accumulation of certain neuropathologies such as Alzheimer's disease neurofibrillary tau tangles. The MTL cortex is composed of several subregions which differ in their functional and cytoarchitectonic features. As neuroanatomical schools rely on different cytoarchitectonic definitions of these subregions, it is unclear to what extent their delineations of MTL cortex subregions overlap. Here, we provide an overview of cytoarchitectonic definitions of the cortices that make up the parahippocampal gyrus (entorhinal and parahippocampal cortices) and the adjacent Brodmann areas (BA) 35 and 36, as provided by four neuroanatomists from different laboratories, aiming to identify the rationale for overlapping and diverging delineations. Nissl-stained series were acquired from the temporal lobes of three human specimens (two right and one left hemisphere). Slices (50 µm thick) were prepared perpendicular to the long axis of the hippocampus spanning the entire longitudinal extent of the MTL cortex. Four neuroanatomists annotated MTL cortex subregions on digitized (20X resolution) slices with 5 mm spacing. Parcellations, terminology, and border placement were compared among neuroanatomists. Cytoarchitectonic features of each subregion are described in detail. Qualitative analysis of the annotations showed higher agreement in the definitions of the entorhinal cortex and BA35, while definitions of BA36 and the parahippocampal cortex exhibited less overlap among neuroanatomists. The degree of overlap of cytoarchitectonic definitions was partially reflected in the neuroanatomists' agreement on the respective delineations. Lower agreement in annotations was observed in transitional zones between structures where seminal cytoarchitectonic features are expressed more gradually. The results highlight that definitions and parcellations of the MTL cortex differ among neuroanatomical schools and thereby increase understanding of why these differences may arise. This work sets a crucial foundation to further advance anatomically-informed human neuroimaging research on the MTL cortex.
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Affiliation(s)
- Anika Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Jenna N Adams
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Robin de Flores
- INSERM UMR-S U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain, Caen-Normandie University, Caen-Normandie, France
| | | | - Negar Mazloum-Farzaghi
- University of Toronto, Toronto, ON, Canada
- Rotman Research Institute, North York, ON, Canada
| | - Rosanna K Olsen
- University of Toronto, Toronto, ON, Canada
- Rotman Research Institute, North York, ON, Canada
| | - Vyash Puliyadi
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Tammy T Tran
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Arnold Bakker
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Kelsey L Canada
- 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
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco USA
| | - Lei Wang
- The Ohio State University, Columbus, OH, USA
| | - Madigan Bedard
- Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Eunice Chung
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | - Edward B Lee
- University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Lim
- University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | | | | | - Alicia Vela
- University of Castilla-La Mancha, Albacete, Spain
| | | | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- C. & O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine-University, Düsseldorf, Germany
| | | | | | | | - Olga Kedo
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
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4
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Sadaghiani S, Trotman W, Lim SA, Chung E, Ittyerah R, Ravikumar S, Khandelwal P, Prabhakaran K, Lavery ML, Ohm DT, Gabrielyan M, Das SR, Schuck T, Capp N, Peterson CS, Migdal E, Artacho-Pérula E, del Mar Arroyo Jiménez M, del Pilar Marcos Rabal M, Sánchez SC, de la Rosa Prieto C, Parada MC, Insausti R, Robinson JL, McMillan C, Grossman M, Lee EB, Detre JA, Xie SX, Trojanowski JQ, Tisdall MD, Wisse LEM, Irwin DJ, Wolk DA, Yushkevich PA. Associations of phosphorylated tau pathology with whole-hemisphere ex vivo morphometry in 7 tesla MRI. Alzheimers Dement 2023; 19:2355-2364. [PMID: 36464907 PMCID: PMC10239526 DOI: 10.1002/alz.12884] [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: 05/16/2022] [Revised: 09/29/2022] [Accepted: 10/27/2022] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Neurodegenerative disorders are associated with different pathologies that often co-occur but cannot be measured specifically with in vivo methods. METHODS Thirty-three brain hemispheres from donors with an Alzheimer's disease (AD) spectrum diagnosis underwent T2-weighted magnetic resonance imaging (MRI). Gray matter thickness was paired with histopathology from the closest anatomic region in the contralateral hemisphere. RESULTS Partial Spearman correlation of phosphorylated tau and cortical thickness with TAR DNA-binding protein 43 (TDP-43) and α-synuclein scores, age, sex, and postmortem interval as covariates showed significant relationships in entorhinal and primary visual cortices, temporal pole, and insular and posterior cingulate gyri. Linear models including Braak stages, TDP-43 and α-synuclein scores, age, sex, and postmortem interval showed significant correlation between Braak stage and thickness in the parahippocampal gyrus, entorhinal cortex, and Broadman area 35. CONCLUSION We demonstrated an association of measures of AD pathology with tissue loss in several AD regions despite a limited range of pathology in these cases. HIGHLIGHTS Neurodegenerative disorders are associated with co-occurring pathologies that cannot be measured specifically with in vivo methods. Identification of the topographic patterns of these pathologies in structural magnetic resonance imaging (MRI) may provide probabilistic biomarkers. We demonstrated the correlation of the specific patterns of tissue loss from ex vivo brain MRI with underlying pathologies detected in postmortem brain hemispheres in patients with Alzheimer's disease (AD) spectrum disorders. The results provide insight into the interpretation of in vivo structural MRI studies in patients with AD spectrum disorders.
