1
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Hu Y, Feng Y, Long X, Zheng D, Liu G, Lu Y, Ren Q, Huang Z. Megahertz multi-parametric ophthalmic OCT system for whole eye imaging. BIOMEDICAL OPTICS EXPRESS 2024; 15:3000-3017. [PMID: 38855668 PMCID: PMC11161356 DOI: 10.1364/boe.517757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 04/02/2024] [Accepted: 04/04/2024] [Indexed: 06/11/2024]
Abstract
An ultrahigh-speed, wide-field OCT system for the imaging of anterior, posterior, and ocular biometers is crucial for obtaining comprehensive ocular parameters and quantifying ocular pathology size. Here, we demonstrate a multi-parametric ophthalmic OCT system with a speed of up to 1 MHz for wide-field imaging of the retina and 50 kHz for anterior chamber and ocular biometric measurement. A spectrum correction algorithm is proposed to ensure the accurate pairing of adjacent A-lines and elevate the A-scan speed from 500 kHz to 1 MHz for retinal imaging. A registration method employing position feedback signals was introduced, reducing pixel offsets between forward and reverse galvanometer scanning by 2.3 times. Experimental validation on glass sheets and the human eye confirms feasibility and efficacy. Meanwhile, we propose a revised formula to determine the "true" fundus size using all-axial length parameters from different fields of view. The efficient algorithms and compact design enhance system compatibility with clinical requirements, showing promise for widespread commercialization.
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Affiliation(s)
- Yicheng Hu
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518071, China
| | - Yutao Feng
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China
- The College of Biochemical Engineering, Beijing Union University, Beijing 100021, China
| | - Xing Long
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China
| | - Dongye Zheng
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518071, China
| | - Gangjun Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518071, 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
| | - Qiushi Ren
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518071, China
| | - Zhiyu Huang
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen 518071, China
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2
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Hormel TT, Jia Y. OCT angiography and its retinal biomarkers [Invited]. BIOMEDICAL OPTICS EXPRESS 2023; 14:4542-4566. [PMID: 37791289 PMCID: PMC10545210 DOI: 10.1364/boe.495627] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/13/2023] [Accepted: 07/13/2023] [Indexed: 10/05/2023]
Abstract
Optical coherence tomography angiography (OCTA) is a high-resolution, depth-resolved imaging modality with important applications in ophthalmic practice. An extension of structural OCT, OCTA enables non-invasive, high-contrast imaging of retinal and choroidal vasculature that are amenable to quantification. As such, OCTA offers the capability to identify and characterize biomarkers important for clinical practice and therapeutic research. Here, we review new methods for analyzing biomarkers and discuss new insights provided by OCTA.
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Affiliation(s)
- Tristan T. Hormel
- Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Yali Jia
- Casey Eye Institute, Oregon Health & Science University, Portland, Oregon, USA
- Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
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3
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Pan M, Wang Y, Gong P, Wang Q, Cense B. Feasibility of deep learning-based polarization-sensitive optical coherence tomography angiography for imaging cutaneous microvasculature. BIOMEDICAL OPTICS EXPRESS 2023; 14:3856-3870. [PMID: 37799704 PMCID: PMC10549757 DOI: 10.1364/boe.488822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/09/2023] [Accepted: 06/05/2023] [Indexed: 10/07/2023]
Abstract
Polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization states of the backscattered light from tissue that can improve angiography based on conventional optical coherence tomography (OCT). We present a feasibility study on PS-OCT integrated with deep learning for PS-OCT angiography (PS-OCTA) imaging of human cutaneous microvasculature. Two neural networks were assessed for PS-OCTA, including the residual dense network (RDN), which previously showed superior performance for angiography with conventional OCT and the upgraded grouped RDN (GRDN). We also investigated different protocols to process the multiple signal channels provided by the Jones matrices from the PS-OCT system to achieve optimal PS-OCTA performance. The training and testing of the deep learning-based PS-OCTA were performed using PS-OCT scans collected from 18 skin locations comprising 16,600 B-scan pairs. The results demonstrated a moderately improved performance of GRDN over RDN, and of the use of the combined signal from the Jones matrix elements over the separate use of the elements, as well as a similar image quality to that provided by speckle decorrelation angiography. GRDN-based PS-OCTA also showed ∼2-3 times faster processing and improved mitigation of tissue motion as compared to speckle decorrelation angiography, and enabled fully automatic processing. Deep learning-based PS-OCTA can be used for imaging cutaneous microvasculature, which may enable easy adoption of PS-OCTA for preclinical and clinical applications.
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Affiliation(s)
- Moning Pan
- Key Laboratory for Biomedical Engineering of Ministry of Education, Embedded System Engineering Research Center of Ministry of Education and Zhejiang Provincial Key Laboratory for Network Multimedia Technologies, Zhejiang University, Hangzhou, 310027, China
| | - Yuxing Wang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Embedded System Engineering Research Center of Ministry of Education and Zhejiang Provincial Key Laboratory for Network Multimedia Technologies, Zhejiang University, Hangzhou, 310027, China
| | - Peijun Gong
- Key Laboratory for Biomedical Engineering of Ministry of Education, Embedded System Engineering Research Center of Ministry of Education and Zhejiang Provincial Key Laboratory for Network Multimedia Technologies, Zhejiang University, Hangzhou, 310027, China
- BRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands and Centre for Medical Research,
The University of Western Australia, Perth, WA 6009, Australia
- Department of Electrical, Electronic & Computer Engineering, School of Engineering, The University of Western Australia, Perth, WA 6009, Australia
| | - Qiang Wang
- Department of Electrical, Electronic & Computer Engineering, School of Engineering, The University of Western Australia, Perth, WA 6009, Australia
| | - Barry Cense
- Department of Electrical, Electronic & Computer Engineering, School of Engineering, The University of Western Australia, Perth, WA 6009, Australia
- Department of Mechanical Engineering, Yonsei University, Seoul, 03722, Republic of Korea
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4
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Beckmann L, Cai Z, Margolis M, Fang R, Djalilian A, Zhang HF. Recent advances in optical coherence tomography for anterior segment imaging in small animals and their clinical implications. Ocul Surf 2022; 26:222-233. [PMID: 36195237 PMCID: PMC10040227 DOI: 10.1016/j.jtos.2022.08.011] [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: 04/01/2022] [Revised: 08/16/2022] [Accepted: 08/17/2022] [Indexed: 12/05/2022]
Abstract
Anterior segment optical coherence tomography (AS-OCT) is a rapidly evolving area of OCT imaging, providing high-resolution and non-invasive volumetric imaging of the anterior segment. This review focuses on recent advances in AS-OCT imaging in small animals, which we categorize into ultrahigh-resolution, spectroscopic, magnetomotive, polarization-sensitive, and angiographic AS-OCTs. We summarize their technical foundations, review their applications to small animal imaging, and briefly discuss their current and future clinical applications.
