1
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Cheng S, Chang S, Li Y, Novoseltseva A, Lin S, Wu Y, Zhu J, McKee AC, Rosene DL, Wang H, Bigio IJ, Boas DA, Tian L. Enhanced Multiscale Human Brain Imaging by Semi-supervised Digital Staining and Serial Sectioning Optical Coherence Tomography. RESEARCH SQUARE 2024:rs.3.rs-4014687. [PMID: 38562721 PMCID: PMC10984089 DOI: 10.21203/rs.3.rs-4014687/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
A major challenge in neuroscience is to visualize the structure of the human brain at different scales. Traditional histology reveals micro- and meso-scale brain features, but suffers from staining variability, tissue damage and distortion that impedes accurate 3D reconstructions. Here, we present a new 3D imaging framework that combines serial sectioning optical coherence tomography (S-OCT) with a deep-learning digital staining (DS) model. We develop a novel semi-supervised learning technique to facilitate DS model training on weakly paired images. The DS model performs translation from S-OCT to Gallyas silver staining. We demonstrate DS on various human cerebral cortex samples with consistent staining quality. Additionally, we show that DS enhances contrast across cortical layer boundaries. Furthermore, we showcase geometry-preserving 3D DS on cubic-centimeter tissue blocks and visualization of meso-scale vessel networks in the white matter. We believe that our technique offers the potential for high-throughput, multiscale imaging of brain tissues and may facilitate studies of brain structures.
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Affiliation(s)
- Shiyi Cheng
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA, 02215, USA
| | - Shuaibin Chang
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA, 02215, USA
| | - Yunzhe Li
- Department of Electrical Engineering and Computer Sciences, University of California, Cory Hall, Berkeley, California, 94720, USA
| | - Anna Novoseltseva
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA
| | - Sunni Lin
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA
| | - Yicun Wu
- Department of Computer Science, Boston University, 665 Commonwealth Ave, Boston, MA, 02215, USA
| | - Jiahui Zhu
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA, 02215, USA
| | - Ann C. McKee
- Boston University Alzheimer’s Disease Research Center and CTE Center, Boston University, Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Neurology, Boston University, Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Jamaica Plain, MA, 02130, USA
- Department of Psychiatry and Ophthalmology, Boston University School of Medicine, Boston, MA, 02118, USA
- Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Douglas L. Rosene
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts, USA
| | - Hui Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, 02129, USA
| | - Irving J. Bigio
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA
- Neurophotonics Center, Boston University, Boston, MA, 02215, USA
| | - David A. Boas
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA
- Neurophotonics Center, Boston University, Boston, MA, 02215, USA
| | - Lei Tian
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA, 02215, USA
- Neurophotonics Center, Boston University, Boston, MA, 02215, USA
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2
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Chang S, Yang J, Novoseltseva A, Abdelhakeem A, Hyman M, Fu X, Li C, Chen S, Augustinack JC, Magnain C, Fischl B, Mckee AC, Boas DA, Chen IA, Wang H. Multi-Scale Label-Free Human Brain Imaging with Integrated Serial Sectioning Polarization Sensitive Optical Coherence Tomography and Two-Photon Microscopy. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2303381. [PMID: 37882348 PMCID: PMC10724383 DOI: 10.1002/advs.202303381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 08/29/2023] [Indexed: 10/27/2023]
Abstract
The study of aging and neurodegenerative processes in the human brain requires a comprehensive understanding of cytoarchitectonic, myeloarchitectonic, and vascular structures. Recent computational advances have enabled volumetric reconstruction of the human brain using thousands of stained slices, however, tissue distortions and loss resulting from standard histological processing have hindered deformation-free reconstruction. Here, the authors describe an integrated serial sectioning polarization-sensitive optical coherence tomography (PSOCT) and two photon microscopy (2PM) system to provide label-free multi-contrast imaging of intact brain structures, including scattering, birefringence, and autofluorescence of human brain tissue. The authors demonstrate high-throughput reconstruction of 4 × 4 × 2cm3 sample blocks and simple registration between PSOCT and 2PM images that enable comprehensive analysis of myelin content, vascular structure, and cellular information. The high-resolution 2PM images provide microscopic validation and enrichment of the cellular information provided by the PSOCT optical properties on the same sample, revealing the densely packed fibers, capillaries, and lipofuscin-filled cell bodies in the cortex and white matter. It is shown that the imaging system enables quantitative characterization of various pathological features in aging process, including myelin degradation, lipofuscin accumulation, and microvascular changes, which opens up numerous opportunities in the study of neurodegenerative diseases in the future.
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Affiliation(s)
- Shuaibin Chang
- Department of Electrical and Computer EngineeringBoston University8 St Mary's StBoston02215USA
| | - Jiarui Yang
- Department of Biomedical EngineeringBoston University44 Cummington MallBoston02215USA
| | - Anna Novoseltseva
- Department of Biomedical EngineeringBoston University44 Cummington MallBoston02215USA
| | - Ayman Abdelhakeem
- Department of Electrical and Computer EngineeringBoston University8 St Mary's StBoston02215USA
| | - Mackenzie Hyman
- Department of Biomedical EngineeringBoston University44 Cummington MallBoston02215USA
| | - Xinlei Fu
- Department of Mechanical EngineeringThe Chinese University of Hong KongHong Kong999077China
| | - Chenglin Li
- Department of Mechanical EngineeringThe Chinese University of Hong KongHong Kong999077China
| | - Shih‐Chi Chen
- Department of Mechanical EngineeringThe Chinese University of Hong KongHong Kong999077China
| | - Jean C. Augustinack
- Department of RadiologyMassachusetts General HospitalA.A. Martinos Center for Biomedical Imaging13th StreetBoston02129USA
| | - Caroline Magnain
- Department of RadiologyMassachusetts General HospitalA.A. Martinos Center for Biomedical Imaging13th StreetBoston02129USA
| | - Bruce Fischl
- Department of RadiologyMassachusetts General HospitalA.A. Martinos Center for Biomedical Imaging13th StreetBoston02129USA
| | - Ann C. Mckee
- VA Boston Healthcare SystemU.S. Department of Veteran AffairsBoston02132USA
- Boston University Chobanian and Avedisian School of MedicineBoston University Alzheimer's Disease Research Center and CTE CenterBoston02118USA
- Department of NeurologyBoston University Chobanian and Avedisian School of MedicineBoston02118USA
- Department of Pathology and Laboratory MedicineBoston University Chobanian and Avedisian School of MedicineBoston02118USA
- VA Bedford Healthcare SystemU.S. Department of Veteran AffairsBedfordMA01730‐1114USA
| | - David A. Boas
- Department of Electrical and Computer EngineeringBoston University8 St Mary's StBoston02215USA
- Department of Biomedical EngineeringBoston University44 Cummington MallBoston02215USA
| | - Ichun Anderson Chen
- Department of Biomedical EngineeringBoston University44 Cummington MallBoston02215USA
| | - Hui Wang
- Department of RadiologyMassachusetts General HospitalA.A. Martinos Center for Biomedical Imaging13th StreetBoston02129USA
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3
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Chang S, Yang J, Novoseltseva A, Fu X, Li C, Chen SC, Augustinack JC, Magnain C, Fischl B, Mckee AC, Boas DA, Chen IA, Wang H. Multi-Scale Label-free Human Brain Imaging with Integrated Serial Sectioning Polarization Sensitive Optical Coherence Tomography and Two-Photon Microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.22.541785. [PMID: 37293092 PMCID: PMC10245911 DOI: 10.1101/2023.05.22.541785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The study of neurodegenerative processes in the human brain requires a comprehensive understanding of cytoarchitectonic, myeloarchitectonic, and vascular structures. Recent computational advances have enabled volumetric reconstruction of the human brain using thousands of stained slices, however, tissue distortions and loss resulting from standard histological processing have hindered deformation-free reconstruction of the human brain. The development of a multi-scale and volumetric human brain imaging technique that can measure intact brain structure would be a major technical advance. Here, we describe the development of integrated serial sectioning Polarization Sensitive Optical Coherence Tomography (PSOCT) and Two Photon Microscopy (2PM) to provide label-free multi-contrast imaging, including scattering, birefringence and autofluorescence of human brain tissue. We demonstrate that high-throughput reconstruction of 4×4×2cm3 sample blocks and simple registration of PSOCT and 2PM images enable comprehensive analysis of myelin content, vascular structure, and cellular information. We show that 2μm in-plane resolution 2PM images provide microscopic validation and enrichment of the cellular information provided by the PSOCT optical property maps on the same sample, revealing the sophisticated capillary networks and lipofuscin filled cell bodies across the cortical layers. Our method is applicable to the study of a variety of pathological processes, including demyelination, cell loss, and microvascular changes in neurodegenerative diseases such as Alzheimer's disease (AD) and Chronic Traumatic Encephalopathy (CTE).
