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Juarez-Ramirez JC, Coyotl-Ocelotl B, Choi B, Ramos-Garcia R, Spezzia-Mazzocco T, Ramirez-San-Juan JC. Improved spatial speckle contrast model for tissue blood flow imaging: effects of spatial correlation among neighboring camera pixels. J Biomed Opt 2023; 28:125002. [PMID: 38074216 PMCID: PMC10704254 DOI: 10.1117/1.jbo.28.12.125002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 12/18/2023]
Abstract
Significance Speckle contrast analysis is the basis of laser speckle imaging (LSI), a simple, inexpensive, noninvasive technique used in various fields of medicine and engineering. A common application of LSI is the measurement of tissue blood flow. Accurate measurement of speckle contrast is essential to correctly measure blood flow. Variables, such as speckle grain size and camera pixel size, affect the speckle pattern and thus the speckle contrast. Aim We studied the effects of spatial correlation among adjacent camera pixels on the resulting speckle contrast values. Approach We derived a model that accounts for the potential correlation of intensity values in the common experimental situation where the speckle grain size is larger than the camera pixel size. In vitro phantom experiments were performed to test the model. Results Our spatial correlation model predicts that speckle contrast first increases, then decreases as the speckle grain size increases relative to the pixel size. This decreasing trend opposes what is observed with a standard speckle contrast model that does not consider spatial correlation. Experimental data are in good agreement with the predictions of our spatial correlation model. Conclusions We present a spatial correlation model that provides a more accurate measurement of speckle contrast, which should lead to improved accuracy in tissue blood flow measurements. The associated correlation factors only need to be calculated once, and open-source software is provided to assist with the calculation.
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Affiliation(s)
| | - Beatriz Coyotl-Ocelotl
- Instituto Nacional de Astrofisica, Optica y Electronica, Departamento de Optica, Tonantzintla, Mexico
| | - Bernard Choi
- University of California, Irvine, Beckman Laser Institute and Medical Clinic, Department of Surgery, Irvine, California, United States
| | - Ruben Ramos-Garcia
- Instituto Nacional de Astrofisica, Optica y Electronica, Departamento de Optica, Tonantzintla, Mexico
| | - Teresita Spezzia-Mazzocco
- Instituto Nacional de Astrofisica, Optica y Electronica, Departamento de Optica, Tonantzintla, Mexico
| | - Julio C. Ramirez-San-Juan
- Instituto Nacional de Astrofisica, Optica y Electronica, Departamento de Optica, Tonantzintla, Mexico
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2
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González Olmos A, Zilpelwar S, Sunil S, Boas DA, Postnov DD. Optimizing the precision of laser speckle contrast imaging. Sci Rep 2023; 13:17970. [PMID: 37864006 PMCID: PMC10589309 DOI: 10.1038/s41598-023-45303-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/18/2023] [Indexed: 10/22/2023] Open
Abstract
Laser speckle contrast imaging (LSCI) is a rapidly developing technology broadly applied for the full-field characterization of tissue perfusion. Over the recent years, significant advancements have been made in interpreting LSCI measurements and improving the technique's accuracy. On the other hand, the method's precision has yet to be studied in detail, despite being as important as accuracy for many biomedical applications. Here we combine simulation, theory and animal experiments to systematically evaluate and re-analyze the role of key factors defining LSCI precision-speckle-to-pixel size ratio, polarisation, exposure time and camera-related noise. We show that contrary to the established assumptions, smaller speckle size and shorter exposure time can improve the precision, while the camera choice is less critical and does not affect the signal-to-noise ratio significantly.
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Affiliation(s)
| | - Sharvari Zilpelwar
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Smrithi Sunil
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - David A Boas
- Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA
| | - Dmitry D Postnov
- Department of Clinical Medicine, Aarhus University, 8200, Aarhus, Denmark.