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Affiliation(s)
- Lisa Beckmann
- Department of Biomedical Engineering, Northwestern University, Evanston IL, USA
| | - Zhen Cai
- Department of Biomedical Engineering, Northwestern University, Evanston IL, USA; Currently with Department of Ophthalmology, Tongji Medical College, HuaZhong University of Science and Technology, Wuhan, Hubei, China
| | - Mathew Margolis
- Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago IL, USA
| | - Raymond Fang
- Department of Biomedical Engineering, Northwestern University, Evanston IL, USA
| | - Ali Djalilian
- Department of Ophthalmology and Visual Science, University of Illinois at Chicago, Chicago IL, USA
| | - Hao F Zhang
- Department of Biomedical Engineering, Northwestern University, Evanston IL, USA.
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5
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Chen G, Wang W, Li Y. Comparative study of OCTA algorithms with a high-sensitivity multi-contrast Jones matrix OCT system for human skin imaging. BIOMEDICAL OPTICS EXPRESS 2022; 13:4718-4736. [PMID: 36187265 PMCID: PMC9484425 DOI: 10.1364/boe.462941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 07/21/2022] [Accepted: 07/28/2022] [Indexed: 06/16/2023]
Abstract
The multi-contrast Jones matrix OCT (JMT) system can not only improve the tissue-specific contrast but also enhance the sensitivity of detecting flow, which is gaining increasing attention. However, for the JMT system, there is currently a lack of studies evaluating and guiding the selection of suitable angiography algorithms to map the most appealing quality of angiograms for clinical use. In this paper, by a homemade high-sensitivity multi-contrast JMT system based 200 kHz swept source, the performance of two complex-signal-based OCTA methods that are insensitive to phase instability and one amplitude-signal-based OCTA method are compared for in-vivo imaging of human skin qualitatively and quantitatively. Six metrics, including vascular connectivity, image contrast-to-noise ratio, image signal-to-noise ratio, vessel diameter index, blood vessel density, and processing time, are assessed. The results show that the vascular networks processed by all OCTA methods and the texture of skin could be visualized simultaneously and markedly. Additionally, the complex-signal-based OCTA methods successfully suppress phase instabilities and even outperform the amplitude-signal-based OCTA algorithm in some indicators. This paper has a certain guiding significance for selecting an appropriate angiography algorithm and expanding the application field with this system.
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Affiliation(s)
- Guoqiang Chen
- Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China, School of Optics and Photonics, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing 100081, China
| | - Wen’ai Wang
- Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China, School of Optics and Photonics, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing 100081, China
- Institute of Engineering Medicine, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing 100081, China
| | - Yanqiu Li
- Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China, School of Optics and Photonics, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing 100081, China
- Institute of Engineering Medicine, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing 100081, China
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6
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Jiang Z, Huang Z, You Y, Geng M, Meng X, Qiu B, Zhu L, Gao M, Wang J, Zhou C, Ren Q, Lu Y. Rethinking the neighborhood information for deep learning‐based optical coherence tomography angiography. Med Phys 2022; 49:3705-3716. [DOI: 10.1002/mp.15618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 02/08/2022] [Accepted: 03/11/2022] [Indexed: 10/18/2022] Open
Affiliation(s)
- Zhe Jiang
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Zhiyu Huang
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Yunfei You
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Mufeng Geng
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Xiangxi Meng
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education) Department of Nuclear Medicine Peking University Cancer Hospital & Institute Beijing 100142 China
| | - Bin Qiu
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Lei Zhu
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Mengdi Gao
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Jing Wang
- Sir Run Run Shaw Hospital Zhejiang University School of Medicine Hangzhou 310058 China
| | - Chuanqing Zhou
- College of Medical Instrument Shanghai University of Medicine and Health Sciences Shanghai 201318 China
| | - Qiushi Ren
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Department of Biomedical Engineering College of Future Technology Peking University Beijing 100871 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
- Institute of Biomedical Engineering Shenzhen Bay Laboratory 5F Shenzhen 518071 China
| | - Yanye Lu
- Institute of Medical Technology Peking University Health Science Center Peking University Beijing 100191 China
- Institute of Biomedical Engineering Peking University Shenzhen Graduate School Shenzhen 518055 China
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7
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Hormel TT, Hwang TS, Bailey ST, Wilson DJ, Huang D, Jia Y. Artificial intelligence in OCT angiography. Prog Retin Eye Res 2021; 85:100965. [PMID: 33766775 PMCID: PMC8455727 DOI: 10.1016/j.preteyeres.2021.100965] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/09/2021] [Accepted: 03/15/2021] [Indexed: 12/21/2022]
Abstract
Optical coherence tomographic angiography (OCTA) is a non-invasive imaging modality that provides three-dimensional, information-rich vascular images. With numerous studies demonstrating unique capabilities in biomarker quantification, diagnosis, and monitoring, OCTA technology has seen rapid adoption in research and clinical settings. The value of OCTA imaging is significantly enhanced by image analysis tools that provide rapid and accurate quantification of vascular features and pathology. Today, the most powerful image analysis methods are based on artificial intelligence (AI). While AI encompasses a large variety of techniques, machine-learning-based, and especially deep-learning-based, image analysis provides accurate measurements in a variety of contexts, including different diseases and regions of the eye. Here, we discuss the principles of both OCTA and AI that make their combination capable of answering new questions. We also review contemporary applications of AI in OCTA, which include accurate detection of pathologies such as choroidal neovascularization, precise quantification of retinal perfusion, and reliable disease diagnosis.