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Affiliation(s)
- Shokufeh Sadaghiani
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Winifred Trotman
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sydney A Lim
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Eunice Chung
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ranjit Ittyerah
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sadhana Ravikumar
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Pulkit Khandelwal
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Karthik Prabhakaran
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Madigan L Lavery
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel T Ohm
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marianna Gabrielyan
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sandhitsu R. Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theresa Schuck
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Noah Capp
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Claire S Peterson
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Elyse Migdal
- College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Emilio Artacho-Pérula
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | | | | | - Sandra Cebada Sánchez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | - Carlos de la Rosa Prieto
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | - Marta Córcoles Parada
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | - John L Robinson
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Corey McMillan
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - John A. Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sharon X. Xie
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - M Dylan Tisdall
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Laura EM Wisse
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Diagnostic Radiology, Lund University, 22242 Lund, Sweden
| | - David J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Paul A. Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
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5
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Oltmer J, Slepneva N, Llamas Rodriguez J, Greve DN, Williams EM, Wang R, Champion SN, Lang-Orsini M, Nestor K, Fernandez-Ros N, Fischl B, Frosch MP, Magnain C, van der Kouwe AJW, Augustinack JC. Quantitative and histologically validated measures of the entorhinal subfields in ex vivo MRI. Brain Commun 2022; 4:fcac074. [PMID: 35620167 PMCID: PMC9128374 DOI: 10.1093/braincomms/fcac074] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 01/04/2022] [Accepted: 03/17/2022] [Indexed: 12/15/2022] Open
Abstract
Neuroimaging studies have routinely used hippocampal volume as a measure of Alzheimer's disease severity, but hippocampal changes occur too late in the disease process for potential therapies to be effective. The entorhinal cortex is one of the first cortical areas affected by Alzheimer's disease; its neurons are especially vulnerable to neurofibrillary tangles. Entorhinal atrophy also relates to the conversion from non-clinical to clinical Alzheimer's disease. In neuroimaging, the human entorhinal cortex has so far mostly been considered in its entirety or divided into a medial and a lateral region. Cytoarchitectonic differences provide the opportunity for subfield parcellation. We investigated the entorhinal cortex on a subfield-specific level-at a critical time point of Alzheimer's disease progression. While MRI allows multidimensional quantitative measurements, only histology provides enough accuracy to determine subfield boundaries-the pre-requisite for quantitative measurements within the entorhinal cortex. This study used histological data to validate ultra-high-resolution 7 Tesla ex vivo MRI and create entorhinal subfield parcellations in a total of 10 pre-clinical Alzheimer's disease and normal control cases. Using ex vivo MRI, eight entorhinal subfields (olfactory, rostral, medial intermediate, intermediate, lateral rostral, lateral caudal, caudal, and caudal limiting) were characterized for cortical thickness, volume, and pial surface area. Our data indicated no influence of sex, or Braak and Braak staging on volume, cortical thickness, or pial surface area. The volume and pial surface area for mean whole entorhinal cortex were 1131 ± 55.72 mm3 and 429 ± 22.6 mm2 (mean ± SEM), respectively. The subfield volume percentages relative to the entire entorhinal cortex were olfactory: 18.73 ± 1.82%, rostral: 14.06 ± 0.63%, lateral rostral: 14.81 ± 1.22%, medial intermediate: 6.72 ± 0.72%, intermediate: 23.36 ± 1.85%, lateral caudal: 5.42 ± 0.33%, caudal: 10.99 ± 1.02%, and caudal limiting: 5.91 ± 0.40% (all mean ± SEM). Olfactory and intermediate subfield revealed the most extensive intra-individual variability (cross-subject variance) in volume and pial surface area. This study provides validated measures. It maps individuality and demonstrates human variability in the entorhinal cortex, providing a baseline for approaches in individualized medicine. Taken together, this study serves as a ground-truth validation study for future in vivo comparisons and treatments.
