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Vulasala SS, Sutphin P, Shyn P, Kalva S. Intraoperative Imaging Techniques in Oncology. Clin Oncol (R Coll Radiol) 2024; 36:e255-e268. [PMID: 38242817 DOI: 10.1016/j.clon.2024.01.004] [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: 09/07/2023] [Accepted: 01/05/2024] [Indexed: 01/21/2024]
Abstract
Imaging-based procedures have become well integrated into the diagnosis and management of oncological patients and play a significant role in reducing morbidity and mortality rates. Here we describe the established and upcoming surgical oncological imaging techniques and their impact on cancer management.
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Affiliation(s)
- S S Vulasala
- Department of Radiology, University of Florida College of Medicine, Jacksonville, Florida, USA.
| | - P Sutphin
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - P Shyn
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - S Kalva
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
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2
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Mo W, Ke Q, Yang Q, Zhou M, Xie G, Qi D, Peng L, Wang X, Wang F, Ni S, Wang A, Huang J, Wen J, Yang Y, Du K, Wang X, Du X, Zhao Z. A Dual-Modal, Label-Free Raman Imaging Method for Rapid Virtual Staining of Large-Area Breast Cancer Tissue Sections. Anal Chem 2024. [PMID: 38967251 DOI: 10.1021/acs.analchem.4c00870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/06/2024]
Abstract
As one of the most common cancers, accurate, rapid, and simple histopathological diagnosis is very important for breast cancer. Raman imaging is a powerful technique for label-free analysis of tissue composition and histopathology, but it suffers from slow speed when applied to large-area tissue sections. In this study, we propose a dual-modal Raman imaging method that combines Raman mapping data with microscopy bright-field images to achieve virtual staining of breast cancer tissue sections. We validate our method on various breast tissue sections with different morphologies and biomarker expressions and compare it with the golden standard of histopathological methods. The results demonstrate that our method can effectively distinguish various types and components of tissues, and provide staining images comparable to stained tissue sections. Moreover, our method can improve imaging speed by up to 65 times compared to general spontaneous Raman imaging methods. It is simple, fast, and suitable for clinical applications.
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Affiliation(s)
- Wenbo Mo
- National Key Laboratory of Plasma Physics, Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Qi Ke
- Mianyang Central Hospital, 621000 Mianyang, China
| | - Qiang Yang
- China Academy of Engineering Physics, 621900 Mianyang, China
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Minjie Zhou
- Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Gang Xie
- Mianyang Central Hospital, 621000 Mianyang, China
| | - Daojian Qi
- Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Lijun Peng
- Mianyang Central Hospital, 621000 Mianyang, China
| | - Xinming Wang
- Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Fei Wang
- Mianyang Central Hospital, 621000 Mianyang, China
| | - Shuang Ni
- Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Anqun Wang
- Mianyang Central Hospital, 621000 Mianyang, China
| | - Jinglin Huang
- Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Jiaxing Wen
- National Key Laboratory of Plasma Physics, Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Yue Yang
- National Key Laboratory of Plasma Physics, Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Kai Du
- Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
| | - Xuewu Wang
- Department of Engineering Physics, Tsinghua University, 100084 Beijing, China
| | - Xiaobo Du
- Mianyang Central Hospital, 621000 Mianyang, China
| | - Zongqing Zhao
- National Key Laboratory of Plasma Physics, Laser Fusion Research Center, China Academy of Engineering Physics, 621900 Mianyang, China
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3
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Raghunathan R, Vasquez M, Zhang K, Zhao H, Wong STC. Label-free optical imaging for brain cancer assessment. Trends Cancer 2024; 10:557-570. [PMID: 38575412 PMCID: PMC11168891 DOI: 10.1016/j.trecan.2024.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 04/06/2024]
Abstract
Advances in label-free optical imaging offer a promising avenue for brain cancer assessment, providing high-resolution, real-time insights without the need for radiation or exogeneous agents. These cost-effective and intricately detailed techniques overcome the limitations inherent in magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) scans by offering superior resolution and more readily accessible imaging options. This comprehensive review explores a variety of such methods, including photoacoustic imaging (PAI), optical coherence tomography (OCT), Raman imaging, and IR microscopy. It focuses on their roles in the detection, diagnosis, and management of brain tumors. By highlighting recent advances in these imaging techniques, the review aims to underscore the importance of label-free optical imaging in enhancing early detection and refining therapeutic strategies for brain cancer.
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Affiliation(s)
- Raksha Raghunathan
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Matthew Vasquez
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Katherine Zhang
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Hong Zhao
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA; Department of Medicine, Weill Cornell Medicine, New York, NY 10065, USA.
| | - Stephen T C Wong
- Department of Systems Medicine and Bioengineering and T.T. and W.F. Chao Center for BRAIN, Houston Methodist Neal Cancer Center, Houston Methodist Hospital, Houston, TX 77030, USA; Advanced Cellular and Tissue Microscopy Core, Houston Methodist Neal Cancer Center and Houston Methodist Research Institute, Houston, TX 77030, USA; Departments of Radiology, Pathology, and Laboratory Medicine and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10065, USA
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4
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Ma L, Luo K, Liu Z, Ji M. Stain-Free Histopathology with Stimulated Raman Scattering Microscopy. Anal Chem 2024; 96:7907-7925. [PMID: 38713830 DOI: 10.1021/acs.analchem.4c02061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2024]
Affiliation(s)
- Liyang Ma
- State Key Laboratory of Surface Physics and Department of Physics, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Shanghai Key Laboratory of Metasurfaces for Light Manipulation, Fudan University, Shanghai 200433, China
| | - Kuan Luo
- State Key Laboratory of Surface Physics and Department of Physics, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Shanghai Key Laboratory of Metasurfaces for Light Manipulation, Fudan University, Shanghai 200433, China
| | - Zhijie Liu
- State Key Laboratory of Surface Physics and Department of Physics, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Shanghai Key Laboratory of Metasurfaces for Light Manipulation, Fudan University, Shanghai 200433, China
| | - Minbiao Ji
- State Key Laboratory of Surface Physics and Department of Physics, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Shanghai Key Laboratory of Metasurfaces for Light Manipulation, Fudan University, Shanghai 200433, China
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Huang X, Xue Z, Zhang D, Lee HJ. Pinpointing Fat Molecules: Advances in Coherent Raman Scattering Microscopy for Lipid Metabolism. Anal Chem 2024; 96:7945-7958. [PMID: 38700460 DOI: 10.1021/acs.analchem.4c01398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Affiliation(s)
- Xiangjie Huang
- College of Biomedical Engineering & Instrument Science, and Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China
| | - Zexin Xue
- College of Biomedical Engineering & Instrument Science, and Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China
| | - Delong Zhang
- MOE Frontier Science Center for Brain Science & Brain-Machine Integration, Zhejiang University, Hangzhou 310027, China
- Zhejiang Key Laboratory of Micro-nano Quantum Chips and Quantum Control, and School of Physics, Zhejiang University, Hangzhou 310027, China
| | - Hyeon Jeong Lee
- College of Biomedical Engineering & Instrument Science, and Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027, China
- MOE Frontier Science Center for Brain Science & Brain-Machine Integration, Zhejiang University, Hangzhou 310027, China
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Kim D, Ko HY, Chung JI, Park YM, Lee S, Kim SY, Kim J, Chun JH, Han KS, Lee M, Ju YH, Park SJ, Park KD, Nam MH, Kim SH, Shim JK, Park Y, Lim H, Park J, Lee GH, Kim H, Kim S, Park U, Ryu H, Lee SY, Park S, Kang SG, Chang JH, Lee CJ, Yun M. Visualizing cancer-originating acetate uptake through monocarboxylate transporter 1 in reactive astrocytes in the glioblastoma tumor microenvironment. Neuro Oncol 2024; 26:843-857. [PMID: 38085571 PMCID: PMC11066945 DOI: 10.1093/neuonc/noad243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2024] Open
Abstract
BACKGROUND Reactive astrogliosis is a hallmark of various brain pathologies, including neurodegenerative diseases and glioblastomas. However, the specific intermediate metabolites contributing to reactive astrogliosis remain unknown. This study investigated how glioblastomas induce reactive astrogliosis in the neighboring microenvironment and explore 11C-acetate PET as an imaging technique for detecting reactive astrogliosis. METHODS Through in vitro, mouse models, and human tissue experiments, we examined the association between elevated 11C-acetate uptake and reactive astrogliosis in gliomas. We explored acetate from glioblastoma cells, which triggers reactive astrogliosis in neighboring astrocytes by upregulating MAO-B and monocarboxylate transporter 1 (MCT1) expression. We evaluated the presence of cancer stem cells in the reactive astrogliosis region of glioblastomas and assessed the correlation between the volume of 11C-acetate uptake beyond MRI and prognosis. RESULTS Elevated 11C-acetate uptake is associated with reactive astrogliosis and astrocytic MCT1 in the periphery of glioblastomas in human tissues and mouse models. Glioblastoma cells exhibit increased acetate production as a result of glucose metabolism, with subsequent secretion of acetate. Acetate derived from glioblastoma cells induces reactive astrogliosis in neighboring astrocytes by increasing the expression of MAO-B and MCT1. We found cancer stem cells within the reactive astrogliosis at the tumor periphery. Consequently, a larger volume of 11C-acetate uptake beyond contrast-enhanced MRI was associated with a worse prognosis. CONCLUSIONS Our results highlight the role of acetate derived from glioblastoma cells in inducing reactive astrogliosis and underscore the potential value of 11C-acetate PET as an imaging technique for detecting reactive astrogliosis, offering important implications for the diagnosis and treatment of glioblastomas.
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Affiliation(s)
- Dongwoo Kim
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hae Young Ko
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jee-In Chung
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yongmin Mason Park
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, Republic of Korea
- IBS School, University of Science and Technology, Daejeon, Republic of Korea
| | - Sangwon Lee
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Seon Yoo Kim
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jisu Kim
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Joong-Hyun Chun
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Kyung-Seok Han
- Department of Biological Sciences, Chungnam National University, Daejeon, Republic of Korea
| | - Misu Lee
- Division of Life Science, College of Life Science and Bioengineering, Incheon National University, Incheon, Republic of Korea
| | - Yeon Ha Ju
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, Republic of Korea
- IBS School, University of Science and Technology, Daejeon, Republic of Korea
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Sun Jun Park
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
- Division of Bio-Med Science & Technology, KIST School, Korea University of Science and Technology, Seoul, Republic of Korea
| | - Ki Duk Park
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
- Division of Bio-Med Science & Technology, KIST School, Korea University of Science and Technology, Seoul, Republic of Korea
| | - Min-Ho Nam
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
- Division of Bio-Med Science & Technology, KIST School, Korea University of Science and Technology, Seoul, Republic of Korea
- Department of KHU-KIST Convergence Science and Technology, Kyung Hee University, Seoul, Republic of Korea
| | - Se Hoon Kim
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jin-Kyoung Shim
- Department of Neurosurgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Youngjoo Park
- Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hyunkeong Lim
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jaekyung Park
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Gwan-Ho Lee
- Research Resources Division, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Hyunjin Kim
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Suhyun Kim
- K-Laboratory, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Uiyeol Park
- K-Laboratory, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Hoon Ryu
- K-Laboratory, Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - So Yun Lee
- Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Sunghyouk Park
- Natural Products Research Institute, College of Pharmacy, Seoul National University, Seoul, Republic of Korea
| | - Seok-Gu Kang
- Department of Neurosurgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - C Justin Lee
- IBS School, University of Science and Technology, Daejeon, Republic of Korea
| | - Mijin Yun
- Department of Nuclear Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
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Burström G, Amini M, El-Hajj VG, Arfan A, Gharios M, Buwaider A, Losch MS, Manni F, Edström E, Elmi-Terander A. Optical Methods for Brain Tumor Detection: A Systematic Review. J Clin Med 2024; 13:2676. [PMID: 38731204 PMCID: PMC11084501 DOI: 10.3390/jcm13092676] [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: 04/11/2024] [Revised: 04/28/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Background: In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. Methods: This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. Results: In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. Conclusions: This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.
