1
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Georgiadis M, auf der Heiden F, Abbasi H, Ettema L, Nirschl J, Taghavi HM, Wakatsuki M, Liu A, Ho WHD, Carlson M, Doukas M, Koppes SA, Keereweer S, Sobel RA, Setsompop K, Liao C, Amunts K, Axer M, Zeineh M, Menzel M. Uncovering microstructural architecture from histology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.26.586745. [PMID: 38585744 PMCID: PMC10996646 DOI: 10.1101/2024.03.26.586745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Microstructural tissue organization underlies the complex connectivity of the brain and controls properties of connective, muscle, and epithelial tissue. However, discerning microstructural architecture with high resolution for large fields of view remains prohibitive. We address this challenge with computational scattered light imaging (ComSLI), which exploits the anisotropic light scattering of aligned structures. Using a rotating lightsource and a high-resolution camera, ComSLI determines fiber architecture with micrometer resolution from histological sections across preparation and staining protocols. We show complex fiber architecture in brain and non-brain sections, including histological paraffin-embedded sections with various stains, and demonstrate its applicability on animal and human tissue, including disease cases with altered microstructure. ComSLI opens new avenues for investigating fiber architecture in new and archived sections across organisms, tissues, and diseases.
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Affiliation(s)
| | - Franca auf der Heiden
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH; 52425 Jülich, Germany
| | - Hamed Abbasi
- Department of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology; 2628 CJ Delft, the Netherlands
- Department of Otorhinolaryngology and Head and Neck Surgery, Erasmus MC, University Medical Center Rotterdam; 3015 CN Rotterdam, the Netherlands
| | - Loes Ettema
- Department of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology; 2628 CJ Delft, the Netherlands
| | - Jeffrey Nirschl
- Department of Pathology, Stanford University; Stanford, 94305, USA
| | | | - Moe Wakatsuki
- Department of Radiology, Stanford University; Stanford, 94305, USA
| | - Andy Liu
- Department of Radiology, Stanford University; Stanford, 94305, USA
| | | | - Mackenzie Carlson
- Department of Radiology, Stanford University; Stanford, 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University; Stanford, 94305, USA
| | - Michail Doukas
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam; 3015 CN Rotterdam, the Netherlands
| | - Sjors A. Koppes
- Department of Pathology, Erasmus MC, University Medical Center Rotterdam; 3015 CN Rotterdam, the Netherlands
| | - Stijn Keereweer
- Department of Otorhinolaryngology and Head and Neck Surgery, Erasmus MC, University Medical Center Rotterdam; 3015 CN Rotterdam, the Netherlands
| | - Raymond A. Sobel
- Department of Pathology, Stanford University; Stanford, 94305, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University; Stanford, 94305, USA
| | - Congyu Liao
- Department of Radiology, Stanford University; Stanford, 94305, USA
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH; 52425 Jülich, Germany
- C. and O. Vogt Institute for Brain Research, University Hospital Düsseldorf, Medical Faculty, University Düsseldorf, Germany
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH; 52425 Jülich, Germany
- Department of Physics, School of Mathematics and Natural Sciences, University of Wuppertal; 52119 Wuppertal, Germany
| | - Michael Zeineh
- Department of Radiology, Stanford University; Stanford, 94305, USA
| | - Miriam Menzel
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH; 52425 Jülich, Germany
- Department of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology; 2628 CJ Delft, the Netherlands
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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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3
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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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Yang F, Ding W, Fu X, Chen W, Tang J. Photoacoustic elasto-viscography and optical coherence microscopy for multi-parametric ex vivo brain imaging. BIOMEDICAL OPTICS EXPRESS 2023; 14:5615-5628. [PMID: 38021134 PMCID: PMC10659785 DOI: 10.1364/boe.503847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 09/22/2023] [Accepted: 09/22/2023] [Indexed: 12/01/2023]
Abstract
Optical coherence microscopy (OCM) has shown the importance of imaging ex vivo brain slices at the microscopic level for a better understanding of the disease pathology and mechanism. However, the current OCM-based techniques are mainly limited to providing the tissue's optical properties, such as the attenuation coefficient, scattering coefficient, and cell architecture. Imaging the tissue's mechanical properties, including the elasticity and viscosity, in addition to the optical properties, to provide a comprehensive multi-parametric assessment of the sample has remained a challenge. Here, we present an integrated photoacoustic elasto-viscography (PAEV) and OCM imaging system to measure the sample's optical absorption coefficient, attenuation coefficient, and mechanical properties, including elasticity and viscosity. The obtained mechanical and optical properties were consistent with anatomical features observed in the PAEV and OCM images. The elasticity and viscosity maps showed rich variations of microstructural mechanical properties of mice brain. In the reconstructed elasto-viscogram of brain slices, greater elasticity, and lower viscosity were observed in white matter than in gray matter. With the ability to provide multi-parametric properties of the sample, the PAEV-OCM system holds the potential for a more comprehensive study of brain disease pathology.