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Affiliation(s)
- Tristan T Hormel
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Thomas S Hwang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Steven T Bailey
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - David J Wilson
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - David Huang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Yali Jia
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, 97239, USA.
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8
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Nakamichi Y, Chiu KS, Sun CW. Signal properties of split-spectrum amplitude decorrelation angiography for quantitative optical coherence tomography-based velocimetry. BIOMEDICAL OPTICS EXPRESS 2021; 12:5955-5968. [PMID: 34745715 PMCID: PMC8548019 DOI: 10.1364/boe.432297] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/19/2021] [Accepted: 08/26/2021] [Indexed: 05/17/2023]
Abstract
Split-spectrum amplitude-decorrelation angiography (SSADA) is a noninvasive and three-dimensional angiographic technique with a microscale spatial resolution based on optical coherence tomography. The SSADA signal is known to be correlated with the blood flow velocity and the quantitative velocimetry with SSADA has been expected; however, the signal properties of SSADA are not completely understood due to lack of comprehensive investigations of parameters related to SSADA signals. In this study, phantom experiments were performed to comprehensively investigate the relation of SSADA signals with flow velocities, time separations, particle concentrations, signal-to-noise ratios, beam spot sizes, and viscosities, and revealed that SSADA signals reflect the spatial commonality within a coherence volume between adjacent A-scans.
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Affiliation(s)
- Yu Nakamichi
- Department of Mechanical Engineering, Faculty of Engineering, Sanyo-Onoda City University, 1-1-1, Daigaku-dori, Sanyo-Onoda, Yamaguchi, 756-0884, Japan
| | - Kai-shih Chiu
- Biomedical Optical Imaging Lab, Department of Photonics, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, No. 1001, Daxue Rd., East Dist., Hsinchu, 30010, Taiwan
| | - Chia-Wei Sun
- Biomedical Optical Imaging Lab, Department of Photonics, College of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, No. 1001, Daxue Rd., East Dist., Hsinchu, 30010, Taiwan
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9
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Ringel MJ, Tang EM, Tao YK. Advances in multimodal imaging in ophthalmology. Ther Adv Ophthalmol 2021; 13:25158414211002400. [PMID: 35187398 PMCID: PMC8855415 DOI: 10.1177/25158414211002400] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 02/23/2021] [Indexed: 12/12/2022] Open
Abstract
Multimodality ophthalmic imaging systems aim to enhance the contrast, resolution, and functionality of existing technologies to improve disease diagnostics and therapeutic guidance. These systems include advanced acquisition and post-processing methods using optical coherence tomography (OCT), combined scanning laser ophthalmoscopy and OCT systems, adaptive optics, surgical guidance, and photoacoustic technologies. Here, we provide an overview of these ophthalmic imaging systems and their clinical and basic science applications.
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Affiliation(s)
- Morgan J. Ringel
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Eric M. Tang
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Yuankai K. Tao
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
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10
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Jiang Z, Huang Z, Qiu B, Meng X, You Y, Liu X, Geng M, Liu G, Zhou C, Yang K, Maier A, Ren Q, Lu Y. Weakly Supervised Deep Learning-Based Optical Coherence Tomography Angiography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:688-698. [PMID: 33136539 DOI: 10.1109/tmi.2020.3035154] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Deep learning networks have been widely applied in the field of OCTA reconstruction, benefiting from its powerful mapping capability among images. However, these existing deep learning-based methods depend on high-quality labels, which are hard to acquire considering imaging hardware limitations and practical data acquisition conditions. In this article, we proposed an unprecedented weakly supervised deep learning-based pipeline for OCTA reconstruction task, in the absence of high-quality training labels. The proposed pipeline was investigated on an in vivo animal dataset and a human eye dataset by a cross-validation strategy. Compared with supervised learning approaches, the proposed approach demonstrated similar or even better performance in the OCTA reconstruction task. These investigations indicate that the proposed weakly supervised learning strategy is well capable of performing OCTA reconstruction, and has a certain potential towards clinical applications.
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11
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Hormel TT, Jia Y, Jian Y, Hwang TS, Bailey ST, Pennesi ME, Wilson DJ, Morrison JC, Huang D. Plexus-specific retinal vascular anatomy and pathologies as seen by projection-resolved optical coherence tomographic angiography. Prog Retin Eye Res 2021; 80:100878. [PMID: 32712135 PMCID: PMC7855241 DOI: 10.1016/j.preteyeres.2020.100878] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 05/13/2020] [Accepted: 05/18/2020] [Indexed: 12/22/2022]
Abstract
Optical coherence tomographic angiography (OCTA) is a novel technology capable of imaging retinal vasculature three-dimensionally at capillary scale without the need to inject any extrinsic dye contrast. However, projection artifacts cause superficial retinal vascular patterns to be duplicated in deeper layers, thus interfering with the clean visualization of some retinal plexuses and vascular pathologies. Projection-resolved OCTA (PR-OCTA) uses post-processing algorithms to reduce projection artifacts. With PR-OCTA, it is now possible to resolve up to 4 distinct retinal vascular plexuses in the living human eye. The technology also allows us to detect and distinguish between various retinal and optic nerve diseases. For example, optic nerve diseases such as glaucoma primarily reduces the capillary density in the superficial vascular complex, which comprises the nerve fiber layer plexus and the ganglion cell layer plexus. Outer retinal diseases such as retinitis pigmentosa primarily reduce the capillary density in the deep vascular complex, which comprises the intermediate capillary plexus and the deep capillary plexus. Retinal vascular diseases such as diabetic retinopathy and vein occlusion affect all plexuses, but with different patterns of capillary loss and vascular malformations. PR-OCTA is also useful in distinguishing various types of choroidal neovascularization and monitoring their response to anti-angiogenic medications. In retinal angiomatous proliferation and macular telangiectasia type 2, PR-OCTA can trace the pathologic vascular extension into deeper layers as the disease progress through stages. Plexus-specific visualization and measurement of retinal vascular changes are improving our ability to diagnose, stage, monitor, and assess treatment response in a wide variety of optic nerve and retinal diseases. These applications will be further enhanced with the continuing improvement of the speed and resolution of the OCT platforms, as well as the development of software algorithms to reduce artifacts, improve image quality, and make quantitative measurements.