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Affiliation(s)
- Gustav Burström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Misha Amini
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Victor Gabriel El-Hajj
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Arooj Arfan
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Maria Gharios
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Ali Buwaider
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
| | - Merle S. Losch
- Department of Biomechanical Engineering, Faculty of Mechanical Engineering, Delft University of Technology, 2627 Delft, The Netherlands
| | - Francesca Manni
- Department of Electrical Engineering, Eindhoven University of Technology (TU/e), 5612 Eindhoven, The Netherlands;
| | - Erik Edström
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
| | - Adrian Elmi-Terander
- Department of Clinical Neuroscience, Karolinska Institute, 171 77 Stockholm, Sweden; (G.B.); (M.A.); (A.A.); (M.G.); (A.B.); (E.E.)
- Capio Spine Center Stockholm, Löwenströmska Hospital, 194 80 Upplands-Väsby, Sweden
- Department of Medical Sciences, Örebro University, 701 85 Örebro, Sweden
- Department of Surgical Sciences, Uppsala University, 751 35 Uppsala, Sweden
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Chadha R, Guerrero JA, Wei L, Sanchez LM. Seeing is Believing: Developing Multimodal Metabolic Insights at the Molecular Level. ACS CENTRAL SCIENCE 2024; 10:758-774. [PMID: 38680555 PMCID: PMC11046475 DOI: 10.1021/acscentsci.3c01438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 02/16/2024] [Accepted: 02/20/2024] [Indexed: 05/01/2024]
Abstract
This outlook explores how two different molecular imaging approaches might be combined to gain insight into dynamic, subcellular metabolic processes. Specifically, we discuss how matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and stimulated Raman scattering (SRS) microscopy, which have significantly pushed the boundaries of imaging metabolic and metabolomic analyses in their own right, could be combined to create comprehensive molecular images. We first briefly summarize the recent advances for each technique. We then explore how one might overcome the inherent limitations of each individual method, by envisioning orthogonal and interchangeable workflows. Additionally, we delve into the potential benefits of adopting a complementary approach that combines both MSI and SRS spectro-microscopy for informing on specific chemical structures through functional-group-specific targets. Ultimately, by integrating the strengths of both imaging modalities, researchers can achieve a more comprehensive understanding of biological and chemical systems, enabling precise metabolic investigations. This synergistic approach holds substantial promise to expand our toolkit for studying metabolites in complex environments.
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Affiliation(s)
- Rahuljeet
S Chadha
- Division
of Chemistry and Chemical Engineering, California
Institute of Technology, Pasadena, California 91125 United States
| | - Jason A. Guerrero
- Department
of Chemistry and Biochemistry, University
of California, Santa Cruz, Santa
Cruz, California 95064 United States
| | - Lu Wei
- Division
of Chemistry and Chemical Engineering, California
Institute of Technology, Pasadena, California 91125 United States
| | - Laura M. Sanchez
- Department
of Chemistry and Biochemistry, University
of California, Santa Cruz, Santa
Cruz, California 95064 United States
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Abraham TM, Levenson R. Current Landscape of Advanced Imaging Tools for Pathology Diagnostics. Mod Pathol 2024; 37:100443. [PMID: 38311312 DOI: 10.1016/j.modpat.2024.100443] [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: 07/25/2023] [Revised: 12/13/2023] [Accepted: 01/26/2024] [Indexed: 02/10/2024]
Abstract
Histopathology relies on century-old workflows of formalin fixation, paraffin embedding, sectioning, and staining tissue specimens on glass slides. Despite being robust, this conventional process is slow, labor-intensive, and limited to providing two-dimensional views. Emerging technologies promise to enhance and accelerate histopathology. Slide-free microscopy allows rapid imaging of fresh, unsectioned specimens, overcoming slide preparation delays. Methods such as fluorescence confocal microscopy, multiphoton microscopy, along with more recent innovations including microscopy with UV surface excitation and fluorescence-imitating brightfield imaging can generate images resembling conventional histology directly from the surface of tissue specimens. Slide-free microscopy enable applications such as rapid intraoperative margin assessment and, with appropriate technology, three-dimensional histopathology. Multiomics profiling techniques, including imaging mass spectrometry and Raman spectroscopy, provide highly multiplexed molecular maps of tissues, although clinical translation remains challenging. Artificial intelligence is aiding the adoption of new imaging modalities via virtual staining, which converts methods such as slide-free microscopy into synthetic brightfield-like or even molecularly informed images. Although not yet commonplace, these emerging technologies collectively demonstrate the potential to modernize histopathology. Artificial intelligence-assisted workflows will ease the transition to new imaging modalities. With further validation, these advances may transform the century-old conventional histopathology pipeline to better serve 21st-century medicine. This review provides an overview of these enabling technology platforms and discusses their potential impact.
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Affiliation(s)
- Tanishq Mathew Abraham
- Department of Biomedical Engineering, University of California, Davis, Davis, California
| | - Richard Levenson
- Department of Pathology and Laboratory Medicine, UC Davis Health, Sacramento, California.
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10
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Meißner AK, Goldbrunner R, Neuschmelting V. [Intraoperative stimulated Raman histology for personalized brain tumor surgery]. CHIRURGIE (HEIDELBERG, GERMANY) 2024; 95:274-279. [PMID: 38334774 DOI: 10.1007/s00104-024-02038-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/11/2024] [Indexed: 02/10/2024]
Abstract
BACKGROUND In brain tumor surgery a personalized surgical approach is crucial to achieve a maximum safe tumor resection. The extent of resection decisively depends on the histological diagnosis. Stimulated Raman histology (SRH), a fiber laser-based optical imaging method, offers the possibility for evaluation of an intraoperative diagnosis in a few minutes. OBJECTIVE To provide an overview on the applications of SRH in neurosurgery and transference of the technique to other surgical disciplines. METHODS Description of the technique and review of the current literature on SRH. RESULTS The SRH technique was successfully used in multiple neuro-oncological tumor entities. Initial pilot projects showed the potential for analysis of extracranial tumors. CONCLUSION The use of SRH provides a near real-time diagnosis with high diagnostic accuracy and provides further developmental potential to improve personalized tumor surgery.
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Affiliation(s)
- Anna-Katharina Meißner
- Klinik für allgemeine Neurochirurgie, Zentrum für Neurochirurgie, Medizinische Fakultät und Universitätsklinik Köln, Universität zu Köln, Kerpener Str. 62, 50937, Köln, Deutschland
| | - Roland Goldbrunner
- Klinik für allgemeine Neurochirurgie, Zentrum für Neurochirurgie, Medizinische Fakultät und Universitätsklinik Köln, Universität zu Köln, Kerpener Str. 62, 50937, Köln, Deutschland
| | - Volker Neuschmelting
- Klinik für allgemeine Neurochirurgie, Zentrum für Neurochirurgie, Medizinische Fakultät und Universitätsklinik Köln, Universität zu Köln, Kerpener Str. 62, 50937, Köln, Deutschland.
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11
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Kren J, Skambath I, Kuppler P, Buschschlüter S, Detrez N, Burhan S, Huber R, Brinkmann R, Bonsanto MM. Mechanical characteristics of glioblastoma and peritumoral tumor-free human brain tissue. Acta Neurochir (Wien) 2024; 166:102. [PMID: 38396016 PMCID: PMC10891200 DOI: 10.1007/s00701-024-06009-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/16/2024] [Indexed: 02/25/2024]
Abstract
BACKGROUND The diagnosis of brain tumor is a serious event for the affected patient. Surgical resection is a crucial part in the treatment of brain tumors. However, the distinction between tumor and brain tissue can be difficult, even for experienced neurosurgeons. This is especially true in the case of gliomas. In this project we examined whether the biomechanical parameters elasticity and stress relaxation behavior are suitable as additional differentiation criteria between tumorous (glioblastoma multiforme; glioblastoma, IDH-wildtype; GBM) and non-tumorous, peritumoral tissue. METHODS Indentation measurements were used to examine non-tumorous human brain tissue and GBM samples for the biomechanical properties of elasticity and stress-relaxation behavior. The results of these measurements were then used in a classification algorithm (Logistic Regression) to distinguish between tumor and non-tumor. RESULTS Differences could be found in elasticity spread and relaxation behavior between tumorous and non-tumorous tissue. Classification was successful with a sensitivity/recall of 83% (sd = 12%) and a precision of 85% (sd = 9%) for detecting tumorous tissue. CONCLUSION The findings imply that the data on mechanical characteristics, with particular attention to stress relaxation behavior, can serve as an extra element in differentiating tumorous brain tissue from non-tumorous brain tissue.
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Affiliation(s)
- Jessica Kren
- Department of Neurosurgery, University Hospital Schleswig-Holstein, Luebeck, Germany.
| | - Isabelle Skambath
- Department of Neurosurgery, University Hospital Schleswig-Holstein, Luebeck, Germany
| | - Patrick Kuppler
- Department of Neurosurgery, University Hospital Schleswig-Holstein, Luebeck, Germany
| | | | - Nicolas Detrez
- Medizinisches Laserzentrum Lübeck GmbH, Luebeck, Germany
| | - Sazgar Burhan
- Institute of Biomedical Optics, University of Luebeck, Luebeck, Germany
| | - Robert Huber
- Institute of Biomedical Optics, University of Luebeck, Luebeck, Germany
| | - Ralf Brinkmann
- Medizinisches Laserzentrum Lübeck GmbH, Luebeck, Germany
| | - Matteo Mario Bonsanto
- Department of Neurosurgery, University Hospital Schleswig-Holstein, Luebeck, Germany
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12
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Gao C, Zhao P, Fan Q, Jing H, Dang R, Sun W, Feng Y, Hu B, Wang Q. Deep neural network: As the novel pipelines in multiple preprocessing for Raman spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 302:123086. [PMID: 37451210 DOI: 10.1016/j.saa.2023.123086] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 06/24/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023]
Abstract
Raman spectroscopy is a kind of vibrational method that can rapidly and non-invasively gives chemical structural information with the Raman spectrometer. Despite its technical advantages, in practical application scenarios, Raman spectroscopy often suffers from interference, such as noises and baseline drifts, resulting in the inability to acquire high-quality Raman spectroscopy signals, which brings challenges to subsequent spectral analysis. The commonly applied spectral preprocessing methods, such as Savitzky-Golay smooth and wavelet transform, can only perform corresponding single-item processing and require manual intervention to carry out a series of tedious trial parameters. Especially, each scheme can only be used for a specific data set. In recent years, the development of deep neural networks has provided new solutions for intelligent preprocessing of spectral data. In this paper, we first creatively started from the basic mechanism of spectral signal generation and constructed a mathematical model of the Raman spectral signal. By counting the noise parameters of the real system, we generated a simulation dataset close to the output of the real system, which alleviated the dependence on data during deep learning training. Due to the powerful nonlinear fitting ability of the neural network, fully connected network model is constructed to complete the baseline estimation task simply and quickly. Then building the Unet model can effectively achieve spectral denoising, and combining it with baseline estimation can realize intelligent joint processing. Through the simulation dataset experiment, it is proved that compared with the classic method, the method proposed in this paper has obvious advantages, which can effectively improve the signal quality and further ensure the accuracy of the peak intensity. At the same time, when the proposed method is applied to the actual system, it also achieves excellent performance compared with the common method, which indirectly indicates the effectiveness of the Raman signal simulation model. The research presented in this paper offers a variety of efficient pipelines for the intelligent processing of Raman spectroscopy, which can adapt to the requirements of different tasks while providing a new idea for enhancing the quality of Raman spectroscopy signals.
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Affiliation(s)
- Chi Gao
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peng Zhao
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qi Fan
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China
| | - Haonan Jing
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ruochen Dang
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weifeng Sun
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yutao Feng
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China
| | - Bingliang Hu
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China
| | - Quan Wang
- Xi'an Institute of Optics and Precision Mechanics of the Chinese Academy of Sciences, Shaanxi, 710076, China; The Key Laboratory of Biomedical Spectroscopy of Xi'an, Shaanxi, 710076, China.