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Affiliation(s)
- Shuaibin Chang
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston 02215, USA
| | - Jiarui Yang
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston 02215, USA
| | - Anna Novoseltseva
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston 02215, USA
| | - Xinlei Fu
- The Chinese University of Hong Kong, Department of Mechanical Engineering, Hong Kong Special Administrative Region, China
| | - Chenglin Li
- The Chinese University of Hong Kong, Department of Mechanical Engineering, Hong Kong Special Administrative Region, China
| | - Shih-Chi Chen
- The Chinese University of Hong Kong, Department of Mechanical Engineering, Hong Kong Special Administrative Region, China
| | - Jean C. Augustinack
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston 02129, USA
| | - Caroline Magnain
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston 02129, USA
| | - Bruce Fischl
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston 02129, USA
| | - Ann C. Mckee
- VA Boston Healthcare System, U.S. Department of Veteran Affairs
- Boston University Chobanian and Avedisian School of Medicine, Boston University Alzheimer’s Disease Research Center and CTE Center
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine
- Department of Pathology and Laboratory Medicine, Boston University Chobanian and Avedisian School of Medicine
- VA Bedford Healthcare System, U.S. Department of Veteran Affairs, Bedford, MA, USA
| | - David A. Boas
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston 02215, USA
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston 02215, USA
| | - Ichun Anderson Chen
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston 02215, USA
| | - Hui Wang
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston 02129, USA
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Menzel M, Gräßel D, Rajkovic I, Zeineh MM, Georgiadis M. Using light and X-ray scattering to untangle complex neuronal orientations and validate diffusion MRI. eLife 2023; 12:e84024. [PMID: 37166005 PMCID: PMC10259419 DOI: 10.7554/elife.84024] [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: 10/07/2022] [Accepted: 05/02/2023] [Indexed: 05/12/2023] Open
Abstract
Disentangling human brain connectivity requires an accurate description of nerve fiber trajectories, unveiled via detailed mapping of axonal orientations. However, this is challenging because axons can cross one another on a micrometer scale. Diffusion magnetic resonance imaging (dMRI) can be used to infer axonal connectivity because it is sensitive to axonal alignment, but it has limited spatial resolution and specificity. Scattered light imaging (SLI) and small-angle X-ray scattering (SAXS) reveal axonal orientations with microscopic resolution and high specificity, respectively. Here, we apply both scattering techniques on the same samples and cross-validate them, laying the groundwork for ground-truth axonal orientation imaging and validating dMRI. We evaluate brain regions that include unidirectional and crossing fibers in human and vervet monkey brain sections. SLI and SAXS quantitatively agree regarding in-plane fiber orientations including crossings, while dMRI agrees in the majority of voxels with small discrepancies. We further use SAXS and dMRI to confirm theoretical predictions regarding SLI determination of through-plane fiber orientations. Scattered light and X-ray imaging can provide quantitative micrometer 3D fiber orientations with high resolution and specificity, facilitating detailed investigations of complex fiber architecture in the animal and human brain.
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Affiliation(s)
- Miriam Menzel
- Department of Imaging Physics, Faculty of Applied Sciences, Delft University of TechnologyDelftNetherlands
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbHJülichGermany
| | - David Gräßel
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbHJülichGermany
| | - Ivan Rajkovic
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator LaboratoryStandfordUnited States
| | - Michael M Zeineh
- Department of Radiology, Stanford School of MedicineStanfordUnited States
| | - Marios Georgiadis
- Department of Radiology, Stanford School of MedicineStanfordUnited States
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5
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Smirnov M, Maldonado IL, Destrieux C. Using ex vivo arterial injection and dissection to assess white matter vascularization. Sci Rep 2023; 13:809. [PMID: 36646713 PMCID: PMC9842749 DOI: 10.1038/s41598-022-26227-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 12/12/2022] [Indexed: 01/18/2023] Open
Abstract
Advances in the techniques for assessing human cerebral white matter have recently contributed to greater attention to structural connectivity. Yet, little is known about the vascularization of most white matter fasciculi and the fascicular composition of the vascular territories. This paper presents an original method to label the arterial supply of macroscopic white matter fasciculi based on a standardized protocol for post-mortem injection of colored material into main cerebral arteries combined with a novel fiber dissection technique. Twelve whole human cerebral hemispheres obtained post-mortem were included. A detailed description of every step, from obtaining the specimen to image acquisition of its dissection, is provided. Injection and dissection were reproducible and manageable without any sophisticated equipment. They successfully showed the arterial supply of the dissected fasciculi. In addition, we discuss the challenges we faced and overcame during the development of the presented method, highlight its originality. Henceforth, this innovative method serves as a tool to provide a precise anatomical description of the vascularization of the main white matter tracts.
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Affiliation(s)
- Mykyta Smirnov
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.
| | - Igor Lima Maldonado
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France
- CHRU de Tours, Tours, France
| | - Christophe Destrieux
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France
- CHRU de Tours, Tours, France
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6
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Wang H, Gong D, Augustinack JC, Magnain C. Quantitative optical coherence microscopy of neuron morphology in human entorhinal cortex. Front Neurosci 2023; 17:1074660. [PMID: 37152599 PMCID: PMC10160389 DOI: 10.3389/fnins.2023.1074660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 03/06/2023] [Indexed: 05/09/2023] Open
Abstract
Introduction The size and shape of neurons are important features indicating aging and the pathology of neurodegenerative diseases. Despite the significant advances of optical microscopy, quantitative analysis of the neuronal features in the human brain remains largely incomplete. Traditional histology on thin slices bears tremendous distortions in three-dimensional reconstruction, the magnitude of which are often greater than the structure of interest. Recently development of tissue clearing techniques enable the whole brain to be analyzed in small animals; however, the application in the human remains challenging. Methods In this study, we present a label-free quantitative optical coherence microscopy (OCM) technique to obtain the morphological parameters of neurons in human entorhinal cortex (EC). OCM uses the intrinsic back-scattering property of tissue to identify individual neurons in 3D. The area, length, width, and orientation of individual neurons are quantified and compared between layer II and III in EC. Results The high-resolution mapping of neuron size, shape, and orientation shows significant differences between layer II and III neurons in EC. The results are validated by standard Nissl staining of the same samples. Discussion The quantitative OCM technique in our study offers a new solution to analyze variety of neurons and their organizations in the human brain, which opens new insights in advancing our understanding of neurodegenerative diseases.
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7
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Yang J, Chang S, Chen IA, Kura S, Rosen GA, Saltiel NA, Huber BR, Varadarajan D, Balbastre Y, Magnain C, Chen SC, Fischl B, McKee AC, Boas DA, Wang H. Volumetric Characterization of Microvasculature in Ex Vivo Human Brain Samples By Serial Sectioning Optical Coherence Tomography. IEEE Trans Biomed Eng 2022; 69:3645-3656. [PMID: 35560084 PMCID: PMC9888394 DOI: 10.1109/tbme.2022.3175072] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Serial sectioning optical coherence tomography (OCT) enables accurate volumetric reconstruction of several cubic centimeters of human brain samples. We aimed to identify anatomical features of the ex vivo human brain, such as intraparenchymal blood vessels and axonal fiber bundles, from the OCT data in 3D, using intrinsic optical contrast. METHODS We developed an automatic processing pipeline to enable characterization of the intraparenchymal microvascular network in human brain samples. RESULTS We demonstrated the automatic extraction of the vessels down to a 20 μm in diameter using a filtering strategy followed by a graphing representation and characterization of the geometrical properties of microvascular network in 3D. We also showed the ability to extend this processing strategy to extract axonal fiber bundles from the volumetric OCT image. CONCLUSION This method provides a viable tool for quantitative characterization of volumetric microvascular network as well as the axonal bundle properties in normal and pathological tissues of the ex vivo human brain.
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8
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Varadarajan D, Magnain C, Fogarty M, Boas DA, Fischl B, Wang H. A novel algorithm for multiplicative speckle noise reduction in ex vivo human brain OCT images. Neuroimage 2022; 257:119304. [PMID: 35568350 PMCID: PMC10018743 DOI: 10.1016/j.neuroimage.2022.119304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 05/06/2022] [Accepted: 05/10/2022] [Indexed: 10/18/2022] Open
Abstract
Optical coherence tomography (OCT) images of ex vivo human brain tissue are corrupted by multiplicative speckle noise that degrades the contrast to noise ratio (CNR) of microstructural compartments. This work proposes a novel algorithm to reduce noise corruption in OCT images that minimizes the penalized negative log likelihood of gamma distributed speckle noise. The proposed method is formulated as a majorize-minimize problem that reduces to solving an iterative regularized least squares optimization. We demonstrate the usefulness of the proposed method by removing speckle in simulated data, phantom data and real OCT images of human brain tissue. We compare the proposed method with state of the art filtering and non-local means based denoising methods. We demonstrate that our approach removes speckle accurately, improves CNR between different tissue types and better preserves small features and edges in human brain tissue.
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Affiliation(s)
- Divya Varadarajan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Radiology, Harvard Medical School, Boston, MA 02115, USA.
| | - Caroline Magnain
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Radiology, Harvard Medical School, Boston, MA 02115, USA
| | - Morgan Fogarty
- Imaging Science Program, Washington University McKelvey School of Engineering, St. Louis, MO 63130, USA; Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - David A Boas
- Biomedical Engineering and Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Radiology, Harvard Medical School, Boston, MA 02115, USA; Harvard-MIT Health Science and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Hui Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Radiology, Harvard Medical School, Boston, MA 02115, USA
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9
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Yendiki A, Aggarwal M, Axer M, Howard AF, van Cappellen van Walsum AM, Haber SN. Post mortem mapping of connectional anatomy for the validation of diffusion MRI. Neuroimage 2022; 256:119146. [PMID: 35346838 PMCID: PMC9832921 DOI: 10.1016/j.neuroimage.2022.119146] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 01/13/2023] Open
Abstract
Diffusion MRI (dMRI) is a unique tool for the study of brain circuitry, as it allows us to image both the macroscopic trajectories and the microstructural properties of axon bundles in vivo. The Human Connectome Project ushered in an era of impressive advances in dMRI acquisition and analysis. As a result of these efforts, the quality of dMRI data that could be acquired in vivo improved substantially, and large collections of such data became widely available. Despite this progress, the main limitation of dMRI remains: it does not image axons directly, but only provides indirect measurements based on the diffusion of water molecules. Thus, it must be validated by methods that allow direct visualization of axons but that can only be performed in post mortem brain tissue. In this review, we discuss methods for validating the various features of connectional anatomy that are extracted from dMRI, both at the macro-scale (trajectories of axon bundles), and at micro-scale (axonal orientations and other microstructural properties). We present a range of validation tools, including anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.
