Our lab is focusing on advanced ophthalmic instrumentation and quantitative imaging technology to advance retinal study, disease diagnosis and treatment evaluation. Our current research includes wide field fundus photography, functional optical coherence tomography (OCT), quantitative OCT angiography (OCTA), super-resolution ophthalmoscopy, functional imaging of neurovascular coupling, machine learning based image analysis and AI classification.
Wide field fundus photography Heading link
It is known that wide filed fundus photography is an essential component for remote screening, diagnosis and treatment evaluation of eye diseases. However, it is technically difficult to construct wide field fundus camera due to the complexity of conventional transpupillary illumination and imaging mechanisms. We have recently demonstrated smartphone fundus cameras with trans-palpebral illumination (Fig. 1A) and miniaturized indirect ophthalmoscopy (Fig. 1B) for wide-field retinal imaging (Fig. 1C). We are currently pursuing trans-pars-planar illumination for ultra-wide field fundus photography. Further development of low-cost, easy-to-use wide field fundus photography promises an affordable solution to conduct telemedicine assessment of eye diseases, which will improve access to eye care for patients in rural and underserved areas.
Wide field fundus Image 1 Heading link
Figure 1. (A) Smartphone fundus cameras with trans-pars-planar illumination. (B) Indirect ophthalmoscopy illumination for wide-field retinal imaging. (C) Portable 200o PedCam with trans-pars-planar illumination (C1). Comparative imaging with the 200o PedCam and a clinical 200o RetCam (C2). Representative fundus images captured with the prototype PedCam from a ROP patient, with trans-pars-planar illumination light delivered from the temporal (C3) and nasal (C4) sides, respectively.
- Toslak, F. Chau, M. K. Erol, C. Liu, R. V. P. Chan, T. Son, and X. Yao, “Trans-pars-planar illumination enables a 200° ultra-wide field pediatric fundus camera for easy examination of the retina,” Biomed. Opt. Express 11, 68-76 (2020) [Full text].
- Toslak, A. C. Liu, M. N. Alam, andX. Yao. “Near infrared light guided miniaturized indirect ophthalmoscopy for nonmydriatic wide-field fundus photography”. Optics Letters 43 (11) 2551-2554 (2018) [Full Text]
- Toslak, A. Ayata, C. Liu, M. K. Erol, and X. Yao. “Wide-field smartphone fundus video camera based on miniaturized indirect ophthalmoscopy”. Retina (Philadelphia, Pa.), 38(2), 438-441(2018). [Full Text]
- Toslak, D. Thapa, Y.Chen, M. K. Erol, R.V. Paul Chan, and X.Yao. Trans-palpebral illumination: an approach for wide-angle fundus photography without the need for pupil dilation. Optics Letters41, 2688-2691 (2016) [Full Text]
Quantitative OCTA analysis and AI classification of eye diseases Heading link
Early detection is an essential step for effective intervention of eye diseases. Emerging optical coherence tomography (OCT) (Fig. 2A1) and OCT angiography (OCTA) (Fig. A2) provide excellent three-dimensional resolution to enable label-free, noninvasive visualization of chorioretinal structures, promising improved sensitivity in detecting diabetic retinopathy (DR), age-related macular degeneration (AMD), sickle cell retinopathy (SCR), etc. Quantitative interpretation of clinical OCTA is valuable for disease detection and treatment evaluation. Recently, we have conducted a comprehensive analysis of OCTA images to derive quantitative OCTA features, including blood vessel tortuosity (BVT), blood vessel diameter (BVD), vessel perimeter index (VPI), foveal avascular zone (FAZ) area, FAZ contour irregularity and parafoveal avascular density (PAD), and validated them for machine learning based automated classification of DR and SCR. Moreover, color fundus image analysis and OCT geometric feature analysis guided (Fig. 2B) were demonstrated to improve OCTA detection of DR and SCR. We are currently pursuing machine learning based retinal image analysis and AI classification of eye diseases.
Image Quantitative OCTA Analysis Heading link
Figure 2. (A) Representative OCT (A1) and OCTA (A2) images. (B) Color fundus image analysis guided artery–vein classification in OCTA images of control (B1), mild SCR (B2), and severe SCR (C3).
- Alam, D. Toslak, J. I. Lim, and X. Yao, “OCT feature analysis guided artery-vein differentiation in OCTA ”. Biomedical Optics Express 10(4): 2055-2066 (2019) [Full Text]
- Alam, J. I. Lim, D. Toslak, and X. Yao, “Differential artery-vein analysis improves the performance of OCTA staging of sickle cell retinopathy”. Translational Vision Science & Technology, 8(3) (2019) [Full Text]
- Alam, Y. Zhang, J. I. Lim, R. Chan, M. Yang, and X. Yao, “Quantitative OCT angiography features for objective classification and staging of diabetic retinopathy”. Retina (Philadelphia, Pa.) [Full Text].
