1
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Roh TT, Alex A, Chandramouleeswaran PM, Sorrells JE, Ho A, Iyer RR, Spillman DR, Marjanovic M, Ekert JE, Sridharan B, Prabhakarpandian B, Hood SR, Boppart SA. Predicting DNA damage response in non-small cell lung cancer organoids via simultaneous label-free autofluorescence multiharmonic microscopy. Redox Biol 2024; 75:103280. [PMID: 39083897 PMCID: PMC11340607 DOI: 10.1016/j.redox.2024.103280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 07/16/2024] [Accepted: 07/20/2024] [Indexed: 08/02/2024] Open
Abstract
The DNA damage response (DDR) is a fundamental readout for evaluating efficacy of cancer therapeutics, many of which target DNA associated processes. Current techniques to evaluate DDR rely on immunostaining for phosphorylated histone H2AX (γH2AX), which is an indicator of DNA double-strand breaks. While γH2AX immunostaining can provide a snapshot of DDR in fixed cell and tissue samples, this method is technically cumbersome due to temporal monitoring of DDR requiring timepoint replicates, extensive assay development efforts for 3D cell culture samples such as organoids, and time-consuming protocols for γH2AX immunostaining and its evaluation. The goal of this current study is to reduce overall burden on assay duration and development in non-small cell lung cancer (NSCLC) organoids by leveraging label-free multiphoton imaging. In this study, simultaneous label-free autofluorescence multiharmonic (SLAM) microscopy was used to provide rich intracellular information based on endogenous contrasts. SLAM microscopy enables imaging of live samples eliminating the need to generate sacrificial sample replicates and has improved image acquisition in 3D space over conventional confocal microscopy. Predictive modeling between label-free SLAM microscopy and γH2AX immunostained images confirmed strong correlation between SLAM image features and γH2AX signal. Across multiple DNA targeting chemotherapeutics and multiple patient-derived NSCLC organoid lines, the optical redox ratio and third harmonic generation channels were used to robustly predict DDR. Imaging via SLAM microscopy can be used to more rapidly predict DDR in live 3D NSCLC organoids with minimal sample handling and without labeling.
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Affiliation(s)
- Terrence T Roh
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; In Vitro In Vivo Translation, GSK plc, Collegeville, PA, 19426, USA
| | - Aneesh Alex
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; In Vitro In Vivo Translation, GSK plc, Collegeville, PA, 19426, USA
| | | | - Janet E Sorrells
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Alexander Ho
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Rishyashring R Iyer
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Darold R Spillman
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; NIH/NIBIB Center for Label-free Imaging and Multi-scale Biophotonics (CLIMB), University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Marina Marjanovic
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; NIH/NIBIB Center for Label-free Imaging and Multi-scale Biophotonics (CLIMB), University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jason E Ekert
- In Vitro In Vivo Translation, GSK plc, Collegeville, PA, 19426, USA
| | | | | | - Steve R Hood
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; In Vitro In Vivo Translation, GSK plc, Stevenage, SG1 2NY, UK
| | - Stephen A Boppart
- GSK Center for Optical Molecular Imaging, Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; Cancer Center at Illinois, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA; NIH/NIBIB Center for Label-free Imaging and Multi-scale Biophotonics (CLIMB), University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
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2
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Iyer RR, Applegate CC, Arogundade OH, Bangru S, Berg IC, Emon B, Porras-Gomez M, Hsieh PH, Jeong Y, Kim Y, Knox HJ, Moghaddam AO, Renteria CA, Richard C, Santaliz-Casiano A, Sengupta S, Wang J, Zambuto SG, Zeballos MA, Pool M, Bhargava R, Gaskins HR. Inspiring a convergent engineering approach to measure and model the tissue microenvironment. Heliyon 2024; 10:e32546. [PMID: 38975228 PMCID: PMC11226808 DOI: 10.1016/j.heliyon.2024.e32546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 05/22/2024] [Accepted: 06/05/2024] [Indexed: 07/09/2024] Open
Abstract
Understanding the molecular and physical complexity of the tissue microenvironment (TiME) in the context of its spatiotemporal organization has remained an enduring challenge. Recent advances in engineering and data science are now promising the ability to study the structure, functions, and dynamics of the TiME in unprecedented detail; however, many advances still occur in silos that rarely integrate information to study the TiME in its full detail. This review provides an integrative overview of the engineering principles underlying chemical, optical, electrical, mechanical, and computational science to probe, sense, model, and fabricate the TiME. In individual sections, we first summarize the underlying principles, capabilities, and scope of emerging technologies, the breakthrough discoveries enabled by each technology and recent, promising innovations. We provide perspectives on the potential of these advances in answering critical questions about the TiME and its role in various disease and developmental processes. Finally, we present an integrative view that appreciates the major scientific and educational aspects in the study of the TiME.
