Longitudinal detection of retinal alterations by visible and near-infrared optical coherence tomography in a dexamethasone-induced ocular hypertension mouse model

Visible Light Optical Coherence Tomography of Peripapillary Retinal Nerve Fiber Layer Reflectivity in Glaucoma

Purpose

To evaluate the clinical utility of visible light optical coherence tomography (VIS-OCT) and to test whether VIS-OCT reflectivity and spectroscopy of peripapillary retinal nerve fiber layer (pRNFL) are correlated with severity of glaucoma, compared with standard-of-care OCT thickness measurements.

Methods

In total 54 eyes (20 normal, 17 suspect/preperimetric glaucoma [GS/PPG], 17 perimetric glaucoma [PG]) were successfully imaged with complete datasets. All the eyes were scanned by a custom-designed dual-channel device that simultaneously acquired VIS-OCT and near-infrared OCT (NIR-OCT) images. A 5 × 5 mm2 scan was taken of the pRNFL. The pRNFL reflectivity was calculated for both channels and the spectroscopic marker was quantified by pVN, defined as the ratio of VIS-OCT to NIR-OCT pRNFL reflectivity. The results were compared with ophthalmic examinations and Zeiss Cirrus OCT.

Results

VIS-OCT pRNFL reflectivity significantly, sequentially decreased from normal to GS/PPG to PG, as did NIR-OCT pRNFL reflectivity. The pVN had the same decreasing trend among three groups. Normal and GS/PPG eyes were significantly different in VIS-OCT pRNFL reflectivity (P = 0.002) and pVN (P < 0.001), but were not in NIR-OCT pRNFL reflectivity (P = 0.14), circumpapillary RNFL thickness (P = 0.17), or macular ganglion cell layer and inner plexiform layer thickness (P = 0.07) in a mixed linear regression model.

Conclusions

VIS-OCT pRNFL reflectivity and pVN better distinguished GS/PPG from normal eyes than Cirrus OCT thickness measurements.

Translational Relevance

VIS-OCT pRNFL reflectivity and pVN could be useful metrics in the early detection of glaucoma upon further longitudinal validation.

Simultaneous visible light optical coherence tomography and near infrared OCT angiography in retinal pathologies: A case study

A dual-channel optical coherence tomography system with wavelengths in the visible and near-infrared light ranges can provide both structural and functional information for retinal microvasculature simultaneously. We applied this integrated system in an ongoing clinical study of patients with various retinal pathologies. Here, we present case study results of patients with diabetic retinopathy, central retinal vein occlusion, and sickle cell retinopathy compared to a healthy subject. For the first time, this comparison validates the system's ability to detect structural anomalies in both en face and B-scan images with simultaneous retinal optical coherence tomography angiography and measurement of sO₂ in parafoveal vessels that are around 20-30 µm in diameter. This integrated system represents a powerful instrument with potentially far-reaching clinical implications for the early detection and diagnosis of retinal vascular diseases.

Visible light optical coherence tomography angiography (vis-OCTA) facilitates local microvascular oximetry in the human retina

We report herein the first visible light optical coherence tomography angiography (vis-OCTA) for human retinal imaging. Compared to the existing vis-OCT systems, we devised a spectrometer with a narrower bandwidth to increase the spectral power density for OCTA imaging, while retaining the major spectral contrast in the blood. We achieved a 100 kHz A-line rate, the fastest acquisition speed reported so far for human retinal vis-OCT. We rigorously optimized the imaging protocol such that a single acquisition took < 6 seconds with a field of view (FOV) of 3×7.8 mm². The angiography enables accurate localization of microvasculature down to the capillary level and thus enables oximetry at vessels < 100 µm in diameter. We demonstrated microvascular hemoglobin oxygen saturation (sO₂) at the feeding and draining vessels at the perifoveal region. The longitudinal repeatability was assessed by < 5% coefficient of variation (CV). The unique capabilities of our vis-OCTA system may allow studies on the role of microvascular oxygen in various retinal pathologies.

Is oblique scanning laser ophthalmoscope applicable to human ocular optics? A feasibility study using an eye model for volumetric imaging

Oblique scanning laser ophthalmoscopy (oSLO) is a novel imaging modality to provide volumetric retinal imaging without depth sectioning over a large field of view (FOV). It has been successfully demonstrated in vivo in rodent eyes for volumetric fluorescein angiography (vFA). However, engineering oSLO for human retinal imaging is challenging because of the low numerical aperture (NA) of human ocular optics. To overcome this challenge, we implement optical designs to (a) increase the angle of the intermediate image under Scheimpflug condition, and (b) expand the magnification in the depth dimension with cylindrical lens to enable sufficient sampling density. In addition, we adopt a scanning-and-descaning strategy, resulting in a compact oSLO system. We experimentally show that the current setup can achieve a FOV of ~3 × 6 × 0.8 mm³ , and the transverse and axial resolutions of 7 and 41 μm, respectively. This feasibility study serves an important step for future in vivo human retinal imaging.

Retinal capillary oximetry with visible light optical coherence tomography

Assessing oxygen saturation (sO₂) remains challenging but is nonetheless necessary for understanding retinal metabolism. We and others previously achieved oximetry on major retinal vessels and measured the total retinal oxygen metabolic rate in rats using visible-light optical coherence tomography. Here we extend oximetry measurements to capillaries and investigate all three retinal vascular plexuses by amplifying and extracting the spectroscopic signal from each capillary segment under the guidance of optical coherence tomography (OCT) angiography. Using this approach, we measured capillary sO₂ in the retinal circulation in rats, demonstrated reproducibility of the results, validated the measurements in superficial capillaries with known perfusion pathways, and determined sO₂ responses to hypoxia and hyperoxia in the different retinal capillary beds. OCT capillary oximetry has the potential to provide new insights into the retinal circulation in the normal eye as well as in retinal vascular diseases.

Deep spectral learning for label-free optical imaging oximetry with uncertainty quantification

Measurement of blood oxygen saturation (sO2) by optical imaging oximetry provides invaluable insight into local tissue functions and metabolism. Despite different embodiments and modalities, all label-free optical-imaging oximetry techniques utilize the same principle of sO2-dependent spectral contrast from haemoglobin. Traditional approaches for quantifying sO2 often rely on analytical models that are fitted by the spectral measurements. These approaches in practice suffer from uncertainties due to biological variability, tissue geometry, light scattering, systemic spectral bias, and variations in the experimental conditions. Here, we propose a new data-driven approach, termed deep spectral learning (DSL), to achieve oximetry that is highly robust to experimental variations and, more importantly, able to provide uncertainty quantification for each sO2 prediction. To demonstrate the robustness and generalizability of DSL, we analyse data from two visible light optical coherence tomography (vis-OCT) setups across two separate in vivo experiments on rat retinas. Predictions made by DSL are highly adaptive to experimental variabilities as well as the depth-dependent backscattering spectra. Two neural-network-based models are tested and compared with the traditional least-squares fitting (LSF) method. The DSL-predicted sO2 shows significantly lower mean-square errors than those of the LSF. For the first time, we have demonstrated en face maps of retinal oximetry along with a pixel-wise confidence assessment. Our DSL overcomes several limitations of traditional approaches and provides a more flexible, robust, and reliable deep learning approach for in vivo non-invasive label-free optical oximetry.