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13
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Bin-Alamer O, Abou-Al-Shaar H, Gersey ZC, Huq S, Kallos JA, McCarthy DJ, Head JR, Andrews E, Zhang X, Hadjipanayis CG. Intraoperative Imaging and Optical Visualization Techniques for Brain Tumor Resection: A Narrative Review. Cancers (Basel) 2023; 15:4890. [PMID: 37835584 PMCID: PMC10571802 DOI: 10.3390/cancers15194890] [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: 08/29/2023] [Revised: 09/26/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023] Open
Abstract
Advancements in intraoperative visualization and imaging techniques are increasingly central to the success and safety of brain tumor surgery, leading to transformative improvements in patient outcomes. This comprehensive review intricately describes the evolution of conventional and emerging technologies for intraoperative imaging, encompassing the surgical microscope, exoscope, Raman spectroscopy, confocal microscopy, fluorescence-guided surgery, intraoperative ultrasound, magnetic resonance imaging, and computed tomography. We detail how each of these imaging modalities contributes uniquely to the precision, safety, and efficacy of neurosurgical procedures. Despite their substantial benefits, these technologies share common challenges, including difficulties in image interpretation and steep learning curves. Looking forward, innovations in this field are poised to incorporate artificial intelligence, integrated multimodal imaging approaches, and augmented and virtual reality technologies. This rapidly evolving landscape represents fertile ground for future research and technological development, aiming to further elevate surgical precision, safety, and, most critically, patient outcomes in the management of brain tumors.
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Affiliation(s)
- Othman Bin-Alamer
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Hussam Abou-Al-Shaar
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Zachary C. Gersey
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Sakibul Huq
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Justiss A. Kallos
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - David J. McCarthy
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Jeffery R. Head
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Edward Andrews
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Xiaoran Zhang
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Constantinos G. Hadjipanayis
- Center for Image-Guided Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA; (O.B.-A.); (H.A.-A.-S.); (Z.C.G.); (S.H.); (J.A.K.); (D.J.M.); (J.R.H.); (E.A.); (X.Z.)
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
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14
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Xie XS. Round-Trip Journey of a Physical Chemist. J Phys Chem B 2023; 127:7800-7809. [PMID: 37731371 DOI: 10.1021/acs.jpcb.3c05597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Affiliation(s)
- Xiaoliang Sunney Xie
- Biomedical Pioneering Innovation Center, Peking University, 5 Yiheyuan Road, Beijing 100871, China
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15
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Teng G, Wang Q, Hao Q, Fan A, Yang H, Xu X, Chen G, Wei K, Zhao Z, Khan MN, Idrees BS, Bao M, Luo T, Zheng Y, Lu B. Full-Stokes polarization laser-induced breakdown spectroscopy detection of infiltrative glioma boundary tissue. BIOMEDICAL OPTICS EXPRESS 2023; 14:3469-3490. [PMID: 37497487 PMCID: PMC10368052 DOI: 10.1364/boe.492983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/30/2023] [Accepted: 06/05/2023] [Indexed: 07/28/2023]
Abstract
The glioma boundary is difficult to identify during surgery due to the infiltrative characteristics of tumor cells. In order to ensure a full resection rate and increase the postoperative survival of patients, it is often necessary to make an expansion range resection, which may have harmful effects on the quality of the patient's survival. A full-Stokes laser-induced breakdown spectroscopy (FSLIBS) theory with a corresponding system is proposed to combine the elemental composition information and polarization information for glioma boundary detection. To verify the elemental content of brain tissues and provide an analytical basis, inductively coupled plasma mass spectrometry (ICP-MS) and LIBS are also applied to analyze the healthy, boundary, and glioma tissues. Totally, 42 fresh tissue samples are analyzed, and the Ca, Na, K elemental lines and CN, C2 molecular fragmental bands are proved to take an important role in the different tissue identification. The FSLIBS provides complete polarization information and elemental information than conventional LIBS elemental analysis. The Stokes parameter spectra can significantly reduce the under-fitting phenomenon of artificial intelligence identification models. Meanwhile, the FSLIBS spectral features within glioma samples are relatively more stable than boundary and healthy tissues. Other tissues may be affected obviously by individual differences in lesion positions and patients. In the future, the FSLIBS may be used for the precise identification of glioma boundaries based on polarization and elemental characterizing ability.
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Affiliation(s)
- Geer Teng
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, OX3 7LD, United Kingdom
| | - Qianqian Wang
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314033, China
| | - Qun Hao
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314033, China
| | - Axin Fan
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
| | - Haifeng Yang
- Department of Neuro-Oncology, Chongqing University Cancer Hospital, Chongqing, 400030, China
| | - Xiangjun Xu
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314033, China
| | - Guoyan Chen
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Kai Wei
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Zhifang Zhao
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - M Nouman Khan
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Bushra Sana Idrees
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Mengyu Bao
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Tianzhong Luo
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
- Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing, 314033, China
| | - Yongyue Zheng
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Bingheng Lu
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, 100081, China
- Key Laboratory of Photonic Information Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, 100081, China
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16
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Bortot B, Mangogna A, Di Lorenzo G, Stabile G, Ricci G, Biffi S. Image-guided cancer surgery: a narrative review on imaging modalities and emerging nanotechnology strategies. J Nanobiotechnology 2023; 21:155. [PMID: 37202750 DOI: 10.1186/s12951-023-01926-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/11/2023] [Indexed: 05/20/2023] Open
Abstract
Surgical resection is the cornerstone of solid tumour treatment. Current techniques for evaluating margin statuses, such as frozen section, imprint cytology, and intraoperative ultrasound, are helpful. However, an intraoperative assessment of tumour margins that is accurate and safe is clinically necessary. Positive surgical margins (PSM) have a well-documented negative effect on treatment outcomes and survival. As a result, surgical tumour imaging methods are now a practical method for reducing PSM rates and improving the efficiency of debulking surgery. Because of their unique characteristics, nanoparticles can function as contrast agents in image-guided surgery. While most image-guided surgical applications utilizing nanotechnology are now in the preclinical stage, some are beginning to reach the clinical phase. Here, we list the various imaging techniques used in image-guided surgery, such as optical imaging, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine imaging, and the most current developments in the potential of nanotechnology to detect surgical malignancies. In the coming years, we will see the evolution of nanoparticles tailored to specific tumour types and the introduction of surgical equipment to improve resection accuracy. Although the promise of nanotechnology for producing exogenous molecular contrast agents has been clearly demonstrated, much work remains to be done to put it into practice.
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Affiliation(s)
- Barbara Bortot
- Obstetrics and Gynecology, Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
| | - Alessandro Mangogna
- Obstetrics and Gynecology, Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
| | - Giovanni Di Lorenzo
- Obstetrics and Gynecology, Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
| | - Guglielmo Stabile
- Obstetrics and Gynecology, Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
| | - Giuseppe Ricci
- Obstetrics and Gynecology, Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy
| | - Stefania Biffi
- Obstetrics and Gynecology, Institute for Maternal and Child Health, IRCCS Burlo Garofolo, Trieste, Italy.
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17
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Yan S, Li Y, Huang Z, Yuan X, Wang P. High-Speed Stimulated Raman Scattering Microscopy Using Inertia-Free AOD Scanning. J Phys Chem B 2023; 127:4229-4234. [PMID: 37140210 DOI: 10.1021/acs.jpcb.2c09114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
High-throughput stimulated Raman scattering (SRS) microscopy is highly desired for large tissue imaging with chemical specificity. However, the mapping speed remains as the major short board of conventional SRS, primarily owing to the mechanical inertia existing in galvanometers or other laser scanning alternatives. Here, we developed inertia-free acousto-optic deflector (AOD)-based high-speed large-field stimulated Raman scattering microscopy, in which both the speed and integration time are ensured by immune of the mechanical response time. To avoid laser beam distortion induced by the intrinsic spatial dispersion of AODs, two spectral compression systems are implemented to compress the broad-band femtosecond pulse to picosecond laser. We achieved an SRS imaging of a 12 × 8 mm2 mouse brain slice in only 8 min at an image resolution of approximately 1 μm and 32 slices from a whole brain in 12 h. The AOD-based inertia-free SRS mapping can be much faster after further upgrading and allow broad-spectrum applications of chemical imaging in the future.
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Affiliation(s)
- Shuai Yan
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
- Changping Laboratory, Beijing 102206, China
| | - Yiran Li
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Zhiliang Huang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Xiaocong Yuan
- Research Center for Humanoid Sensing, Zhejiang Laboratory, Hangzhou 311100, Zhejiang, China
| | - Ping Wang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
- Optics Valley Laboratory, Wuhan 430074, Hubei, China
- Huaiyin Institute of Technology, Huai'an 223001, Jiangsu, China
- Changping Laboratory, Beijing 102206, China
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18
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Alfonso-Garcia A, Anbunesan SN, Bec J, Lee HS, Jin LW, Bloch O, Marcu L. In vivo characterization of the human glioblastoma infiltrative edge with label-free intraoperative fluorescence lifetime imaging. BIOMEDICAL OPTICS EXPRESS 2023; 14:2196-2208. [PMID: 37206147 PMCID: PMC10191664 DOI: 10.1364/boe.481304] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 03/24/2023] [Accepted: 03/29/2023] [Indexed: 05/21/2023]
Abstract
Challenges in identifying a glioblastoma's infiltrative edge during neurosurgical procedures result in rapid recurrence. A label-free fluorescence lifetime imaging (FLIm) device was used to evaluate glioblastoma's infiltrative edge in vivo in 15 patients (89 samples). FLIm data were analyzed according to tumor cell density, infiltrating tissue type (gray and white matter), and diagnosis history (new or recurrent). Infiltrations in white matter from new glioblastomas showed decreasing lifetimes and a spectral red shift with increasing tumor cell density. Areas of high versus low tumor cell density were separated through a linear discriminant analysis with a ROC-AUC=0.74. Current results support the feasibility of intraoperative FLIm for real-time in vivo brain measurements and encourage refinement to predict glioblastoma infiltrative edge, underscoring the ability of FLIm to optimize neurosurgical outcomes.
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Affiliation(s)
- Alba Alfonso-Garcia
- Biomedical Engineering Department,
University of California, Davis, One Shields Ave, Davis, CA 95616, USA
| | - Silvia Noble Anbunesan
- Biomedical Engineering Department,
University of California, Davis, One Shields Ave, Davis, CA 95616, USA
| | - Julien Bec
- Biomedical Engineering Department,
University of California, Davis, One Shields Ave, Davis, CA 95616, USA
| | - Han Sung Lee
- Pathology and Laboratory Medicine Department, University of California, Davis, 4400 V St, Sacramento, CA 95817, USA
| | - Lee-Way Jin
- Pathology and Laboratory Medicine Department, University of California, Davis, 4400 V St, Sacramento, CA 95817, USA
| | - Orin Bloch
- Neurological Surgery Department, University of California, Davis, 4860 Y St, Sacramento, CA 95817, USA
| | - Laura Marcu
- Biomedical Engineering Department,
University of California, Davis, One Shields Ave, Davis, CA 95616, USA
- Neurological Surgery Department, University of California, Davis, 4860 Y St, Sacramento, CA 95817, USA
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19
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Chen X, Wu Z, He Y, Hao Z, Wang Q, Zhou K, Zhou W, Wang P, Shan F, Li Z, Ji J, Fan Y, Li Z, Yue S. Accurate and Rapid Detection of Peritoneal Metastasis from Gastric Cancer by AI-Assisted Stimulated Raman Molecular Cytology. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2300961. [PMID: 37114845 PMCID: PMC10375130 DOI: 10.1002/advs.202300961] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 04/04/2023] [Indexed: 06/19/2023]
Abstract
Peritoneal metastasis (PM) is the mostcommon form of distant metastasis and one of the leading causes of death in gastriccancer (GC). For locally advanced GC, clinical guidelines recommend peritoneal lavage cytology for intraoperative PM detection. Unfortunately, current peritoneal lavage cytology is limited by low sensitivity (<60%). Here the authors established the stimulated Raman molecular cytology (SRMC), a chemical microscopy-based intelligent cytology. The authors firstly imaged 53 951 exfoliated cells in ascites obtained from 80 GC patients (27 PM positive, 53 PM negative). Then, the authors revealed 12 single cell features of morphology and composition that are significantly different between PM positive and negative specimens, including cellular area, lipid protein ratio, etc. Importantly, the authors developed a single cell phenotyping algorithm to further transform the above raw features to feature matrix. Such matrix is crucial to identify the significant marker cell cluster, the divergence of which is finally used to differentiate the PM positive and negative. Compared with histopathology, the gold standard of PM detection, their SRMC method could reach 81.5% sensitivity, 84.9% specificity, and the AUC of 0.85, within 20 minutes for each patient. Together, their SRMC method shows great potential for accurate and rapid detection of PM from GC.