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Affiliation(s)
- Anastasia Yendiki
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States,Corresponding author (A. Yendiki)
| | - Manisha Aggarwal
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Markus Axer
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich, Germany,Department of Physics, University of Wuppertal Germany
| | - Amy F.D. Howard
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Anne-Marie van Cappellen van Walsum
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Nijmegen, the Netherland,Cognition and Behaviour, Donders Institute for Brain, Nijmegen, the Netherland
| | - Suzanne N. Haber
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States,McLean Hospital, Belmont, MA, United States
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10
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Lautman Z, Winetraub Y, Blacher E, Yu C, Terem I, Chibukhchyan A, Marshel JH, de la Zerda A. Intravital 3D visualization and segmentation of murine neural networks at micron resolution. Sci Rep 2022; 12:13130. [PMID: 35907928 PMCID: PMC9338956 DOI: 10.1038/s41598-022-14450-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 06/06/2022] [Indexed: 12/03/2022] Open
Abstract
Optical coherence tomography (OCT) allows label-free, micron-scale 3D imaging of biological tissues' fine structures with significant depth and large field-of-view. Here we introduce a novel OCT-based neuroimaging setting, accompanied by a feature segmentation algorithm, which enables rapid, accurate, and high-resolution in vivo imaging of 700 μm depth across the mouse cortex. Using a commercial OCT device, we demonstrate 3D reconstruction of microarchitectural elements through a cortical column. Our system is sensitive to structural and cellular changes at micron-scale resolution in vivo, such as those from injury or disease. Therefore, it can serve as a tool to visualize and quantify spatiotemporal brain elasticity patterns. This highly transformative and versatile platform allows accurate investigation of brain cellular architectural changes by quantifying features such as brain cell bodies' density, volume, and average distance to the nearest cell. Hence, it may assist in longitudinal studies of microstructural tissue alteration in aging, injury, or disease in a living rodent brain.
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Affiliation(s)
- Ziv Lautman
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
- Molecular Imaging Program at Stanford, Stanford, CA, 94305, USA
| | - Yonatan Winetraub
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Molecular Imaging Program at Stanford, Stanford, CA, 94305, USA
- Biophysics Program at Stanford, Stanford, CA, 94305, USA
- The Bio-X Program, Stanford, CA, 94305, USA
| | - Eran Blacher
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA, 94305, USA
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Edmond J. Safra Campus Givat-Ram, 9190401, Jerusalem, Israel
| | - Caroline Yu
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Molecular Imaging Program at Stanford, Stanford, CA, 94305, USA
| | - Itamar Terem
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Molecular Imaging Program at Stanford, Stanford, CA, 94305, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA
| | | | - James H Marshel
- CNC Department, Stanford University, Stanford, CA, 94305, USA
| | - Adam de la Zerda
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Molecular Imaging Program at Stanford, Stanford, CA, 94305, USA.
- Biophysics Program at Stanford, Stanford, CA, 94305, USA.
- The Bio-X Program, Stanford, CA, 94305, USA.
- Department of Electrical Engineering, Stanford University, Stanford, CA, 94305, USA.
- The Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
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11
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Automated computation of nerve fibre inclinations from 3D polarised light imaging measurements of brain tissue. Sci Rep 2022; 12:4328. [PMID: 35288611 PMCID: PMC8921329 DOI: 10.1038/s41598-022-08140-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 03/01/2022] [Indexed: 02/06/2023] Open
Abstract
The method 3D polarised light imaging (3D-PLI) measures the birefringence of histological brain sections to determine the spatial course of nerve fibres (myelinated axons). While the in-plane fibre directions can be determined with high accuracy, the computation of the out-of-plane fibre inclinations is more challenging because they are derived from the amplitude of the birefringence signals, which depends e.g. on the amount of nerve fibres. One possibility to improve the accuracy is to consider the average transmitted light intensity (transmittance weighting). The current procedure requires effortful manual adjustment of parameters and anatomical knowledge. Here, we introduce an automated, optimised computation of the fibre inclinations, allowing for a much faster, reproducible determination of fibre orientations in 3D-PLI. Depending on the degree of myelination, the algorithm uses different models (transmittance-weighted, unweighted, or a linear combination), allowing to account for regionally specific behaviour. As the algorithm is parallelised and GPU optimised, it can be applied to large data sets. Moreover, it only uses images from standard 3D-PLI measurements without tilting, and can therefore be applied to existing data sets from previous measurements. The functionality is demonstrated on unstained coronal and sagittal histological sections of vervet monkey and rat brains.
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12
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Chang S, Varadarajan D, Yang J, Chen IA, Kura S, Magnain C, Augustinack JC, Fischl B, Greve DN, Boas DA, Wang H. Scalable mapping of myelin and neuron density in the human brain with micrometer resolution. Sci Rep 2022; 12:363. [PMID: 35013441 PMCID: PMC8748995 DOI: 10.1038/s41598-021-04093-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/03/2021] [Indexed: 12/23/2022] Open
Abstract
Optical coherence tomography (OCT) is an emerging 3D imaging technique that allows quantification of intrinsic optical properties such as scattering coefficient and back-scattering coefficient, and has proved useful in distinguishing delicate microstructures in the human brain. The origins of scattering in brain tissues are contributed by the myelin content, neuron size and density primarily; however, no quantitative relationships between them have been reported, which hampers the use of OCT in fundamental studies of architectonic areas in the human brain and the pathological evaluations of diseases. Here, we built a generalized linear model based on Mie scattering theory that quantitatively links tissue scattering to myelin content and neuron density in the human brain. We report a strong linear relationship between scattering coefficient and the myelin content that is retained across different regions of the brain. Neuronal cell body turns out to be a secondary contribution to the overall scattering. The optical property of OCT provides a label-free solution for quantifying volumetric myelin content and neuron cells in the human brain.
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Affiliation(s)
- Shuaibin Chang
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, 02215, USA
| | - Divya Varadarajan
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston, 02129, USA
| | - Jiarui Yang
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, 02215, USA
| | - Ichun Anderson Chen
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, 02215, USA
| | - Sreekanth Kura
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, 02215, USA
| | - Caroline Magnain
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston, 02129, USA
| | - Jean C Augustinack
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston, 02129, USA
| | - Bruce Fischl
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston, 02129, USA
| | - Douglas N Greve
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston, 02129, USA
| | - David A Boas
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, 02215, USA
- Department of Electrical and Computer Engineering, Boston University, 8 St Mary's St, Boston, 02215, USA
| | - Hui Wang
- Department of Radiology, Massachusetts General Hospital, A.A. Martinos Center for Biomedical Imaging, 13th Street, Boston, 02129, USA.
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13
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Liu CJ, Ammon W, Siless V, Fogarty M, Wang R, Atzeni A, Aganj I, Iglesias JE, Zöllei L, Fischl B, Schmahmann JD, Wang H. Quantification of volumetric morphometry and optical property in the cortex of human cerebellum at micrometer resolution. Neuroimage 2021; 244:118627. [PMID: 34607020 PMCID: PMC8603939 DOI: 10.1016/j.neuroimage.2021.118627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 08/23/2021] [Accepted: 09/27/2021] [Indexed: 11/17/2022] Open
Abstract
The surface of the human cerebellar cortex is much more tightly folded than the cerebral cortex. Volumetric analysis of cerebellar morphometry in magnetic resonance imaging studies suffers from insufficient resolution, and therefore has had limited impact on disease assessment. Automatic serial polarization-sensitive optical coherence tomography (as-PSOCT) is an emerging technique that offers the advantages of microscopic resolution and volumetric reconstruction of large-scale samples. In this study, we reconstructed multiple cubic centimeters of ex vivo human cerebellum tissue using as-PSOCT. The morphometric and optical properties of the cerebellar cortex across five subjects were quantified. While the molecular and granular layers exhibited similar mean thickness in the five subjects, the thickness varied greatly in the granular layer within subjects. Layer-specific optical property remained homogenous within individual subjects but showed higher cross-subject variability than layer thickness. High-resolution volumetric morphometry and optical property maps of human cerebellar cortex revealed by as-PSOCT have great potential to advance our understanding of cerebellar function and diseases.
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Affiliation(s)
- Chao J Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States
| | - William Ammon
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States
| | - Viviana Siless
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States
| | - Morgan Fogarty
- Imaging Science Program, Washington University McKelvey School of Engineering, St. Louis, MO 63130, and Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Ruopeng Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States
| | - Alessia Atzeni
- Centre for Medical Image Computing, University College London, United Kingdom
| | - Iman Aganj
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States
| | - Juan Eugenio Iglesias
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States; Centre for Medical Image Computing, University College London, United Kingdom; MIT HST, Computer Science and AI Lab, Cambridge, MA 02139, United States
| | - Lilla Zöllei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States; MIT HST, Computer Science and AI Lab, Cambridge, MA 02139, United States
| | - Jeremy D Schmahmann
- Ataxia Center, Laboratory for Neuroanatomy and Cerebellar Neurobiology, Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, United States
| | - Hui Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, United States.