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Affiliation(s)
- Fen Yang
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Wenguo Ding
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Xinlei Fu
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Wei Chen
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Jianbo Tang
- Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
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Blanke N, Chang S, Novoseltseva A, Wang H, Boas DA, Bigio IJ. Multiscale label-free imaging of myelin in human brain tissue with polarization-sensitive optical coherence tomography and birefringence microscopy. BIOMEDICAL OPTICS EXPRESS 2023; 14:5946-5964. [PMID: 38021128 PMCID: PMC10659784 DOI: 10.1364/boe.499354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/03/2023] [Accepted: 09/06/2023] [Indexed: 12/01/2023]
Abstract
The combination of polarization-sensitive optical coherence tomography (PS-OCT) and birefringence microscopy (BRM) enables multiscale assessment of myelinated axons in postmortem brain tissue, and these tools are promising for the study of brain connectivity and organization. We demonstrate label-free imaging of myelin structure across the mesoscopic and microscopic spatial scales by performing serial-sectioning PS-OCT of a block of human brain tissue and periodically sampling thin sections for high-resolution imaging with BRM. In co-registered birefringence parameter maps, we observe good correspondence and demonstrate that BRM enables detailed validation of myelin (hence, axonal) organization, thus complementing the volumetric information content of PS-OCT.
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Affiliation(s)
- Nathan Blanke
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Shuaibin Chang
- Department of Electrical & Computer Engineering, Boston University, 8 St. Mary’s St., Boston, MA 02215, USA
| | - Anna Novoseltseva
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Hui Wang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, USA
| | - David A. Boas
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Irving J. Bigio
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
- Department of Electrical & Computer Engineering, Boston University, 8 St. Mary’s St., Boston, MA 02215, USA
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6
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Liu CJ, Ammon W, Jones RJ, Nolan JC, Gong D, Maffei C, Edlow BL, Augustinack JC, Magnain C, Yendiki A, Villiger M, Fischl B, Wang H. Quantitative imaging of three-dimensional fiber orientation in the human brain via two illumination angles using polarization-sensitive optical coherence tomography. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.20.563298. [PMID: 37961162 PMCID: PMC10634685 DOI: 10.1101/2023.10.20.563298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The accurate measurement of three-dimensional (3D) fiber orientation in the brain is crucial for reconstructing fiber pathways and studying their involvement in neurological diseases. Optical imaging methods such as polarization-sensitive optical coherence tomography (PS-OCT) provide important tools to directly quantify fiber orientation at micrometer resolution. However, brain imaging based on the optic axis by PS-OCT so far has been limited to two-dimensional in-plane orientation, preventing the comprehensive study of connectivity in 3D. In this work, we present a novel method to obtain the 3D fiber orientation in full angular space with only two illumination angles. We measure the optic axis orientation and the apparent birefringence by PS-OCT from a normal and a 15 deg tilted illumination, and then apply a computational method yielding the 3D optic axis orientation and true birefringence. We verify that our method accurately recovers a large range of through-plane orientations from -85 deg to 85 deg with a high angular precision. We further present 3D fiber orientation maps of entire coronal sections of human cerebrum and brainstem with 10 μm in-plane resolution, revealing unprecedented details of fiber configurations. We envision that further development of our method will open a promising avenue towards large-scale 3D fiber axis mapping in the human brain and other complex fibrous tissues at microscopic level.
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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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Sorelli M, Costantini I, Bocchi L, Axer M, Pavone FS, Mazzamuto G. Fiber enhancement and 3D orientation analysis in label-free two-photon fluorescence microscopy. Sci Rep 2023; 13:4160. [PMID: 36914673 PMCID: PMC10011555 DOI: 10.1038/s41598-023-30953-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 03/03/2023] [Indexed: 03/16/2023] Open
Abstract
Fluorescence microscopy can be exploited for evaluating the brain's fiber architecture with unsurpassed spatial resolution in combination with different tissue preparation and staining protocols. Differently from state-of-the-art polarimetry-based neuroimaging modalities, the quantification of fiber tract orientations from fluorescence microscopy volume images entails the application of specific image processing techniques, such as Fourier or structure tensor analysis. These, however, may lead to unreliable outcomes as they do not isolate myelinated fibers from the surrounding tissue. In this work, we describe a novel image processing pipeline that enables the computation of accurate 3D fiber orientation maps from both grey and white matter regions, exploiting the selective multiscale enhancement of tubular structures of varying diameters provided by a 3D implementation of the Frangi filter. The developed software tool can efficiently generate orientation distribution function maps at arbitrary spatial scales which may support the histological validation of modern diffusion-weighted magnetic resonance imaging tractography. Despite being tested here on two-photon scanning fluorescence microscopy images, acquired from tissue samples treated with a label-free technique enhancing the autofluorescence of myelinated fibers, the presented pipeline was developed to be employed on all types of 3D fluorescence images and fiber staining.