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Affiliation(s)
- Xun Chen
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
- School of Engineering Medicine, Beihang University, 100191, Beijing, China
| | - Zhouqiao Wu
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, 100142, Beijing, China
| | - Yexuan He
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
| | - Zhe Hao
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
| | - Qi Wang
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, 100142, Beijing, China
| | - Keji Zhou
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
| | - Wanhui Zhou
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
| | - Pu Wang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
| | - Fei Shan
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, 100142, Beijing, China
| | - Zhongwu Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, 100142, Beijing, China
| | - Jiafu Ji
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, 100142, Beijing, China
| | - Yubo Fan
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
- School of Engineering Medicine, Beihang University, 100191, Beijing, China
| | - Ziyu Li
- Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, 100142, Beijing, China
| | - Shuhua Yue
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Institute of Medical Photonics, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191, Beijing, China
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Huang Z, Yan S, Li Y, Ju W, Wang P. Direct Counting and Imaging Chain Lengths of Lipids by Stimulated Raman Scattering Microscopy. Anal Chem 2023; 95:5815-5819. [PMID: 36943034 DOI: 10.1021/acs.analchem.3c00291] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
Direct counting and mapping the chain lengths of fatty acids on a microscopic scale are of particular importance but remain an unsolvable challenge. Although the current hyperspectral stimulated Raman scattering (SRS) microscopy has gained exceptional capability in chemical imaging of the degree of desaturation, the complete lipid characterization, including the carbon chain length quantification, is awaiting a major breakthrough. Here, we pushed the spectral resolution limit of hyperspectral SRS microscopy to 5.4 cm-1 by employing a highly efficient spectral compressor, which achieved spectral narrowing of the fs laser without much energy loss. The SRS imaging with such high spectral resolution enabled us to differ eight types of saturated lipids with carbon chain lengths from C8:0 to C22:0 by interrogating their subtly red-shifting Raman bands of alkyl C-C gauche stretches between 1070 and 1110 cm-1. The SRS microscopy with superior spectral resolution will pave the way for comprehensive lipid characterization and contribute to uncovering the abnormal pathways of lipid metabolism in cancer.
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Affiliation(s)
- Zhiliang Huang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Shuai Yan
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
- Changping Laboratory, Beijing 102206, China
| | - Yiran Li
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Wei Ju
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
| | - Ping Wang
- Britton Chance Center and MoE Key Laboratory for Biomedical Photonics, Advanced Biomedical Imaging Facility, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
- Changping Laboratory, Beijing 102206, China
- Research Center for Humanoid Sensing, Zhejiang Laboratory, Hangzhou 311100, Zhejiang, China
- Optics Valley Laboratory, Wuhan 430074, Hubei, China
- Huaiyin Institute of Technology, Huai'an 223001, Jiangsu, China
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21
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Ao J, Shao X, Liu Z, Liu Q, Xia J, Shi Y, Qi L, Pan J, Ji M. Stimulated Raman Scattering Microscopy Enables Gleason Scoring of Prostate Core Needle Biopsy by a Convolutional Neural Network. Cancer Res 2023; 83:641-651. [PMID: 36594873 PMCID: PMC9929517 DOI: 10.1158/0008-5472.can-22-2146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 10/19/2022] [Accepted: 12/29/2022] [Indexed: 01/04/2023]
Abstract
Focal therapy (FT) has been proposed as an approach to eradicate clinically significant prostate cancer while preserving the normal surrounding tissues to minimize treatment-related toxicity. Rapid histology of core needle biopsies is essential to ensure the precise FT for localized lesions and to determine tumor grades. However, it is difficult to achieve both high accuracy and speed with currently available histopathology methods. Here, we demonstrated that stimulated Raman scattering (SRS) microscopy could reveal the largely heterogeneous histologic features of fresh prostatic biopsy tissues in a label-free and near real-time manner. A diagnostic convolutional neural network (CNN) built based on images from 61 patients could classify Gleason patterns of prostate cancer with an accuracy of 85.7%. An additional 22 independent cases introduced as external test dataset validated the CNN performance with 84.4% accuracy. Gleason scores of core needle biopsies from 21 cases were calculated using the deep learning SRS system and showed a 71% diagnostic consistency with grading from three pathologists. This study demonstrates the potential of a deep learning-assisted SRS platform in evaluating the tumor grade of prostate cancer, which could help simplify the diagnostic workflow and provide timely histopathology compatible with FT treatment. SIGNIFICANCE A platform combining stimulated Raman scattering microscopy and a convolutional neural network provides rapid histopathology and automated Gleason scoring on fresh prostate core needle biopsies without complex tissue processing.
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Affiliation(s)
- Jianpeng Ao
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute of Fudan University, Fudan University, Shanghai, P.R. China
| | - Xiaoguang Shao
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Zhijie Liu
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute of Fudan University, Fudan University, Shanghai, P.R. China
| | - Qiang Liu
- Department of Pathology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Jun Xia
- Department of Pathology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Yongheng Shi
- Department of Pathology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Lin Qi
- Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, P.R. China
| | - Jiahua Pan
- Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, P.R. China
| | - Minbiao Ji
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute of Fudan University, Fudan University, Shanghai, P.R. China
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22
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Wang C, Hodge S, Ravi D, Chen EY, Hoopes PJ, Tichauer KM, Samkoe KS. Rapid and Quantitative Intraoperative Pathology-Assisted Surgery by Paired-Agent Imaging-Derived Confidence Map. Mol Imaging Biol 2023; 25:190-202. [PMID: 36315374 DOI: 10.1007/s11307-022-01780-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 02/03/2023]
Abstract
PURPOSE In nonmetastatic head and neck cancer treatment, surgical margin status is the most important prognosticator of recurrence and patient survival. Fresh frozen sectioning (FFS) of tissue margins is the standard of care for intraoperative margin assessment. However, FFS is time intensive, and its accuracy is not consistent among institutes. Mapping the epidermal growth factor receptor (EGFR) using paired-agent imaging (PAI) has the potential to provide more consistent intraoperative margin assessment in a fraction of the time as FFS. PROCEDURES PAI was carried out through IV injection of an anti-epidermal growth factor receptor (EGFR) affibody molecule (ABY-029, eIND 122,681) and an untargeted IRDye680LT carboxylate. Imaging was performed on 4 µm frozen sections from three oral squamous cell carcinoma xenograft mouse models (n = 24, 8 samples per cell line). The diagnostic ability and tumor contrast were compared between binding potential, targeted, and untargeted images. Confidence maps were constructed based on group histogram-derived tumor probability curves. Tumor differentiability and contrast by confidence maps were evaluated. RESULTS PAI outperformed ABY-029 and IRDye 680LT alone, demonstrating the highest individual receiver operating characteristic (ROC) curve area under the curve (PAI AUC: 0.91, 0.90, and 0.79) and contrast-to-noise ratio (PAI CNR: 1, 1.1, and 0.6) for FaDu, Det 562, and A253. PAI confidence maps (PAI CM) maintain high tumor diagnostic ability (PAI CMAUC: 0.91, 0.90, and 0.79) while significantly enhancing tumor contrast (PAI CMCNR: 1.5, 1.3, and 0.8) in FaDu, Det 562, and A253. Additionally, the PAI confidence map allows avascular A253 to be differentiated from a healthy tissue with significantly higher contrast than PAI. Notably, PAI does not require additional staining and therefore significantly reduces the tumor delineation time in a 5 [Formula: see text] 5 mm slice from ~ 35 min to under a minute. CONCLUSION This study demonstrated that PAI improved tumor detection in frozen sections with high diagnostic accuracy and rapid analysis times. The novel PAI confidence map improved the contrast in vascular tumors and differentiability in avascular tumors. With a larger database, the PAI confidence map promises to standardize fluorescence imaging in intraoperative pathology-assisted surgery (IPAS).
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Affiliation(s)
- Cheng Wang
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - Sassan Hodge
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - Divya Ravi
- Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Eunice Y Chen
- Department of Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.,Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - P Jack Hoopes
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA.,Department of Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.,Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Kenneth M Tichauer
- Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Kimberley S Samkoe
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA. .,Department of Surgery, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA. .,Geisel School of Medicine, Dartmouth College, Hanover, NH, USA.
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23
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Yang Y, Liu Z, Huang J, Sun X, Ao J, Zheng B, Chen W, Shao Z, Hu H, Yang Y, Ji M. Histological diagnosis of unprocessed breast core-needle biopsy via stimulated Raman scattering microscopy and multi-instance learning. Theranostics 2023; 13:1342-1354. [PMID: 36923541 PMCID: PMC10008736 DOI: 10.7150/thno.81784] [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: 12/12/2022] [Accepted: 01/09/2023] [Indexed: 03/14/2023] Open
Abstract
Core-needle biopsy (CNB) plays a vital role in the initial diagnosis of breast cancer. However, the complex tissue processing and global shortage of pathologists have hindered traditional histopathology from timely diagnosis on fresh biopsies. In this work, we developed a full digital platform by integrating label-free stimulated Raman scattering (SRS) microscopy with weakly-supervised learning for rapid and automated cancer diagnosis on un-labelled breast CNB. Methods: We first compared the results of SRS imaging with standard hematoxylin and eosin (H&E) staining on adjacent frozen tissue sections. Then fresh unprocessed biopsy tissues were imaged by SRS to reveal diagnostic histoarchitectures. Next, weakly-supervised learning, i.e., the multi-instance learning (MIL) model was conducted to evaluate the ability to differentiate between benign and malignant cases, and compared with the performance of supervised learning model. Finally, gradient-weighted class activation mapping (Grad-CAM) and semantic segmentation were performed to spatially resolve benign/malignant areas with high efficiency. Results: We verified the ability of SRS in revealing essential histological hallmarks of breast cancer in both thin frozen sections and fresh unprocessed biopsy, generating histoarchitectures well correlated with H&E staining. Moreover, we demonstrated that weakly-supervised MIL model could achieve superior classification performance to supervised learnings, reaching diagnostic accuracy of 95% on 61 biopsy specimens. Furthermore, Grad-CAM allowed the trained MIL model to visualize the histological heterogeneity within the CNB. Conclusion: Our results indicate that MIL-assisted SRS microscopy provides rapid and accurate diagnosis on histologically heterogeneous breast CNB, and could potentially help the subsequent management of patients.
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Affiliation(s)
- Yifan Yang
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute, Fudan University, Shanghai 200433, China
| | - Zhijie Liu
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute, Fudan University, Shanghai 200433, China
| | - Jing Huang
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute, Fudan University, Shanghai 200433, China
| | - Xiangjie Sun
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Jianpeng Ao
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute, Fudan University, Shanghai 200433, China
| | - Bin Zheng
- Otolaryngology & Head and Neck Center, Cancer Center, Department of Otolaryngology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Wanyuan Chen
- Cancer Center, Department of Pathology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Zhiming Shao
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Hao Hu
- Endoscopy Center and Endoscopy Research Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032 China
| | - Yinlong Yang
- Department of Breast Surgery, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Minbiao Ji
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Yiwu Research Institute, Fudan University, Shanghai 200433, China
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24
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Ranasinghe JC, Wang Z, Huang S. Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications. BIOSENSORS 2022; 13:27. [PMID: 36671862 PMCID: PMC9855372 DOI: 10.3390/bios13010027] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/13/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.