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14
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Peter L, Alexander DC, Magnain C, Iglesias JE. Uncertainty-Aware Annotation Protocol to Evaluate Deformable Registration Algorithms. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2053-2065. [PMID: 33819151 DOI: 10.1109/tmi.2021.3070842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Landmark correspondences are a widely used type of gold standard in image registration. However, the manual placement of corresponding points is subject to high inter-user variability in the chosen annotated locations and in the interpretation of visual ambiguities. In this paper, we introduce a principled strategy for the construction of a gold standard in deformable registration. Our framework: (i) iteratively suggests the most informative location to annotate next, taking into account its redundancy with previous annotations; (ii) extends traditional pointwise annotations by accounting for the spatial uncertainty of each annotation, which can either be directly specified by the user, or aggregated from pointwise annotations from multiple experts; and (iii) naturally provides a new strategy for the evaluation of deformable registration algorithms. Our approach is validated on four different registration tasks. The experimental results show the efficacy of suggesting annotations according to their informativeness, and an improved capacity to assess the quality of the outputs of registration algorithms. In addition, our approach yields, from sparse annotations only, a dense visualization of the errors made by a registration method. The source code of our approach supporting both 2D and 3D data is publicly available at https://github.com/LoicPeter/evaluation-deformable-registration.
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15
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Leuze C, Goubran M, Barakovic M, Aswendt M, Tian Q, Hsueh B, Crow A, Weber EMM, Steinberg GK, Zeineh M, Plowey ED, Daducci A, Innocenti G, Thiran JP, Deisseroth K, McNab JA. Comparison of diffusion MRI and CLARITY fiber orientation estimates in both gray and white matter regions of human and primate brain. Neuroimage 2021; 228:117692. [PMID: 33385546 PMCID: PMC7953593 DOI: 10.1016/j.neuroimage.2020.117692] [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: 06/25/2019] [Revised: 12/16/2020] [Accepted: 12/18/2020] [Indexed: 11/30/2022] Open
Abstract
Diffusion MRI (dMRI) represents one of the few methods for mapping brain fiber orientations non-invasively. Unfortunately, dMRI fiber mapping is an indirect method that relies on inference from measured diffusion patterns. Comparing dMRI results with other modalities is a way to improve the interpretation of dMRI data and help advance dMRI technologies. Here, we present methods for comparing dMRI fiber orientation estimates with optical imaging of fluorescently labeled neurofilaments and vasculature in 3D human and primate brain tissue cuboids cleared using CLARITY. The recent advancements in tissue clearing provide a new opportunity to histologically map fibers projecting in 3D, which represents a captivating complement to dMRI measurements. In this work, we demonstrate the capability to directly compare dMRI and CLARITY in the same human brain tissue and assess multiple approaches for extracting fiber orientation estimates from CLARITY data. We estimate the three-dimensional neuronal fiber and vasculature orientations from neurofilament and vasculature stained CLARITY images by calculating the tertiary eigenvector of structure tensors. We then extend CLARITY orientation estimates to an orientation distribution function (ODF) formalism by summing multiple sub-voxel structure tensor orientation estimates. In a sample containing part of the human thalamus, there is a mean angular difference of 19o±15o between the primary eigenvectors of the dMRI tensors and the tertiary eigenvectors from the CLARITY neurofilament stain. We also demonstrate evidence that vascular compartments do not affect the dMRI orientation estimates by showing an apparent lack of correspondence (mean angular difference = 49o±23o) between the orientation of the dMRI tensors and the structure tensors in the vasculature stained CLARITY images. In a macaque brain dataset, we examine how the CLARITY feature extraction depends on the chosen feature extraction parameters. By varying the volume of tissue over which the structure tensor estimates are derived, we show that orientation estimates are noisier with more spurious ODF peaks for sub-voxels below 30 µm3 and that, for our data, the optimal gray matter sub-voxel size is between 62.5 µm3 and 125 µm3. The example experiments presented here represent an important advancement towards robust multi-modal MRI-CLARITY comparisons.
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Affiliation(s)
- C Leuze
- Department of Radiology, Stanford University, Stanford, CA, USA.
| | - M Goubran
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - M Barakovic
- Department of Radiology, Stanford University, Stanford, CA, USA; Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - M Aswendt
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Q Tian
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - B Hsueh
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - A Crow
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - E M M Weber
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - G K Steinberg
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - M Zeineh
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - E D Plowey
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - A Daducci
- Department of Computer Science, University of Verona, Verona, Italy
| | - G Innocenti
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden; Brain and Mind Institute, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - J-P Thiran
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - K Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - J A McNab
- Department of Radiology, Stanford University, Stanford, CA, USA
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16
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Almog IF, Chen F, Senova S, Fomenko A, Gondard E, Sacher WD, Lozano AM, Poon JKS. Full-field swept-source optical coherence tomography and neural tissue classification for deep brain imaging. JOURNAL OF BIOPHOTONICS 2020; 13:e201960083. [PMID: 31710771 PMCID: PMC7065632 DOI: 10.1002/jbio.201960083] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2019] [Revised: 10/19/2019] [Accepted: 11/06/2019] [Indexed: 05/28/2023]
Abstract
Optical coherence tomography can differentiate brain regions with intrinsic contrast and at a micron scale resolution. Such a device can be particularly useful as a real-time neurosurgical guidance tool. We present, to our knowledge, the first full-field swept-source optical coherence tomography system operating near a wavelength of 1310 nm. The proof-of-concept system was integrated with an endoscopic probe tip, which is compatible with deep brain stimulation keyhole neurosurgery. Neuroimaging experiments were performed on ex vivo brain tissues and in vivo in rat brains. Using classification algorithms involving texture features and optical attenuation, images were successfully classified into three brain tissue types.
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Affiliation(s)
- Ilan Felts Almog
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
- Krembil Research InstituteToronto Western HospitalTorontoOntarioCanada
| | - Fu‐Der Chen
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
- Krembil Research InstituteToronto Western HospitalTorontoOntarioCanada
| | - Suhan Senova
- Krembil Research InstituteToronto Western HospitalTorontoOntarioCanada
- Department of NeurosurgeryCentre Hospitalier Universitaire Henri‐Mondor, APHPCréteilFrance
- INSERM Unit 955, Institut Mondor de Recherche Biomédicale, Université Paris‐EstCréteilFrance
| | - Anton Fomenko
- Krembil Research InstituteToronto Western HospitalTorontoOntarioCanada
| | - Elise Gondard
- Krembil Research InstituteToronto Western HospitalTorontoOntarioCanada
| | - Wesley D. Sacher
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
- Max Planck Institute of Microstructure PhysicsHalleGermany
| | - Andres M. Lozano
- Krembil Research InstituteToronto Western HospitalTorontoOntarioCanada
- Division of Neurosurgery, Department of SurgeryToronto Western HospitalTorontoOntarioCanada
| | - Joyce K. S. Poon
- Edward S. Rogers Sr. Department of Electrical and Computer EngineeringUniversity of TorontoTorontoOntarioCanada
- Krembil Research InstituteToronto Western HospitalTorontoOntarioCanada
- Max Planck Institute of Microstructure PhysicsHalleGermany
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17
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Kiseleva EB, Yashin KS, Moiseev AA, Timofeeva LB, Kudelkina VV, Alekseeva AI, Meshkova SV, Polozova AV, Gelikonov GV, Zagaynova EV, Gladkova ND. Optical coefficients as tools for increasing the optical coherence tomography contrast for normal brain visualization and glioblastoma detection. NEUROPHOTONICS 2019; 6:035003. [PMID: 31312669 PMCID: PMC6630098 DOI: 10.1117/1.nph.6.3.035003] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 06/27/2019] [Indexed: 05/14/2023]
Abstract
The methods used for digital processing of optical coherence tomography (OCT) and crosspolarization (CP) OCT images are focused on improving the contrast ratio of native structural OCT images. Such advances are particularly important for the intraoperative detection of glioma margins where the visual assessment of OCT images can be difficult and lead to errors. The aim of the study was to investigate the application of optical coefficients obtained from CP OCT data for the differentiation of glial tumorous tissue from a normal brain. Pseudocolor en-face OCT maps based on two optical coefficients (the commonly used rate of attenuation in the cochannel, and in addition, the interchannel attenuation difference) were constructed for normal rat brain coronal cross sections and for brains with a 101.8 rat glioblastoma model. It was shown that the use of optical coefficients significantly increased the available information from the OCT data in comparison with unprocessed images. As a result, this allowed contrasting of the white matter from the gray matter and tumorous tissue ex vivo, and for this purpose, the interchannel attenuation difference worked better. The interchannel attenuation difference values of white matter were at least seven and two times higher than corresponding values of the cortex and tumorous tissue, whereas the same parameter for cochannel attenuation coefficient values of white matter are about 4 and 1.4. However, quantitative analysis shows that both coefficients are suitable for the purpose of glioblastoma detection from normal brain tissue regardless of whether a necrotic component was present (in all compared groups p < 0.001 ).