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Affiliation(s)
- Rishyashring R. Iyer
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Catherine C. Applegate
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Opeyemi H. Arogundade
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Sushant Bangru
- Department of Biochemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ian C. Berg
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Bashar Emon
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Marilyn Porras-Gomez
- Department of Materials Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Pei-Hsuan Hsieh
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Yoon Jeong
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Yongdeok Kim
- Department of Materials Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Hailey J. Knox
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Amir Ostadi Moghaddam
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Carlos A. Renteria
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Craig Richard
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ashlie Santaliz-Casiano
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Sourya Sengupta
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jason Wang
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Samantha G. Zambuto
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Maria A. Zeballos
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Marcia Pool
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Rohit Bhargava
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemical and Biochemical Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- NIH/NIBIB P41 Center for Label-free Imaging and Multiscale Biophotonics (CLIMB), University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - H. Rex Gaskins
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Animal Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Biomedical and Translational Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Pathobiology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
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3
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Zhou W, Liu D, Fang T, Chen X, Jia H, Tian X, Hao C, Yue S. Rapid and Precise Diagnosis of Retroperitoneal Liposarcoma with Deep-Learned Label-Free Molecular Microscopy. Anal Chem 2024; 96:9353-9361. [PMID: 38810149 DOI: 10.1021/acs.analchem.3c05417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
The retroperitoneal liposarcoma (RLPS) is a rare malignancy whose only curative therapy is surgical resection. However, well-differentiated liposarcomas (WDLPSs), one of its most common types, can hardly be distinguished from normal fat during operation without an effective margin assessment method, jeopardizing the prognosis severely with a high recurrence risk. Here, we combined dual label-free nonlinear optical modalities, stimulated Raman scattering (SRS) microscopy and second harmonic generation (SHG) microscopy, to image two predominant tissue biomolecules, lipids and collagen fibers, in 35 RLPSs and 34 normal fat samples collected from 35 patients. The produced dual-modal tissue images were used for RLPS diagnosis based on deep learning. Dramatically decreasing lipids and increasing collagen fibers during tumor progression were reflected. A ResNeXt101-based model achieved 94.7% overall accuracy and 0.987 mean area under the ROC curve (AUC) in differentiating among normal fat, WDLPSs, and dedifferentiated liposarcomas (DDLPSs). In particular, WDLPSs were detected with 94.1% precision and 84.6% sensitivity superior to existing methods. The ablation experiment showed that such performance was attributed to both SRS and SHG microscopies, which increased the sensitivity of recognizing WDLPS by 16.0 and 3.6%, respectively. Furthermore, we utilized this model on RLPS margins to identify the tumor infiltration. Our method holds great potential for accurate intraoperative liposarcoma detection.