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25
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Wahl J, Klint E, Hallbeck M, Hillman J, Wårdell K, Ramser K. Impact of preprocessing methods on the Raman spectra of brain tissue. BIOMEDICAL OPTICS EXPRESS 2022; 13:6763-6777. [PMID: 36589553 PMCID: PMC9774863 DOI: 10.1364/boe.476507] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/04/2022] [Accepted: 11/10/2022] [Indexed: 06/01/2023]
Abstract
Delineating cancer tissue while leaving functional tissue intact is crucial in brain tumor resection. Despite several available aids, surgeons are limited by preoperative or subjective tools. Raman spectroscopy is a label-free optical technique with promising indications for tumor tissue identification. To allow direct comparisons between measurements preprocessing of the Raman signal is required. There are many recognized methods for preprocessing Raman spectra; however, there is no universal standard. In this paper, six different preprocessing methods were tested on Raman spectra (n > 900) from fresh brain tissue samples (n = 34). The sample cohort included both primary brain tumors, such as adult-type diffuse gliomas and meningiomas, as well as metastases of breast cancer. Each tissue sample was classified according to the CNS WHO 2021 guidelines. The six methods include both direct and iterative polynomial fitting, mathematical morphology, signal derivative, commercial software, and a neural network. Data exploration was performed using principal component analysis, t-distributed stochastic neighbor embedding, and k-means clustering. For each of the six methods, the parameter combination that explained the most variance in the data, i.e., resulting in the highest Gap-statistic, was chosen and compared to the other five methods. Depending on the preprocessing method, the resulting clusters varied in number, size, and associated spectral features. The detected features were associated with hemoglobin, neuroglobin, carotenoid, water, and protoporphyrin, as well as proteins and lipids. However, the spectral features seen in the Raman spectra could not be unambiguously assigned to tissue labels, regardless of preprocessing method. We have illustrated that depending on the chosen preprocessing method, the spectral appearance of Raman features from brain tumor tissue can change. Therefore, we argue both for caution in comparing spectral features from different Raman studies, as well as the importance of transparency of methodology and implementation of the preprocessing. As discussed in this study, Raman spectroscopy for in vivo guidance in neurosurgery requires fast and adaptive preprocessing. On this basis, a pre-trained neural network appears to be a promising approach for the operating room.
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Affiliation(s)
- Joel Wahl
- Department of Engineering Sciences and Mathematics, Luleå University of Technology, 971 87, Luleå, Sweden
| | - Elisabeth Klint
- Department of Biomedical Engineering, Linköping University, 581 85 Linköping, Sweden
| | - Martin Hallbeck
- Department of Clinical Pathology and Biomedical and Clinical Sciences, Linköping University, 581 85 Linköping, Sweden
| | - Jan Hillman
- Department of Neurosurgery and Biomedical and Clinical Sciences, Linköping University, 581 85 Linköping, Sweden
| | - Karin Wårdell
- Department of Biomedical Engineering, Linköping University, 581 85 Linköping, Sweden
| | - Kerstin Ramser
- Department of Engineering Sciences and Mathematics, Luleå University of Technology, 971 87, Luleå, Sweden
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26
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Review of Intraoperative Adjuncts for Maximal Safe Resection of Gliomas and Its Impact on Outcomes. Cancers (Basel) 2022; 14:cancers14225705. [PMID: 36428797 PMCID: PMC9688206 DOI: 10.3390/cancers14225705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/12/2022] [Accepted: 11/18/2022] [Indexed: 11/22/2022] Open
Abstract
Maximal safe resection is the mainstay of treatment in the neurosurgical management of gliomas, and preserving functional integrity is linked to favorable outcomes. How these modalities differ in their effectiveness on the extent of resection (EOR), survival, and complications remains unknown. A systematic literature search was performed with the following inclusion criteria: published between 2005 and 2022, involving brain glioma surgery, and including one or a combination of intraoperative modalities: intraoperative magnetic resonance imaging (iMRI), awake/general anesthesia craniotomy mapping (AC/GA), fluorescence-guided imaging, or combined modalities. Of 525 articles, 464 were excluded and 61 articles were included, involving 5221 glioma patients, 7(11.4%) articles used iMRI, 21(36.8%) used cortical mapping, 15(24.5%) used 5-aminolevulinic acid (5-ALA) or fluorescein sodium, and 18(29.5%) used combined modalities. The heterogeneity in reporting the amount of surgical resection prevented further analysis. Progression-free survival/overall survival (PFS/OS) were reported in 18/61(29.5%) articles, while complications and permanent disability were reported in 38/61(62.2%) articles. The reviewed studies demonstrate that intraoperative adjuncts such as iMRI, AC/GA mapping, fluorescence-guided imaging, and a combination of these modalities improve EOR. However, PFS/OS were underreported. Combining multiple intraoperative modalities seems to have the highest effect compared to each adjunct alone.
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27
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Haddad AF, Aghi MK, Butowski N. Novel intraoperative strategies for enhancing tumor control: Future directions. Neuro Oncol 2022; 24:S25-S32. [PMID: 36322096 PMCID: PMC9629473 DOI: 10.1093/neuonc/noac090] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023] Open
Abstract
Maximal safe surgical resection plays a key role in the care of patients with gliomas. A range of technologies have been developed to aid surgeons in distinguishing tumor from normal tissue, with the goal of increasing tumor resection and limiting postoperative neurological deficits. Technologies that are currently being investigated to aid in improving tumor control include intraoperative imaging modalities, fluorescent tumor makers, intraoperative cell and molecular profiling of tumors, improved microscopic imaging, intraoperative mapping, augmented and virtual reality, intraoperative drug and radiation delivery, and ablative technologies. In this review, we summarize the aforementioned advancements in neurosurgical oncology and implications for improving patient outcomes.
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Affiliation(s)
- Alexander F Haddad
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Manish K Aghi
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Nicholas Butowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA
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28
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Wei W, Qiu Z. Diagnostics and theranostics of central nervous system diseases based on aggregation-induced emission luminogens. Biosens Bioelectron 2022; 217:114670. [PMID: 36126555 DOI: 10.1016/j.bios.2022.114670] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 08/25/2022] [Accepted: 08/26/2022] [Indexed: 11/02/2022]
Abstract
Central nervous system (CNS) diseases include Alzheimer's disease (AD), Parkinson's disease (PD), brain tumors, strokes, and other important diseases that are harmful and fatal to human beings. CNS diseases have the characteristics of high fatality rates, difficult diagnosis, and costly treatment. The diagnosis and treatment of CNS diseases by molecular imaging are usually limited by the depth of tissue penetration and the blood-brain barrier (BBB). Therefore, it is still a huge challenge to distinguish between the lesion and the surrounding parenchymal boundary with high sensitivity and specificity. Compared with traditional fluorophores with aggregation-caused quenching effect, luminogens with aggregation-induced emission (AIE) characteristics have strong near-infrared deep penetration, large Stokes shift, excellent biocompatibility, light stability, and desirable BBB permeability. In view of this, developing novel AIE-based materials for diagnostics and theranostics of CNS diseases is promising and of great significance. Herein, we highlight the recent research progress in this field with a special focus on near-infrared imaging and AIE nanorobots for CNS diseases. The design principle of AIE probes is discussed in detail, and the outlook is presented as well.
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Affiliation(s)
- Weichen Wei
- Materials Science and Engineering Program, University of California San Diego, La Jolla, CA, 92093, United States
| | - Zijie Qiu
- Shenzhen Institute of Aggregate Science and Technology, School of Science and Engineering, The Chinese University of Hong Kong, 2001 Longxiang Boulevard, Longgang District, Shenzhen City, Guangdong, 518172, China; Max Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany.
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29
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Li G, Rodrigues A, Kim L, Garcia C, Jain S, Zhang M, Hayden-Gephart M. 5-Aminolevulinic Acid Imaging of Malignant Glioma. Surg Oncol Clin N Am 2022; 31:581-593. [DOI: 10.1016/j.soc.2022.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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30
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Zhang B, Yao T, Chen Y, Wang C, Bao Y, Wang Z, Zhao K, Ji M. Label-Free Delineation of Human Uveal Melanoma Infiltration With Pump–Probe Microscopy. Front Oncol 2022; 12:891282. [PMID: 35936703 PMCID: PMC9354715 DOI: 10.3389/fonc.2022.891282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Uveal melanoma (UM) is the most frequent primary intraocular malignancy in adults, characterized by melanin depositions in melanocytes located in the uveal tract in the eyes. Differentiation of melanin species (eumelanin and pheomelanin) is crucial in the diagnosis and management of UM, yet it remains inaccessible for conventional histology. Here, we report that femtosecond time-resolved pump-probe microscopy could provide label-free and chemical-specific detection of melanin species in human UM based on their distinct transient relaxation dynamics at the subpicosecond timescale. The method is capable of delineating the interface between melanoma and paracancerous regions on various tissue conditions, including frozen sections, paraffin sections, and fresh tissues. Moreover, transcriptome sequencing was conducted to confirm the active eumelanin synthesis in UM. Our results may hold potential for sensitive detection of tumor boundaries and biomedical research on melanin metabolism in UM.
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Affiliation(s)
- Bohan Zhang
- State Key Laboratory of Surface Physics and Department of Physics, Multiscale Research Institute of Complex Systems, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Academy for Engineering and Technology, Human Phenome Institute, Fudan University, Shanghai, China
| | - Tengteng Yao
- Department of Ophthalmology, The Shanghai Tenth People’s Hospital of Tongji University, Shanghai, China
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yaxin Chen
- State Key Laboratory of Surface Physics and Department of Physics, Multiscale Research Institute of Complex Systems, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Academy for Engineering and Technology, Human Phenome Institute, Fudan University, Shanghai, China
| | - Chuqiao Wang
- Department of Ophthalmology, The Shanghai Tenth People’s Hospital of Tongji University, Shanghai, China
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yongyang Bao
- Department of Ophthalmology, Shanghai Ninth People’s Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Zhaoyang Wang
- Department of Ophthalmology, The Shanghai Tenth People’s Hospital of Tongji University, Shanghai, China
- *Correspondence: Minbiao Ji, ; Keke Zhao, ; Zhaoyang Wang,
| | - Keke Zhao
- Department of Ophthalmology, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
- *Correspondence: Minbiao Ji, ; Keke Zhao, ; Zhaoyang Wang,
| | - Minbiao Ji
- State Key Laboratory of Surface Physics and Department of Physics, Multiscale Research Institute of Complex Systems, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Academy for Engineering and Technology, Human Phenome Institute, Fudan University, Shanghai, China
- *Correspondence: Minbiao Ji, ; Keke Zhao, ; Zhaoyang Wang,
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31
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Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated Raman histology. Nat Commun 2022; 13:4050. [PMID: 35831299 PMCID: PMC9279377 DOI: 10.1038/s41467-022-31339-8] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 06/15/2022] [Indexed: 12/18/2022] Open
Abstract
Gastroscopic biopsy provides the only effective method for gastric cancer diagnosis, but the gold standard histopathology is time-consuming and incompatible with gastroscopy. Conventional stimulated Raman scattering (SRS) microscopy has shown promise in label-free diagnosis on human tissues, yet it requires the tuning of picosecond lasers to achieve chemical specificity at the cost of time and complexity. Here, we demonstrate that single-shot femtosecond SRS (femto-SRS) reaches the maximum speed and sensitivity with preserved chemical resolution by integrating with U-Net. Fresh gastroscopic biopsy is imaged in <60 s, revealing essential histoarchitectural hallmarks perfectly agreed with standard histopathology. Moreover, a diagnostic neural network (CNN) is constructed based on images from 279 patients that predicts gastric cancer with accuracy >96%. We further demonstrate semantic segmentation of intratumor heterogeneity and evaluation of resection margins of endoscopic submucosal dissection (ESD) tissues to simulate rapid and automated intraoperative diagnosis. Our method holds potential for synchronizing gastroscopy and histopathological diagnosis. Diagnosis of gastric cancer currently requires gastroscopic biopsy, which requires time and expertize to perform. Here, the authors demonstrate a femto-SRS imaging method which showed high accuracy in diagnosing gastric cancer without the need for pathologistbased diagnosis.