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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
| | - Natalya Slepneva
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Josue Llamas Rodriguez
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Douglas N. Greve
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA
| | - Emily M. Williams
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Ruopeng Wang
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Melanie Lang-Orsini
- Department of Neuropathology, Massachusetts General
Hospital, Boston, MA, USA
| | - Kimberly Nestor
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Nídia Fernandez-Ros
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA,CSAIL, Cambridge, MA, USA
| | - Matthew P. Frosch
- Department of Neuropathology, Massachusetts General
Hospital, Boston, MA, USA
| | - Caroline Magnain
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, Boston, MA,
USA
| | - Andre J. W. van der Kouwe
- Department of Radiology, Athinoula A. Martinos
Center, Massachusetts General Hospital, Charlestown, MA, USA,Harvard Medical School, 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,Correspondence to: Jean C. Augustinack Department of
Radiology Athinoula A. Martinos Center for Biomedical Imaging Massachusetts
General Hospital Building 149, 13th St Room 2301 Charlestown, MA 02129, USA
E-mail:
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6
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Boonstra JT, Michielse S, Roebroeck A, Temel Y, Jahanshahi A. Dedicated container for postmortem human brain ultra-high field magnetic resonance imaging. Neuroimage 2021; 235:118010. [PMID: 33819610 DOI: 10.1016/j.neuroimage.2021.118010] [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: 11/06/2020] [Revised: 03/14/2021] [Accepted: 03/23/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND The emerging field of ultra-high field MRI (UHF-MRI, 7 Tesla and higher) provides the opportunity to image human brains at a higher resolution and with higher signal-to-noise ratios compared to the more widely available 1.5 and 3T scanners. Scanning postmortem tissue additionally allows for greatly increased scan times and fewer movement issues leading to improvements in image quality. However, typical postmortem neuroimaging routines involve placing the tissue within plastic bags that leave room for susceptibility artifacts from tissue-air interfaces, inadequate submersion, and leakage issues. To address these challenges in postmortem imaging, a custom-built nonferromagnetic container was developed that allows whole brain hemispheres to be scanned at sub-millimeter resolution within typical head-coils. METHOD The custom-built polymethylmethacrylaat container consists of a cylinder with a hemispheric side and a lid with valves on the adjacent side. This shape fits within common MR head-coils and allows whole hemispheres to be submerged and vacuum sealed within it reducing imaging artifacts that would otherwise arise at air-tissue boundaries. Two hemisphere samples were scanned on a Siemens 9.4T Magnetom MRI scanner. High resolution T2* weighted data was obtained with a custom 3D gradient echo (GRE) sequence and diffusion-weighted imaging (DWI) scans were obtained with a 3D kT-dSTEAM sequence along 48 directions. RESULTS The custom-built container proved to submerge and contain tissue samples effectively and showed no interferences with MR scanning acquisition. The 3D GRE sequence provided high resolution isotropic T2* weighted data at 250 μm which showed a clear visualization of gray and white matter structures. DWI scans allowed for dense reconstruction of structural white matter connections via tractography. CONCLUSION Using this custom-built container worked towards achieving high quality MR images of postmortem brain material. This procedure can have advantages over traditional schemes including utilization of a standardized protocol and the reduced likelihood of leakage. This methodology could be adjusted and used to improve typical postmortem imaging routines.
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Affiliation(s)
- Jackson Tyler Boonstra
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands.
| | - Stijn Michielse
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, the Netherlands
| | - Yasin Temel
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands
| | - Ali Jahanshahi
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands
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7
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Lin YH, Dhanaraj V, Mackenzie AE, Young IM, Tanglay O, Briggs RG, Chakraborty AR, Hormovas J, Fonseka RD, Kim SJ, Yeung JT, Teo C, Sughrue ME. Anatomy and White Matter Connections of the Parahippocampal Gyrus. World Neurosurg 2021; 148:e218-e226. [PMID: 33412321 DOI: 10.1016/j.wneu.2020.12.136] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 12/23/2020] [Accepted: 12/24/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND The parahippocampal gyrus is understood to have a role in high cognitive functions including memory encoding and retrieval and visuospatial processing. A detailed understanding of the exact location and nature of associated white tracts could significantly improve postoperative morbidity related to declining capacity. Through diffusion tensor imaging-based fiber tracking validated by gross anatomic dissection as ground truth, we have characterized these connections based on relationships to other well-known structures. METHODS Diffusion imaging from the Human Connectome Project for 10 healthy adult controls was used for tractography analysis. We evaluated the parahippocampal gyrus as a whole based on connectivity with other regions. All parahippocampal gyrus tracts were mapped in both hemispheres, and a lateralization index was calculated with resultant tract volumes. RESULTS We identified 2 connections of the parahippocampal gyrus: inferior longitudinal fasciculus and cingulum. Lateralization of the cingulum was detected (P < 0.05). CONCLUSIONS The parahippocampal gyrus is an important center for memory processing. Subtle differences in executive functioning following surgery for limbic tumors may be better understood in the context of the fiber-bundle anatomy highlighted by this study.