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3
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Long K, Liu J, Shen S, Thong M, Wang D, Chen N. Light-sheet laser speckle imaging for cilia motility assessment. Comput Struct Biotechnol J 2023; 21:1661-9. [PMID: 36874161 DOI: 10.1016/j.csbj.2023.02.036] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/18/2023] [Accepted: 02/18/2023] [Indexed: 02/22/2023] Open
Abstract
Mucociliary clearance is an important innate defense mechanism predominantly mediated by ciliated cells in the upper respiratory tract. Ciliary motility on the respiratory epithelium surface and mucus pathogen trapping assist in maintaining healthy airways. Optical imaging methods have been used to obtain several indicators for assessing ciliary movement. Light-sheet laser speckle imaging (LSH-LSI) is a label-free and non-invasive optical technique for three-dimensional and quantitative mapping of velocities of microscopic scatterers. Here, we propose to use an inverted LSH-LSI platform to study cilia motility. We have experimentally confirmed that LSH-LSI can reliably measure the ciliary beating frequency and has the potential to provide many additional quantitative indicators for characterizing the ciliary beating pattern without labeling. For example, the asymmetry between the power stroke and the recovery stroke is apparent in the local velocity waveform. PIV (particle imaging velocimetry) analysis of laser speckle data could determine the cilia motion directions in different phases.
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4
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Feng X, Geng M, Meng X, Zou D, Jin Z, Liu G, Zhou C, Ren Q, Lu Y. SGLSA: Sphygmus gated laser speckle angiography for microcirculation hemodynamics imaging. Comput Med Imaging Graph 2023; 103:102164. [PMID: 36563513 DOI: 10.1016/j.compmedimag.2022.102164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 11/16/2022] [Accepted: 12/08/2022] [Indexed: 12/23/2022]
Abstract
Hemodynamics imaging of the retinal microcirculation has been demonstrated to be potential access to evaluating ophthalmic diseases, cardio-cerebrovascular diseases, and metabolic diseases. However, existing structural and functional imaging techniques are insufficient in spatial or temporal resolution. The sphygmus gated laser speckle angiography (SGLSA) is proposed for structural and functional imaging with high spatiotemporal resolution. Compared with classic LSCI algorithms, SGLSA presents a much clearer perfusion image and higher signal-to-noise ratio pulsatility. The SGLSA algorithm also shows better performance on patients than traditional LSCI methods. The high spatiotemporal resolution provided by the SGLSA algorithm greatly enhances the ability of retinal microcirculation analysis, which makes up for the deficiency of the LSCI technology, and attaches great significance to retinal hemodynamic imaging, biomarker research, and clinical diagnosis.
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Affiliation(s)
- Ximeng Feng
- Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing, China; Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China; National Biomedical Imaging Center, Peking University, Beijing, China; Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Mufeng Geng
- Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing, China; Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China; National Biomedical Imaging Center, Peking University, Beijing, China; Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Xiangxi Meng
- Key Laboratory of Carcinogenesis and Translational Research, Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China
| | - Da Zou
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Zi Jin
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Gangjun Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Chuanqing Zhou
- College of Medical Instrument, Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Qiushi Ren
- Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing, China; Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China; National Biomedical Imaging Center, Peking University, Beijing, China; Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Yanye Lu
- Institute of Medical Technology, Peking University Health Science Center, Peking University, Beijing, China; National Biomedical Imaging Center, Peking University, Beijing, China; Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China.
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5
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Qiu C, Situ J, Wang SY, Vaghefi E. Inter-day repeatability assessment of human retinal blood flow using clinical laser speckle contrast imaging. Biomed Opt Express 2022; 13:6136-6152. [PMID: 36733735 PMCID: PMC9872875 DOI: 10.1364/boe.468871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/06/2022] [Accepted: 10/05/2022] [Indexed: 06/18/2023]
Abstract
Laser speckle contrast imaging (LSCI) can generate retinal blood flow maps inexpensively and non-invasively. These flow maps can be used to identify various eye disorders associated with reduced blood flow. Despite early success, one of the major obstacles to clinical adoption of LSCI is poor repeatability of the modality. Here, we propose an LSCI registration pipeline that registers contrast maps to correct for rigid movements. Post-registration, intra(same)-day and inter(next)-day repeatability are studied using various quantitative metrics. We have studied LSCI repeatability intra-day by using the coefficient of variation. Using the processing pipelines and custom hardware developed, similar repeatability was observed when compared to previously reported values in the literature. Inter-day repeatability analysis indicates no statistical evidence (p = 0.09) of a difference between flow measurements performed on two independent days. Further improvements to hardware, environmental controls, and participant control must be made to provide higher confidence in the repeatability of blood flow. However, this is the first time that repeatability across two different days (inter-day) using multiple exposure speckle imaging (MESI) has been analyzed and reported.