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Affiliation(s)
- Tristan T Hormel
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Yali Jia
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Yifan Jian
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Thomas S Hwang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Steven T Bailey
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Mark E Pennesi
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - David J Wilson
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - John C Morrison
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - David Huang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA.
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12
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Tan B, Sim R, Chua J, Wong DWK, Yao X, Garhöfer G, Schmidl D, Werkmeister RM, Schmetterer L. Approaches to quantify optical coherence tomography angiography metrics. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:1205. [PMID: 33241054 PMCID: PMC7576021 DOI: 10.21037/atm-20-3246] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Optical coherence tomography (OCT) has revolutionized the field of ophthalmology in the last three decades. As an OCT extension, OCT angiography (OCTA) utilizes a fast OCT system to detect motion contrast in ocular tissue and provides a three-dimensional representation of the ocular vasculature in a non-invasive, dye-free manner. The first OCT machine equipped with OCTA function was approved by U.S. Food and Drug Administration in 2016 and now it is widely applied in clinics. To date, numerous methods have been developed to aid OCTA interpretation and quantification. In this review, we focused on the workflow of OCTA-based interpretation, beginning from the generation of the OCTA images using signal decorrelation, which we divided into intensity-based, phase-based and phasor-based methods. We further discussed methods used to address image artifacts that are commonly observed in clinical settings, to the algorithms for image enhancement, binarization, and OCTA metrics extraction. We believe a better grasp of these technical aspects of OCTA will enhance the understanding of the technology and its potential application in disease diagnosis and management. Moreover, future studies will also explore the use of ocular OCTA as a window to link ocular vasculature to the function of other organs such as the kidney and brain.
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Affiliation(s)
- Bingyao Tan
- Institute for Health Technologies, Nanyang Technological University, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.,SERI-NTU Advanced Ocular Engineering (STANCE) Program, Nanyang Technological University, Singapore, Singapore
| | - Ralene Sim
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Jacqueline Chua
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.,Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
| | - Damon W K Wong
- Institute for Health Technologies, Nanyang Technological University, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.,SERI-NTU Advanced Ocular Engineering (STANCE) Program, Nanyang Technological University, Singapore, Singapore
| | - Xinwen Yao
- Institute for Health Technologies, Nanyang Technological University, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.,SERI-NTU Advanced Ocular Engineering (STANCE) Program, Nanyang Technological University, Singapore, Singapore
| | - Gerhard Garhöfer
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Doreen Schmidl
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - René M Werkmeister
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Leopold Schmetterer
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.,SERI-NTU Advanced Ocular Engineering (STANCE) Program, Nanyang Technological University, Singapore, Singapore.,Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore.,Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.,Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.,Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore.,Department of Ophthalmology, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.,Institute of Molecular and Clinical Ophthalmology, Basel, Switzerland
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13
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Evaluation of Microvascular Structure Changes after Conbercept Treatment on Macular Edema Secondary to Retinal Vein Occlusion. BIOMED RESEARCH INTERNATIONAL 2020; 2020:9046781. [PMID: 32685542 PMCID: PMC7322615 DOI: 10.1155/2020/9046781] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 05/27/2020] [Indexed: 11/18/2022]
Abstract
Aims To confirm the therapeutic efficacy of conbercept for the treatment of macular edema (ME) secondary to retinal vein occlusion (RVO) by using optical coherence tomography angiography (OCTA) and to find out the differences in therapeutic efficacy between ischemic and nonischemic retinal vein occlusion (iRVO or non-iRVO) after conbercept treatment. Methods In this prospective, randomized, and comparative study, 60 unilateral eyes suffered from RVO combined with macular edema were included and fellow eye as controls. After an initial intravitreal injection of conbercept (IVIC), a pro re nata (PRN) strategy was adopted, and the follow-up time was 6 months. The foveal avascular zone (FAZ), vascular density of superficial capillary plexus (SCP), and vascular density of deep retinal capillary plexus (DCP), nonperfused areas (NPAs) were evaluated with OCTA on baseline and after treatment. Results The mean intravitreal injection number was 2.9 ± 0.89 times during six months in iRVO patients and 2.1 ± 0.86 times in non-iRVO patients, with statistically significant difference (p < 0.05). On baseline, central macular thickness (CMT) and FAZ were significantly thickened and enlarged compared to those of healthy fellow eyes; the vascular density of SCP and DCP were significantly decreased, and the differences were statistically significant (p < 0.05). Compared to baseline, after treatment, the best-corrected visual acuity (BCVA) was improved in either iRVO or non-iRVO (−0.601 ± 0.387, −0.241 ± 0.341 logMAR, p < 0.05). In iRVO, the improvement was more substantial than that of the non-iRVO group. FAZ in the non-iRVO group had significantly decreased compared to that in iRVO group (−0.044 ± 0.040 versus 0.014 ± 0.043 mm2, p < 0.05). CMT, the vascular density of SCP, and DCP had no significant difference. Conclusions The changes of microvascular structure can be quantitatively evaluated by using OCTA for the patients with RVO. Conbercept had a significant effect on treatment of RVO with macular edema. A more profound effect was achieved in the iRVO group on visual improvement and FAZ reduction in the non-iRVO group after conbercept treatment.
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14
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Jiang Z, Huang Z, Qiu B, Meng X, You Y, Liu X, Liu G, Zhou C, Yang K, Maier A, Ren Q, Lu Y. Comparative study of deep learning models for optical coherence tomography angiography. BIOMEDICAL OPTICS EXPRESS 2020; 11:1580-1597. [PMID: 32206430 PMCID: PMC7075619 DOI: 10.1364/boe.387807] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 02/21/2020] [Accepted: 02/21/2020] [Indexed: 05/10/2023]
Abstract
Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Meanwhile, deep learning has achieved rapid development in image-to-image translation tasks. Some studies have proposed applying deep learning models to OCTA reconstruction and have obtained preliminary results. However, current studies are mostly limited to a few specific deep neural networks. In this paper, we conducted a comparative study to investigate OCTA reconstruction using deep learning models. Four representative network architectures including single-path models, U-shaped models, generative adversarial network (GAN)-based models and multi-path models were investigated on a dataset of OCTA images acquired from rat brains. Three potential solutions were also investigated to study the feasibility of improving performance. The results showed that U-shaped models and multi-path models are two suitable architectures for OCTA reconstruction. Furthermore, merging phase information should be the potential improving direction in further research.