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Affiliation(s)
- Yueh-Hsin Lin
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - Vukshitha Dhanaraj
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - Alana E Mackenzie
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | | | - Onur Tanglay
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Arpan R Chakraborty
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Jorge Hormovas
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - Sihyong J Kim
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - Jacky T Yeung
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery Prince of Wales Private Hospital, Sydney, Australia.
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8
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Edlow BL, Mareyam A, Horn A, Polimeni JR, Witzel T, Tisdall MD, Augustinack JC, Stockmann JP, Diamond BR, Stevens A, Tirrell LS, Folkerth RD, Wald LL, Fischl B, van der Kouwe A. 7 Tesla MRI of the ex vivo human brain at 100 micron resolution. Sci Data 2019; 6:244. [PMID: 31666530 PMCID: PMC6821740 DOI: 10.1038/s41597-019-0254-8] [Citation(s) in RCA: 146] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 09/23/2019] [Indexed: 12/15/2022] Open
Abstract
We present an ultra-high resolution MRI dataset of an ex vivo human brain specimen. The brain specimen was donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes. After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI scanner at 100 µm isotropic resolution using a custom-built 31-channel receive array coil. Single-echo multi-flip Fast Low-Angle SHot (FLASH) data were acquired over 100 hours of scan time (25 hours per flip angle), allowing derivation of synthesized FLASH volumes. This dataset provides an unprecedented view of the three-dimensional neuroanatomy of the human brain. To optimize the utility of this resource, we warped the dataset into standard stereotactic space. We now distribute the dataset in both native space and stereotactic space to the academic community via multiple platforms. We envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance understanding of human brain anatomy in health and disease.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Department of Neurology, Boston, MA, 02114, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA.
| | - Azma Mareyam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Andreas Horn
- Movement Disorders & Neuromodulation Section, Department for Neurology, Charité - University Medicine Berlin, Berlin, Germany
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Thomas Witzel
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - M Dylan Tisdall
- Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Jean C Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Jason P Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Bram R Diamond
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Allison Stevens
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Lee S Tirrell
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Rebecca D Folkerth
- City of New York Office of the Chief Medical Examiner, and New York University School of Medicine, New York, NY, 10016, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Charlestown, MA, 02129, USA
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9
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Vasung L, Charvet CJ, Shiohama T, Gagoski B, Levman J, Takahashi E. Ex vivo fetal brain MRI: Recent advances, challenges, and future directions. Neuroimage 2019; 195:23-37. [PMID: 30905833 PMCID: PMC6617515 DOI: 10.1016/j.neuroimage.2019.03.034] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Revised: 03/12/2019] [Accepted: 03/16/2019] [Indexed: 12/21/2022] Open
Abstract
During early development, the fetal brain undergoes dynamic morphological changes. These changes result from neurogenic events, such as neuronal proliferation, migration, axonal elongation, retraction, and myelination. The duration and intensity of these events vary across species. Comparative assessments of these neurogenic events give us insight into evolutionary changes and the complexity of human brain development. Recent advances in magnetic resonance imaging (MRI), especially ex vivo MRI, permit characterizing and comparing fetal brain development across species. Comparative ex vivo MRI studies support the detection of species-specific differences that occur during early brain development. In this review, we provide a comprehensive overview of ex vivo MRI studies that characterize early brain development in humans, monkeys, cats, as well as rats/mice. Finally, we discuss the current advantages and limitations of ex vivo fetal brain MRI.