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Affiliation(s)
- Chen Qiu
- Department of Physiology, School of Medical Sciences, University of Auckland, New Zealand
- Department of Physics, University of Oxford, United Kingdom
| | - Josephine Situ
- Department of Engineering Science, University of Auckland, New Zealand
| | - Sheng-Ya Wang
- Department of Engineering Science, University of Auckland, New Zealand
| | - Ehsan Vaghefi
- School of Optometry and Vision Science, University of Auckland, New Zealand
- Auckland Bioengineering Institute, University of Auckland, New Zealand
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6
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Feng X, Jin Z, Zhou Z, Gao M, Jiang C, Hu Y, Lu Y, Li J, Ren Q, Zhou C. Retinal oxygen kinetics imaging and analysis (ROKIA) based on the integration and fusion of structural-functional imaging. Biomed Opt Express 2022; 13:5400-5417. [PMID: 36425629 PMCID: PMC9664891 DOI: 10.1364/boe.465991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/27/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
Abstract
The retina is one of the most metabolically active tissues in the body. The dysfunction of oxygen kinetics in the retina is closely related to the disease and has important clinical value. Dynamic imaging and comprehensive analyses of oxygen kinetics in the retina depend on the fusion of structural and functional imaging and high spatiotemporal resolution. But it's currently not clinically available, particularly via a single imaging device. Therefore, this work aims to develop a retinal oxygen kinetics imaging and analysis (ROKIA) technology by integrating dual-wavelength imaging with laser speckle contrast imaging modalities, which achieves structural and functional analysis with high spatial resolution and dynamic measurement, taking both external and lumen vessel diameters into account. The ROKIA systematically evaluated eight vascular metrics, four blood flow metrics, and fifteen oxygenation metrics. The single device scheme overcomes the incompatibility of optical design, harmonizes the field of view and resolution of different modalities, and reduces the difficulty of registration and image processing algorithms. More importantly, many of the metrics (such as oxygen delivery, oxygen metabolism, vessel wall thickness, etc.) derived from the fusion of structural and functional information, are unique to ROKIA. The oxygen kinetic analysis technology proposed in this paper, to our knowledge, is the first demonstration of the vascular metrics, blood flow metrics, and oxygenation metrics via a single system, which will potentially become a powerful tool for disease diagnosis and clinical research.
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Affiliation(s)
- Ximeng Feng
- Department of Biomedical Engineering,
College of Future Technology, Peking
University, Beijing 100871, China
- Institute of Biomedical
Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071,
China
- Institute of Biomedical
Engineering, Peking University Shenzhen Graduate School,
Shenzhen 518055, China
- Institute of Medical
Technology, Peking University Health Science Center, Peking
University, Beijing 100191, China
| | - Zi Jin
- Institute of Biomedical
Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071,
China
- Institute of Biomedical
Engineering, Peking University Shenzhen Graduate School,
Shenzhen 518055, China
| | - Zixia Zhou
- Department of Ophthalmology,
Peking University Shenzhen Hospital,
Shenzhen 518034, China
| | - Mengdi Gao
- Department of Biomedical Engineering,
College of Future Technology, Peking
University, Beijing 100871, China
- Institute of Biomedical
Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071,
China
- Institute of Biomedical
Engineering, Peking University Shenzhen Graduate School,
Shenzhen 518055, China
- Institute of Medical
Technology, Peking University Health Science Center, Peking
University, Beijing 100191, China
| | - Chunxia Jiang
- Department of Ophthalmology,
Peking University Shenzhen Hospital,
Shenzhen 518034, China
| | - Yicheng Hu
- Department of Biomedical Engineering,
College of Future Technology, Peking
University, Beijing 100871, China
- Institute of Biomedical
Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071,
China
- Institute of Biomedical
Engineering, Peking University Shenzhen Graduate School,
Shenzhen 518055, China
- Institute of Medical
Technology, Peking University Health Science Center, Peking
University, Beijing 100191, China
| | - Yanye Lu