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Affiliation(s)
- Michele Sorelli
- Department of Physics and Astronomy, University of Florence, 50019, Sesto Fiorentino, Italy.,European Laboratory for Non-Linear Spectroscopy (LENS), 50019, Sesto Fiorentino, Italy
| | - Irene Costantini
- European Laboratory for Non-Linear Spectroscopy (LENS), 50019, Sesto Fiorentino, Italy. .,Department of Biology, University of Florence, 50019, Sesto Fiorentino, Italy. .,National Research Council, National Institute of Optics (CNR-INO), 50019, Sesto Fiorentino, Italy.
| | - Leonardo Bocchi
- Department of Information Engineering, University of Florence, 50039, Florence, Italy
| | - Markus Axer
- Research Centre Jülich, Institute of Neuroscience and Medicine, 52428, Jülich, Germany
| | - Francesco Saverio Pavone
- Department of Physics and Astronomy, University of Florence, 50019, Sesto Fiorentino, Italy.,European Laboratory for Non-Linear Spectroscopy (LENS), 50019, Sesto Fiorentino, Italy.,National Research Council, National Institute of Optics (CNR-INO), 50019, Sesto Fiorentino, Italy
| | - Giacomo Mazzamuto
- Department of Physics and Astronomy, University of Florence, 50019, Sesto Fiorentino, Italy.,European Laboratory for Non-Linear Spectroscopy (LENS), 50019, Sesto Fiorentino, Italy.,National Research Council, National Institute of Optics (CNR-INO), 50019, Sesto Fiorentino, Italy
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9
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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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10
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Yang D, Yuan Z, Hu M, Liang Y. Zebrafish brain and skull imaging based on polarization-sensitive optical coherence tomography. JOURNAL OF BIOPHOTONICS 2022; 15:e202200112. [PMID: 36054179 DOI: 10.1002/jbio.202200112] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 08/19/2022] [Accepted: 08/19/2022] [Indexed: 06/15/2023]
Abstract
Zebrafish brain imaging is very important for the study of brain disease and regeneration. We scanned the adult zebrafish brain before and after skull removal and monitored the recovery process of a head wound by polarization-sensitive optical coherence tomography (PS-OCT) in this paper. We analyzed the structure and polarization characteristics of the brain and skull in PS-OCT images, and found their internal microstructure can be clearly identified with the polarization information. Further, we estimated the pigment distribution of the skull area and found that the density of pigment in skull is a critical factor of affecting zebrafish brain in vivo polarization imaging. Our results demonstrated that more features of brain can be displayed by introducing the polarization information, and proved high-resolution PS-OCT will play a great potential role in studying the zebrafish brain and skull.
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Affiliation(s)
- Di Yang
- Institute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Tianjin, China
| | - Zhuoqun Yuan
- Institute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Tianjin, China
| | - Muyun Hu
- Institute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Tianjin, China
| | - Yanmei Liang
- Institute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-scale Optical Information Science and Technology, Tianjin, China
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11
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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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12
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Axer M, Amunts K. Scale matters: The nested human connectome. Science 2022; 378:500-504. [DOI: 10.1126/science.abq2599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
A comprehensive description of how neurons and entire brain regions are interconnected is fundamental for a mechanistic understanding of brain function and dysfunction. Neuroimaging has shaped the way to approaching the human brain’s connectivity on the basis of diffusion magnetic resonance imaging and tractography. At the same time, polarization, fluorescence, and electron microscopy became available, which pushed spatial resolution and sensitivity to the axonal or even to the synaptic level. New methods are mandatory to inform and constrain whole-brain tractography by regional, high-resolution connectivity data and local fiber geometry. Machine learning and simulation can provide predictions where experimental data are missing. Future interoperable atlases require new concepts, including high-resolution templates and directionality, to represent variants of tractography solutions and estimates of their accuracy.
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Affiliation(s)
- Markus Axer
- Institute of Neurosciences and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Department of Physics, School of Mathematics and Natural Sciences, Bergische Universität Wuppertal, Wuppertal, Germany
| | - Katrin Amunts
- Institute of Neurosciences and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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13
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Costantini I, Axer M, Magnain C, Hof PR. Editorial: The human brain multiscale imaging challenge. Front Neuroanat 2022; 16:1060405. [DOI: 10.3389/fnana.2022.1060405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 10/14/2022] [Indexed: 11/13/2022] Open
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14
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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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15
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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: 26] [Impact Index Per Article: 13.0] [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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16
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Song M, Yang Z, Jiang T. Multimodal Brain Imaging Fusion for the White-Matter Fiber Architecture in the Human Brain. Neurosci Bull 2022; 38:561-564. [PMID: 35099675 PMCID: PMC9106764 DOI: 10.1007/s12264-022-00822-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Accepted: 12/12/2021] [Indexed: 12/22/2022] Open
Affiliation(s)
- Ming Song
- National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhengyi Yang
- National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China
- University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Tianzi Jiang
- National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China.