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Affiliation(s)
- Elena B. Kiseleva
- Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Address all correspondence to Elena B. Kiseleva, E-mail:
| | | | - Alexander A. Moiseev
- Russian Academy of Sciences, Institute of Applied Physics, Nizhny Novgorod, Russia
| | | | | | | | | | | | - Grigory V. Gelikonov
- Russian Academy of Sciences, Institute of Applied Physics, Nizhny Novgorod, Russia
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18
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Caspers S, Axer M. Decoding the microstructural correlate of diffusion MRI. NMR IN BIOMEDICINE 2019; 32:e3779. [PMID: 28858413 DOI: 10.1002/nbm.3779] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 06/28/2017] [Accepted: 07/05/2017] [Indexed: 06/07/2023]
Abstract
Diffusion imaging has evolved considerably over the past decade. While it provides valuable information about the structural connectivity at the macro- and mesoscopic scale, bridging the gap to the microstructure at the level of single nerve fibers poses an enormous challenge. This is particularly true for the human brain with its large size, its large white-matter volume and availability of histological techniques for studying human whole-brain sections and subsequent 3D reconstruction. Classic post-mortem techniques for studying the fiber architecture of the brain, such as myeloarchitectonic staining or dye tracing, are complemented by novel histological approaches, such as 3D polarized light imaging or optical coherence tomography, enabling unique insight into the fiber architecture from large fiber bundles within deep white matter to single nerve fibers in the cortex. The present review discusses the benefits and challenges of these latest developments in comparison with the classic techniques, with particular focus on the mutual exchange between in vivo and post-mortem diffusion imaging and post-mortem microstructural approaches for understanding the wiring of the brain across different scales.
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Affiliation(s)
- Svenja Caspers
- C. and O. Vogt Institute for Brain Research, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- JARA-BRAIN, Jülich-Aachen Research Alliance, Jülich, Germany
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
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19
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Roebroeck A, Miller KL, Aggarwal M. Ex vivo diffusion MRI of the human brain: Technical challenges and recent advances. NMR IN BIOMEDICINE 2019; 32:e3941. [PMID: 29863793 PMCID: PMC6492287 DOI: 10.1002/nbm.3941] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2016] [Revised: 04/17/2018] [Accepted: 04/17/2018] [Indexed: 05/23/2023]
Abstract
This review discusses ex vivo diffusion magnetic resonance imaging (dMRI) as an important research tool for neuroanatomical investigations and the validation of in vivo dMRI techniques, with a focus on the human brain. We review the challenges posed by the properties of post-mortem tissue, and discuss state-of-the-art tissue preparation methods and recent advances in pulse sequences and acquisition techniques to tackle these. We then review recent ex vivo dMRI studies of the human brain, highlighting the validation of white matter orientation estimates and the atlasing and mapping of large subcortical structures. We also give particular emphasis to the delineation of layered gray matter structure with ex vivo dMRI, as this application illustrates the strength of its mesoscale resolution over large fields of view. We end with a discussion and outlook on future and potential directions of the field.
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Affiliation(s)
- Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology & NeuroscienceMaastricht UniversityMaastrichtthe Netherlands
| | | | - Manisha Aggarwal
- Department of RadiologyJohns Hopkins University School of MedicineBaltimoreMDUSA
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20
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Morawski M, Kirilina E, Scherf N, Jäger C, Reimann K, Trampel R, Gavriilidis F, Geyer S, Biedermann B, Arendt T, Weiskopf N. Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology. Neuroimage 2018; 182:417-428. [PMID: 29196268 PMCID: PMC6189522 DOI: 10.1016/j.neuroimage.2017.11.060] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 11/22/2017] [Accepted: 11/26/2017] [Indexed: 01/21/2023] Open
Abstract
Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates.
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Affiliation(s)
- Markus Morawski
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany.
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany; Center for Cognitive Neuroscience Berlin, Free University Berlin, Habelschwerdter Allee 45, 14195, Berlin, Germany.
| | - Nico Scherf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Katja Reimann
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Filippos Gavriilidis
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Stefan Geyer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Bernd Biedermann
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany
| | - Thomas Arendt
- Paul Flechsig Institute of Brain Research, University of Leipzig, Liebigstr. 19, 04103, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103, Leipzig, Germany
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21
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Colocalization of neurons in optical coherence microscopy and Nissl-stained histology in Brodmann's area 32 and area 21. Brain Struct Funct 2018; 224:351-362. [PMID: 30328512 DOI: 10.1007/s00429-018-1777-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 10/03/2018] [Indexed: 12/11/2022]
Abstract
Optical coherence tomography is an optical technique that uses backscattered light to highlight intrinsic structure, and when applied to brain tissue, it can resolve cortical layers and fiber bundles. Optical coherence microscopy (OCM) is higher resolution (i.e., 1.25 µm) and is capable of detecting neurons. In a previous report, we compared the correspondence of OCM acquired imaging of neurons with traditional Nissl stained histology in entorhinal cortex layer II. In the current method-oriented study, we aimed to determine the colocalization success rate between OCM and Nissl in other brain cortical areas with different laminar arrangements and cell packing density. We focused on two additional cortical areas: medial prefrontal, pre-genual Brodmann area (BA) 32 and lateral temporal BA 21. We present the data as colocalization matrices and as quantitative percentages. The overall average colocalization in OCM compared to Nissl was 67% for BA 32 (47% for Nissl colocalization) and 60% for BA 21 (52% for Nissl colocalization), but with a large variability across cases and layers. One source of variability and confounds could be ascribed to an obscuring effect from large and dense intracortical fiber bundles. Other technical challenges, including obstacles inherent to human brain tissue, are discussed. Despite limitations, OCM is a promising semi-high throughput tool for demonstrating detail at the neuronal level, and, with further development, has distinct potential for the automatic acquisition of large databases as are required for the human brain.
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22
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Van Essen DC, Glasser MF. Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans. Neuron 2018; 99:640-663. [PMID: 30138588 PMCID: PMC6149530 DOI: 10.1016/j.neuron.2018.07.002] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 06/25/2018] [Accepted: 07/02/2018] [Indexed: 10/28/2022]
Abstract
The cerebral cortex in mammals contains a mosaic of cortical areas that differ in function, architecture, connectivity, and/or topographic organization. A combination of local connectivity (within-area microcircuitry) and long-distance (between-area) connectivity enables each area to perform a unique set of computations. Some areas also have characteristic within-area mesoscale organization, reflecting specialized representations of distinct types of information. Cortical areas interact with one another to form functional networks that mediate behavior, and each area may be a part of multiple, partially overlapping networks. Given their importance to the understanding of brain organization, mapping cortical areas across species is a major objective of systems neuroscience and has been a century-long challenge. Here, we review recent progress in multi-modal mapping of mouse and nonhuman primate cortex, mainly using invasive experimental methods. These studies also provide a neuroanatomical foundation for mapping human cerebral cortex using noninvasive neuroimaging, including a new map of human cortical areas that we generated using a semiautomated analysis of high-quality, multimodal neuroimaging data. We contrast our semiautomated approach to human multimodal cortical mapping with various extant fully automated human brain parcellations that are based on only a single imaging modality and offer suggestions on how to best advance the noninvasive brain parcellation field. We discuss the limitations as well as the strengths of current noninvasive methods of mapping brain function, architecture, connectivity, and topography and of current approaches to mapping the brain's functional networks.
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Affiliation(s)
- David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Matthew F Glasser
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA; St. Luke's Hospital, St. Louis, MO 63107, USA.
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23
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Troiani F, Nikolic K, Constandinou TG. Simulating optical coherence tomography for observing nerve activity: A finite difference time domain bi-dimensional model. PLoS One 2018; 13:e0200392. [PMID: 29990346 PMCID: PMC6039043 DOI: 10.1371/journal.pone.0200392] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Accepted: 06/24/2018] [Indexed: 11/19/2022] Open
Abstract
We present a finite difference time domain (FDTD) model for computation of A line scans in time domain optical coherence tomography (OCT). The OCT output signal is created using two different simulations for the reference and sample arms, with a successive computation of the interference signal with external software. In this paper we present the model applied to two different samples: a glass rod filled with water-sucrose solution at different concentrations and a peripheral nerve. This work aims to understand to what extent time domain OCT can be used for non-invasive, direct optical monitoring of peripheral nerve activity.
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Affiliation(s)
- Francesca Troiani
- Centre for Bio-Inspired Technology, Imperial College London, London, United Kingdom
| | - Konstantin Nikolic
- Centre for Bio-Inspired Technology, Imperial College London, London, United Kingdom
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24
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Marchand PJ, Szlag D, Bouwens A, Lasser T. In vivo high-resolution cortical imaging with extended-focus optical coherence microscopy in the visible-NIR wavelength range. JOURNAL OF BIOMEDICAL OPTICS 2018; 23:1-7. [PMID: 29575831 DOI: 10.1117/1.jbo.23.3.036012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Accepted: 03/07/2018] [Indexed: 05/10/2023]
Abstract
Visible light optical coherence tomography has shown great interest in recent years for spectroscopic and high-resolution retinal and cerebral imaging. Here, we present an extended-focus optical coherence microscopy system operating from the visible to the near-infrared wavelength range for high axial and lateral resolution imaging of cortical structures in vivo. The system exploits an ultrabroad illumination spectrum centered in the visible wavelength range (λc = 650 nm, Δλ ∼ 250 nm) offering a submicron axial resolution (∼0.85 μm in water) and an extended-focus configuration providing a high lateral resolution of ∼1.4 μm maintained over ∼150 μm in depth in water. The system's axial and lateral resolution are first characterized using phantoms, and its imaging performance is then demonstrated by imaging the vasculature, myelinated axons, and neuronal cells in the first layers of the somatosensory cortex of mice in vivo.