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Affiliation(s)
- Zhe Jiang
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, No. 2199 Lishui Road, Nanshan District, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
| | - Zhiyu Huang
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, No. 2199 Lishui Road, Nanshan District, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
| | - Bin Qiu
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, No. 2199 Lishui Road, Nanshan District, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
| | - Xiangxi Meng
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Yunfei You
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, No. 2199 Lishui Road, Nanshan District, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
| | - Xi Liu
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
| | - Gangjun Liu
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, No. 2199 Lishui Road, Nanshan District, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
| | - Chuangqing Zhou
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
| | - Kun Yang
- College of Quality and Technical Supervision, Hebei University, No. 2666 Qiyidong Road, Baoding, 071000, China
| | - Andreas Maier
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuremberg, Martensstrasse 3, 91058 Erlangen, Germany
| | - Qiushi Ren
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, No. 2199 Lishui Road, Nanshan District, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
| | - Yanye Lu
- Department of Biomedical Engineering, College of Engineering, Peking University, No. 5 Yihe Yuan Road, Haidian District, Beijing 100871, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, No. 2199 Lishui Road, Nanshan District, Shenzhen 518055, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory 5F, No. 9 Duxue Road, Nanshan District, Shenzhen 518071, China
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuremberg, Martensstrasse 3, 91058 Erlangen, Germany
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15
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Usman M, Iqbal K, Ali MH, Nafees K. Features and Diagnostic Accuracy of Optical Coherence Tomography Angiography in Neovascular Age-related Macular Degeneration. Cureus 2019; 11:e6485. [PMID: 32025408 PMCID: PMC6984172 DOI: 10.7759/cureus.6485] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 12/28/2019] [Indexed: 11/05/2022] Open
Abstract
Introduction Age-related macular degeneration (AMD) is one of the important causes of visual impairment in aging population. Fundus fluorescein angiography (FFA) is gold standard for the diagnosis of neovascular AMD (nAMD) while optical coherence tomography (OCT) aids in the diagnosis of nAMD and is very useful for follow-up. OCT angiography (OCTA) is an evolving imaging technology that can be used as a valid diagnostic tool to study morphology of choroidal neovascularization (CNV) that is seen in nAMD. This study was conducted with the objective to determine diagnostic accuracy and OCTA features of occult and classic CNV in patients with nAMD. Methods In this prospective observational study, 90 eyes of 58 patients with nAMD were studied with OCT, OCTA and FFA. OCTA scans were analyzed to qualitatively describe the morphological appearance of CNV in terms of location, pattern and configuration. The OCTA sensitivity and specificity for CNV detection were calculated by comparing it with FFA. Results FFA detected CNV in 70 of the 90 eyes (77.77%) whereas OCTA identified CNV in 69 eyes (76.7%). Among 69 eyes with CNV, it was well-defined in 51 (73.9%) eyes and poorly defined in 18 (26.1%) eyes. There were four false positive and five false negative cases. The sensitivity, specificity, positive predictive value and negative predictive value of OCTA in detection of nAMD were found to be 92.85%, 80.0%, 94.2 and 76.2, respectively. Conclusion OCTA is a useful, noninvasive, reproducible imaging tool for diagnosing, classifying and localizing CNV. The technique has high sensitivity and specificity and can be used reliably in cases where FFA is contraindicated or inconclusive.
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Affiliation(s)
- Maria Usman
- Division of Vitreoretinal Surgery, Layton Rehmatulla Benevolent Trust (LRBT) Free Eye Hospital, Lahore, PAK
| | - Kashif Iqbal
- Ophthalmology: Vitreo-retina, Layton Rehmatulla Benevolent Trust (LRBT) Free Eye Hospital, Lahore, PAK
| | | | - Khurram Nafees
- Ophthalmology, FMH College of Medicine and Dentistry, Lahore, PAK
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16
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Lee HJ, Samiudin NM, Lee TG, Doh I, Lee SW. Retina phantom for the evaluation of optical coherence tomography angiography based on microfluidic channels. BIOMEDICAL OPTICS EXPRESS 2019; 10:5535-5548. [PMID: 31799029 PMCID: PMC6865089 DOI: 10.1364/boe.10.005535] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 09/28/2019] [Accepted: 09/28/2019] [Indexed: 05/22/2023]
Abstract
Optical coherence tomography (OCT) angiography (OCTA) has been actively studied as a noninvasive imaging technology to generate retinal blood vessel network maps for the diagnoses of retinal diseases. Given that the uses of OCT and OCTA have increased in the field of ophthalmology, it is necessary to develop retinal phantoms for clinical OCT for product development, performance evaluation, calibration, certification, medical device licensing, and production processes. We developed a retinal layer-mimicking phantom with microfluidic channels based on microfluidic fabrication technology using polydimethylsiloxane (PDMS) and titanium dioxide (TiO2) powder. We implemented superficial and deep retinal vessels using microfluidic channels. In addition, multilayered thin films were synthesized with multiple spin-coating processes that comprised layers that corresponded to the retinal layers, including the ganglion cell layer (GCL), inner plexiform layer (IPL), and inner nuclear layer (INL). The phantom was formed by merging the multilayered thin film, and microfluidic channels were assembled with an optical lens, water chamber, and an aluminum tube case. Finally, we obtained cross-sectional OCT images and en-face OCTA images of the retinal phantom using lab-made ophthalmic OCT. From the cross-sectional OCT image, we could compare each of the layer thicknesses of the phantom with the corresponding layer thicknesses of the human retina. In addition, we obtained en-face OCTA images with injections of intralipid solutions. It is shown that this phantom will be able to be potentially used as a convenient tool to evaluate and standardize the quality and accuracy of OCT and OCTA images.