- Brainnetome Center, Institute of Automation, The Chinese Academy of Sciences, Beijing, 100190, China.
- University of the Chinese Academy of Sciences, Beijing, 100049, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing, 100190, China.
- Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 625014, China.
- The Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia.
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17
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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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18
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Liu CJ, Ammon W, Jones RJ, Nolan J, Wang R, Chang S, Frosch MP, Yendiki A, Boas DA, Magnain C, Fischl B, Wang H. Refractive-index matching enhanced polarization sensitive optical coherence tomography quantification in human brain tissue. BIOMEDICAL OPTICS EXPRESS 2022; 13:358-372. [PMID: 35154876 PMCID: PMC8803034 DOI: 10.1364/boe.443066] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 11/16/2021] [Accepted: 11/23/2021] [Indexed: 05/11/2023]
Abstract
The importance of polarization-sensitive optical coherence tomography (PS-OCT) has been increasingly recognized in human brain imaging. Despite the recent progress of PS-OCT in revealing white matter architecture and orientation, quantification of fine-scale fiber tracts in the human brain cortex has been a challenging problem, due to a low birefringence in the gray matter. In this study, we investigated the effect of refractive index matching by 2,2'-thiodiethanol (TDE) immersion on the improvement of PS-OCT measurements in ex vivo human brain tissue. We show that we can obtain fiber orientation maps of U-fibers that underlie sulci, as well as cortical fibers in the gray matter, including radial fibers in gyri and distinct layers of fibers exhibiting laminar organization. Further analysis shows that index matching reduces the noise in axis orientation measurements by 56% and 39%, in white and gray matter, respectively. Index matching also enables precise measurements of apparent birefringence, which was underestimated in the white matter by 82% but overestimated in the gray matter by 16% prior to TDE immersion. Mathematical simulations show that the improvements are primarily attributed to the reduction in the tissue scattering coefficient, leading to an enhanced signal-to-noise ratio in deeper tissue regions, which could not be achieved by conventional noise reduction methods.
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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, USA
| | - William Ammon
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Robert J Jones
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Jackson Nolan
- 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
| | - Shuaibin Chang
- Department of Electrical and Computer Engineering, Boston University, Boston, MA 02215, USA
| | - Matthew P Frosch
- C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital/Harvard Medical School, Boston, MA 02114, USA
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - David A Boas
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Caroline Magnain
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
- MIT HST, Computer Science and AI Lab, Cambridge, MA 02139, USA
| | - Hui Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129, USA
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19
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Jones R, Maffei C, Augustinack J, Fischl B, Wang H, Bilgic B, Yendiki A. High-fidelity approximation of grid- and shell-based sampling schemes from undersampled DSI using compressed sensing: Post mortem validation. Neuroimage 2021; 244:118621. [PMID: 34587516 PMCID: PMC8631240 DOI: 10.1016/j.neuroimage.2021.118621] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/02/2021] [Accepted: 09/24/2021] [Indexed: 12/31/2022] Open
Abstract
While many useful microstructural indices, as well as orientation distribution functions, can be obtained from multi-shell dMRI data, there is growing interest in exploring the richer set of microstructural features that can be extracted from the full ensemble average propagator (EAP). The EAP can be readily computed from diffusion spectrum imaging (DSI) data, at the cost of a very lengthy acquisition. Compressed sensing (CS) has been used to make DSI more practical by reducing its acquisition time. CS applied to DSI (CS-DSI) attempts to reconstruct the EAP from significantly undersampled q-space data. We present a post mortem validation study where we evaluate the ability of CS-DSI to approximate not only fully sampled DSI but also multi-shell acquisitions with high fidelity. Human brain samples are imaged with high-resolution DSI at 9.4T and with polarization-sensitive optical coherence tomography (PSOCT). The latter provides direct measurements of axonal orientations at microscopic resolutions, allowing us to evaluate the mesoscopic orientation estimates obtained from diffusion MRI, in terms of their angular error and the presence of spurious peaks. We test two fast, dictionary-based, L2-regularized algorithms for CS-DSI reconstruction. We find that, for a CS acceleration factor of R=3, i.e., an acquisition with 171 gradient directions, one of these methods is able to achieve both low angular error and low number of spurious peaks. With a scan length similar to that of high angular resolution multi-shell acquisition schemes, this CS-DSI approach is able to approximate both fully sampled DSI and multi-shell data with high accuracy. Thus it is suitable for orientation reconstruction and microstructural modeling techniques that require either grid- or shell-based acquisitions. We find that the signal-to-noise ratio (SNR) of the training data used to construct the dictionary can have an impact on the accuracy of CS-DSI, but that there is substantial robustness to loss of SNR in the test data. Finally, we show that, as the CS acceleration factor increases beyond R=3, the accuracy of these reconstruction methods degrade, either in terms of the angular error, or in terms of the number of spurious peaks. Our results provide useful benchmarks for the future development of even more efficient q-space acceleration techniques.