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Affiliation(s)
- Paul J Marchand
- Ecole Polytechnique Fédérale de Lausanne, Laboratoire d' Optique Biomédicale, Lausanne, Switzerland
| | - Daniel Szlag
- Ecole Polytechnique Fédérale de Lausanne, Laboratoire d' Optique Biomédicale, Lausanne, Switzerland
| | - Arno Bouwens
- Ecole Polytechnique Fédérale de Lausanne, Laboratoire d' Optique Biomédicale, Lausanne, Switzerland
| | - Theo Lasser
- Ecole Polytechnique Fédérale de Lausanne, Laboratoire d' Optique Biomédicale, Lausanne, Switzerland
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25
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Fischl B, Sereno MI. Microstructural parcellation of the human brain. Neuroimage 2018; 182:219-231. [PMID: 29496612 DOI: 10.1016/j.neuroimage.2018.01.036] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 01/12/2018] [Accepted: 01/15/2018] [Indexed: 12/27/2022] Open
Abstract
The human cerebral cortex is composed of a mosaic of areas thought to subserve different functions. The parcellation of the cortex into areas has a long history and has been carried out using different combinations of structural, connectional, receptotopic, and functional properties. Here we give a brief overview of the history of cortical parcellation, and explore different microstructural properties and analysis techniques that can be used to define the borders between different regions. We show that accounting for the 3D geometry of the highly folded human cortex is especially critical for accurate parcellation. We close with some thoughts on future directions and best practices for combining modalities.
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Affiliation(s)
- Bruce Fischl
- Department of Radiology, Harvard Medical School, United States; Athinoula A. Martinos Center for Biomedical Imaging Mass, General Hospital, United States; Division of Health Sciences and Technology and Engineering and Computer Science MIT, Cambridge, MA, United States.
| | - Martin I Sereno
- Department of Psychology, SDSU Imaging Center, San Diego State University, San Diego, CA 92182, United States.
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26
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Beaujoin J, Palomero-Gallagher N, Boumezbeur F, Axer M, Bernard J, Poupon F, Schmitz D, Mangin JF, Poupon C. Post-mortem inference of the human hippocampal connectivity and microstructure using ultra-high field diffusion MRI at 11.7 T. Brain Struct Funct 2018; 223:2157-2179. [PMID: 29387938 PMCID: PMC5968081 DOI: 10.1007/s00429-018-1617-1] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 01/22/2018] [Indexed: 12/11/2022]
Abstract
The human hippocampus plays a key role in memory management and is one of the first structures affected by Alzheimer's disease. Ultra-high magnetic resonance imaging provides access to its inner structure in vivo. However, gradient limitations on clinical systems hinder access to its inner connectivity and microstructure. A major target of this paper is the demonstration of diffusion MRI potential, using ultra-high field (11.7 T) and strong gradients (750 mT/m), to reveal the extra- and intra-hippocampal connectivity in addition to its microstructure. To this purpose, a multiple-shell diffusion-weighted acquisition protocol was developed to reach an ultra-high spatio-angular resolution with a good signal-to-noise ratio. The MRI data set was analyzed using analytical Q-Ball Imaging, Diffusion Tensor Imaging (DTI), and Neurite Orientation Dispersion and Density Imaging models. High Angular Resolution Diffusion Imaging estimates allowed us to obtain an accurate tractography resolving more complex fiber architecture than DTI models, and subsequently provided a map of the cross-regional connectivity. The neurite density was akin to that found in the histological literature, revealing the three hippocampal layers. Moreover, a gradient of connectivity and neurite density was observed between the anterior and the posterior part of the hippocampus. These results demonstrate that ex vivo ultra-high field/ultra-high gradients diffusion-weighted MRI allows the mapping of the inner connectivity of the human hippocampus, its microstructure, and to accurately reconstruct elements of the polysynaptic intra-hippocampal pathway using fiber tractography techniques at very high spatial/angular resolutions.
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Affiliation(s)
- Justine Beaujoin
- CEA NeuroSpin/UNIRS, Gif-sur-Yvette, France.
- Université Paris-Saclay, Orsay, France.
- France Life Imaging, Orsay, France.
| | - Nicola Palomero-Gallagher
- Forschungszentrum Jülich, INM-1, Jülich, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany
| | - Fawzi Boumezbeur
- CEA NeuroSpin/UNIRS, Gif-sur-Yvette, France
- Université Paris-Saclay, Orsay, France
- France Life Imaging, Orsay, France
| | - Markus Axer
- Forschungszentrum Jülich, INM-1, Jülich, Germany
| | - Jeremy Bernard
- CEA NeuroSpin/UNIRS, Gif-sur-Yvette, France
- Université Paris-Saclay, Orsay, France
- France Life Imaging, Orsay, France
| | - Fabrice Poupon
- Université Paris-Saclay, Orsay, France
- France Life Imaging, Orsay, France
- CEA NeuroSpin/UNATI, Gif-sur-Yvette, France
| | | | - Jean-François Mangin
- Université Paris-Saclay, Orsay, France
- France Life Imaging, Orsay, France
- CEA NeuroSpin/UNATI, Gif-sur-Yvette, France
- CATI Neuroimaging Platform
| | - Cyril Poupon
- CEA NeuroSpin/UNIRS, Gif-sur-Yvette, France
- Université Paris-Saclay, Orsay, France
- France Life Imaging, Orsay, France
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27
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Unschuld PG. Novel Translational Research Methodology and the Prospect to a Better Understanding of Neurodegenerative Disease. NEURODEGENER DIS 2018; 18:1-4. [PMID: 29339665 DOI: 10.1159/000486565] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Affiliation(s)
- Paul G Unschuld
- Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich, Zurich, Switzerland.,Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
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28
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Wang H, Magnain C, Wang R, Dubb J, Varjabedian A, Tirrell LS, Stevens A, Augustinack JC, Konukoglu E, Aganj I, Frosch MP, Schmahmann JD, Fischl B, Boas DA. as-PSOCT: Volumetric microscopic imaging of human brain architecture and connectivity. Neuroimage 2018; 165:56-68. [PMID: 29017866 PMCID: PMC5732037 DOI: 10.1016/j.neuroimage.2017.10.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 10/05/2017] [Accepted: 10/06/2017] [Indexed: 01/21/2023] Open
Abstract
Polarization sensitive optical coherence tomography (PSOCT) with serial sectioning has enabled the investigation of 3D structures in mouse and human brain tissue samples. By using intrinsic optical properties of back-scattering and birefringence, PSOCT reliably images cytoarchitecture, myeloarchitecture and fiber orientations. In this study, we developed a fully automatic serial sectioning polarization sensitive optical coherence tomography (as-PSOCT) system to enable volumetric reconstruction of human brain samples with unprecedented sample size and resolution. The 3.5 μm in-plane resolution and 50 μm through-plane voxel size allow inspection of cortical layers that are a single-cell in width, as well as small crossing fibers. We show the abilities of as-PSOCT in quantifying layer thicknesses of the cerebellar cortex and creating microscopic tractography of intricate fiber networks in the subcortical nuclei and internal capsule regions, all based on volumetric reconstructions. as-PSOCT provides a viable tool for studying quantitative cytoarchitecture and myeloarchitecture and mapping connectivity with microscopic resolution in the human brain.
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Affiliation(s)
- Hui Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA.
| | - Caroline Magnain
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Ruopeng Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Jay Dubb
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Ani Varjabedian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Lee S Tirrell
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Allison Stevens
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Jean C Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Ender Konukoglu
- Computer Vision Laboratory, ETH Zurich, 8092 Zurich, Switzerland
| | - Iman Aganj
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Matthew P Frosch
- C.S. Kubik Laboratory for Neuropathology, Pathology Service, Massachusetts General Hospital, Boston, MA 02115, USA
| | - Jeremy D Schmahmann
- Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA; MIT Computer Science and AI Lab, Cambridge, MA 02139, USA
| | - David A Boas
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
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29
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Mokbul MI. Optical Coherence Tomography: Basic Concepts and Applications in Neuroscience Research. J Med Eng 2017; 2017:3409327. [PMID: 29214158 PMCID: PMC5682075 DOI: 10.1155/2017/3409327] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Revised: 06/22/2017] [Accepted: 09/14/2017] [Indexed: 12/28/2022] Open
Abstract
Optical coherence tomography is a micrometer-scale imaging modality that permits label-free, cross-sectional imaging of biological tissue microstructure using tissue backscattering properties. After its invention in the 1990s, OCT is now being widely used in several branches of neuroscience as well as other fields of biomedical science. This review study reports an overview of OCT's applications in several branches or subbranches of neuroscience such as neuroimaging, neurology, neurosurgery, neuropathology, and neuroembryology. This study has briefly summarized the recent applications of OCT in neuroscience research, including a comparison, and provides a discussion of the remaining challenges and opportunities in addition to future directions. The chief aim of the review study is to draw the attention of a broad neuroscience community in order to maximize the applications of OCT in other branches of neuroscience too, and the study may also serve as a benchmark for future OCT-based neuroscience research. Despite some limitations, OCT proves to be a useful imaging tool in both basic and clinical neuroscience research.