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Affiliation(s)
- Wanhui Zhou
- Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Daoning Liu
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma Center, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Tinghe Fang
- Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Xun Chen
- Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
- School of Engineering Medicine, Beihang University, Beijing 100191, China
| | - Hao Jia
- Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Xiuyun Tian
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma Center, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Chunyi Hao
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery/Sarcoma Center, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Shuhua Yue
- Key Laboratory of Biomechanics and Mechanobiology (Beihang University), Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
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4
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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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5
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Sánchez-Hernández A, Polleys CM, Georgakoudi I. Formalin fixation and paraffin embedding interfere with the preservation of optical metabolic assessments based on endogenous NAD(P)H and FAD two-photon excited fluorescence. BIOMEDICAL OPTICS EXPRESS 2023; 14:5238-5253. [PMID: 37854574 PMCID: PMC10581792 DOI: 10.1364/boe.498297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/23/2023] [Accepted: 08/30/2023] [Indexed: 10/20/2023]
Abstract
Endogenous NAD(P)H and FAD two-photon excited fluorescence (TPEF) images provide functional metabolic information with high spatial resolution for a wide range of living specimens. Preservation of metabolic function optical metrics upon fixation would facilitate studies which assess the impact of metabolic changes in the context of numerous diseases. However, robust assessments of the impact of formalin fixation, paraffin embedding, and sectioning on the preservation of optical metabolic readouts are lacking. Here, we evaluate intensity and lifetime images at excitation/emission settings optimized for NAD(P)H and FAD TPEF detection from freshly excised murine oral epithelia and corresponding bulk and sectioned fixed tissues. We find that fixation impacts the overall intensity as well as the intensity fluctuations of the images acquired. Accordingly, the depth-dependent variations of the optical redox ratio (defined as FAD/(NAD(P)H + FAD)) across squamous epithelia are not preserved following fixation. This is consistent with significant changes in the 755 nm excited spectra, which reveal broadening upon fixation and additional distortions upon paraffin embedding and sectioning. Analysis of fluorescence lifetime images acquired for excitation/emission settings optimized for NAD(P)H TPEF detection indicate that fixation alters the long lifetime of the observed fluorescence and the long lifetime intensity fraction. These parameters as well as the short TPEF lifetime are significantly modified upon embedding and sectioning. Thus, our studies highlight that the autofluorescence products formed during formalin fixation, paraffin embedding and sectioning overlap highly with NAD(P)H and FAD emission and limit the potential to utilize such tissues to assess metabolic activity.
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Affiliation(s)
| | | | - Irene Georgakoudi
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
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6
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Martell MT, Haven NJM, Cikaluk BD, Restall BS, McAlister EA, Mittal R, Adam BA, Giannakopoulos N, Peiris L, Silverman S, Deschenes J, Li X, Zemp RJ. Deep learning-enabled realistic virtual histology with ultraviolet photoacoustic remote sensing microscopy. Nat Commun 2023; 14:5967. [PMID: 37749108 PMCID: PMC10519961 DOI: 10.1038/s41467-023-41574-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 09/11/2023] [Indexed: 09/27/2023] Open
Abstract
The goal of oncologic surgeries is complete tumor resection, yet positive margins are frequently found postoperatively using gold standard H&E-stained histology methods. Frozen section analysis is sometimes performed for rapid intraoperative margin evaluation, albeit with known inaccuracies. Here, we introduce a label-free histological imaging method based on an ultraviolet photoacoustic remote sensing and scattering microscope, combined with unsupervised deep learning using a cycle-consistent generative adversarial network for realistic virtual staining. Unstained tissues are scanned at rates of up to 7 mins/cm2, at resolution equivalent to 400x digital histopathology. Quantitative validation suggests strong concordance with conventional histology in benign and malignant prostate and breast tissues. In diagnostic utility studies we demonstrate a mean sensitivity and specificity of 0.96 and 0.91 in breast specimens, and respectively 0.87 and 0.94 in prostate specimens. We also find virtual stain quality is preferred (P = 0.03) compared to frozen section analysis in a blinded survey of pathologists.