- Institute of Biomedical
Engineering, Peking University Shenzhen Graduate School,
Shenzhen 518055, China
- Institute of Medical
Technology, Peking University Health Science Center, Peking
University, Beijing 100191, China
| | - Jinying Li
- Department of Ophthalmology,
Peking University Shenzhen Hospital,
Shenzhen 518034, China
| | - Qiushi Ren
- Department of Biomedical Engineering,
College of Future Technology, Peking
University, Beijing 100871, China
- Institute of Biomedical
Engineering, Shenzhen Bay Laboratory, Shenzhen 5181071,
China
- Institute of Biomedical
Engineering, Peking University Shenzhen Graduate School,
Shenzhen 518055, China
- Institute of Medical
Technology, Peking University Health Science Center, Peking
University, Beijing 100191, China
| | - Chuanqing Zhou
- College of Medical Instrument, Shanghai University of Medicine and Health Sciences, Shanghai 201318, China
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7
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Zheng S, Mertz J. Direct characterization of tissue dynamics with laser speckle contrast imaging. Biomed Opt Express 2022; 13:4118-4133. [PMID: 36032565 PMCID: PMC9408238 DOI: 10.1364/boe.462913] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/14/2022] [Accepted: 06/26/2022] [Indexed: 05/18/2023]
Abstract
Laser speckle contrast imaging (LSCI) has gained broad appeal as a technique to monitor tissue dynamics (broadly defined to include blood flow dynamics), in part because of its remarkable simplicity. When laser light is backscattered from a tissue, it produces speckle patterns that vary in time. A measure of the speckle field decorrelation time provides information about the tissue dynamics. In conventional LSCI, this measure requires numerical fitting to a specific theoretical model for the field decorrelation. However, this model may not be known a priori, or it may vary over the image field of view. We describe a method to reconstruct the speckle field decorrelation time that is completely model free, provided that the measured speckle dynamics are ergodic. We also extend our approach to allow for the possibility of non-ergodic measurements caused by the presence of a background static speckle field. In both ergodic and non-ergodic cases, our approach accurately retrieves the correlation time without any recourse to numerical fitting and is largely independent of camera exposure time. We apply our method to tissue phantom and in-vivo mouse brain imaging. Our aim is to facilitate and add robustness to LSCI processing methods for potential clinical or pre-clinical applications.
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Affiliation(s)
- Shuqi Zheng
- Department of Electrical and Computer Engineering, Boston University, 8 St. Mary’s St. Boston MA 02215, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston MA 02215, USA
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8
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Sang X, Chen B, Li D, Pan D, Sang X. Transient Thermal Response of Blood Vessels during Laser Irradiation Monitored by Laser Speckle Contrast Imaging. Photonics 2022; 9:520. [DOI: 10.3390/photonics9080520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Real-time monitoring of blood flow and thrombosis formation induced by laser irradiation is critical to reveal the thermal-damage mechanism and successfully implement vascular-dermatology laser surgery. Laser speckle contrast imaging (LSCI) is a non-invasive technique to visualize perfusion in various tissues. However, the ability of the LSCI to monitor the transient thermal response of blood vessels, especially thrombus formation during laser irradiation, requires further research. In this paper, an LSCI system was constructed and a 632 nm He-Ne laser was employed to illuminate a Sprague Dawley rat dorsal skin chamber model irradiated by a 1064 nm Nd: YAG therapy laser. The anisotropic diffusion filtering (ADF) technique is implemented after temporal LSCI (tLSCI) processing to improve the SNR and temporal resolution. The speckle flow index is used to characterize the blood-flow velocity to reduce the computational cost. The combination of the tLSCI and ADF increases the temporal resolution by five times and the SNR by 17.2 times and 16.14 times, without and with laser therapy, respectively. The laser-induced thrombus formation and vascular damage during laser surgery can be visualized without any exogenous labels, which provides a powerful tool for thrombus monitoring during laser surgery.
