Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography
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 emer...
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| Format: | Article |
| Language: | English |
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Nature Publishing Group
2025-01-01
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| Series: | Light: Science & Applications |
| Online Access: | https://doi.org/10.1038/s41377-024-01658-0 |
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| author | Shiyi Cheng Shuaibin Chang Yunzhe Li Anna Novoseltseva Sunni Lin Yicun Wu Jiahui Zhu Ann C. McKee Douglas L. Rosene Hui Wang Irving J. Bigio David A. Boas Lei Tian |
| author_facet | Shiyi Cheng Shuaibin Chang Yunzhe Li Anna Novoseltseva Sunni Lin Yicun Wu Jiahui Zhu Ann C. McKee Douglas L. Rosene Hui Wang Irving J. Bigio David A. Boas Lei Tian |
| author_sort | Shiyi Cheng |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-891d9d597f2a4267b8f636f3069ad92c |
| institution | Kabale University |
| issn | 2047-7538 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Light: Science & Applications |
| spelling | doaj-art-891d9d597f2a4267b8f636f3069ad92c2025-01-26T12:53:15ZengNature Publishing GroupLight: Science & Applications2047-75382025-01-0114111910.1038/s41377-024-01658-0Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomographyShiyi Cheng0Shuaibin Chang1Yunzhe Li2Anna Novoseltseva3Sunni Lin4Yicun Wu5Jiahui Zhu6Ann C. McKee7Douglas L. Rosene8Hui Wang9Irving J. Bigio10David A. Boas11Lei Tian12Department of Electrical and Computer Engineering, Boston UniversityDepartment of Electrical and Computer Engineering, Boston UniversityDepartment of Electrical Engineering and Computer Sciences, University of CaliforniaDepartment of Biomedical Engineering, Boston UniversityDepartment of Electrical and Computer Engineering, Boston UniversityDepartment of Computer Science, Boston UniversityDepartment of Electrical and Computer Engineering, Boston UniversityBoston University Alzheimer’s Disease Research Center and CTE Center, Boston University School of MedicineDepartment of Anatomy & Neurobiology, Boston University School of MedicineDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalDepartment of Electrical and Computer Engineering, Boston UniversityDepartment of Electrical and Computer Engineering, Boston UniversityDepartment of Electrical and Computer Engineering, Boston UniversityAbstract 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.https://doi.org/10.1038/s41377-024-01658-0 |
| spellingShingle | Shiyi Cheng Shuaibin Chang Yunzhe Li Anna Novoseltseva Sunni Lin Yicun Wu Jiahui Zhu Ann C. McKee Douglas L. Rosene Hui Wang Irving J. Bigio David A. Boas Lei Tian Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography Light: Science & Applications |
| title | Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography |
| title_full | Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography |
| title_fullStr | Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography |
| title_full_unstemmed | Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography |
| title_short | Enhanced multiscale human brain imaging by semi-supervised digital staining and serial sectioning optical coherence tomography |
| title_sort | enhanced multiscale human brain imaging by semi supervised digital staining and serial sectioning optical coherence tomography |
| url | https://doi.org/10.1038/s41377-024-01658-0 |
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