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Affiliation(s)
- Hyun-Ji Lee
- Center for Nano-Bio Measurement, Korea Research Institute of Standards and Science, 267 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
- Department of Medical Physics, Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
| | - Nafra M Samiudin
- Center for Medical Convergence Metrology, Korea Research Institute of Standards and Science, 267 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
- Department of Medical Physics, Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
| | - Tae Geol Lee
- Center for Nano-Bio Measurement, Korea Research Institute of Standards and Science, 267 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
- Department of Nano Science, Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
| | - Il Doh
- Center for Medical Convergence Metrology, Korea Research Institute of Standards and Science, 267 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
- Department of Medical Physics, Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
| | - Sang-Won Lee
- Center for Nano-Bio Measurement, Korea Research Institute of Standards and Science, 267 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
- Department of Medical Physics, Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, South Korea
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17
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Liu X, Huang Z, Wang Z, Wen C, Jiang Z, Yu Z, Liu J, Liu G, Huang X, Maier A, Ren Q, Lu Y. A deep learning based pipeline for optical coherence tomography angiography. JOURNAL OF BIOPHOTONICS 2019; 12:e201900008. [PMID: 31168927 DOI: 10.1002/jbio.201900008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 05/28/2019] [Accepted: 05/29/2019] [Indexed: 05/11/2023]
Abstract
Optical coherence tomography angiography (OCTA) is a relatively new imaging modality that generates microvasculature map. Meanwhile, deep learning has been recently attracting considerable attention in image-to-image translation, such as image denoising, super-resolution and prediction. In this paper, we propose a deep learning based pipeline for OCTA. This pipeline consists of three parts: training data preparation, model learning and OCTA predicting using the trained model. To be mentioned, the datasets used in this work were automatically generated by a conventional system setup without any expert labeling. Promising results have been validated by in-vivo animal experiments, which demonstrate that deep learning is able to outperform traditional OCTA methods. The image quality is improved in not only higher signal-to-noise ratio but also better vasculature connectivity by laser speckle eliminating, showing potential in clinical use. Schematic description of the deep learning based optical coherent tomography angiography pipeline.
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Affiliation(s)
- Xi Liu
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Zhiyu Huang
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Zhenzhou Wang
- Department of Emergency Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Chenyao Wen
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Zhe Jiang
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Zekuan Yu
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | - Jingfeng Liu
- Department of Emergency Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Gangjun Liu
- Shenzhen Graduate School, Peking University, Shenzhen, China
| | - Xiaolin Huang
- Institute of Image Processing and Pattern Recognition, Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
| | - Andreas Maier
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Qiushi Ren
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
- Shenzhen Graduate School, Peking University, Shenzhen, China
| | - Yanye Lu
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
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18
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Kim SJ, Yang J, Liu G, Huang D, Campbell JP. Optical Coherence Tomography Angiography and Ultra-Widefield Optical Coherence Tomography in a Child With Incontinentia Pigmenti. Ophthalmic Surg Lasers Imaging Retina 2019; 49:273-275. [PMID: 29664986 DOI: 10.3928/23258160-20180329-11] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 11/01/2017] [Indexed: 01/23/2023]
Abstract
Incontinentia pigmenti (IP) is a rare X-linked dominant disorder that can cause retinal nonperfusion, neovascularization, and retinal detachment. Evaluation of the peripheral retinal vasculature and appropriate treatment can reduce the risk of blindness. The authors report the use of a handheld prototype optical coherence tomography angiography (OCTA) and ultra-widefield OCT (UWF-OCT) during exam under anesthesia of a 2-year-old with a history of severe early onset IP. UWF-OCT and OCTA may be used as noninvasive imaging modalities for IP and similar retinal vascular disorders in supine young children. [Ophthalmic Surg Lasers Imaging Retina. 2018;49:273-275.].
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19
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Chua J, Tan B, Ang M, Nongpiur ME, Tan AC, Najjar RP, Milea D, Schmetterer L. Future clinical applicability of optical coherence tomography angiography. Clin Exp Optom 2018; 102:260-269. [PMID: 30537233 DOI: 10.1111/cxo.12854] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 09/28/2018] [Accepted: 10/12/2018] [Indexed: 12/28/2022] Open
Abstract
Optical coherence tomography angiography (OCT-A) is an emerging technology that allows for the non-invasive imaging of the ocular microvasculature. Despite the wealth of observations and numerous research studies illustrating the potential clinical uses of OCT-A, this technique is currently rarely used in routine clinical settings. In this review, technical and clinical aspects of OCT-A imaging are discussed, and the future clinical potential of OCT-A is considered. An understanding of the basic principles and limitations of OCT-A technology will better inform clinicians of its future potential in the diagnosis and management of ocular diseases.
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Affiliation(s)
- Jacqueline Chua
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Eye, Academic Clinical Program, Duke-NUS Medical School, Singapore
| | - Bingyao Tan
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Marcus Ang
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Eye, Academic Clinical Program, Duke-NUS Medical School, Singapore.,External Disease and Cornea Service, Moorfields Eye Hospital, London, UK
| | - Monisha E Nongpiur
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Eye, Academic Clinical Program, Duke-NUS Medical School, Singapore
| | - Anna Cs Tan
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Eye, Academic Clinical Program, Duke-NUS Medical School, Singapore
| | - Raymond P Najjar
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Eye, Academic Clinical Program, Duke-NUS Medical School, Singapore
| | - Dan Milea
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Eye, Academic Clinical Program, Duke-NUS Medical School, Singapore
| | - Leopold Schmetterer
- Ocular Imaging Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.,Eye, Academic Clinical Program, Duke-NUS Medical School, Singapore.,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
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20
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Lal C, Subhash HM, Alexandrov S, Leahy MJ. Feasibility of correlation mapping optical coherence tomography angiographic technique using a 200 kHz vertical-cavity surface-emitting laser source for in vivo microcirculation imaging applications. APPLIED OPTICS 2018; 57:E224-E231. [PMID: 30117906 DOI: 10.1364/ao.57.00e224] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 07/04/2018] [Indexed: 05/19/2023]
Abstract
Optical coherence tomography (OCT) angiography is a well-established in vivo imaging technique to assess the overall vascular morphology of tissues and is an emerging field of research for the assessment of blood flow dynamics and functional parameters such as oxygen saturation. In this study, we present a modified scanning-based correlation mapping OCT using a 200 kHz high-speed swept-source OCT system operating at 1300 nm and demonstrate its wide field-imaging capability in ocular angiographic studies.