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9
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Abedkarimi S, Ghavami Sabouri S. Speckle Analyzer: open-source package in MATLAB for finding metrics of physical quantities based on laser speckle pattern analyzing. Appl Opt 2021; 60:9728-9735. [PMID: 34807157 DOI: 10.1364/ao.438122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 09/29/2021] [Indexed: 06/13/2023]
Abstract
We provide an open-source user-friendly graphical-user interface software in a MATLAB environment, named Speckle Analyzer, as a tool for calculating and analyzing statistical parameters of a laser speckle pattern to find metrics for an object's physical quantity. The first- and second-order statistical functions containing gray-level co-occurrence and gray-level run-length matrices and speckle grains geometrical properties are included in Speckle Analyzer. To validate the software's operation, statistical parameters of the laser speckle pattern, to find metrics for the size and concentration of particles suspended in liquid, are investigated.
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10
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Patel DD, Dhalla AH, Viehland C, Connor TB, Lipinski DM. Development of a Preclinical Laser Speckle Contrast Imaging Instrument for Assessing Systemic and Retinal Vascular Function in Small Rodents. Transl Vis Sci Technol 2021; 10:19. [PMID: 34403474 PMCID: PMC8374978 DOI: 10.1167/tvst.10.9.19] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose To develop and test a non-contact, contrast-free, retinal laser speckle contrast imaging (LSCI) instrument for use in small rodents to assess vascular anatomy, quantify hemodynamics, and measure physiological changes in response to retinal vascular dysfunction over a wide field of view (FOV). Methods A custom LSCI instrument capable of wide-field and non-contact imaging in small rodents was constructed. The effect of camera gain, laser power, and exposure duration on speckle contrast variance was standardized before the repeatability of LSCI measurements was determined in vivo. Finally, the ability of LSCI to detect alterations in local and systemic vascular function was evaluated using a laser-induced branch retinal vein occlusion and isoflurane anesthesia model, respectively. Results The LSCI system generates contrast-free maps of retinal blood flow with a 50° FOV at >376 frames per second (fps) and under a short exposure duration (>50 µs) with high reliability (intraclass correlation R = 0.946). LSCI was utilized to characterize retinal vascular anatomy affected by laser injury and longitudinally measure alterations in perfusion and blood flow profile. Under varied doses of isoflurane, LSCI could assess cardiac and systemic vascular function, including heart rate, peripheral resistance, contractility, and pulse propagation. Conclusions We present a LSCI system for detecting anatomical and physiological changes in retinal and systemic vascular health and function in small rodents. Translational Relevance Detecting and quantifying early anatomical and physiological changes in vascular function in animal models of retinal, systemic, and neurodegenerative diseases could strengthen our understanding of disease progression and enable the identification of new prognostic and diagnostic biomarkers for disease management and for assessing treatment efficacies.
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Affiliation(s)
- Dwani D Patel
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.,Department of Ophthalmology and Visual Science, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Al-Hafeez Dhalla
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Thomas B Connor
- Department of Ophthalmology and Visual Science, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Daniel M Lipinski
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.,Department of Ophthalmology and Visual Science, Medical College of Wisconsin, Milwaukee, WI, USA.,Nuffield Laboratory of Ophthalmology, University of Oxford, Oxford, UK
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11
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Abstract
The retina is the posterior neuro-integrated layer of the eye that conducts impulses induced by light to the optic nerve for human vision. Diseases of the retina often leads to diminished vision and in some cases blindness. Diabetes mellitus (DM) is a worldwide public health issue and globally, there is an estimated 463 million people that are affected by DM and its consequences. Diabetic retinopathy (DR) is a blinding complication of chronic uncontrolled DM and is the most common cause of blindness in the United States between the ages 24-75. It is estimated that the global prevalence of DR will increase to 191.0 million by 2030, of those 56.3 million possessing vision-threatening diabetic retinopathy (VTDR). For the most part, current treatment modalities control the complications of DR without addressing the underlying pathophysiology of the disease. Therefore, there is an unmet need for new therapeutics that not only repair the damaged retinal tissue, but also reverse the course of DR. The key element in developing these treatments is expanding our basic knowledge by studying DR pathogenesis in animal models of proliferative and non-proliferative DR (PDR and NPDR). There are numerous models available for the research of both PDR and NPDR with substantial overlap. Animal models available include those with genetic backgrounds prone to hyperglycemic states, immunologic etiologies, or environmentally induced disease. In this review we aimed to comprehensively summarize the available animal models for DR while also providing insight to each model's ocular therapeutic potential for drug discovery.