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Wang G, Wang J, Niu C, Zhao Y, Wu P. Neutrophils: New Critical Regulators of Glioma. Front Immunol 2022; 13:927233. [PMID: 35860278 PMCID: PMC9289230 DOI: 10.3389/fimmu.2022.927233] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 06/06/2022] [Indexed: 11/22/2022] Open
Abstract
In cancer, neutrophils are an important part of the tumour microenvironment (TME). Previous studies have shown that circulating and infiltrating neutrophils are associated with malignant progression and immunosuppression in gliomas. However, recent studies have shown that neutrophils have an antitumour effect. In this review, we focus on the functional roles of neutrophils in the circulation and tumour sites in patients with glioma. The mechanisms of neutrophil recruitment, immunosuppression and the differentiation of neutrophils are discussed. Finally, the potential of neutrophils as clinical biomarkers and therapeutic targets is highlighted. This review can help us gain a deeper and systematic understanding of the role of neutrophils, and provide new insights for treatment in gliomas.
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Affiliation(s)
- Guanyu Wang
- Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jinpeng Wang
- Department of Urology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Chaoshi Niu
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Anhui Provincial Stereotactic Neurosurgical Institute, Hefei, China
- Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, China
- Anhui Provincial Clinical Research Center for Neurosurgical Disease, Hefei, China
- *Correspondence: Pengfei Wu, ; Yan Zhao, ; Chaoshi Niu,
| | - Yan Zhao
- Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- *Correspondence: Pengfei Wu, ; Yan Zhao, ; Chaoshi Niu,
| | - Pengfei Wu
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Anhui Provincial Stereotactic Neurosurgical Institute, Hefei, China
- Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, China
- Anhui Provincial Clinical Research Center for Neurosurgical Disease, Hefei, China
- Anhui Province Key Laboratory of Translational Cancer Research, Bengbu Medical College, Bengbu, China
- *Correspondence: Pengfei Wu, ; Yan Zhao, ; Chaoshi Niu,
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Ge X, Pereira FC, Mitteregger M, Berry D, Zhang M, Hausmann B, Zhang J, Schintlmeister A, Wagner M, Cheng JX. SRS-FISH: A high-throughput platform linking microbiome metabolism to identity at the single-cell level. Proc Natl Acad Sci U S A 2022; 119:e2203519119. [PMID: 35727976 PMCID: PMC9245642 DOI: 10.1073/pnas.2203519119] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/08/2022] [Indexed: 12/26/2022] Open
Abstract
One of the biggest challenges in microbiome research in environmental and medical samples is to better understand functional properties of microbial community members at a single-cell level. Single-cell isotope probing has become a key tool for this purpose, but the current detection methods for determination of isotope incorporation into single cells do not allow high-throughput analyses. Here, we report on the development of an imaging-based approach termed stimulated Raman scattering-two-photon fluorescence in situ hybridization (SRS-FISH) for high-throughput metabolism and identity analyses of microbial communities with single-cell resolution. SRS-FISH offers an imaging speed of 10 to 100 ms per cell, which is two to three orders of magnitude faster than achievable by state-of-the-art methods. Using this technique, we delineated metabolic responses of 30,000 individual cells to various mucosal sugars in the human gut microbiome via incorporation of deuterium from heavy water as an activity marker. Application of SRS-FISH to investigate the utilization of host-derived nutrients by two major human gut microbiome taxa revealed that response to mucosal sugars tends to be dominated by Bacteroidales, with an unexpected finding that Clostridia can outperform Bacteroidales at foraging fucose. With high sensitivity and speed, SRS-FISH will enable researchers to probe the fine-scale temporal, spatial, and individual activity patterns of microbial cells in complex communities with unprecedented detail.
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Affiliation(s)
- Xiaowei Ge
- Department of Electrical & Computer Engineering, Boston University, Boston, MA 02215
| | - Fátima C. Pereira
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - Matthias Mitteregger
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - David Berry
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - Meng Zhang
- Department of Electrical & Computer Engineering, Boston University, Boston, MA 02215
| | - Bela Hausmann
- Joint Microbiome Facility of the Medical University of Vienna and the University of Vienna, 1030 Vienna, Austria
- Department of Laboratory Medicine, Medical University of Vienna, 1090 Vienna, Austria
| | - Jing Zhang
- Department of Biomedical Engineering, Photonics Center, Boston University, Boston, MA 02215
| | - Arno Schintlmeister
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
| | - Michael Wagner
- Centre for Microbiology and Environmental Systems Science, Department of Microbiology and Ecosystem Science, University of Vienna, 1030 Vienna, Austria
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark
| | - Ji-Xin Cheng
- Department of Electrical & Computer Engineering, Boston University, Boston, MA 02215
- Department of Biomedical Engineering, Photonics Center, Boston University, Boston, MA 02215
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Einstein EH, Ablyazova F, Rosenberg A, Harshan M, Wahl S, Har-El G, Constantino PD, Ellis JA, Boockvar JA, Langer DJ, D'Amico RS. Stimulated Raman histology facilitates accurate diagnosis in neurosurgical patients: a one-to-one noninferiority study. J Neurooncol 2022; 159:369-375. [PMID: 35764906 DOI: 10.1007/s11060-022-04071-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 06/16/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVE Stimulated Raman histology (SRH) offers efficient and accurate intraoperative neuropathological tissue analysis without procedural alteration to the diagnostic specimen. However, there are limited data demonstrating one-to-one tissue comparisons between SRH and traditional frozen sectioning. This study explores the non-inferiority of SRH as compared to frozen section on the same piece of tissue in neurosurgical patients. METHODS Tissue was collected over a 1-month period from 18 patients who underwent resection of central nervous system lesions. SRH and frozen section analyses were compared for diagnostic capabilities as well as assessed for quality and condition of tissue via a survey completed by pathologists. RESULTS SRH was sufficient for diagnosis in 78% of specimens as compared to 94% of specimens by frozen section of the same specimen. A Fisher's exact test determined there was no significant difference in diagnostic capability between the two groups. Additionally, both quality of SRH and condition of tissue after SRH were deemed to be non-inferior to frozen section. CONCLUSIONS This study provides further evidence for the non-inferiority of SRH techniques. It is also the first study to demonstrate SRH accuracy using one-to-one tissue analysis in neuropathological specimens.
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Affiliation(s)
- Evan H Einstein
- Department of Neurosurgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA.
| | - Faina Ablyazova
- Department of Neurosurgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Ashley Rosenberg
- Department of Neurosurgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Manju Harshan
- Department of Pathology, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Samuel Wahl
- Department of Pathology, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Gady Har-El
- Department of Otolaryngology-Head and Neck Surgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Peter D Constantino
- Department of Otolaryngology-Head and Neck Surgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Jason A Ellis
- Department of Neurosurgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - John A Boockvar
- Department of Neurosurgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - David J Langer
- Department of Neurosurgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Randy S D'Amico
- Department of Neurosurgery, Lenox Hill Hospital/Donald, Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
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35
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Manifold B, Fu D. Quantitative Stimulated Raman Scattering Microscopy: Promises and Pitfalls. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2022; 15:269-289. [PMID: 35300525 PMCID: PMC10083020 DOI: 10.1146/annurev-anchem-061020-015110] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Since its first demonstration, stimulated Raman scattering (SRS) microscopy has become a powerful chemical imaging tool that shows promise in numerous biological and biomedical applications. The spectroscopic capability of SRS enables identification and tracking of specific molecules or classes of molecules, often without labeling. SRS microscopy also has the hallmark advantage of signal strength that is directly proportional to molecular concentration, allowing for in situ quantitative analysis of chemical composition of heterogeneous samples with submicron spatial resolution and subminute temporal resolution. However, it is important to recognize that quantification through SRS microscopy requires assumptions regarding both system and sample. Such assumptions are often taken axiomatically, which may lead to erroneous conclusions without proper validation. In this review, we focus on the tacitly accepted, yet complex, quantitative aspect of SRS microscopy. We discuss the various approaches to quantitative analysis, examples of such approaches, challenges in different systems, and potential solutions. Through our examination of published literature, we conclude that a scrupulous approach to experimental design can further expand the powerful and incisive quantitative capabilities of SRS microscopy.
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Affiliation(s)
- Bryce Manifold
- Department of Chemistry, University of Washington, Seattle, Washington, USA;
| | - Dan Fu
- Department of Chemistry, University of Washington, Seattle, Washington, USA;
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Brzozowski K, Matuszyk E, Pieczara A, Firlej J, Nowakowska AM, Baranska M. Stimulated Raman scattering microscopy in chemistry and life science - Development, innovation, perspectives. Biotechnol Adv 2022; 60:108003. [PMID: 35690271 DOI: 10.1016/j.biotechadv.2022.108003] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/02/2022] [Accepted: 06/03/2022] [Indexed: 11/30/2022]
Abstract
In this review, we present a summary of the basics of the Stimulated Raman Scattering (SRS) phenomenon, methods of detecting the signal, and collection of the SRS images. We demonstrate the advantages of SRS imaging, and recent developments, but also the limitations, especially in image capture speeds and spatial resolution. We also compare the use of SRS microscopy in biological system studies with other techniques such as fluorescence microscopy, second-harmonic generation (SHG)-based microscopy, coherent anti-Stokes Raman scattering (CARS), and spontaneous Raman, and we show the compatibility of SRS-based systems with other discussed methods. The review is also focused on indicating innovations in SRS microscopy, on the background of which we present the layout and performance of our homemade setup built from commercially available elements enabling for imaging of the molecular structure of single cells over the spectral range of 800-3600 cm-1. Methods of image analysis are discussed, including machine learning methods for obtaining images of the distribution of selected molecules and for the detection of pathological lesions in tissues or malignant cells in the context of clinical diagnosis of a wide range of diseases with the use of SRS microscopy. Finally, perspectives for the development of SRS microscopy are proposed.
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Affiliation(s)
- K Brzozowski
- Faculty of Chemistry, Jagiellonian University, 2 Gronostajowa Str., 30-387 Krakow, Poland
| | - E Matuszyk
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland
| | - A Pieczara
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland
| | - J Firlej
- Faculty of Chemistry, Jagiellonian University, 2 Gronostajowa Str., 30-387 Krakow, Poland
| | - A M Nowakowska
- Faculty of Chemistry, Jagiellonian University, 2 Gronostajowa Str., 30-387 Krakow, Poland
| | - M Baranska
- Faculty of Chemistry, Jagiellonian University, 2 Gronostajowa Str., 30-387 Krakow, Poland; Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, 14 Bobrzynskiego Str., 30-348 Krakow, Poland.
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Voskuil FJ, Vonk J, van der Vegt B, Kruijff S, Ntziachristos V, van der Zaag PJ, Witjes MJH, van Dam GM. Intraoperative imaging in pathology-assisted surgery. Nat Biomed Eng 2022; 6:503-514. [PMID: 34750537 DOI: 10.1038/s41551-021-00808-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 06/17/2021] [Indexed: 12/12/2022]
Abstract
The pathological assessment of surgical specimens during surgery can reduce the incidence of positive resection margins, which otherwise can result in additional surgeries or aggressive therapeutic regimens. To improve patient outcomes, intraoperative spectroscopic, fluorescence-based, structural, optoacoustic and radiological imaging techniques are being tested on freshly excised tissue. The specific clinical setting and tumour type largely determine whether endogenous or exogenous contrast is to be detected and whether the tumour specificity of the detected biomarker, image resolution, image-acquisition times or penetration depth are to be prioritized. In this Perspective, we describe current clinical standards for intraoperative tissue analysis and discuss how intraoperative imaging is being implemented. We also discuss potential implementations of intraoperative pathology-assisted surgery for clinical decision-making.