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Affiliation(s)
- Matthew T Martell
- Department of Electrical and Computer Engineering, University of Alberta, 116 Street & 85 Avenue, Edmonton, AB, T6G 2R3, Canada
| | - Nathaniel J M Haven
- Department of Electrical and Computer Engineering, University of Alberta, 116 Street & 85 Avenue, Edmonton, AB, T6G 2R3, Canada
| | - Brendyn D Cikaluk
- Department of Electrical and Computer Engineering, University of Alberta, 116 Street & 85 Avenue, Edmonton, AB, T6G 2R3, Canada
| | - Brendon S Restall
- Department of Electrical and Computer Engineering, University of Alberta, 116 Street & 85 Avenue, Edmonton, AB, T6G 2R3, Canada
| | - Ewan A McAlister
- Department of Electrical and Computer Engineering, University of Alberta, 116 Street & 85 Avenue, Edmonton, AB, T6G 2R3, Canada
| | - Rohan Mittal
- Department of Laboratory Medicine and Pathology, University of Alberta, 11405 87 Avenue NW, Edmonton, AB, T6G 1C9, Canada
| | - Benjamin A Adam
- Department of Laboratory Medicine and Pathology, University of Alberta, 11405 87 Avenue NW, Edmonton, AB, T6G 1C9, Canada
| | - Nadia Giannakopoulos
- Department of Laboratory Medicine and Pathology, University of Alberta, 11405 87 Avenue NW, Edmonton, AB, T6G 1C9, Canada
| | - Lashan Peiris
- Department of Surgery, University of Alberta, 8440 - 112 Street, Edmonton, AB, T6G 2B7, Canada
| | - Sveta Silverman
- Department of Laboratory Medicine and Pathology, University of Alberta, 11405 87 Avenue NW, Edmonton, AB, T6G 1C9, Canada
| | - Jean Deschenes
- Department of Laboratory Medicine and Pathology, University of Alberta, 11405 87 Avenue NW, Edmonton, AB, T6G 1C9, Canada
| | - Xingyu Li
- Department of Electrical and Computer Engineering, University of Alberta, 116 Street & 85 Avenue, Edmonton, AB, T6G 2R3, Canada
| | - Roger J Zemp
- Department of Electrical and Computer Engineering, University of Alberta, 116 Street & 85 Avenue, Edmonton, AB, T6G 2R3, Canada.
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7
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Sánchez-Hernández A, Polleys CM, Georgakoudi I. Formalin fixation and paraffin embedding interfere with preservation of optical metabolic assessments based on endogenous NAD(P)H and FAD two photon excited fluorescence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.16.545363. [PMID: 37398103 PMCID: PMC10312786 DOI: 10.1101/2023.06.16.545363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Endogenous NAD(P)H and FAD two-photon excited fluorescence (TPEF) images provide functional metabolic information with high spatial resolution for a wide range of living specimens. Preservation of metabolic function optical metrics upon fixation would facilitate studies which assess the impact of metabolic changes in the context of numerous diseases. However, robust assessments of the impact of formalin fixation, paraffin embedding, and sectioning on the preservation of optical metabolic readouts are lacking. Here, we evaluate intensity and lifetime images at excitation/emission settings optimized for NAD(P)H and FAD TPEF detection from freshly excised murine oral epithelia and corresponding bulk and sectioned fixed tissues. We find that fixation impacts the overall intensity as well as the intensity fluctuations of the images acquired. Accordingly, the depth-dependent variations of the optical redox ratio (defined as FAD/(NAD(P)H + FAD)) across squamous epithelia are not preserved following fixation. This is consistent with significant changes in the 755 nm excited spectra, which reveal broadening upon fixation and additional distortions upon paraffin embedding and sectioning. Analysis of fluorescence lifetime images acquired for excitation/emission settings optimized for NAD(P)H TPEF detection indicate that fixation alters the long lifetime of the observed fluorescence and the long lifetime intensity fraction. These parameters as well as the short TPEF lifetime are significantly modified upon embedding and sectioning. Thus, our studies highlight that the autofluorescence products formed during formalin fixation, paraffin embedding and sectioning overlap highly with NAD(P)H and FAD emission and limit the potential to utilize such tissues to assess metabolic activity.