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Affiliation(s)
- Robert Jones
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA.
| | - Chiara Maffei
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Jean Augustinack
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Hui Wang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Berkin Bilgic
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anastasia Yendiki
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
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20
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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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21
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Hartmann K, Stein KP, Neyazi B, Sandalcioglu IE. Theranostic applications of optical coherence tomography in neurosurgery? Neurosurg Rev 2021; 45:421-427. [PMID: 34398385 PMCID: PMC8827310 DOI: 10.1007/s10143-021-01599-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 03/11/2021] [Accepted: 06/27/2021] [Indexed: 12/14/2022]
Abstract
In light of our own experiences, we value the existing literature to critically point out possible “near” future applications of optical coherence tomography (OCT) as an intraoperative neurosurgical guidance tool. “Pub Med”, “Cochrane Library”, “Crossref Metadata Search”, and “IEEE Xplore” databases as well as the search engine “Google Scholar” were screened for “optical coherence tomography + neurosurgery”, “optical coherence tomography + intraoperative imaging + neurosurgery”, and “microscope integrated optical coherence tomography + neurosurgery”. n = 51 articles related to the use of OCT as an imaging technique in the field of neurosurgery or neurosurgical research. n = 7 articles documented the intraoperative use of OCT in patients. n = 4 articles documented the use of microscope-integrated optical coherence tomography as a neurosurgical guidance tool. The Results demonstrate that OCT is the first imaging technique to study microanatomy in vivo. Postoperative analysis of intraoperative scans holds promise to enrich our physiological and pathophysiological understanding of the human brain. No data exists to prove that OCT-guided surgery minimizes perioperative morbidity or extends tumor resection. But results suggest that regular use of microscope-integrated OCT could increase security during certain critical microsurgical steps like, e.g., dural dissection at cavernous sinus, transtentorial approaches, or aneurysm clip placement. Endoscopy integration could aid surgery in regions which are not yet accessible to real-time imaging modalities like the ventricles or hypophysis. Theranostic instruments which combine OCT with laser ablation might gain importance in the emerging field of minimal invasive tumor surgery. OCT depicts vessel wall layers and its pathologies uniquely. Doppler OCT could further visualize blood flow in parallel. These abilities shed light on promising future applications in the field of vascular neurosurgery.
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Affiliation(s)
- Karl Hartmann
- Universitätsklinik Für Neurochirurgie, Otto-Von-Guericke-Universität Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Deutschland.
| | - Klaus-Peter Stein
- Universitätsklinik Für Neurochirurgie, Otto-Von-Guericke-Universität Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Deutschland
| | - Belal Neyazi
- Universitätsklinik Für Neurochirurgie, Otto-Von-Guericke-Universität Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Deutschland
| | - I Erol Sandalcioglu
- Universitätsklinik Für Neurochirurgie, Otto-Von-Guericke-Universität Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Deutschland
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22
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Dolganova IN, Aleksandrova PV, Nikitin PV, Alekseeva AI, Chernomyrdin NV, Musina GR, Beshplav ST, Reshetov IV, Potapov AA, Kurlov VN, Tuchin VV, Zaytsev KI. Capability of physically reasonable OCT-based differentiation between intact brain tissues, human brain gliomas of different WHO grades, and glioma model 101.8 from rats. BIOMEDICAL OPTICS EXPRESS 2020; 11:6780-6798. [PMID: 33282523 PMCID: PMC7687948 DOI: 10.1364/boe.409692] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 10/19/2020] [Accepted: 10/22/2020] [Indexed: 05/17/2023]
Abstract
Optical coherence tomography (OCT) of the ex vivo rat and human brain tissue samples is performed. The set of samples comprises intact white and gray matter, as well as human brain gliomas of the World Health Organization (WHO) Grades I-IV and glioma model 101.8 from rats. Analysis of OCT signals is aimed at comparing the physically reasonable properties of tissues, and determining the attenuation coefficient, parameter related to effective refractive index, and their standard deviations. Data analysis is based on the linear discriminant analysis and estimation of their dispersion in a four-dimensional principal component space. The results demonstrate the distinct contrast between intact tissues and low-grade gliomas and moderate contrast between intact tissues and high-grade gliomas. Particularly, the mean values of attenuation coefficient are 7.56±0.91, 3.96±0.98, and 5.71±1.49 mm-1 for human white matter, glioma Grade I, and glioblastoma, respectively. The significant variability of optical properties of high Grades and essential differences between rat and human brain tissues are observed. The dispersion of properties enlarges with increase of the glioma WHO Grade, which can be attributed to the growing heterogeneity of pathological brain tissues. The results of this study reveal the advantages and drawbacks of OCT for the intraoperative diagnosis of brain gliomas and compare its abilities separately for different grades of malignancy. The perspective of OCT to differentiate low-grade gliomas is highlighted by the low performance of the existing intraoperational methods and instruments.
