Split-spectrum amplitude-decorrelation angiography with optical coherence tomography

Amplitude decorrelation measurement is sensitive to transverse flow and immune to phase noise in comparison to Doppler and other phase-based approaches. However, the high axial resolution of OCT makes it very sensitive to the pulsatile bulk motion noise in the axial direction. To overcome this limitation, we developed split-spectrum amplitude-decorrelation angiography (SSADA) to improve the signal-to-noise ratio (SNR) of flow detection. The full OCT spectrum was split into several narrower bands. Inter-B-scan decorrelation was computed using the spectral bands separately and then averaged. The SSADA algorithm was tested on in vivo images of the human macula and optic nerve head. It significantly improved both SNR for flow detection and connectivity of microvascular network when compared to other amplitude-decorrelation algorithms.National Institutes of Health (U.S.) (Grant R01 EY013516)National Institutes of Health (U.S.) (Grant R01-EY11289-26)United States. Air Force Office of Scientific Research (FA9550-10-1-0551

Optical Coherence Tomography Angiography in Eyes with Non-infectious Posterior Uveitis; Some Practical Aspects

Optical coherence tomography angiography (OCTA) is an innovative imaging technology enabling clinicians to learn more about the pathophysiology of disease processes as it facilitates visualization of the retinal and choroidal circulation without injection of a dye. Also it provides ample qualitative and quantitative data on the vascular supply. OCTA has become an important tool nowadays in the diagnosis and follow-up of patients with age-related macular degeneration, inherited chorioretinal diseases, diabetic retinopathy, retinal vascular occlusive diseases and optic nerve disorders. However, its place is relatively less known in non-infectious posterior uveitis (NIPU). OCTA may help mainly in assessing macular and peripheric retinal perfusion status, detection of retinal and/or disc neovascularization, diagnose of inflammatory choroidal neovascularization and visualizing the uveitic white-dot lesions. This mini-review describes the use of OCTA in patients with NIPU and summarizes some practical points in several uveitic entities. Epub: October 1, 2019

Early Detection of Microvascular Changes in Patients with Diabetes Mellitus without and with Diabetic Retinopathy: Comparison between Different Swept-Source OCT-A Instruments

Optical coherence tomography angiography (OCT-A) has recently improved the ability to detect subclinical and early clinically visible microvascular changes occurring in patients with diabetes mellitus (DM). The aim of the present study is to evaluate and compare early quantitative changes of macular perfusion parameters in patients with DM without DR and with mild nonproliferative DR (NPDR) evaluated by two different swept-source (SS) OCT-A instruments using two scan protocols (3 73 mm and 6 76 mm). One hundred eleven subjects/eyes were prospectively evaluated: 18 healthy controls (control group), 73 eyes with DM but no DR (no-DR group), and 20 eyes with mild NPDR (DR group). All quantitative analyses were performed using ImageJ and included vessel and perfusion density, area and circularity index of the FAZ, and vascular complexity parameters. The agreement between methods was assessed according to the method of Bland-Altman. A significant decrease in the majority of the considered parameters was found in the DR group versus the controls with both instruments. The results of Bland-Altman analysis showed the presence of a systemic bias between the two instruments with PLEX Elite providing higher values for the majority of the tested parameters when considering 6 76 mm angiocubes and a less definite difference in 3 73 mm angiocubes. In conclusion, this study documents early microvascular changes occurring in the macular region of patients at initial stages of DR, confirmed with both SS OCT-A instruments. The fact that early microvascular alterations could not be detected with one instrument does not necessarily mean that these alterations are not actually present, but this could be an intrinsic limitation of the device itself. Further, larger longitudinal studies are needed to better understand microvascular damage at very early stages of diabetic retinal disease and to define the strengths and weaknesses of different OCT-A devices

OCTAVA: An open-source toolbox for quantitative analysis of optical coherence tomography angiography images

Optical coherence tomography angiography (OCTA) performs non-invasive visualization and characterization of microvasculature in research and clinical applications mainly in ophthalmology and dermatology. A wide variety of instruments, imaging protocols, processing methods and metrics have been used to describe the microvasculature, such that comparing different study outcomes is currently not feasible. With the goal of contributing to standardization of OCTA data analysis, we report a user-friendly, open-source toolbox, OCTAVA (OCTA Vascular Analyzer), to automate the pre-processing, segmentation, and quantitative analysis of en face OCTA maximum intensity projection images in a standardized workflow. We present each analysis step, including optimization of filtering and choice of segmentation algorithm, and definition of metrics. We perform quantitative analysis of OCTA images from different commercial and non-commercial instruments and samples and show OCTAVA can accurately and reproducibly determine metrics for characterization of microvasculature. Wide adoption could enable studies and aggregation of data on a scale sufficient to develop reliable microvascular biomarkers for early detection, and to guide treatment, of microvascular disease

The angular spectrum of the scattering coefficient map reveals subsurface colorectal cancer

