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Wijesinghe RE, Kahatapitiya NS, Lee C, Han S, Kim S, Saleah SA, Seong D, Silva BN, Wijenayake U, Ravichandran NK, Jeon M, Kim J. Growing Trend to Adopt Speckle Variance Optical Coherence Tomography for Biological Tissue Assessments in Pre-Clinical Applications. MICROMACHINES 2024; 15:564. [PMID: 38793137 PMCID: PMC11122893 DOI: 10.3390/mi15050564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/26/2024]
Abstract
Speckle patterns are a generic feature in coherent imaging techniques like optical coherence tomography (OCT). Although speckles are granular like noise texture, which degrades the image, they carry information that can be benefited by processing and thereby furnishing crucial information of sample structures, which can serve to provide significant important structural details of samples in in vivo longitudinal pre-clinical monitoring and assessments. Since the motions of tissue molecules are indicated through speckle patterns, speckle variance OCT (SV-OCT) can be well-utilized for quantitative assessments of speckle variance (SV) in biological tissues. SV-OCT has been acknowledged as a promising method for mapping microvasculature in transverse-directional blood vessels with high resolution in micrometers in both the transverse and depth directions. The fundamental scope of this article reviews the state-of-the-art and clinical benefits of SV-OCT to assess biological tissues for pre-clinical applications. In particular, focus on precise quantifications of in vivo vascular response, therapy assessments, and real-time temporal vascular effects of SV-OCT are primarily emphasized. Finally, SV-OCT-incorporating pre-clinical techniques with high potential are presented for future biomedical applications.
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Affiliation(s)
- Ruchire Eranga Wijesinghe
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka;
- Center for Excellence in Intelligent Informatics, Electronics & Transmission (CIET), Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka
| | - Nipun Shantha Kahatapitiya
- Department of Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka; (N.S.K.); (U.W.)
| | - Changho Lee
- Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju 61186, Republic of Korea
- Department of Nuclear Medicine, Chonnam National University Medical School & Hwasun Hospital, 264, Seoyang-ro, Hwasun 58128, Republic of Korea
| | - Sangyeob Han
- ICT Convergence Research Center, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea
| | - Shinheon Kim
- ICT Convergence Research Center, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea
| | - Sm Abu Saleah
- ICT Convergence Research Center, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea
| | - Daewoon Seong
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea
| | - Bhagya Nathali Silva
- Center for Excellence in Intelligent Informatics, Electronics & Transmission (CIET), Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka
- Faculty of Computing, Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka
| | - Udaya Wijenayake
- Department of Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka; (N.S.K.); (U.W.)
| | - Naresh Kumar Ravichandran
- Center for Scientific Instrumentation, Korea Basic Science Institute, 169-148, Gwahak-ro, Yuseong-gu, Daejeon 34133, Republic of Korea
| | - Mansik Jeon
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea
| | - Jeehyun Kim
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea
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Lin Q, Choyke PL, Sato N. Visualizing vasculature and its response to therapy in the tumor microenvironment. Theranostics 2023; 13:5223-5246. [PMID: 37908739 PMCID: PMC10614675 DOI: 10.7150/thno.84947] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 07/30/2023] [Indexed: 11/02/2023] Open
Abstract
Tumor vasculature plays a critical role in the progression and metastasis of tumors, antitumor immunity, drug delivery, and resistance to therapies. The morphological and functional changes of tumor vasculature in response to therapy take place in a spatiotemporal-dependent manner, which can be predictive of treatment outcomes. Dynamic monitoring of intratumor vasculature contributes to an improved understanding of the mechanisms of action of specific therapies or reasons for treatment failure, leading to therapy optimization. There is a rich history of methods used to image the vasculature. This review describes recent advances in imaging technologies to visualize the tumor vasculature, with a focus on enhanced intravital imaging techniques and tumor window models. We summarize new insights on spatial-temporal vascular responses to various therapies, including changes in vascular perfusion and permeability and immune-vascular crosstalk, obtained from intravital imaging. Finally, we briefly discuss the clinical applications of intravital imaging techniques.
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Affiliation(s)
| | | | - Noriko Sato
- Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
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Selection of antibody and light exposure regimens alters therapeutic effects of EGFR-targeted near-infrared photoimmunotherapy. Cancer Immunol Immunother 2022; 71:1877-1887. [PMID: 35013765 PMCID: PMC9271517 DOI: 10.1007/s00262-021-03124-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 11/26/2021] [Indexed: 11/27/2022]
Abstract
Near-infrared photoimmunotherapy (NIR-PIT) is a cell-specific cancer therapy that uses an antibody-photoabsorber (IRDye700DX, IR700) conjugate (APC) and NIR light. Intravenously injected APC binds the target cells, and subsequent NIR light exposure induces immunogenic cell death only in targeted cells. Panitumumab and cetuximab are antibodies that target human epidermal growth factor receptor (hEGFR) and are suitable for NIR-PIT. In athymic nude mouse models, panitumumab-based NIR-PIT showed superior therapeutic efficacy compared to cetuximab-based NIR-PIT because of the longer half-life of panitumumab-IR700 (pan-IR700) compared with cetuximab-IR700 (cet-IR700). Two light exposures on two consecutive days have also been shown to induce superior effects compared to a single light exposure in the athymic nude mouse model. However, the optimal regimen has not been assessed in immunocompetent mice. In this study, we compared panitumumab and cetuximab in APCs for NIR-PIT, and single and double light exposures using a newly established hEGFR-expressing cancer cell line derived from immunocompetent C57BL/6 mice (mEERL-hEGFR cell line). Fluorescence imaging showed that the decline of pan-IR700 was slower than cet-IR700 confirming a longer clearance time. Among all the combinations tested, mice receiving pan-IR700 and double light exposure showed the greatest tumor growth inhibition. This group was also shown to activate CD8+ T lymphocytes in lymph nodes and accumulate CD8+ T lymphocytes to a greater extent within the tumor compared with the control group. These results showed that APCs with longer half-life and double light exposure lead to superior outcomes in cancer cell-targeted NIR-PIT in an immunocompetent mouse model.
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