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Affiliation(s)
- Lana Vasung
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 401 Park Dr., Boston, MA, 02215, USA
| | - Christine J Charvet
- Department of Molecular Biology and Genetics, Cornell University, 526 Campus Rd, Ithaca, NY, 14850, USA; Department of Psychology, Delaware State University, Dover, DE, 19901, USA
| | - Tadashi Shiohama
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 401 Park Dr., Boston, MA, 02215, USA; Department of Pediatrics, Chiba University Hospital, Inohana 1-8-1, Chiba-shi, Chiba, 2608670, Japan
| | - Borjan Gagoski
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, 401 Park Dr., Boston, MA, 02215, USA
| | - Jacob Levman
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 401 Park Dr., Boston, MA, 02215, USA; Department of Mathematics, Statistics and Computer Science, St. Francis Xavier University, Antigonish, NS, B2G 2W5, Canada
| | - Emi Takahashi
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, 401 Park Dr., Boston, MA, 02215, USA.
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10
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Bouyeure A, Germanaud D, Bekha D, Delattre V, Lefèvre J, Pinabiaux C, Mangin JF, Rivière D, Fischer C, Chiron C, Hertz-Pannier L, Noulhiane M. Three-Dimensional Probabilistic Maps of Mesial Temporal Lobe Structures in Children and Adolescents' Brains. Front Neuroanat 2018; 12:98. [PMID: 30498435 PMCID: PMC6249374 DOI: 10.3389/fnana.2018.00098] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 10/29/2018] [Indexed: 11/13/2022] Open
Abstract
The hippocampus and the adjacent perirhinal, entorhinal, temporopolar, and parahippocampal cortices are interconnected in a hierarchical MTL system crucial for memory processes. A probabilistic description of the anatomical location and spatial variability of MTL cortices in the child and adolescent brain would help to assess structure-function relationships. The rhinal sulcus (RS) and the collateral sulcus (CS) that border MTL cortices and influence their morphology have never been described in these populations. In this study, we identified the aforementioned structures on magnetic resonance images of 38 healthy subjects aged 7-17 years old. Relative to sulcal morphometry in the MTL, we showed RS-CS conformation is an additional factor of variability in the MTL that is not explained by other variables such as age, sex and brain volume; with an innovative method using permutation testing of the extrema of structures of interest, we showed that RS-SC conformation was not associated with differences of location of MTL sulci. Relative to probabilistic maps, we offered for the first time a systematic mapping of MTL structures in children and adolescent, mapping all the structures of the MTL system while taking sulcal morphology into account. Our results, with the probabilistic maps described here being freely available for download, will help to understand the anatomy of this region and help functional and clinical studies to accurately test structure-function hypotheses in the MTL during development. Free access to MTL pediatric atlas: http://neurovault.org/collections/2381/.
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Affiliation(s)
- Antoine Bouyeure
- INSERM, CEA, Université Paris Descartes, Sorbonne Paris Cité, Neurospin, UNIACT, UMR1129, Gif-sur-Yvette, France
| | - David Germanaud
- INSERM, CEA, Université Paris Descartes, Sorbonne Paris Cité, Neurospin, UNIACT, UMR1129, Gif-sur-Yvette, France
- Université Paris Diderot, Sorbonne Paris Cité, AP-HP, Hôpital Robert-Debré, DHU Protect, Service de Neurologie Pédiatrique et des Maladies Métaboliques, Paris, France
| | - Dhaif Bekha
- INSERM, CEA, Université Paris Descartes, Sorbonne Paris Cité, Neurospin, UNIACT, UMR1129, Gif-sur-Yvette, France
| | - Victor Delattre
- INSERM, CEA, Université Paris Descartes, Sorbonne Paris Cité, Neurospin, UNIACT, UMR1129, Gif-sur-Yvette, France
| | - Julien Lefèvre
- CNRS, ENSAM, LSIS UMR 7296, Aix Marseille University, Toulon University, Toulon, France
| | - Charlotte Pinabiaux
- Université Paris Ouest Nanterre La Défense, Laboratoire CHArt (EA 4004), Nanterre, France
| | | | - Denis Rivière
- CEA, University Paris Saclay, NeuroSpin, UNATI, Gif-sur-Yvette, France
| | - Clara Fischer
- CEA, University Paris Saclay, NeuroSpin, UNATI, Gif-sur-Yvette, France
| | - Catherine Chiron
- INSERM, CEA, Université Paris Descartes, Sorbonne Paris Cité, Neurospin, UNIACT, UMR1129, Gif-sur-Yvette, France
| | - Lucie Hertz-Pannier
- INSERM, CEA, Université Paris Descartes, Sorbonne Paris Cité, Neurospin, UNIACT, UMR1129, Gif-sur-Yvette, France
| | - Marion Noulhiane
- INSERM, CEA, Université Paris Descartes, Sorbonne Paris Cité, Neurospin, UNIACT, UMR1129, Gif-sur-Yvette, France
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11