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21
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Soomro T, Talks J. The use of optical coherence tomography angiography for detecting choroidal neovascularization, compared to standard multimodal imaging. Eye (Lond) 2018; 32:661-672. [PMID: 29600987 DOI: 10.1038/eye.2018.2] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Accepted: 12/13/2017] [Indexed: 01/10/2023] Open
Abstract
PurposeTo assess OCT angiography (OCTA) effectiveness at detecting choroidal neovascularization (CNV) in cases of suspected neovascular age related macular degeneration (nAMD), chronic central serous retinopathy (cCSR) and pathological myopia compared to FFA and how it compares to a multimodal approach (OCT, FFA and ICGA) for detecting the vascular network.MethodsThis was a retrospective observational cohort study of patients who had clinical and/or OCT findings suggestive of CNV, having further investigation with FFA, with or without ICG, and had same day OCTA using the Heidelberg Spectralis OCT2 beta angiography module. Multimodal imaging interpretation was compared to OCTA images. OCTA images were also analysed for inter-rater reliability (using kappa statistic). The diagnostic accuracy of OCTA was compared to FFA (using Cochran's Q, p<0.05). OCTA was also compared to a multimodal approach in defining a vascular network.ResultsOverall sensitivity of OCTA compared to FFA was 71% and specificity of 81% (p=0.108). Subgroup analysis for OCTA vs FFA for detecting classic nAMD/type II CNV sensitivity was 100% and specificity of 76% (p<0.05). OCTA vs FFA for detecting occult nAMD/type-I CNV sensitivity was 47% and specificity of 76%, (p=0.248). OCTA was better than FFA at defining a vascular network overall, when OCT was suspicious (59% vs 49%).ConclusionsOCTA was better at detecting classic nAMD/type II CNV compared to FFA and for defining a vascular network in nAMD compared to FFA and ICGA. It was able to aid in making the diagnosis in cases where evidence of CNV was uncertain following FFA/ICGA.
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Affiliation(s)
- T Soomro
- Newcastle Eye Centre, Ophthalmology Department, Royal Victoria Infirmary, Newcastle-upon-tyne, NE1 4LP, UK
| | - J Talks
- Newcastle Eye Centre, Ophthalmology Department, Royal Victoria Infirmary, Newcastle-upon-tyne, NE1 4LP, UK
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22
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Affiliation(s)
- Justis P Ehlers
- Cole Eye Institute, Cleveland Clinic, Cleveland, OH 44195.,Ophthalmic Imaging Center, Cleveland Clinic, Cleveland, OH 44195
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23
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Xu J, Song S, Li Y, Wang RK. Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems. Phys Med Biol 2017; 63:015023. [PMID: 29049034 DOI: 10.1088/1361-6560/aa94bc] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is < ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.
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Affiliation(s)
- Jingjiang Xu
- Department of Bioengineering, University of Washington, Seattle, WA 98195, United States of America
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24
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Liu G, Yang J, Wang J, Li Y, Zang P, Jia Y, Huang D. Extended axial imaging range, widefield swept source optical coherence tomography angiography. JOURNAL OF BIOPHOTONICS 2017; 10:1464-1472. [PMID: 28493437 PMCID: PMC6145849 DOI: 10.1002/jbio.201600325] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 04/18/2017] [Accepted: 04/19/2017] [Indexed: 05/05/2023]
Abstract
We developed a high-speed, swept source OCT system for widefield OCT angiography (OCTA) imaging. The system has an extended axial imaging range of 6.6 mm. An electrical lens is used for fast, automatic focusing. The recently developed split-spectrum amplitude and phase-gradient angiography allow high-resolution OCTA imaging with only two B-scan repetitions. An improved post-processing algorithm effectively removed trigger jitter artifacts and reduced noise in the flow signal. We demonstrated high contrast 3 mm×3 mm OCTA image with 400×400 pixels acquired in 3 seconds and high-definition 8 mm×6 mm and 12 mm×6 mm OCTA images with 850×400 pixels obtained in 4 seconds. A widefield 8 mm×11 mm OCTA image is produced by montaging two 8 mm×6 mm scans. An ultra-widefield (with a maximum of 22 mm along both vertical and horizontal directions) capillary-resolution OCTA image is obtained by montaging six 12 mm×6 mm scans.
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Affiliation(s)
- Gangjun Liu
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Jianlong Yang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Jie Wang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Yan Li
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Pengxiao Zang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Yali Jia
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
| | - David Huang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, 97239, USA
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25
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Pi S, Camino A, Zhang M, Cepurna W, Liu G, Huang D, Morrison J, Jia Y. Angiographic and structural imaging using high axial resolution fiber-based visible-light OCT. BIOMEDICAL OPTICS EXPRESS 2017; 8:4595-4608. [PMID: 29082087 PMCID: PMC5654802 DOI: 10.1364/boe.8.004595] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2017] [Revised: 09/14/2017] [Accepted: 09/17/2017] [Indexed: 05/20/2023]
Abstract
Optical coherence tomography using visible-light sources can increase the axial resolution without the need for broader spectral bandwidth. Here, a high-resolution, fiber-based, visible-light optical coherence tomography system is built and used to image normal retina in rats and blood vessels in chicken embryo. In the rat retina, accurate segmentation of retinal layer boundaries and quantification of layer thicknesses are accomplished. Furthermore, three distinct capillary plexuses in the retina and the choriocapillaris are identified and the characteristic pattern of the nerve fiber layer thickness in rats is revealed. In the chicken embryo model, the microvascular network and a venous bifurcation are examined and the ability to identify and segment large vessel walls is demonstrated.