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Affiliation(s)
- Floris J Voskuil
- Department of Oral and Maxillofacial Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jasper Vonk
- Department of Oral and Maxillofacial Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Bert van der Vegt
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Schelto Kruijff
- Department of Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Vasilis Ntziachristos
- Chair for Biological Imaging, Center for Translational Cancer Research, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany.,Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Neuherberg, Germany
| | - Pieter J van der Zaag
- Phillips Research Laboratories, Eindhoven, The Netherlands.,Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Molecular Biophysics, Zernike Institute, University of Groningen, Groningen, The Netherlands
| | - Max J H Witjes
- Department of Oral and Maxillofacial Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Gooitzen M van Dam
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. .,AxelaRx/TRACER BV, Groningen, The Netherlands.
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Haddad AF, Young JS, Morshed RA, Berger MS. FLAIRectomy: Resecting beyond the Contrast Margin for Glioblastoma. Brain Sci 2022; 12:brainsci12050544. [PMID: 35624931 PMCID: PMC9139350 DOI: 10.3390/brainsci12050544] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 04/21/2022] [Accepted: 04/21/2022] [Indexed: 12/11/2022] Open
Abstract
The standard of care for isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) is maximal resection followed by chemotherapy and radiation. Studies investigating the resection of GBM have primarily focused on the contrast enhancing portion of the tumor on magnetic resonance imaging. Histopathological studies, however, have demonstrated tumor infiltration within peri-tumoral fluid-attenuated inversion recovery (FLAIR) abnormalities, which is often not resected. The histopathology of FLAIR and local recurrence patterns of GBM have prompted interest in the resection of peri-tumoral FLAIR, or FLAIRectomy. To this point, recent studies have suggested a significant survival benefit associated with safe peri-tumoral FLAIR resection. In this review, we discuss the evidence surrounding the composition of peri-tumoral FLAIR, outcomes associated with FLAIRectomy, future directions of the field, and potential implications for patients.
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39
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Shin KS, Men S, Wong A, Cobb-Bruno C, Chen EY, Fu D. Quantitative Chemical Imaging of Bone Tissue for Intraoperative and Diagnostic Applications. Anal Chem 2022; 94:3791-3799. [PMID: 35188370 PMCID: PMC8944199 DOI: 10.1021/acs.analchem.1c04354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Bone is difficult to image using traditional histopathological methods, leading to challenges in intraoperative pathological evaluation that is critical in guiding surgical treatment, particularly in orthopedic oncology. In this study, we demonstrate that a multimodal quantitative imaging approach that combines stimulated Raman scattering (SRS) microscopy, two-photon fluorescence (TPF) microscopy, and second-harmonic generation (SHG) microscopy can provide useful diagnostic information regarding intact bone tissue fragments from surgical excision or biopsy specimens. We imaged bone samples from 17 patient cases and performed quantitative chemical and morphological analyses of both mineral and organic components of bone. Our main findings show that carbonate content combined with morphometric analysis of bone organic matrix can separate several major classes of bone cancer-associated diagnostic categories with an average accuracy of 92%. This proof-of-principle study demonstrates that quantitative multimodal imaging and machine learning-based analysis of bony tissue can provide crucial diagnostic information for guiding clinical decisions in orthopedic oncology. Moreover, the general methodology of morphological and chemical imaging combined with machine learning can be readily extended to other tissue types for tissue diagnosis in intraoperative and other clinical settings.
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Affiliation(s)
- Kseniya S Shin
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States.,School of Medicine, University of Washington, Seattle, Washington 98195, United States
| | - Shuaiqian Men
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Angel Wong
- Department of Bioengineering, University of Washington, Seattle, Washington 98195, United States
| | - Colburn Cobb-Bruno
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Eleanor Y Chen
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington 98195, United States
| | - Dan Fu
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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40
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Yang K, Wu J, Ao J, Hao Q, Yan M, Huang K, Ji M, Zeng H. Generation of broadband parabolic pulses based on a pre-chirper free, core-pumped nonlinear fiber amplifier for coherent anti-Stokes Raman imaging. OPTICS EXPRESS 2022; 30:7636-7646. [PMID: 35299521 DOI: 10.1364/oe.448975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/09/2022] [Indexed: 06/14/2023]
Abstract
We report the generation of parabolic pulses with broadband spectrum from a core-pumped Yb-doped fiber amplifier seeded by a dispersion managed fiber oscillator. The net cavity dispersion of Yb-doped oscillator was continuously changed from 0.074 to -0.170 ps2, which enabled us to achieve dissipative soliton, stretched pulse and soliton mode-locking operations. Spectral evolution processes in the core-pumped nonlinear fiber amplifier seeded by various input solitons were investigated experimentally and theoretically. Our finding indicates that cavity dispersion of oscillator can be used to engineer the input pulse parameter for amplifier, thus forming a pre-chirper free fiber amplification structure. In the experiment, we obtained 410-mW parabolic pulses with spectral bandwidth up to 56 nm. In combination with a passively synchronized frequency-doubled Er-doped fiber laser, we have demonstrated coherent anti-Stokes Raman imaging. The compact dual-color fiber laser source may facilitate practical applications of nonlinear biomedical imaging beyond the laboratory environment.
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41
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Wilson TJ, Toland A, Cayrol R, Vogel H. Initial Experience with Label-free Stimulated Raman Scattering Microscopy for Intraoperative Assessment of Peripheral Nerves. Clin Neurol Neurosurg 2022; 214:107180. [DOI: 10.1016/j.clineuro.2022.107180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/14/2022] [Accepted: 02/16/2022] [Indexed: 11/27/2022]
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42
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Lauwerends LJ, Abbasi H, Bakker Schut TC, Van Driel PBAA, Hardillo JAU, Santos IP, Barroso EM, Koljenović S, Vahrmeijer AL, Baatenburg de Jong RJ, Puppels GJ, Keereweer S. The complementary value of intraoperative fluorescence imaging and Raman spectroscopy for cancer surgery: combining the incompatibles. Eur J Nucl Med Mol Imaging 2022; 49:2364-2376. [PMID: 35102436 PMCID: PMC9165240 DOI: 10.1007/s00259-022-05705-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 01/23/2022] [Indexed: 01/09/2023]
Abstract
A clear margin is an important prognostic factor for most solid tumours treated by surgery. Intraoperative fluorescence imaging using exogenous tumour-specific
fluorescent agents has shown particular benefit in improving complete resection of tumour tissue. However, signal processing for fluorescence imaging is complex, and fluorescence signal intensity does not always perfectly correlate with tumour location. Raman spectroscopy has the capacity to accurately differentiate between malignant and healthy tissue based on their molecular composition. In Raman spectroscopy, specificity is uniquely high, but signal intensity is weak and Raman measurements are mainly performed in a point-wise manner on microscopic tissue volumes, making whole-field assessment temporally unfeasible. In this review, we describe the state-of-the-art of both optical techniques, paying special attention to the combined intraoperative application of fluorescence imaging and Raman spectroscopy in current clinical research. We demonstrate how these techniques are complementary and address the technical challenges that have traditionally led them to be considered mutually exclusive for clinical implementation. Finally, we present a novel strategy that exploits the optimal characteristics of both modalities to facilitate resection with clear surgical margins.
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Affiliation(s)
- L J Lauwerends
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - H Abbasi
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands.,Center for Optical Diagnostics and Therapy, Department of Dermatology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - T C Bakker Schut
- Center for Optical Diagnostics and Therapy, Department of Dermatology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - P B A A Van Driel
- Department of Orthopedic Surgery, Isala Hospital, Zwolle, Netherlands
| | - J A U Hardillo
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - I P Santos
- Molecular Physical-Chemistry R&D Unit, Department of Chemistry, University of Coimbra, Coimbra, Portugal
| | | | - S Koljenović
- Department of Pathology, Antwerp University Hospital/Antwerp University, Antwerp, Belgium
| | - A L Vahrmeijer
- Department of Surgery, Leiden University Medical Center, Leiden, Netherlands
| | - R J Baatenburg de Jong
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - G J Puppels
- Center for Optical Diagnostics and Therapy, Department of Dermatology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - S Keereweer
- Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus MC Cancer Institute, Rotterdam, Netherlands.
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Liu Y, Levenson RM, Jenkins MW. Slide Over: Advances in Slide-Free Optical Microscopy as Drivers of Diagnostic Pathology. THE AMERICAN JOURNAL OF PATHOLOGY 2022; 192:180-194. [PMID: 34774514 PMCID: PMC8883436 DOI: 10.1016/j.ajpath.2021.10.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 10/12/2021] [Accepted: 10/18/2021] [Indexed: 02/03/2023]
Abstract
Conventional analysis using clinical histopathology is based on bright-field microscopy of thinly sliced tissue specimens. Although bright-field microscopy is a simple and robust method of examining microscope slides, the preparation of the slides needed is a lengthy and labor-intensive process. Slide-free histopathology, however, uses direct imaging of intact, minimally processed tissue samples using advanced optical-imaging systems, bypassing the extended workflow now required for the preparation of tissue sections. This article explains the technical basis of slide-free microscopy, reviews common slide-free optical microscopy techniques, and discusses the opportunities and challenges involved in clinical implementation.
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Affiliation(s)
- Yehe Liu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Richard M. Levenson
- Department of Pathology and Laboratory Medicine, University of California–Davis, Sacramento, California,Address correspondence to Richard M. Levenson, M.D., UC Davis Health, Path Building, 4400 V St., Sacramento, CA 95817; or Michael W. Jenkins, Ph.D., 2109 Adelbert Rd., Wood Bldg., WG28, Cleveland, OH 44106.
| | - Michael W. Jenkins
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio,Address correspondence to Richard M. Levenson, M.D., UC Davis Health, Path Building, 4400 V St., Sacramento, CA 95817; or Michael W. Jenkins, Ph.D., 2109 Adelbert Rd., Wood Bldg., WG28, Cleveland, OH 44106.
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Doran CE, Frank CB, McGrath S, Packer RA. Use of Handheld Raman Spectroscopy for Intraoperative Differentiation of Normal Brain Tissue From Intracranial Neoplasms in Dogs. Front Vet Sci 2022; 8:819200. [PMID: 35155651 PMCID: PMC8825786 DOI: 10.3389/fvets.2021.819200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 12/16/2021] [Indexed: 11/13/2022] Open
Abstract
The aim of this study was to assess feasibility and accuracy of a hand-held, intraoperative Raman spectroscopy device as a neuronavigation aid to accurately detect neoplastic tissue from adjacent normal gray and white matter. Although Raman spectra are complicated fingerprints of cell signature, the relative shift corresponding to lipid and protein content (2,845 and 2,930 cm−1, respectively), can provide a rapid assessment of whether tissue is normal white or gray matter vs. neoplasia for real-time guidance of tumor resection. Thirteen client-owned dogs were initially enrolled in the study. Two were excluded from final analysis due to incomplete data acquisition or lack of neoplastic disease. The diagnoses of the remaining 11 dogs included six meningiomas, two histiocytic sarcomas, and three gliomas. Intraoperatively, interrogated tissues included normal gray and/or white matter and tumor. A total of five Raman spectra readings were recorded from the interrogated tissues, and samples were submitted for confirmation of Raman spectra by histopathology. A resultant total of 24 samples, 13 from neoplastic tissue and 11 from normal gray or white matter, were used to calculate sensitivity and specificity of Raman spectra compared to histopathology. The handheld Raman spectroscopy device had sensitivity of 85.7% and specificity of 90% with a positive predictive value of 92.3% and negative predictive value of 81.6%. The Raman device was feasible to use intraoperatively with rapid interpretation of spectra. Raman spectroscopy may be useful for intraoperative guidance of tumor resection.