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Kwan BY, Salehi F, Kope R, Lee DH, Sharma M, Hammond R, Burneo JG, Steven D, Peters T, Khan AR. Evaluation of ex-vivo 9.4T MRI in post-surgical specimens from temporal lobe epilepsy patients. J Neuroradiol 2017; 44:377-380. [DOI: 10.1016/j.neurad.2017.05.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 04/03/2017] [Accepted: 05/25/2017] [Indexed: 12/28/2022]
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12
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Matsuda KM, Lopes-Calcas A, Honke ML, O'Brien-Moran Z, Buist R, West M, Martin M. Ex vivo tissue imaging for radiology-pathology correlation: a pilot study with a small bore 7-T MRI in a rare pigmented ganglioglioma exhibiting complex MR signal characteristics associated with melanin and hemosiderin. J Med Imaging (Bellingham) 2017; 4:036001. [PMID: 28924575 PMCID: PMC5596201 DOI: 10.1117/1.jmi.4.3.036001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Accepted: 08/09/2017] [Indexed: 12/02/2022] Open
Abstract
To advance magnetic resonance imaging (MRI) technologies further for in vivo tissue characterization with histopathologic validation, we investigated the feasibility of ex vivo tissue imaging of a surgically removed human brain tumor as a comprehensive approach for radiology–pathology correlation in histoanatomically identical fashion in a rare case of pigmented ganglioglioma with complex paramagnetic properties. Pieces of surgically removed ganglioglioma, containing melanin and hemosiderin pigments, were imaged with a small bore 7-T MRI scanner to obtain T1-, T2-, and T2*-weighted image and diffusion tensor imaging (DTI). Corresponding histopathological slides were prepared for routine hematoxylin and eosin stain and special stains for melanin and iron/hemosiderin to correlate with MRI signal characteristics. Furthermore, mean diffusivity (MD) maps were generated from DTI data and correlated with cellularity using image analysis. While the presence of melanin was difficult to interpret in in vivo MRI with certainty due to concomitant hemosiderin pigments and calcium depositions, ex vivo tissue imaging clearly demonstrated pieces of tissue exhibiting the characteristic MR signal pattern for melanin with pathologic confirmation in a histoanatomically identical location. There was also concordant correlation between MD and cellularity. Although it is still in an initial phase of development, ex vivo tissue imaging is a promising approach, which offers radiology–pathology correlation in a straightforward and comprehensive manner.
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Affiliation(s)
- Kant M Matsuda
- University of Manitoba, Max Rady College of Medicine, Department of Pathology, Rady Faculty of Health Sciences, Winnipeg, Manitoba, Canada.,Health Sciences Centre Winnipeg, Department of Pathology, Diagnostic Services of Manitoba, Winnipeg, Manitoba, Canada.,Memorial Sloan-Kettering Cancer Center, Department of Pathology, New York, New York, United States
| | - Ana Lopes-Calcas
- University of Manitoba, Max Rady College of Medicine, Department of Pathology, Rady Faculty of Health Sciences, Winnipeg, Manitoba, Canada
| | - Michael L Honke
- University of Winnipeg, Department of Physics, Winnipeg, Manitoba, Canada
| | - Zoe O'Brien-Moran
- University of Winnipeg, Department of Physics, Winnipeg, Manitoba, Canada
| | - Richard Buist
- University of Manitoba, Max Rady College of Medicine, Department of Radiology, Rady Faculty of Health Sciences, Winnipeg, Manitoba, Canada
| | - Michael West
- University of Manitoba, Max Rady College of Medicine, Department of Neurosurgery, Rady Faculty of Health Sciences, Winnipeg, Manitoba, Canada
| | - Melanie Martin
- University of Winnipeg, Department of Physics, Winnipeg, Manitoba, Canada.,University of Manitoba, Max Rady College of Medicine, Department of Radiology, Rady Faculty of Health Sciences, Winnipeg, Manitoba, Canada
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13
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Sengupta S, Fritz FJ, Harms RL, Hildebrand S, Tse DHY, Poser BA, Goebel R, Roebroeck A. High resolution anatomical and quantitative MRI of the entire human occipital lobe ex vivo at 9.4T. Neuroimage 2017; 168:162-171. [PMID: 28336427 PMCID: PMC5862655 DOI: 10.1016/j.neuroimage.2017.03.039] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2016] [Revised: 03/17/2017] [Accepted: 03/19/2017] [Indexed: 11/06/2022] Open
Abstract