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Affiliation(s)
- I. N. Dolganova
- Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia
- Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia
| | - P. V. Aleksandrova
- Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia
| | - P. V. Nikitin
- Burdenko Neurosurgery Institute, Moscow 125047, Russia
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
| | - A. I. Alekseeva
- Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia
- Research Institute of Human Morphology, Moscow 117418, Russia
| | - N. V. Chernomyrdin
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
| | - G. R. Musina
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
| | - S. T. Beshplav
- Burdenko Neurosurgery Institute, Moscow 125047, Russia
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
| | - I. V. Reshetov
- Institute for Cluster Oncology, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia
- Academy of Postgraduate Education FSCC FMBA, Moscow 125310, Russia
| | - A. A. Potapov
- Burdenko Neurosurgery Institute, Moscow 125047, Russia
| | - V. N. Kurlov
- Institute of Solid State Physics of the Russian Academy of Sciences, Chernogolovka 142432, Russia
- Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia
| | - V. V. Tuchin
- Saratov State University, Saratov 410012, Russia
- Institute of Precision Mechanics and Control of the Russian Academy of Sciences, Saratov 410028, Russia
- Tomsk State University, Tomsk 634050, Russia
| | - K. I. Zaytsev
- Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), Moscow 119991, Russia
- Prokhorov General Physics Institute of the Russian Academy of Sciences, Moscow 119991, Russia
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23
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Takemura H, Thiebaut de Schotten M. Perspectives given by structural connectivity bridge the gap between structure and function. Brain Struct Funct 2020; 225:1189-1192. [PMID: 32415413 PMCID: PMC7270985 DOI: 10.1007/s00429-020-02080-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka University, Suita-shi, Japan. .,Graduate School of Frontier Biosciences, Osaka University, Suita-shi, Japan.
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France.,Groupe D'Imagerie Neurofonctionnelle, Institut Des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
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24
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Takemura H, Palomero-Gallagher N, Axer M, Gräßel D, Jorgensen MJ, Woods R, Zilles K. Anatomy of nerve fiber bundles at micrometer-resolution in the vervet monkey visual system. eLife 2020; 9:e55444. [PMID: 32844747 PMCID: PMC7532002 DOI: 10.7554/elife.55444] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 08/22/2020] [Indexed: 12/11/2022] Open
Abstract
Although the primate visual system has been extensively studied, detailed spatial organization of white matter fiber tracts carrying visual information between areas has not been fully established. This is mainly due to the large gap between tracer studies and diffusion-weighted MRI studies, which focus on specific axonal connections and macroscale organization of fiber tracts, respectively. Here we used 3D polarization light imaging (3D-PLI), which enables direct visualization of fiber tracts at micrometer resolution, to identify and visualize fiber tracts of the visual system, such as stratum sagittale, inferior longitudinal fascicle, vertical occipital fascicle, tapetum and dorsal occipital bundle in vervet monkey brains. Moreover, 3D-PLI data provide detailed information on cortical projections of these tracts, distinction between neighboring tracts, and novel short-range pathways. This work provides essential information for interpretation of functional and diffusion-weighted MRI data, as well as revision of wiring diagrams based upon observations in the vervet visual system.
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Affiliation(s)
- Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, and Osaka UniversityOsakaJapan
- Graduate School of Frontier Biosciences, Osaka UniversityOsakaJapan
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH AachenAachenGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
| | - Markus Axer
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - David Gräßel
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Matthew J Jorgensen
- Department of Pathology, Section on Comparative Medicine, Wake Forest School of MedicineWinston-SalemUnited States
| | - Roger Woods
- Ahmanson-Lovelace Brain Mapping Center, Departments of Neurology and of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLALos AngelesUnited States
| | - Karl Zilles
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- JARA - Translational Brain MedicineAachenGermany
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25
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Guo SM, Yeh LH, Folkesson J, Ivanov IE, Krishnan AP, Keefe MG, Hashemi E, Shin D, Chhun BB, Cho NH, Leonetti MD, Han MH, Nowakowski TJ, Mehta SB. Revealing architectural order with quantitative label-free imaging and deep learning. eLife 2020; 9:e55502. [PMID: 32716843 PMCID: PMC7431134 DOI: 10.7554/elife.55502] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 07/24/2020] [Indexed: 01/21/2023] Open
Abstract
We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to predict fluorescence images of diverse cell and tissue structures. QLIPP images reveal anatomical regions and axon tract orientation in prenatal human brain tissue sections that are not visible using brightfield imaging. We report a variant of U-Net architecture, multi-channel 2.5D U-Net, for computationally efficient prediction of fluorescence images in three dimensions and over large fields of view. Further, we develop data normalization methods for accurate prediction of myelin distribution over large brain regions. We show that experimental defects in labeling the human tissue can be rescued with quantitative label-free imaging and neural network model. We anticipate that the proposed method will enable new studies of architectural order at spatial scales ranging from organelles to tissue.