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Affiliation(s)
| | | | - Irene Georgakoudi
- Department of Biomedical Engineering, Tufts University, Medford, MA, US
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8
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Laurino A, Franceschini A, Pesce L, Cinci L, Montalbano A, Mazzamuto G, Sancataldo G, Nesi G, Costantini I, Silvestri L, Pavone FS. A Guide to Perform 3D Histology of Biological Tissues with Fluorescence Microscopy. Int J Mol Sci 2023; 24:ijms24076747. [PMID: 37047724 PMCID: PMC10094801 DOI: 10.3390/ijms24076747] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 04/09/2023] Open
Abstract
The analysis of histological alterations in all types of tissue is of primary importance in pathology for highly accurate and robust diagnosis. Recent advances in tissue clearing and fluorescence microscopy made the study of the anatomy of biological tissue possible in three dimensions. The combination of these techniques with classical hematoxylin and eosin (H&E) staining has led to the birth of three-dimensional (3D) histology. Here, we present an overview of the state-of-the-art methods, highlighting the optimal combinations of different clearing methods and advanced fluorescence microscopy techniques for the investigation of all types of biological tissues. We employed fluorescence nuclear and eosin Y staining that enabled us to obtain hematoxylin and eosin pseudo-coloring comparable with the gold standard H&E analysis. The computational reconstructions obtained with 3D optical imaging can be analyzed by a pathologist without any specific training in volumetric microscopy, paving the way for new biomedical applications in clinical pathology.
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Affiliation(s)
- Annunziatina Laurino
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy
| | - Alessandra Franceschini
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy
| | - Luca Pesce
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy
| | - Lorenzo Cinci
- Department of Experimental and Clinical Biomedical Sciences, Radiodiagnostic Unit n. 2, Careggi University Hospital, 50134 Florence, Italy
| | - Alberto Montalbano
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Neurofarba Section of Pharmacology and Toxicology, University of Florence, 50139 Florence, Italy
| | - Giacomo Mazzamuto
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy
- National Research Council—National Institute of Optics (CNR-INO), 50125 Sesto Fiorentino, Italy
| | - Giuseppe Sancataldo
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy
| | - Gabriella Nesi
- Department of Health Sciences, University of Florence, 50139 Florence, Italy
| | - Irene Costantini
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- National Research Council—National Institute of Optics (CNR-INO), 50125 Sesto Fiorentino, Italy
- Department of Biology, University of Florence, 50019 Florence, Italy
| | - Ludovico Silvestri
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy
- National Research Council—National Institute of Optics (CNR-INO), 50125 Sesto Fiorentino, Italy
| | - Francesco Saverio Pavone
- European Laboratory for Non-linear Spectroscopy, LENS, 50019 Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy
- National Research Council—National Institute of Optics (CNR-INO), 50125 Sesto Fiorentino, Italy
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9
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Ecclestone BR, Bell K, Sparkes S, Dinakaran D, Mackey JR, Haji Reza P. Label-free complete absorption microscopy using second generation photoacoustic remote sensing. Sci Rep 2022; 12:8464. [PMID: 35589763 PMCID: PMC9120477 DOI: 10.1038/s41598-022-11235-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 04/14/2022] [Indexed: 11/24/2022] Open
Abstract
In the past decades, absorption modalities have emerged as powerful tools for label-free functional and structural imaging of cells and tissues. Many biomolecules present unique absorption spectra providing chromophore-specific information on properties such as chemical bonding, and sample composition. As chromophores absorb photons the absorbed energy is emitted as photons (radiative relaxation) or converted to heat and under specific conditions pressure (non-radiative relaxation). Modalities like fluorescence microscopy may capture radiative relaxation to provide contrast, while modalities like photoacoustic microscopy may leverage non-radiative heat and pressures. Here we show an all-optical non-contact total-absorption photoacoustic remote sensing (TA-PARS) microscope, which can capture both radiative and non-radiative absorption effects in a single acquisition. The TA-PARS yields an absorption metric proposed as the quantum efficiency ratio (QER), which visualizes a biomolecule’s proportional radiative and non-radiative absorption response. The TA-PARS provides label-free visualization of a range of biomolecules enabling convincing analogues to traditional histochemical staining of tissues, effectively providing label-free Hematoxylin and Eosin (H&E)-like visualizations. These findings establish an effective all-optical non-contact total-absorption microscope for label-free inspection of biological materials.