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Affiliation(s)
- Mobin Ibne Mokbul
- Notre Dame College, Motijheel Circular Road, Arambagh, Motijheel, Dhaka 1000, Bangladesh
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30
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Ding SL, Royall JJ, Sunkin SM, Ng L, Facer BAC, Lesnar P, Guillozet-Bongaarts A, McMurray B, Szafer A, Dolbeare TA, Stevens A, Tirrell L, Benner T, Caldejon S, Dalley RA, Dee N, Lau C, Nyhus J, Reding M, Riley ZL, Sandman D, Shen E, van der Kouwe A, Varjabedian A, Wright M, Zöllei L, Dang C, Knowles JA, Koch C, Phillips JW, Sestan N, Wohnoutka P, Zielke HR, Hohmann JG, Jones AR, Bernard A, Hawrylycz MJ, Hof PR, Fischl B, Lein ES. Comprehensive cellular-resolution atlas of the adult human brain. J Comp Neurol 2017; 524:3127-481. [PMID: 27418273 PMCID: PMC5054943 DOI: 10.1002/cne.24080] [Citation(s) in RCA: 216] [Impact Index Per Article: 30.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 07/11/2016] [Accepted: 07/13/2016] [Indexed: 12/12/2022]
Abstract
Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole‐brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high‐resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion‐weighted imaging (DWI), and 1,356 large‐format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto‐ and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127–3481, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Song-Lin Ding
- Allen Institute for Brain Science, Seattle, Washington, 98109.
| | - Joshua J Royall
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Susan M Sunkin
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | | | - Phil Lesnar
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | | | - Bergen McMurray
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Aaron Szafer
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Tim A Dolbeare
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Allison Stevens
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | - Lee Tirrell
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | - Thomas Benner
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | | | - Rachel A Dalley
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Christopher Lau
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Julie Nyhus
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Melissa Reding
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Zackery L Riley
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - David Sandman
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Elaine Shen
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Andre van der Kouwe
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | - Ani Varjabedian
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | - Michelle Wright
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | - Lilla Zöllei
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | - Chinh Dang
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - James A Knowles
- Zilkha Neurogenetic Institute, and Department of Psychiatry, University of Southern California, Los Angeles, California, 90033
| | - Christof Koch
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - John W Phillips
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Nenad Sestan
- Department of Neurobiology and Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, Connecticut, 06510
| | - Paul Wohnoutka
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - H Ronald Zielke
- Department of Pediatrics, University of Maryland School of Medicine, Baltimore, Maryland, 21201
| | - John G Hohmann
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Allan R Jones
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | - Amy Bernard
- Allen Institute for Brain Science, Seattle, Washington, 98109
| | | | - Patrick R Hof
- Fishberg Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, 11029
| | - Bruce Fischl
- Department of Radiology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, 02129
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, Washington, 98109.
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31
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Marchand PJ, Bouwens A, Szlag D, Nguyen D, Descloux A, Sison M, Coquoz S, Extermann J, Lasser T. Visible spectrum extended-focus optical coherence microscopy for label-free sub-cellular tomography. BIOMEDICAL OPTICS EXPRESS 2017; 8:3343-3359. [PMID: 28717571 PMCID: PMC5508832 DOI: 10.1364/boe.8.003343] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 06/14/2017] [Accepted: 06/16/2017] [Indexed: 05/09/2023]
Abstract
We present a novel extended-focus optical coherence microscope (OCM) attaining 0.7 μm axial and 0.4 μm lateral resolution maintained over a depth of 40 μm, while preserving the advantages of Fourier domain OCM. Our system uses an ultra-broad spectrum from a supercontinuum laser source. As the spectrum spans from near-infrared to visible wavelengths (240 nm in bandwidth), we call the system visOCM. The combination of such a broad spectrum with a high-NA objective creates an almost isotropic 3D submicron resolution. We analyze the imaging performance of visOCM on microbead samples and demonstrate its image quality on cell cultures and ex-vivo brain tissue of both healthy and alzheimeric mice. In addition to neuronal cell bodies, fibers and plaques, visOCM imaging of brain tissue reveals fine vascular structures and sub-cellular features through its high spatial resolution. Sub-cellular structures were also observed in live cells and were further revealed through a protocol traditionally used for OCT angiography.
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32
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Full-Field Optical Coherence Tomography as a Diagnosis Tool: Recent Progress with Multimodal Imaging. APPLIED SCIENCES-BASEL 2017. [DOI: 10.3390/app7030236] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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33
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Liu CJ, Williams KE, Orr HT, Akkin T. Visualizing and mapping the cerebellum with serial optical coherence scanner. NEUROPHOTONICS 2017; 4:011006. [PMID: 27725947 PMCID: PMC5048104 DOI: 10.1117/1.nph.4.1.011006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 09/12/2016] [Indexed: 05/12/2023]
Abstract
We present the visualization of the mouse cerebellum and adjacent brainstem using a serial optical coherence scanner, which integrates a vibratome slicer and polarization-sensitive optical coherence tomography for ex vivo imaging. The scanner provides intrinsic optical contrasts to distinguish the cerebellar cortical layers and white matter. Images from serial scans reveal the large-scale anatomy in detail and map the nerve fiber pathways in the cerebellum and brainstem. By incorporating a water-immersion microscope objective, we also present high-resolution tiled images that delineate fine structures in the cerebellum and brainstem.
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Affiliation(s)
- Chao J. Liu
- University of Minnesota, Department of Biomedical Engineering, 312 Church Street S.E., Minneapolis, Minnesota 55455, United States
| | - Kristen E. Williams
- University of Minnesota, Department of Biomedical Engineering, 312 Church Street S.E., Minneapolis, Minnesota 55455, United States
| | - Harry T. Orr
- University of Minnesota, Institute of Translational Neuroscience, 2101 6th Street S.E., Minneapolis, Minnesota 55455, United States
- University of Minnesota, Department of Laboratory Medicine and Pathology, 420 Delaware Street S.E., Minneapolis, Minnesota 55455, United States
| | - Taner Akkin
- University of Minnesota, Department of Biomedical Engineering, 312 Church Street S.E., Minneapolis, Minnesota 55455, United States
- Address all correspondence to: Taner Akkin, E-mail:
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34
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Label-free, multi-scale imaging of ex-vivo mouse brain using spatial light interference microscopy. Sci Rep 2016; 6:39667. [PMID: 28009019 PMCID: PMC5180101 DOI: 10.1038/srep39667] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2016] [Accepted: 11/17/2016] [Indexed: 11/26/2022] Open
Abstract
Brain connectivity spans over broad spatial scales, from nanometers to centimeters. In order to understand the brain at multi-scale, the neural network in wide-field has been visualized in detail by taking advantage of light microscopy. However, the process of staining or addition of fluorescent tags is commonly required, and the image contrast is insufficient for delineation of cytoarchitecture. To overcome this barrier, we use spatial light interference microscopy to investigate brain structure with high-resolution, sub-nanometer pathlength sensitivity without the use of exogenous contrast agents. Combining wide-field imaging and a mosaic algorithm developed in-house, we show the detailed architecture of cells and myelin, within coronal olfactory bulb and cortical sections, and from sagittal sections of the hippocampus and cerebellum. Our technique is well suited to identify laminar characteristics of fiber tract orientation within white matter, e.g. the corpus callosum. To further improve the macro-scale contrast of anatomical structures, and to better differentiate axons and dendrites from cell bodies, we mapped the tissue in terms of its scattering property. Based on our results, we anticipate that spatial light interference microscopy can potentially provide multiscale and multicontrast perspectives of gross and microscopic brain anatomy.
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35
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Bastiani M, Oros-Peusquens AM, Seehaus A, Brenner D, Möllenhoff K, Celik A, Felder J, Bratzke H, Shah NJ, Galuske R, Goebel R, Roebroeck A. Automatic Segmentation of Human Cortical Layer-Complexes and Architectural Areas Using Ex vivo Diffusion MRI and Its Validation. Front Neurosci 2016; 10:487. [PMID: 27891069 PMCID: PMC5102896 DOI: 10.3389/fnins.2016.00487] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Accepted: 10/11/2016] [Indexed: 11/14/2022] Open
Abstract
Recently, several magnetic resonance imaging contrast mechanisms have been shown to distinguish cortical substructure corresponding to selected cortical layers. Here, we investigate cortical layer and area differentiation by automatized unsupervised clustering of high-resolution diffusion MRI data. Several groups of adjacent layers could be distinguished in human primary motor and premotor cortex. We then used the signature of diffusion MRI signals along cortical depth as a criterion to detect area boundaries and find borders at which the signature changes abruptly. We validate our clustering results by histological analysis of the same tissue. These results confirm earlier studies which show that diffusion MRI can probe layer-specific intracortical fiber organization and, moreover, suggests that it contains enough information to automatically classify architecturally distinct cortical areas. We discuss the strengths and weaknesses of the automatic clustering approach and its appeal for MR-based cortical histology.