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Affiliation(s)
| | - Li-Hao Yeh
- Chan Zuckerberg BiohubSan FranciscoUnited States
| | | | | | | | - Matthew G Keefe
- Department of Anatomy, University of California, San FranciscoSan FranciscoUnited States
| | - Ezzat Hashemi
- Department of Neurology, Stanford UniversityStanfordUnited States
| | - David Shin
- Department of Anatomy, University of California, San FranciscoSan FranciscoUnited States
| | | | - Nathan H Cho
- Chan Zuckerberg BiohubSan FranciscoUnited States
| | | | - May H Han
- Department of Neurology, Stanford UniversityStanfordUnited States
| | - Tomasz J Nowakowski
- Department of Anatomy, University of California, San FranciscoSan FranciscoUnited States
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26
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Jones R, Grisot G, Augustinack J, Magnain C, Boas DA, Fischl B, Wang H, Yendiki A. Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain. Neuroimage 2020; 214:116704. [PMID: 32151760 PMCID: PMC8488979 DOI: 10.1016/j.neuroimage.2020.116704] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 02/16/2020] [Accepted: 03/03/2020] [Indexed: 11/25/2022] Open
Abstract
In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 mm or smaller but degrades at 2 mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques.
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Affiliation(s)
- Robert Jones
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA, USA
| | | | - Jean Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA, USA
| | - Caroline Magnain
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA, USA
| | - David A Boas
- Neurophotonics Center, Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA, USA
| | - Hui Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA, USA
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA, USA.
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27
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Speckle modulation enables high-resolution wide-field human brain tumor margin detection and in vivo murine neuroimaging. Sci Rep 2019; 9:10388. [PMID: 31316099 PMCID: PMC6637128 DOI: 10.1038/s41598-019-45902-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 06/05/2019] [Indexed: 11/18/2022] Open
Abstract
Current in vivo neuroimaging techniques provide limited field of view or spatial resolution and often require exogenous contrast. These limitations prohibit detailed structural imaging across wide fields of view and hinder intraoperative tumor margin detection. Here we present a novel neuroimaging technique, speckle-modulating optical coherence tomography (SM-OCT), which allows us to image the brains of live mice and ex vivo human samples with unprecedented resolution and wide field of view using only endogenous contrast. The increased visibility provided by speckle elimination reveals white matter fascicles and cortical layer architecture in brains of live mice. To our knowledge, the data reported herein represents the highest resolution imaging of murine white matter structure achieved in vivo across a wide field of view of several millimeters. When applied to an orthotopic murine glioblastoma xenograft model, SM-OCT readily identifies brain tumor margins with resolution of approximately 10 μm. SM-OCT of ex vivo human temporal lobe tissue reveals fine structures including cortical layers and myelinated axons. Finally, when applied to an ex vivo sample of a low-grade glioma resection margin, SM-OCT is able to resolve the brain tumor margin. Based on these findings, SM-OCT represents a novel approach for intraoperative tumor margin detection and in vivo neuroimaging.
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28
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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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29
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Ex vivo visualization of the trigeminal pathways in the human brainstem using 11.7T diffusion MRI combined with microscopy polarized light imaging. Brain Struct Funct 2018; 224:159-170. [PMID: 30293214 PMCID: PMC6373363 DOI: 10.1007/s00429-018-1767-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Accepted: 10/02/2018] [Indexed: 01/12/2023]
Abstract
Classic anatomical atlases depict a contralateral hemispheral representation of each side of the face. Recently, however, a bilateral projection of each hemiface was hypothesized, based on animal studies that showed the coexistence of an additional trigeminothalamic tract sprouting from the trigeminal principal sensory nucleus that ascends ipsilaterally. This study aims to provide an anatomical substrate for the hypothesized bilateral projection. Three post-mortem human brainstems were scanned for anatomical and diffusion magnetic resonance imaging at 11.7T. The trigeminal tracts were delineated in each brainstem using track density imaging (TDI) and tractography. To evaluate the reconstructed tracts, the same brainstems were sectioned for polarized light imaging (PLI). Anatomical 11.7T MRI shows a dispersion of the trigeminal tract (tt) into a ventral and dorsal portion. This bifurcation was also seen on the TDI maps, tractography results and PLI images of all three specimens. Referring to a similar anatomic feature in primate brains, the dorsal and ventral tracts were named the dorsal and ventral trigeminothalamic tract (dtt and vtt), respectively. This study shows that both the dtt and vtt are present in humans, indicating that each hemiface has a bilateral projection, although the functional relevance of these tracts cannot be determined by the present anatomical study. If both tracts convey noxious stimuli, this could open up new insights into and treatments for orofacial pain in patients.