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Affiliation(s)
- Benjamin R Ecclestone
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada.,IllumiSonics Inc, 22 King Street South, Suite 300, Waterloo, ON, N2J 1N8, Canada
| | - Kevan Bell
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada.,IllumiSonics Inc, 22 King Street South, Suite 300, Waterloo, ON, N2J 1N8, Canada
| | - Sarah Sparkes
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada
| | - Deepak Dinakaran
- Department of Oncology, Cross Cancer Institute, University of Alberta, 116 St & 85 Ave, Edmonton, AB, T6G 2V1, Canada
| | - John R Mackey
- Department of Oncology, Cross Cancer Institute, University of Alberta, 116 St & 85 Ave, Edmonton, AB, T6G 2V1, Canada
| | - Parsin Haji Reza
- PhotoMedicine Labs, Department of System Design Engineering, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada.
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10
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Iyer RR, Sorrells JE, Yang L, Chaney EJ, Spillman DR, Tibble BE, Renteria CA, Tu H, Žurauskas M, Marjanovic M, Boppart SA. Label-free metabolic and structural profiling of dynamic biological samples using multimodal optical microscopy with sensorless adaptive optics. Sci Rep 2022; 12:3438. [PMID: 35236862 PMCID: PMC8891278 DOI: 10.1038/s41598-022-06926-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 02/01/2022] [Indexed: 01/21/2023] Open
Abstract
Label-free optical microscopy has matured as a noninvasive tool for biological imaging; yet, it is criticized for its lack of specificity, slow acquisition and processing times, and weak and noisy optical signals that lead to inaccuracies in quantification. We introduce FOCALS (Fast Optical Coherence, Autofluorescence Lifetime imaging, and Second harmonic generation) microscopy capable of generating NAD(P)H fluorescence lifetime, second harmonic generation (SHG), and polarization-sensitive optical coherence microscopy (OCM) images simultaneously. Multimodal imaging generates quantitative metabolic and morphological profiles of biological samples in vitro, ex vivo, and in vivo. Fast analog detection of fluorescence lifetime and real-time processing on a graphical processing unit enables longitudinal imaging of biological dynamics. We detail the effect of optical aberrations on the accuracy of FLIM beyond the context of undistorting image features. To compensate for the sample-induced aberrations, we implemented a closed-loop single-shot sensorless adaptive optics solution, which uses computational adaptive optics of OCM for wavefront estimation within 2 s and improves the quality of quantitative fluorescence imaging in thick tissues. Multimodal imaging with complementary contrasts improves the specificity and enables multidimensional quantification of the optical signatures in vitro, ex vivo, and in vivo, fast acquisition and real-time processing improve imaging speed by 4-40 × while maintaining enough signal for quantitative nonlinear microscopy, and adaptive optics improves the overall versatility, which enable FOCALS microscopy to overcome the limits of traditional label-free imaging techniques.
