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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. LIGHT, SCIENCE & APPLICATIONS 2025; 14:57. [PMID: 39833166 PMCID: PMC11746934 DOI: 10.1038/s41377-024-01658-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 09/29/2024] [Accepted: 10/11/2024] [Indexed: 01/22/2025]
Abstract
A major challenge in neuroscience is visualizing 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, which impedes accurate 3D reconstructions. The emerging label-free serial sectioning optical coherence tomography (S-OCT) technique offers uniform 3D imaging capability across samples but has poor histological interpretability despite its sensitivity to cortical features. Here, we present a novel 3D imaging framework that combines S-OCT with a deep-learning digital staining (DS) model. This enhanced imaging modality integrates high-throughput 3D imaging, low sample variability and high interpretability, making it suitable for 3D histology studies. We develop a novel semi-supervised learning technique to facilitate DS model training on weakly paired images for translating S-OCT to Gallyas silver staining. We demonstrate DS on various human cerebral cortex samples, achieving consistent staining quality and enhancing contrast across cortical layer boundaries. Additionally, we show that DS preserves geometry in 3D on cubic-centimeter tissue blocks, allowing for visualization of meso-scale vessel networks in the white matter. We believe that our technique has 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, Boston, MA, 02215, USA
| | - Shuaibin Chang
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
| | - Yunzhe Li
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, 94720, USA
| | - Anna Novoseltseva
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Sunni Lin
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Yicun Wu
- Department of Computer Science, Boston University, Boston, MA, 02215, USA
| | - Jiahui Zhu
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
| | - Ann C McKee
- Boston University Alzheimer's Disease Research Center and CTE Center, Boston University School of Medicine, Boston, MA, 02118, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
- VA Boston Healthcare System, U.S. Department of Veteran Affairs, Boston, MA, 02130, 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 School of Medicine, Boston, MA, USA
| | - Hui Wang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, 02129, USA
| | - Irving J Bigio
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Neurophotonics Center, Boston University, Boston, MA, 02215, USA
| | - David A Boas
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
- Neurophotonics Center, Boston University, Boston, MA, 02215, USA
| | - Lei Tian
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
- Neurophotonics Center, Boston University, Boston, MA, 02215, USA.
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2
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He Y, Qin MZ, Cao K, Zhang YP, Jiao X, Zhang Z, Wang GH, Liu Q, Liu Q, Ma JB, Jiang X, Guo CX. Assessment of the impact of low-density lipoprotein cholesterol on retinal vessels using optical coherence tomography angiography. Lipids Health Dis 2024; 23:301. [PMID: 39285295 PMCID: PMC11403859 DOI: 10.1186/s12944-024-02287-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2024] [Accepted: 09/07/2024] [Indexed: 09/20/2024] Open
Abstract
BACKGROUND Low-density lipoprotein cholesterol (LDL-C) is acknowledged as an independent risk factor (IRF) for atherosclerotic cardiovascular disease. Nevertheless, studies on the impact of LDL-C on microvasculature are still scarce. The retina, abundant in microvasculature, can now be examined for microvascular alterations through the novel, non-invasive, and quantitative optical coherence tomography angiography (OCTA) technique. METHODS In this cross-sectional study, 243 patients from the geriatric department were recruited (between December 2022 and December 2023). Individuals were classified into four groups based on their LDL-C levels: Group 1 (≤ 1.8 mmol/L), Group 2 (> 1.8 mmol/L to ≤ 2.6 mmol/L), Group 3 (> 2.6 mmol/L to ≤ 3.4 mmol/L), and Group 4 (> 3.4 mmol/L). The OCTA results including retinal vessel density (VD), foveal avascular zone (FAZ) area, macula thickness, and retinal nerve fiber layer (RNFL) thickness were contrasted across these groups. T-tests, analysis of variance, Welch's tests, or rank-sum tests were employed for statistical comparisons. In cases where significant differences between groups were found, post-hoc multiple comparisons or rank-sum tests were performed for pairwise group comparisons. Spearman's correlation coefficient was employed to perform bivariate correlation analysis to evaluate the relationship between LDL-C levels and various OCTA measurements. Multivariable regression analysis was used to evaluate the association between LDL-C levels and various OCTA measurements. Linear regression analysis or mixed-effects linear models were applied. RESULTS It was discovered that individuals with LDL-C levels exceeding 2.6 mmol/L (Groups 3 and 4) exhibited reduced VD in the retina, encompassing both the optic disc and macular regions, compared to those with LDL-C levels at or below 2.6 mmol/L (Groups 1 and 2). A negative correlation among LDL-C levels and retinal VD was identified, with r values spanning from - 0.228 to -0.385. Further regression analysis presented β values between - 0.954 and - 2.378. Additionally, no notable disparities were detected among the groups regarding FAZ area, macular thickness, and RNFL thickness. CONCLUSIONS The outcomes of this study suggest that elevated LDL-C levels constitute an IRF for decreased VD across the entire retina. TRIAL REGISTRATION NCT05644548, December 1, 2022.