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Affiliation(s)
- Jose Quiroz
- Medical Scientist Training Program, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Amirfarbod Yazdanyar
- Department of Ophthalmology and Visual Sciences, State University of New York (SUNY), Upstate Medical University, Syracuse, NY, USA
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12
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Mac Grory B, Schrag M, Poli S, Boisvert CJ, Spitzer MS, Schultheiss M, Nedelmann M, Yaghi S, Guhwe M, Moore EE, Hewitt HR, Barter KM, Kim T, Chen M, Humayun L, Peng C, Chhatbar PY, Lavin P, Zhang X, Jiang X, Raz E, Saidha S, Yao J, Biousse V, Feng W. Structural and Functional Imaging of the Retina in Central Retinal Artery Occlusion - Current Approaches and Future Directions. J Stroke Cerebrovasc Dis 2021; 30:105828. [PMID: 34010777 DOI: 10.1016/j.jstrokecerebrovasdis.2021.105828] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 04/06/2021] [Accepted: 04/08/2021] [Indexed: 01/28/2023] Open
Abstract
Central retinal artery occlusion (CRAO) is a form of acute ischemic stroke which affects the retina. Intravenous thrombolysis is emerging as a compelling therapeutic approach. However, it is not known which patients may benefit from this therapy because there are no imaging modalities that adequately distinguish viable retina from irreversibly infarcted retina. The inner retina receives arterial supply from the central retinal artery and there is robust collateralization between this circulation and the outer retinal circulation, provided by the posterior ciliary circulation. Fundus photography can show canonical changes associated with CRAO including a cherry-red spot, arteriolar boxcarring and retinal pallor. Fluorescein angiography provides 2-dimensional imaging of the retinal circulation and can distinguish a complete from a partial CRAO as well as central versus peripheral retinal non-perfusion. Transorbital ultrasonography may assay flow through the central retinal artery and is useful in the exclusion of other orbital pathology that can mimic CRAO. Optical coherence tomography provides structural information on the different layers of the retina and exploratory work has described its utility in determining the time since onset of ischemia. Two experimental techniques are discussed. 1) Retinal functional imaging permits generation of capillary perfusion maps and can assay retinal oxygenation and blood flow velocity. 2) Photoacoustic imaging combines the principles of optical excitation and ultrasonic detection and - in animal studies - has been used to determine the retinal oxygen metabolic rate. Future techniques to determine retinal viability in clinical practice will require rapid, easily used, and reproducible methods that can be deployed in the emergency setting.
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Affiliation(s)
- Brian Mac Grory
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
| | - Matthew Schrag
- Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
| | - Sven Poli
- Department of Neurology & Stroke, and Hertie Institute for Clinical Brain Research, Eberhard-Karls University, Tübingen, Germany.
| | - Chantal J Boisvert
- Department of Ophthalmology, Duke University School of Medicine, Durham, North Carolina, USA.
| | - Martin S Spitzer
- Department of Ophthalmology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| | | | - Max Nedelmann
- Department of Neurology, Sana Regio Klinikum, Pinneberg, Germany.
| | - Shadi Yaghi
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Mary Guhwe
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
| | - Elizabeth E Moore
- Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
| | - Hunter R Hewitt
- Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
| | - Kelsey M Barter
- Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
| | - Taewon Kim
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
| | - Maomao Chen
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.
| | - Lucas Humayun
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.
| | - Chang Peng
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, North Carolina, USA.
| | - Pratik Y Chhatbar
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
| | - Patrick Lavin
- Department of Neurology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA; Department of Ophthalmology & Visual Sciences, Vanderbilt Eye Institute, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
| | - Xuxiang Zhang
- Department of Ophthalmology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiaoning Jiang
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, North Carolina, USA.
| | - Eytan Raz
- Department of Radiology, NYU Langone Health, New York City, New York. USA.
| | - Shiv Saidha
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
| | - Junjie Yao
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA.
| | - Valérie Biousse
- Departments of Ophthalmology and Neurology, Emory University School of Medicine, Atlanta, Georgia, USA.
| | - Wuwei Feng
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA.
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