Functional OCT of retinal neurovascular coupling Heading link
Retinal neurodegenerative diseases, such as age-related macular degeneration (AMD), retinitis pigmentosa (RP), diabetic retinopathy (DR) and glaucoma, can produce severe vision losses if medical interventions cannot be provided promptly. As one part of the central never system (CNS), the retina is also targeted by other neurodegenerative diseases, such as Parkinson’s and Alzheimer’s diseases which are the major cause of dementia. Early detection of these neurodegenerative diseases is essential for better study and development of preventive strategies. Functional imaging of neurovascular coupling defects promises early detection of neurodegeneration. Direct access to the brain for high-resolution examination of neurovascular coupling defects is difficult. The retina opens a window for high-resolution study of neurovascular coupling defects. We have recently demonstrated functional OCT imaging of transient intrinsic optical signal (IOS) changes correlated with stimulus activated retinal neural activity and hemodynamic response. Functional OCT of neurovascular coupling promises a high spatiotemporal resolution methodology to investigate coherent interactions between neural activities and hemodynamic changes in the retina (Fig. 3). We are currently pursuing quantitative OCT study of retinal neurovascular coupling defects in animal models with neurodegenerative diseases.
Functional OCT image Heading link
Figure 3. (A) Representative flattened B-scan OCT (A1) and spatiotemporal neural-IOS map (A2). (B) Representative flattened B-scan OCTA (B1) and spatiotemporal hemodynamic-IOS map (B2). (C) Neural-IOS changes of photoreceptor layer (PL), outer plexiform layer (OPL), inner plexiform layer (IPL), and ganglion cell layer (GCL). (D) Hemodynamic-IOS changes of superficial vascular plexiform (SVP), intermediate capillary plexiform (ICP), and deep capillary plexiform (DCP). (E) Averaged onset times of neural-IOS changes at PL, OPL, IPL, and GCL. (F) Averaged onset times of hemodynamic-IOS changes of SVP, ICP, and DCP.
- Son, M. Alam, D. Toslak, B. Wang, Y. Lu, andX. Yao, “Functional optical coherence tomography of neurovascular coupling interactions in the retina”. Journal of Biophotonics, e201800089 (2018) [Full Text]
- Son, B. Wang, D. Thapa, Y. Lu, Y. Chen, D. Cao, and X. Yao, Optical coherence tomography angiography of stimulus evoked hemodynamic responses in individual retinal layers. Biomedical Optics Express8, 3151-3162 (2016) [Full Text]
- Wang, Y. Lu, and X. Yao. In vivo optical coherence tomography of stimulus evoked intrinsic optical signals in mouse retinas. Journal of Biomedical Optics 21(9), 096010 (2016) [Full Text].
Super-resolution scanning laser microscopy and ophthalmoscopy Heading link
High resolution microscopy is essential for advanced study of biological structures and accurate diagnosis of medical diseases. The spatial resolution of conventional microscopes is light diffraction limited. Structured illumination has been extensively explored to break the diffraction limit in wide field light microscopy. However, practical deployment of the structured illumination microscopy (SIM) for in vivo retinal imaging is challenging due to unavoidable phase errors due to eye movement. We recently demonstrated super-resolution scanning laser microscopy through virtually structured detection (VSD) to break the diffraction limit. Without the complexity of structured illumination, VSD provides an easy, low-cost and phase-artifact free strategy to achieve super-resolution in scanning laser microscopy. By combing a line-scanning strategy, in vivo super-resolution scanning laser ophthalmoscopy (SLO) has been demonstrated (Fig. 4). We are currently exploring the feasibility of using the VSD based SLO for in vivo super-resolution functional imaging of human photoreceptors.
Super-resolution scanning laser microscopy and ophthalmoscopy Heading link
Figure 4. (A) Experiment setup of super-resolution SLO. (B) Representative image of human retina. (C) Dynamic motility analysis of retinal photoreceptors. (D) Enlarged illustration of the yellow window in C. The yellow and red arrowheads point to individual rod and cone photoreceptors, respectively.
- Lu, T. Son, T. H. Kim, D. Le, and X. Yao, “Virtually structured detection enables super-resolution ophthalmoscopy of rod and cone photoreceptors in human retina”. Quantitative Imaging in Surgery and Medicine, (2020) [Full Text]
- Y. Lu, C. Liu, and X. Yao, “In vivo super-resolution imaging of transient retinal phototropism evoked by oblique light stimulation”. Journal of Biomedical Optics23(5), 050502 (2018) [Full Text]
- C. Liu, Y. Zhi, B. Wang, D. Thapa, Y. Chen, M. Alam, Y. Lu and X. Yao. In vivo super-resolution retinal imaging through virtually structured detection. Journal of Biomedical Optics 21 (12), 120502-120502 (2016) [Full Text]
- R.W. Lu, B.Q. Wang, Q.X. Zhang, and X.C. Yao. Super-resolution scanning laser microscopy through virtually structured detection, Biomedical Optics Express 4, 1673-1682 (2013) [Full Text]
Active grants: Heading link
Functional imaging of retinal photoreceptors
Source: NIH/NEI R01
INSTRUMENT SHOP CORE
Source: NIH/NEI P30
Completed projects: Heading link
Super-resolution ophthalmoscopy for in vivo retinal imaging
Source: NIH/NEI R01
Angle-resolved polarization signal imaging of early receptor potential
Source: NIH/NIBIB R21
Multifocal Optical Coherence Microscope
Source: NIH/NCRR R21
Concurrent Structural and Functional Imaging of Retinal Neurons
Source: DANA Foundation (Brain-Immuno Imaging program)
Development of a Microlens Array Confocal Ophthalmoscope
Source: Eyesight Foundation of Alabama