Several magnetic resonance imaging (MRI) contrasts are sensitive to myelin content in gray matter in vivo which has ignited ambitions of MRI-based in vivo cortical histology. Ultra-high field (UHF) MRI, at fields of 7 T and beyond, is crucial to provide the resolution and contrast needed to sample contrasts over the depth of the cortex and get closer to layer resolved imaging. Ex vivo MRI of human post mortem samples is an important stepping stone to investigate MRI contrast in the cortex, validate it against histology techniques applied in situ to the same tissue, and investigate the resolutions needed to translate ex vivo findings to in vivo UHF MRI. Here, we investigate key technology to extend such UHF studies to large human brain samples while maintaining high resolution, which allows investigation of the layered architecture of several cortical areas over their entire 3D extent and their complete borders where architecture changes. A 16 channel cylindrical phased array radiofrequency (RF) receive coil was constructed to image a large post mortem occipital lobe sample (~80×80×80 mm3) in a wide-bore 9.4 T human scanner with the aim of achieving high-resolution anatomical and quantitative MR images. Compared with a human head coil at 9.4 T, the maximum Signal-to-Noise ratio (SNR) was increased by a factor of about five in the peripheral cortex. Although the transmit profile with a circularly polarized transmit mode at 9.4 T is relatively inhomogeneous over the large sample, this challenge was successfully resolved with parallel transmit using the kT-points method. Using this setup, we achieved 60μm anatomical images for the entire occipital lobe showing increased spatial definition of cortical details compared to lower resolutions. In addition, we were able to achieve sufficient control over SNR, B0 and B1 homogeneity and multi-contrast sampling to perform quantitative T2* mapping over the same volume at 200 μm. Markov Chain Monte Carlo sampling provided maximum posterior estimates of quantitative T2* and their uncertainty, allowing delineation of the stria of Gennari over the entire length and width of the calcarine sulcus. We discuss how custom RF receive coil arrays built to specific large post mortem sample sizes can provide a platform for UHF cortical layer-specific quantitative MRI over large fields of view. Custom-built 16 channel 9.4 T RF-coil to image large post mortem samples at high resolution. Parallel transmit techniques allow homogenization of B1+ for 3D GRE imaging at UHF. 60 μm anatomical MRI of the entire human occipital lobe. 200 μm isotropic quantitative T2* mapping of the entire human occipital lobe. A platform for future UHF cortical layer specific qMRI over large FoVs.
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Affiliation(s)
- S Sengupta
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands.
| | - F J Fritz
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - R L Harms
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - S Hildebrand
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - D H Y Tse
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - B A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - R Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - A Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
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14
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Three-dimensional probability maps of the rhinal and the collateral sulci in the human brain. Brain Struct Funct 2016; 221:4235-4255. [DOI: 10.1007/s00429-016-1189-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2014] [Accepted: 01/12/2016] [Indexed: 10/21/2022]
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15
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Augustinack JC, van der Kouwe AJW. Postmortem imaging and neuropathologic correlations. HANDBOOK OF CLINICAL NEUROLOGY 2016; 136:1321-39. [PMID: 27430472 DOI: 10.1016/b978-0-444-53486-6.00069-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Postmortem imaging refers to scanning autopsy specimens using magnetic resonance imaging (MRI) or optical imaging. This chapter summarizes postmortem imaging and its usefulness in brain mapping. Standard in vivo MRI has limited resolution due to time constraints and does not deliver cortical boundaries (e.g., Brodmann areas). Postmortem imaging offers a means to obtain ultra-high-resolution images with appropriate contrast for delineating cortical regions. Postmortem imaging provides the ability to validate MRI properties against histologic stained sections. This approach has enabled probabilistic mapping that is based on ex vivo MRI contrast, validated to histology, and subsequently mapped on to an in vivo model. This chapter emphasizes structural imaging, which can be validated with histologic assessment. Postmortem imaging has been applied to neuropathologic studies as well. This chapter includes many ex vivo studies, but focuses on studies of the medial temporal lobe, often involved in neurologic disease. New research using optical imaging is also highlighted.
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Affiliation(s)
- Jean C Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA.