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Affiliation(s)
- Caitlin E. Doran
- Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
- *Correspondence: Caitlin E. Doran
| | - Chad B. Frank
- Department of Microbiology, Immunology, Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
| | - Stephanie McGrath
- Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
| | - Rebecca A. Packer
- Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, United States
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45
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Qi Y, Yang L, Liu B, Liu L, Liu Y, Zheng Q, Liu D, Luo J. Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 265:120400. [PMID: 34547683 DOI: 10.1016/j.saa.2021.120400] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 09/07/2021] [Accepted: 09/10/2021] [Indexed: 06/13/2023]
Abstract
Intraoperative detection of the marginal tissues is the last and most important step to complete the resection of adenocarcinoma and squamous cell carcinoma. However, the current intraoperative diagnosis is time-consuming and requires numerous steps including staining. In this paper, we present the use of Raman spectroscopy with deep learning to achieve accurate diagnosis with stain-free process. To make the spectrum more suitable for deep learning, we utilize an unusual way of thinking which regards Raman spectral signal as a sequence and then converts it into two-dimensional Raman spectrogram by short-time Fourier transform as input. The normal-adenocarcinoma deep learning model and normal-squamous carcinoma deep learning model both achieve more than 96% accuracy, 95% sensitivity and 98% specificity when test, which higher than the conventional principal components analysis-linear discriminant analysis method with normal-adenocarcinoma model (0.896 accuracy, 0.867 sensitivity, 0.926 specificity) and normal-squamous carcinoma model (0.821 accuracy, 0.776 sensitivity, 1.000 specificity). The high performance of deep learning models provides a reliable way for intraoperative detection of marginal tissue, and is expected to reduce the detection time and save human lives.
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Affiliation(s)
- Yafeng Qi
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
| | - Lin Yang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Bangxu Liu
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
| | - Li Liu
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yuhong Liu
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China.
| | - Qingfeng Zheng
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
| | - Dameng Liu
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China.
| | - Jianbin Luo
- State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
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46
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Zou F, Zhang L, Zou X, Huang J, Nie C, Jiang J, Guo C, Wang H, Ma X, Ji M. Differential characterization of lumbar spine associated tissue histology with nonlinear optical microscopy. BIOMEDICAL OPTICS EXPRESS 2022; 13:474-484. [PMID: 35154886 PMCID: PMC8803016 DOI: 10.1364/boe.446351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 06/14/2023]
Abstract
Percutaneous endoscopic lumbar discectomy (PELD) is the major effective treatment for lumbar disc herniation, and rapid histological identification of dissected tissue is critical to guide the discectomy. In this work, we revealed the histological features of different types of peridural tissues of the lumbar spine by label-free multi-modal nonlinear optical microscopy. Stimulated Raman scattering (SRS) was used to extract lipid and protein distributions, while second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) signals were applied to image the collagen and elastin fibers at the same time. Our results demonstrated that the nonlinear optical features of the dura and adjacent soft tissues were significantly different, showing the potentials of our method for intraoperative differentiation of these critical tissues and improving the surgical outcome of PELD.
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Affiliation(s)
- Fei Zou
- Department of Orthopaedics, Huashan Hospital, Fudan University, Shanghai 200040, China
- These authors contributed equally
| | - Lili Zhang
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Multiscale Research Institute of Complex Systems, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Fudan University, Shanghai 200433, China
- State Key Laboratory of Infrared Physics, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
- These authors contributed equally
| | - Xiang Zou
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
- These authors contributed equally
| | - Jing Huang
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Multiscale Research Institute of Complex Systems, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Fudan University, Shanghai 200433, China
| | - Cong Nie
- Department of Orthopaedics, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Jianyuan Jiang
- Department of Orthopaedics, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Chongyuan Guo
- Shanghai Starriver Bilingual School, Shanghai 201108, China
| | - Hongli Wang
- Department of Orthopaedics, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Xiaosheng Ma
- Department of Orthopaedics, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Minbiao Ji
- State Key Laboratory of Surface Physics and Department of Physics, Human Phenome Institute, Multiscale Research Institute of Complex Systems, Academy for Engineering and Technology, Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education), Fudan University, Shanghai 200433, China
- Yiwu Research Institute of Fudan University, Chengbei Road, Yiwu City, Zhejiang 322000, China
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Abstract
Stimulated Raman histology (SRH) images are created by the label-free, nondestructive imaging of tissue using stimulated Raman scattering (SRS) microscopy. In a matter of seconds, these images provide real-time histologic information on biopsied tissue in the operating room. SRS microscopy uses two lasers (pump beam and Stokes beam) to amplify the Raman signal of specific chemical bonds found in macromolecules (lipids, proteins, and nucleic acids) in these tissues. The concentrations of these macromolecules are used to produce image contrast. These images are acquired and displayed using an imaging system with five main components: (1) fiber coupled microscope, (2) dual-wavelength fiber-laser module, (3) laser control module, (4) microscope control module, and (5) a computer. This manuscript details how to assemble the dual-wavelength fiber-laser module and how to generate an SRH image.
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Affiliation(s)
| | - Todd Hollon
- NYU Langone Neurosurgery Associates, New York, NY, USA
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Cialla-May D, Krafft C, Rösch P, Deckert-Gaudig T, Frosch T, Jahn IJ, Pahlow S, Stiebing C, Meyer-Zedler T, Bocklitz T, Schie I, Deckert V, Popp J. Raman Spectroscopy and Imaging in Bioanalytics. Anal Chem 2021; 94:86-119. [PMID: 34920669 DOI: 10.1021/acs.analchem.1c03235] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Dana Cialla-May
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Christoph Krafft
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Petra Rösch
- Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Tanja Deckert-Gaudig
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Torsten Frosch
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Izabella J Jahn
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Susanne Pahlow
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
| | - Clara Stiebing
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany
| | - Tobias Meyer-Zedler
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Thomas Bocklitz
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Iwan Schie
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Ernst-Abbe-Hochschule Jena, University of Applied Sciences, Department of Biomedical Engineering and Biotechnology, Carl-Zeiss-Promenade 2, 07745 Jena, Germany
| | - Volker Deckert
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany
| | - Jürgen Popp
- Leibniz-Institute of Photonic Technology, Member of the Leibniz Research Alliance - Leibniz Health Technologies, Albert-Einstein-Str. 9, 07745 Jena, Germany.,Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University, Helmholtzweg 4, 07743 Jena, Germany.,InfectoGnostics Research Campus Jena, Center of Applied Research, Philosophenweg 7, 07743 Jena, Germany
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49
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Serebrennikova KV, Berlina AN, Sotnikov DV, Zherdev AV, Dzantiev BB. Raman Scattering-Based Biosensing: New Prospects and Opportunities. BIOSENSORS 2021; 11:512. [PMID: 34940269 PMCID: PMC8699498 DOI: 10.3390/bios11120512] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 12/10/2021] [Accepted: 12/11/2021] [Indexed: 05/02/2023]
Abstract
The growing interest in the development of new platforms for the application of Raman spectroscopy techniques in biosensor technologies is driven by the potential of these techniques in identifying chemical compounds, as well as structural and functional features of biomolecules. The effect of Raman scattering is a result of inelastic light scattering processes, which lead to the emission of scattered light with a different frequency associated with molecular vibrations of the identified molecule. Spontaneous Raman scattering is usually weak, resulting in complexities with the separation of weak inelastically scattered light and intense Rayleigh scattering. These limitations have led to the development of various techniques for enhancing Raman scattering, including resonance Raman spectroscopy (RRS) and nonlinear Raman spectroscopy (coherent anti-Stokes Raman spectroscopy and stimulated Raman spectroscopy). Furthermore, the discovery of the phenomenon of enhanced Raman scattering near metallic nanostructures gave impetus to the development of the surface-enhanced Raman spectroscopy (SERS) as well as its combination with resonance Raman spectroscopy and nonlinear Raman spectroscopic techniques. The combination of nonlinear and resonant optical effects with metal substrates or nanoparticles can be used to increase speed, spatial resolution, and signal amplification in Raman spectroscopy, making these techniques promising for the analysis and characterization of biological samples. This review provides the main provisions of the listed Raman techniques and the advantages and limitations present when applied to life sciences research. The recent advances in SERS and SERS-combined techniques are summarized, such as SERRS, SE-CARS, and SE-SRS for bioimaging and the biosensing of molecules, which form the basis for potential future applications of these techniques in biosensor technology. In addition, an overview is given of the main tools for success in the development of biosensors based on Raman spectroscopy techniques, which can be achieved by choosing one or a combination of the following approaches: (i) fabrication of a reproducible SERS substrate, (ii) synthesis of the SERS nanotag, and (iii) implementation of new platforms for on-site testing.
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Affiliation(s)
| | | | | | | | - Boris B. Dzantiev
- A.N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, 119071 Moscow, Russia; (K.V.S.); (A.N.B.); (D.V.S.); (A.V.Z.)
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50
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Straehle J, Erny D, Neidert N, Heiland DH, El Rahal A, Sacalean V, Steybe D, Schmelzeisen R, Vlachos A, Mizaikoff B, Reinacher PC, Coenen VA, Prinz M, Beck J, Schnell O. Neuropathological interpretation of stimulated Raman histology images of brain and spine tumors: part B. Neurosurg Rev 2021; 45:1721-1729. [PMID: 34890000 PMCID: PMC8976804 DOI: 10.1007/s10143-021-01711-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 11/22/2021] [Accepted: 11/26/2021] [Indexed: 12/01/2022]
Abstract
Intraoperative histopathological examinations are routinely performed to provide neurosurgeons with information about the entity of tumor tissue. Here, we quantified the neuropathological interpretability of stimulated Raman histology (SRH) acquired using a Raman laser imaging system in a routine clinical setting without any specialized training or prior experience. Stimulated Raman scattering microscopy was performed on 117 samples of pathological tissue from 73 cases of brain and spine tumor surgeries. A board-certified neuropathologist — novice in the interpretation of SRH — assessed image quality by scoring subjective tumor infiltration and stated a diagnosis based on the SRH images. The diagnostic accuracy was determined by comparison to frozen hematoxylin–eosin (H&E)-stained sections and the ground truth defined as the definitive neuropathological diagnosis. The overall SRH imaging quality was rated high with the detection of tumor cells classified as inconclusive in only 4.2% of all images. The accuracy of neuropathological diagnosis based on SRH images was 87.7% and was non-inferior to the current standard of fast frozen H&E-stained sections (87.3 vs. 88.9%, p = 0.783). We found a substantial diagnostic correlation between SRH-based neuropathological diagnosis and H&E-stained frozen sections (κ = 0.8). The interpretability of intraoperative SRH imaging was demonstrated to be equivalent to the current standard method of H&E-stained frozen sections. Further research using this label-free innovative alternative vs. conventional staining is required to determine to which extent SRH-based intraoperative decision-making can be streamlined in order to facilitate the advancement of surgical neurooncology.
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Affiliation(s)
- Jakob Straehle
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Daniel Erny
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Nicolas Neidert
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Freiburg, Germany
| | - Dieter Henrik Heiland
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Freiburg, Germany.,Comprehensive Cancer Center Freiburg (CCCF), Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), partner site Freiburg, Freiburg, Germany.,Medical Faculty of Freiburg University, Freiburg, Germany
| | - Amir El Rahal
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Vlad Sacalean
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Microenvironment and Immunology Research Laboratory, Medical Center, University of Freiburg, Freiburg, Germany
| | - David Steybe
- Department of Oral and Maxillofacial Surgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Rainer Schmelzeisen
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Oral and Maxillofacial Surgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Andreas Vlachos
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Center Brain Links Brain Tools, University of Freiburg, Freiburg, Germany
| | - Boris Mizaikoff
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Ulm, Germany.,Hahn-Schickard Institute for Microanalysis Systems, Ulm, Germany
| | - Peter Christoph Reinacher
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Stereotactic and Functional Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Fraunhofer Institute for Laser Technology (ILT), Aachen, Germany
| | - Volker Arnd Coenen
- Medical Faculty of Freiburg University, Freiburg, Germany.,Department of Stereotactic and Functional Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany
| | - Marco Prinz
- Institute of Neuropathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Medical Faculty of Freiburg University, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany
| | - Jürgen Beck
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Comprehensive Cancer Center Freiburg (CCCF), Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.,Medical Faculty of Freiburg University, Freiburg, Germany.,Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Oliver Schnell
- Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany. .,Medical Faculty of Freiburg University, Freiburg, Germany.
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