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Affiliation(s)
- Matteo Bastiani
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastricht, Netherlands; Research Centre Jülich, Institute of Neuroscience and Medicine (INM-4)Jülich, Germany
| | | | - Arne Seehaus
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastricht, Netherlands; Department of Biology, TU DarmstadtDarmstadt, Germany
| | - Daniel Brenner
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-4) Jülich, Germany
| | - Klaus Möllenhoff
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-4) Jülich, Germany
| | - Avdo Celik
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-4) Jülich, Germany
| | - Jörg Felder
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-4) Jülich, Germany
| | - Hansjürgen Bratzke
- Department of Forensic Medicine, Faculty of Medicine, Goethe University Frankfurt Frankfurt, Germany
| | - Nadim J Shah
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-4)Jülich, Germany; Department of Neurology, Faculty of Medicine, Jülich Aachen Research Alliance, RWTH Aachen UniversityAachen, Germany
| | - Ralf Galuske
- Department of Biology, TU Darmstadt Darmstadt, Germany
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastricht, Netherlands; Department of Neuroimaging and Neuromodeling, Netherlands Institute for Neuroscience - KNAWAmsterdam, Netherlands
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University Maastricht, Netherlands
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Men J, Huang Y, Solanki J, Zeng X, Alex A, Jerwick J, Zhang Z, Tanzi RE, Li A, Zhou C. Optical Coherence Tomography for Brain Imaging and Developmental Biology. IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS : A PUBLICATION OF THE IEEE LASERS AND ELECTRO-OPTICS SOCIETY 2016; 22:6803213. [PMID: 27721647 PMCID: PMC5049888 DOI: 10.1109/jstqe.2015.2513667] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Optical coherence tomography (OCT) is a promising research tool for brain imaging and developmental biology. Serving as a three-dimensional optical biopsy technique, OCT provides volumetric reconstruction of brain tissues and embryonic structures with micrometer resolution and video rate imaging speed. Functional OCT enables label-free monitoring of hemodynamic and metabolic changes in the brain in vitro and in vivo in animal models. Due to its non-invasiveness nature, OCT enables longitudinal imaging of developing specimens in vivo without potential damage from surgical operation, tissue fixation and processing, and staining with exogenous contrast agents. In this paper, various OCT applications in brain imaging and developmental biology are reviewed, with a particular focus on imaging heart development. In addition, we report findings on the effects of a circadian gene (Clock) and high-fat-diet on heart development in Drosophila melanogaster. These findings contribute to our understanding of the fundamental mechanisms connecting circadian genes and obesity to heart development and cardiac diseases.
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Affiliation(s)
- Jing Men
- Department of Electrical and Computer Engineering, Center for Photonics and Nanoelectronics, and Bioengineering Program, Lehigh University, Bethlehem, PA, USA, 18015
| | - Yongyang Huang
- Department of Electrical and Computer Engineering, Center for Photonics and Nanoelectronics, and Bioengineering Program, Lehigh University, Bethlehem, PA, USA, 18015
| | - Jitendra Solanki
- Department of Electrical and Computer Engineering, Center for Photonics and Nanoelectronics, and Bioengineering Program, Lehigh University, Bethlehem, PA, USA, 18015
| | - Xianxu Zeng
- Department of Electrical and Computer Engineering, Center for Photonics and Nanoelectronics, and Bioengineering Program, Lehigh University, Bethlehem, PA, USA, 18015
- Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, P.R. China, 450000
| | - Aneesh Alex
- Department of Electrical and Computer Engineering, Center for Photonics and Nanoelectronics, and Bioengineering Program, Lehigh University, Bethlehem, PA, USA, 18015
| | - Jason Jerwick
- Department of Electrical and Computer Engineering, Center for Photonics and Nanoelectronics, and Bioengineering Program, Lehigh University, Bethlehem, PA, USA, 18015
| | - Zhan Zhang
- Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, P.R. China, 450000
| | - Rudolph E. Tanzi
- Genetics and Aging Research Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA, 02129
| | - Airong Li
- Genetics and Aging Research Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA, 02129
| | - Chao Zhou
- Department of Electrical and Computer Engineering, Center for Photonics and Nanoelectronics, and Bioengineering Program, Lehigh University, Bethlehem, PA, USA, 18015
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Wang H, Akkin T, Magnain C, Wang R, Dubb J, Kostis WJ, Yaseen MA, Cramer A, Sakadžić S, Boas D. Polarization sensitive optical coherence microscopy for brain imaging. OPTICS LETTERS 2016; 41:2213-6. [PMID: 27176965 PMCID: PMC5357322 DOI: 10.1364/ol.41.002213] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Optical coherence tomography (OCT) and optical coherence microscopy (OCM) have demonstrated the ability to investigate cyto- and myelo-architecture in the brain. Polarization-sensitive OCT provides sensitivity to additional contrast mechanisms, specifically the birefringence of myelination and, therefore, is advantageous for investigating white matter fiber tracts. In this Letter, we developed a polarization-sensitive optical coherence microscope (PS-OCM) with a 3.5 μm axial and 1.3 μm transverse resolution to investigate fiber organization and orientation at a finer scale than previously demonstrated with PS-OCT. In a reconstructed mouse brain section, we showed that at the focal depths of 20-70 μm, the PS-OCM reliably identifies the neuronal fibers and quantifies the in-plane orientation.
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Affiliation(s)
- Hui Wang
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
- Corresponding author:
| | - Taner Akkin
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455
| | - Caroline Magnain
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
| | - Ruopeng Wang
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
| | - Jay Dubb
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
| | - William J Kostis
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
| | - Mohammad A Yaseen
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
| | - Avilash Cramer
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
| | - Sava Sakadžić
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
| | - David Boas
- Athinoula A. Martinos Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129
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38
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Magnain C, Wang H, Sakadžić S, Fischl B, Boas DA. En face speckle reduction in optical coherence microscopy by frequency compounding. OPTICS LETTERS 2016; 41:1925-8. [PMID: 27128040 PMCID: PMC5350630 DOI: 10.1364/ol.41.001925] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
We report the use of frequency compounding to significantly reduce speckle noise in optical coherence microscopy, more specifically on the en face images. This method relies on the fact that the speckle patterns recorded from different wavelengths simultaneously are independent; hence their summation yields significant reduction in noise, with only a single acquisition. The results of our experiments with microbeads show that the narrow confocal parameter, due to a high numerical aperture objective, restricts the axial resolution loss that would otherwise theoretically broaden linearly with the number of optical frequency bands used. This speckle reduction scheme preserves the lateral resolution since it is performed on individual A-scans. Finally, we apply this technique to images of fixed human brain tissue, showing significant improvements in contrast-to-noise ratio with only moderate loss of axial resolution, in an effort to improve automatic three-dimensional detection of cells and fibers in the cortex.
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Affiliation(s)
- Caroline Magnain
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, Massachusetts 02129, USA
- Corresponding author:
| | - Hui Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, Massachusetts 02129, USA
| | - Sava Sakadžić
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, Massachusetts 02129, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, Massachusetts 02129, USA
- Computer Science and AI Laboratory, MIT, Cambridge, Massachusetts 02139, USA
| | - David A. Boas
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, Massachusetts 02129, USA
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Amato SP, Pan F, Schwartz J, Ragan TM. Whole Brain Imaging with Serial Two-Photon Tomography. Front Neuroanat 2016; 10:31. [PMID: 27047350 PMCID: PMC4802409 DOI: 10.3389/fnana.2016.00031] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Accepted: 03/07/2016] [Indexed: 12/12/2022] Open
Abstract
Imaging entire mouse brains at submicron resolution has historically been a challenging undertaking and largely confined to the province of dedicated atlasing initiatives. This has limited systematic investigations into important areas of neuroscience, such as neural circuits, brain mapping and neurodegeneration. In this article, we describe in detail Serial Two-Photon (STP) tomography, a robust, reliable method for imaging entire brains with histological detail. We provide examples of how the basic methodology can be extended to other imaging modalities, such as Optical Coherence Tomography (OCT), in order to provide unique contrast mechanisms. Furthermore, we provide a survey of the research that STP tomography has enabled in the field of neuroscience, provide examples of how this technology enables quantitative whole brain studies, and discuss the current limitations of STP tomography-based approaches.
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40
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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: 0.3] [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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41
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Architectonic Mapping of the Human Brain beyond Brodmann. Neuron 2015; 88:1086-1107. [DOI: 10.1016/j.neuron.2015.12.001] [Citation(s) in RCA: 266] [Impact Index Per Article: 29.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Revised: 10/13/2015] [Accepted: 11/20/2015] [Indexed: 12/25/2022]
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42
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Poldrack RA, Farah MJ. Progress and challenges in probing the human brain. Nature 2015; 526:371-9. [DOI: 10.1038/nature15692] [Citation(s) in RCA: 167] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2015] [Accepted: 09/04/2015] [Indexed: 01/20/2023]
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43
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Min E, Lee J, Vavilin A, Jung S, Shin S, Kim J, Jung W. Wide-field optical coherence microscopy of the mouse brain slice. OPTICS LETTERS 2015; 40:4420-3. [PMID: 26421546 DOI: 10.1364/ol.40.004420] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
The imaging capability of optical coherence microscopy (OCM) has great potential to be used in neuroscience research because it is able to visualize anatomic features of brain tissue without labeling or external contrast agents. However, the field of view of OCM is still narrow, which dilutes the strength of OCM and limits its application. In this study, we present fully automated wide-field OCM for mosaic imaging of sliced mouse brains. A total of 308 segmented OCM images were acquired, stitched, and reconstructed as an en-face brain image after intensive imaging processing. The overall imaging area was 11.2×7.0 mm (horizontal×vertical), and the corresponding pixel resolution was 1.2×1.2 μm. OCM images were compared to traditional histology stained with Nissl and Luxol fast blue (LFB). In particular, the orientation of the fibers was analyzed and quantified in wide-field OCM.
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