| | - André J W van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
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Ex vivo magnetic resonance imaging in South African manganese mine workers. Neurotoxicology 2015; 49:8-14. [PMID: 25912463 DOI: 10.1016/j.neuro.2015.04.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Revised: 03/14/2015] [Accepted: 04/13/2015] [Indexed: 11/22/2022]
Abstract
BACKGROUND Manganese (Mn) exposure is associated with increased T1-weighted magnetic resonance imaging (MRI) signal in the basal ganglia. T1 signal intensity has been correlated with occupational Mn exposure but not with clinical symptomatology or neuropathology. OBJECTIVES This study investigated predictors of ex vivo T1 MRI basal ganglia signal intensity in neuropathologic tissue obtained from deceased South African mine workers. METHODS A 3.0 T MRI was performed on ex vivo brain tissue obtained from 19 Mn mine workers and 10 race- and sex-matched mine workers of other commodities. Basal ganglia regions of interest were identified for each subject with T1-weighted intensity indices generated for each region. In a pathology subset, regional T1 indices were compared to neuronal and glial cell density and tissue metal concentrations. RESULTS Intensity indices were higher in Mn mine workers than non-Mn mine workers for the globus pallidus, caudate, anterior putamen, and posterior putamen with the highest values in subjects with the longest cumulative Mn exposure. Intensity indices were inversely correlated with the neuronal cell density in the caudate (p=0.040) and putamen (p=0.050). Tissue Mn concentrations were similar in Mn and non-Mn mine workers. Tissue iron (Fe) concentration trended lower across all regions in Mn mine workers. CONCLUSIONS Mn mine workers demonstrated elevated basal ganglia T1 indices when compared to non-Mn mine workers. Predictors of ex vivo T1 MRI signal intensity in Mn mine workers include duration of Mn exposure and neuronal density.
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Raslau FD, Mark IT, Klein AP, Ulmer JL, Mathews V, Mark LP. Memory part 2: the role of the medial temporal lobe. AJNR Am J Neuroradiol 2014; 36:846-9. [PMID: 25414002 DOI: 10.3174/ajnr.a4169] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- F D Raslau
- From the Department of Radiology (F.D.R.), University of Kentucky, Lexington, Kentucky
| | - I T Mark
- Morsani College of Medicine (I.T.M.), University of South Florida, Tampa, Florida
| | - A P Klein
- Department of Radiology (A.P.K., J.L.U., V.M., L.P.M.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - J L Ulmer
- Department of Radiology (A.P.K., J.L.U., V.M., L.P.M.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - V Mathews
- Department of Radiology (A.P.K., J.L.U., V.M., L.P.M.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - L P Mark
- Department of Radiology (A.P.K., J.L.U., V.M., L.P.M.), Medical College of Wisconsin, Milwaukee, Wisconsin.
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McMillan CT, Avants BB, Cook P, Ungar L, Trojanowski JQ, Grossman M. The power of neuroimaging biomarkers for screening frontotemporal dementia. Hum Brain Mapp 2014; 35:4827-40. [PMID: 24687814 DOI: 10.1002/hbm.22515] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2014] [Accepted: 03/17/2014] [Indexed: 11/09/2022] Open
Abstract
Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative disease that can result from either frontotemporal lobar degeneration (FTLD) or Alzheimer's disease (AD) pathology. It is critical to establish statistically powerful biomarkers that can achieve substantial cost-savings and increase the feasibility of clinical trials. We assessed three broad categories of neuroimaging methods to screen underlying FTLD and AD pathology in a clinical FTD series: global measures (e.g., ventricular volume), anatomical volumes of interest (VOIs) (e.g., hippocampus) using a standard atlas, and data-driven VOIs using Eigenanatomy. We evaluated clinical FTD patients (N = 93) with cerebrospinal fluid, gray matter (GM) magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI) to assess whether they had underlying FTLD or AD pathology. Linear regression was performed to identify the optimal VOIs for each method in a training dataset and then we evaluated classification sensitivity and specificity in an independent test cohort. Power was evaluated by calculating minimum sample sizes required in the test classification analyses for each model. The data-driven VOI analysis using a multimodal combination of GM MRI and DTI achieved the greatest classification accuracy (89% sensitive and 89% specific) and required a lower minimum sample size (N = 26) relative to anatomical VOI and global measures. We conclude that a data-driven VOI approach using Eigenanatomy provides more accurate classification, benefits from increased statistical power in unseen datasets, and therefore provides a robust method for screening underlying pathology in FTD patients for entry into clinical trials.
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Affiliation(s)
- Corey T McMillan
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
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Abstract
The past 25 years have seen great progress in parcellating the cerebral cortex into a mosaic of many distinct areas in mice, monkeys, and humans. Quantitative studies of interareal connectivity have revealed unexpectedly many pathways and a wide range of connection strengths in mouse and macaque cortex. In humans, advances in analyzing "structural" and "functional" connectivity using powerful but indirect noninvasive neuroimaging methods are yielding intriguing insights about brain circuits, their variability across individuals, and their relationship to behavior.
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Affiliation(s)
- David C Van Essen
- Anatomy and Neurobiology Department, Washington University in St. Louis, St. Louis, MO 63110, USA.
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