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Affiliation(s)
- Yu He
- Cardiovascular Center, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang Street, Dongcheng District, Beijing, 100730, People's Republic of China
- Department of Geriatrics, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Ming-Zhao Qin
- Department of Geriatrics, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Kai Cao
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Yong-Peng Zhang
- Department of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Xuan Jiao
- Department of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Zheng Zhang
- Department of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Guo-Hong Wang
- Department of Geriatrics, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Qi Liu
- Department of Geriatrics, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Qian Liu
- Department of Geriatrics, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Jin-Bao Ma
- Department of Geriatrics, Beijing Tongren Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Xue Jiang
- Cardiovascular Center, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang Street, Dongcheng District, Beijing, 100730, People's Republic of China
| | - Cai-Xia Guo
- Cardiovascular Center, Beijing Tongren Hospital, Capital Medical University, No. 1 Dongjiaominxiang Street, Dongcheng District, Beijing, 100730, People's Republic of China.
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Fan Y, Gao E, Liu S, Guo R, Dong G, Tang X, Liao H, Gao T. RMAP-ResNet: Segmentation of brain tumor OCT images using residual multicore attention pooling networks for intelligent minimally invasive theranostics. Biomed Signal Process Control 2024; 90:105805. [DOI: 10.1016/j.bspc.2023.105805] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/24/2025]
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4
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Achkasova K, Kukhnina L, Moiseev A, Kiseleva E, Bogomolova A, Loginova M, Gladkova N. Detection of acute and early-delayed radiation-induced changes in the white matter of the rat brain based on numerical processing of optical coherence tomography data. JOURNAL OF BIOPHOTONICS 2024; 17:e202300458. [PMID: 38253332 DOI: 10.1002/jbio.202300458] [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: 11/03/2023] [Revised: 12/25/2023] [Accepted: 01/11/2024] [Indexed: 01/24/2024]
Abstract
Detection of radiation-induced changes of the brain white matter is important for brain neoplasms repeated surgery. We investigated the influence of irradiation on the scattering properties of the white matter using optical coherence tomography (OCT). Healthy Wistar rats undergone the irradiation of the brain right hemisphere. At seven time points from the irradiation procedure (2-14 weeks), an ex vivo OCT study was performed with subsequent calculation of attenuation coefficient values in the corpus callosum followed by immunohistochemical analysis. As a result, we discovered acute and early-delayed changes characterized by the edema of different severity, accompanied by a statistically significant decrease in attenuation coefficient values. In particular, these changes were found at 2 weeks after irradiation in the irradiated hemisphere, while at 6- and 12-week time points they affected both irradiated and contralateral hemisphere. Thus, radiation-induced changes occurring in white matter during the first 3 months after irradiation can be detected by OCT.
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Affiliation(s)
- Ksenia Achkasova
- Research Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Liudmila Kukhnina
- Research Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Alexander Moiseev
- Laboratory of Highly Sensitive Optical Measurements, Institute of Applied Physics of Russian Academy of Sciences, Nizhny Novgorod, Russia
| | - Elena Kiseleva
- Research Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Alexandra Bogomolova
- Research Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Maria Loginova
- Research Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
| | - Natalia Gladkova
- Research Institute of Experimental Oncology and Biomedical Technologies, Privolzhsky Research Medical University, Nizhny Novgorod, Russia
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5
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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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6
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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: 4] [Impact Index Per Article: 2.0] [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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7
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Luo H, Li S, Kou S, Lin Y, Hagemann IS, Zhu Q. Enhanced 3D visualization of human fallopian tube morphology using a miniature optical coherence tomography catheter. BIOMEDICAL OPTICS EXPRESS 2023; 14:3225-3233. [PMID: 37497483 PMCID: PMC10368054 DOI: 10.1364/boe.489708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/10/2023] [Accepted: 05/29/2023] [Indexed: 07/28/2023]
Abstract
We demonstrate the use of our miniature optical coherence tomography catheter to acquire three-dimensional human fallopian tube images. Images of the fallopian tube's tissue morphology, vasculature, and tissue heterogeneity distribution are enhanced by adaptive thresholding, masking, and intensity inverting, making it easier to differentiate malignant tissue from normal tissue. The results show that normal fallopian tubes tend to have rich vasculature accompanied by a patterned tissue scattering background, features that do not appear in malignant cases. This finding suggests that miniature OCT catheters may have great potential for fast optical biopsy of the fallopian tube.
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Affiliation(s)
- Hongbo Luo
- Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Shuying Li
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Sitai Kou
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Yixiao Lin
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Ian S. Hagemann
- Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, MO 63130, USA
- Department of Obstetrics & Gynecology, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Quing Zhu
- Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
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8
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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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