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Affiliation(s)
- Shaohua Pi
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, USA
- These authors contributed equally to this work
| | - Acner Camino
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, USA
- These authors contributed equally to this work
| | - Miao Zhang
- Optovue Inc. 2800 Bayview Dr., Fremont, CA 94538, USA
| | - William Cepurna
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, USA
| | - Gangjun Liu
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, USA
| | - David Huang
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, USA
| | - John Morrison
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, USA
| | - Yali Jia
- Casey Eye Institute, Oregon Health & Science University, Portland, OR, USA
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26
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Khan HA, Mehmood A, Khan QA, Iqbal F, Rasheed F, Khan N, Pizzimenti JJ. A major review of optical coherence tomography angiography. EXPERT REVIEW OF OPHTHALMOLOGY 2017. [DOI: 10.1080/17469899.2017.1356229] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Affiliation(s)
- Hashim Ali Khan
- Ophthalmology, SEHHAT Foundation Hospital, Main KKH, Danyore, Gilgit, Pakistan
| | - Asim Mehmood
- Ophthalmology, Multan Medical & Dental College, Multan, Pakistan
| | - Qaim Ali Khan
- Ophthalmology, Poonch Medical College, AJK, Pakistan
| | - Fatima Iqbal
- School of Optometry, The University of Faisalabad, Faisalabad, Pakistan
| | - Faisal Rasheed
- Ophthalmology, Sheikh Zayd Medical College, Rahim Yar Khan, Pakistan
| | - Naeemullah Khan
- Ophthalmology, SEHHAT Foundation Hospital, Main KKH, Danyore, Gilgit, Pakistan
| | - Joseph J. Pizzimenti
- Rosenberg School of Optometry, University of the Incarte Word, San Antonio, TX, USA
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27
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Camino A, Jia Y, Liu G, Wang J, Huang D. Regression-based algorithm for bulk motion subtraction in optical coherence tomography angiography. BIOMEDICAL OPTICS EXPRESS 2017; 8:3053-3066. [PMID: 28663926 PMCID: PMC5480449 DOI: 10.1364/boe.8.003053] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Revised: 05/09/2017] [Accepted: 05/09/2017] [Indexed: 05/05/2023]
Abstract
We developed an algorithm to remove decorrelation noise due to bulk motion in optical coherence tomography angiography (OCTA) of the posterior eye. In this algorithm, OCTA B-frames were divided into segments within which the bulk motion velocity could be assumed to be constant. This velocity was recovered using linear regression of decorrelation versus the logarithm of reflectance in axial lines (A-lines) identified as bulk tissue by percentile analysis. The fitting parameters were used to calculate a reflectance-adjusted upper bound threshold for bulk motion decorrelation. Below this threshold, voxels are identified as non-flow tissue, their flow values are set to zeros. Above this threshold, the voxels are identified as flow voxels and bulk motion velocity is subtracted from each using a nonlinear decorrelation-velocity relationship previously established in laboratory flow phantoms. Compared to the simpler median-subtraction method, the regression-based bulk motion subtraction improved angiogram signal-to-noise ratio, contrast, vessel density repeatability, and bulk motion noise cleanup in the foveal avascular zone, while preserving the connectivity of the vascular networks in the angiogram.
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28
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Yang J, Liu L, Campbell JP, Huang D, Liu G. Handheld optical coherence tomography angiography. BIOMEDICAL OPTICS EXPRESS 2017; 8:2287-2300. [PMID: 28736672 PMCID: PMC5516829 DOI: 10.1364/boe.8.002287] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Revised: 02/25/2017] [Accepted: 03/12/2017] [Indexed: 05/03/2023]
Abstract
We developed a handheld optical coherence tomography angiography (OCTA) system using a 100-kHz swept-source laser. The handheld probe weighs 0.4 kg and measures 20.6 × 12.8 × 4.6 cm3. The system has dedicated features for handheld operation. The probe is equipped with a mini iris camera for easy alignment. Real-time display of the en face OCT and cross-sectional OCT images in the system allows accurately locating the imaging target. Fast automatic focusing was achieved by an electrically tunable lens controlled by a golden-section search algorithm. An extended axial imaging range of 6 mm allows easy alignment. A registration algorithm using cross-correlation to register adjacent OCT B-frames with propagation from the central frame was used to effectively minimize motion artifacts in volumetric OCTA images captured in relatively short durations of 1 and 2.1 seconds. 2.5 × 2.5 mm (200 × 200 pixels) and 3.5 × 3.5 mm (300 × 300 pixels) retinal angiograms were demonstrated on two awake adult human subjects without the use of any mydriatic eye drops.
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29
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Chen CL, Wang RK. Optical coherence tomography based angiography [Invited]. BIOMEDICAL OPTICS EXPRESS 2017; 8:1056-1082. [PMID: 28271003 PMCID: PMC5330554 DOI: 10.1364/boe.8.001056] [Citation(s) in RCA: 270] [Impact Index Per Article: 38.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Accepted: 01/16/2017] [Indexed: 05/18/2023]
Abstract
Optical coherence tomography (OCT)-based angiography (OCTA) provides in vivo, three-dimensional vascular information by the use of flowing red blood cells as intrinsic contrast agents, enabling the visualization of functional vessel networks within microcirculatory tissue beds non-invasively, without a need of dye injection. Because of these attributes, OCTA has been rapidly translated to clinical ophthalmology within a short period of time in the development. Various OCTA algorithms have been developed to detect the functional micro-vasculatures in vivo by utilizing different components of OCT signals, including phase-signal-based OCTA, intensity-signal-based OCTA and complex-signal-based OCTA. All these algorithms have shown, in one way or another, their clinical values in revealing micro-vasculatures in biological tissues in vivo, identifying abnormal vascular networks or vessel impairment zones in retinal and skin pathologies, detecting vessel patterns and angiogenesis in eyes with age-related macular degeneration and in skin and brain with tumors, and monitoring responses to hypoxia in the brain tissue. The purpose of this paper is to provide a technical oriented overview of the OCTA developments and their potential pre-clinical and clinical applications, and to shed some lights on its future perspectives. Because of its clinical translation to ophthalmology, this review intentionally places a slightly more weight on ophthalmic OCT angiography.
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Affiliation(s)
- Chieh-Li Chen
- Department of Bioengineering, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
- Department of Ophthalmology, University of Washington, 325 9th Ave, Seattle, WA 98104, USA
| | - Ruikang K. Wang
- Department of Bioengineering, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
- Department of Ophthalmology, University of Washington, 325 9th Ave, Seattle, WA 98104, USA
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