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Affiliation(s)
- Rishyashring R. Iyer
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Janet E. Sorrells
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Lingxiao Yang
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Eric J. Chaney
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Darold R. Spillman
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Brian E. Tibble
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991The School of Molecular and Cellular Biology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Carlos A. Renteria
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Haohua Tu
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Mantas Žurauskas
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Marina Marjanovic
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Stephen A. Boppart
- grid.35403.310000 0004 1936 9991Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, USA ,grid.35403.310000 0004 1936 9991Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, USA
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11
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Wang X, Zhang D, Zhang X, Xing Y, Wu J, Sui X, Huang X, Chang G, Li L. Application of Multiphoton Microscopic Imaging in Study of Gastric Cancer. Technol Cancer Res Treat 2022; 21:15330338221133244. [PMID: 36379591 PMCID: PMC9676310 DOI: 10.1177/15330338221133244] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2024] Open
Abstract
Multiphoton microscopy (MPM) imaging relies on the nonlinear interaction between ultrashort optical pulses and the samples to achieve image contrast. Featuring larger penetration depth, less phototoxicity, 3-dimensional sectioning capability, no need for labeling, MPM become a powerful medical imaging technique that can identify structural characteristics of tissues at the cellular and subcellular levels. In this review paper, we introduce the working principle of MPM imaging, present the current results of MPM imaging applied to the study of gastric tumors, and discuss the future prospects of this interdisciplinary research field.
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Affiliation(s)
- Xiaoying Wang
- Strategic Support Force Medical Center, Beijing, China
| | - Di Zhang
- Ningxia Jingyuan County People's Hospital, Ningxia, China
| | - Xiaochun Zhang
- General Hospital of Ningxia Medical University, Ningxia, China
| | - Yuting Xing
- Institute of Physics, Chinese Academy of Sciences, Beijing, China
| | - Jihua Wu
- Strategic Support Force Medical Center, Beijing, China
| | - Xinke Sui
- Strategic Support Force Medical Center, Beijing, China
| | - Xin Huang
- Strategic Support Force Medical Center, Beijing, China
| | - Guoqing Chang
- Institute of Physics, Chinese Academy of Sciences, Beijing, China
| | - Lianyong Li
- Strategic Support Force Medical Center, Beijing, China
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12
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Lin Y, Lin H, Zhu X, Chen G. Three-dimensional characterizations of two-photon excitation fluorescence images of elastic fibers affected by cutaneous scar duration. Quant Imaging Med Surg 2021; 11:3584-3594. [PMID: 34341733 DOI: 10.21037/qims-20-1051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 03/18/2021] [Indexed: 11/06/2022]
Abstract
Background The type or duration of a scar determines the choice of therapy available. Traditional detection methods can easily cause secondary trauma, so there is an urgent need for a non-invasive, rapid diagnostic approach. Methods A strategy for quantitative analysis of three-dimensional (3D) elastic fibers in human cutaneous scars was designed, which included 3D reconstruction, skeleton extraction, quantitative analysis, and random forest regression. Results Four reconstruction methods were used to reconstruct 3D two-photon excitation fluorescence images of elastic fibers for comparison. In the skeleton extraction stage, the 3D thinning algorithm was improved to prepare for accurate quantitative analysis, in which eight parameters comprising branches number (B-NUM), nodes number (N-NUM), averaged branch broken-line length (AB-BL), averaged linear branch length (AB-LL), averaged branch tortuosity (AB-T), branch direction consistency (B-DC), averaged branch volume (AB-V), and averaged branch sectional area (AB-SA) were presented. Six of them, except averaged branch tortuosity (AB-T) and branch direction consistency (B-DC), showed an explicit tendency to change with scar duration. In the random forests regression analysis, the six extracted parameters could be used to predict scar duration with R2=0.981 and RMSE=0.513. Conclusions The parameters we extracted had a distinct relationship with scar duration, and random forests regression showed better performance in forecasting scar duration than unitary models.
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Affiliation(s)
- Yongping Lin
- School of Optoelectronic and Communication Engineering, Fujian Provincial Key Laboratory of Optoelectronic Technology and Devices, Xiamen University of Technology, Xiamen, China
| | - Hongxin Lin
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China.,Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fujian Normal University, Fuzhou, China
| | - Xiaoqin Zhu
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China.,Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fujian Normal University, Fuzhou, China
| | - Guannan Chen
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China.,Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application, Fujian Normal University, Fuzhou, China
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