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30
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Lefebvre J, Delafontaine-Martel P, Pouliot P, Girouard H, Descoteaux M, Lesage F. Fully automated dual-resolution serial optical coherence tomography aimed at diffusion MRI validation in whole mouse brains. NEUROPHOTONICS 2018; 5:045004. [PMID: 30681668 PMCID: PMC6215086 DOI: 10.1117/1.nph.5.4.045004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 10/12/2018] [Indexed: 06/09/2023]
Abstract
An automated dual-resolution serial optical coherence tomography (2R-SOCT) scanner is developed. The serial histology system combines a low-resolution ( 25 μ m / voxel ) 3 × OCT with a high-resolution ( 1.5 μ m / voxel ) 40 × OCT to acquire whole mouse brains at low resolution and to target specific regions of interest (ROIs) at high resolution. The 40 × ROIs positions are selected either manually by the microscope operator or using an automated ROI positioning selection algorithm. Additionally, a multimodal and multiresolution registration pipeline is developed in order to align the 2R-SOCT data onto diffusion MRI (dMRI) data acquired in the same ex vivo mouse brains prior to automated histology. Using this imaging system, 3 whole mouse brains are imaged, and 250 high-resolution 40 × three-dimensional ROIs are acquired. The capability of this system to perform multimodal imaging studies is demonstrated by labeling the ROIs using a mouse brain atlas and by categorizing the ROIs based on their associated dMRI measures. This reveals a good correspondence of the tissue microstructure imaged by the high-resolution OCT with various dMRI measures such as fractional anisotropy, number of fiber orientations, apparent fiber density, orientation dispersion, and intracellular volume fraction.
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Affiliation(s)
- Joël Lefebvre
- École Polytechnique de Montréal, Laboratoire d’imagerie optique et moléculaire, Montreal, Canada
| | | | - Philippe Pouliot
- École Polytechnique de Montréal, Laboratoire d’imagerie optique et moléculaire, Montreal, Canada
- Université de Montréal, Research Centre, Montréal Heart Institute, Montreal, Canada
| | - Hélène Girouard
- Université de Montréal, Institut universitaire de gériatrie de Montréal, Montreal, Canada
| | - Maxime Descoteaux
- Université de Sherbrooke, Sherbrooke Connectivity Imaging Laboratory, Sherbrooke, Canada
| | - Frédéric Lesage
- École Polytechnique de Montréal, Laboratoire d’imagerie optique et moléculaire, Montreal, Canada
- Université de Montréal, Research Centre, Montréal Heart Institute, Montreal, Canada
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31
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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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32
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Wang SH, Lobier M, Siebenhühner F, Puoliväli T, Palva S, Palva JM. Hyperedge bundling: Data, source code, and precautions to modeling-accuracy bias to synchrony estimates. Data Brief 2018; 18:262-275. [PMID: 29896515 PMCID: PMC5996227 DOI: 10.1016/j.dib.2018.03.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 03/01/2018] [Accepted: 03/02/2018] [Indexed: 11/23/2022] Open
Abstract
It has not been well documented that MEG/EEG functional connectivity graphs estimated with zero-lag-free interaction metrics are severely confounded by a multitude of spurious interactions (SI), i.e., the false-positive "ghosts" of true interactions [1], [2]. These SI are caused by the multivariate linear mixing between sources, and thus they pose a severe challenge to the validity of connectivity analysis. Due to the complex nature of signal mixing and the SI problem, there is a need to intuitively demonstrate how the SI are discovered and how they can be attenuated using a novel approach that we termed hyperedge bundling. Here we provide a dataset with software with which the readers can perform simulations in order to better understand the theory and the solution to SI. We include the supplementary material of [1] that is not directly relevant to the hyperedge bundling per se but reflects important properties of the MEG source model and the functional connectivity graphs. For example, the gyri of dorsal-lateral cortices are the most accurately modeled areas; the sulci of inferior temporal, frontal and the insula have the least modeling accuracy. Importantly, we found the interaction estimates are heavily biased by the modeling accuracy between regions, which means the estimates cannot be straightforwardly interpreted as the coupling between brain regions. This raise a red flag that the conventional method of thresholding graphs by estimate values is rather suboptimal: because the measured topology of the graph reflects the geometric property of source-model instead of the cortical interactions under investigation.
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Affiliation(s)
- Sheng H. Wang
- Neuroscience Center, HiLife, University of Helsinki, Finland
- Doctoral Programme Brain & Mind, University of Helsinki, Finland
- BioMag laboratory, HUS Medical Imaging Center, Helsinki, Finland
| | - Muriel Lobier
- Neuroscience Center, HiLife, University of Helsinki, Finland
| | - Felix Siebenhühner
- Neuroscience Center, HiLife, University of Helsinki, Finland
- Doctoral Programme Brain & Mind, University of Helsinki, Finland
| | - Tuomas Puoliväli
- Neuroscience Center, HiLife, University of Helsinki, Finland
- Doctoral Programme Brain & Mind, University of Helsinki, Finland
| | - Satu Palva
- Neuroscience Center, HiLife, University of Helsinki, Finland
- BioMag laboratory, HUS Medical Imaging Center, Helsinki, Finland
| | - J. Matias Palva
- Neuroscience Center, HiLife, University of Helsinki, Finland
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