Abstract Colorectal cancer diagnosis currently relies on histological detection of endoluminal neoplasia in biopsy specimens. However, clinical visual endoscopy provides no quantitative subsurface cancer information. In this ex vivo study of nine fresh human colon specimens, we report the first use of quantified subsurface scattering coefficient maps acquired by swept-source optical coherence tomography to reveal subsurface abnormities. We generate subsurface scattering coefficient maps with a novel wavelet-based-curve-fitting method that provides significantly improved accuracy. The angular spectra of scattering coefficient maps of normal tissues exhibit a spatial feature distinct from those of abnormal tissues. An angular spectrum index to quantify the differences between the normal and abnormal tissues is derived, and its strength in revealing subsurface cancer in ex vivo samples is statistically analyzed. The study demonstrates that the angular spectrum of the scattering coefficient map can effectively reveal subsurface colorectal cancer and potentially provide a fast and more accurate diagnosis

Penta-Modal Imaging Platform with OCT- Guided Dynamic Focusing for Simultaneous Multimodal Imaging

Complex diseases, such as Alzheimer’s disease, are associated with sequences of changes in multiple disease-specific biomarkers. These biomarkers may show dynamic changes at specific stages of disease progression. Thus, testing/monitoring each biomarker may provide insight into specific disease-related processes, which can result in early diagnosis or even development of preventive measures. Obtaining a comprehensive information of biological tissues requires imaging of multiple optical contrasts, which is not typically offered by a single imaging modality. Thus, combining different contrast mechanisms to achieve simultaneous multimodal imaging is desirable. However, this process is highly challenging due to specific optical and hardware requirements for each optical imaging system. The objective of this dissertation is to develop a novel Penta-modal optical imaging system integrating photoacoustic microscopy (PAM), optical coherence tomography (OCT), optical Doppler tomography (ODT), OCT angiography (OCTA) and confocal fluorescence microscopy (CFM) in one platform providing comprehensive structural, functional, and molecular information of living biological tissues. The system can simultaneously image different biomarkers with a large field-of-view (FOV) and high-speed imaging. The large FOV and the high imaging speed is achieved by combining optical and mechanical scanning mechanisms. To compensate for an uneven surface of biological samples, which result in images with non-uniform resolution and low signal to noise ratio (SNR), we further develop a novel OCT-guided surface contour scanning methodology, a technique for adjusting objective lens focus to follow the contour of the sample surface, to provide a uniform spatial resolution and SNR across the region of interest (ROI). The imaging system was tested by imaging phantoms, ex vivo biological samples, and in vivo. The OCT-guided surface contour scanning methodology was utilized for imaging a leaf of purple queen plant, which resulted in a significant contrast improvement of 41% and 38% across a large imaging area for CFM and PAM, respectively. The nuclei and cells walls were also clearly observed in both images. In an in vivo imaging of the Swiss Webster mouse ear, our multimodal imaging system was able to provide images with uniform resolution in an FOV of 10 mm x 10 mm with an imaging time of around 5 minutes. In addition to measuring the blood flow in the mouse ear, the system also successfully imaged mouse ear blood vessels, sebaceous glands, as well as several tissue structures. We further conducted a comparative study of OCTA for rodent retinal imaging by evaluating the performance of three OCTA algorithms, namely the phase variance (PV), improved speckle contrast (ISC), and optical microangiography (OMAG). It was concluded that the OMAG algorithm provided statistically significant higher mean values of BVD and VPI compared to the ISC algorithm (0.27±0.07 vs. 0.24±0.05 for BVD; 0.09±0.04 and 0.08±0.04 for VPI), while no statistically significant difference was observed for VDI and VCI among the algorithms. Results showed that both the ISC and OMAG algorithms are more robust than PV, and they can reveal similar vasculature features. Lastly, we utilized the proposed imaging system to monitor, for the first time, the invasion process of malaria parasites in the mosquito midgut. The system shows a promising potential to detect parasite motion as well as structural changes inside the mosquito midgut. The multimodal imaging system outlined in this dissertation can be useful in a variety of applications thanks to the specific optical contrast offered by each employed modality, including retinal and brain imaging

Comparison of diabetic retinopathy classification using fluorescein angiography and optical coherence tomography angiography

PURPOSE: To analyse and compare the classification of eyes with diabetic retinopathy using fluorescein angiography (FA) and optical coherence tomography angiography (OCTA) performed either with AngioPlex or AngioVue. METHODS: This was an observational cross-sectional study of 50 eyes from 26 diabetic subjects. Two independent graders classified the FA angiograms, to assess the presence and severity of several characteristics according to the ETDRS Report 11, and a similar evaluation was performed for each 3×3 mm OCTA image from the superficial retinal layer and for the full retina slab. RESULTS: Percentages of non-gradable images for the outline of foveal avascular zone (FAZ) in the central subfield (CSF) were 29.0% for FA, 12.0% for AngioVue and 3.0% for AngioPlex. For capillary loss, percentages of non-gradable images in the CSF were 25.0% for FA, 11% for AngioVue and 0.0% for AngioPlex. For the inner ring (IR), percentages of non-gradable images were 12.5% for FA, 11.5% for AngioVue and 0.5% for AngioPlex. Agreement between graders was substantial for outline of FAZ. For capillary loss, the agreement was fair for the CSF, and moderate for the IR. CONCLUSIONS: The OCTA allows better discrimination of the CSF and parafoveal macular microvasculature than FA, especially for FAZ disruption and capillary dropout, without the need of an intravenous injection of fluorescein. In addition, FA had also a higher number of non-gradable images. The OCTA can replace with advantage the FA, as a non-invasive and more sensitive procedure for detailed morphological evaluation of central macular vascular changes. TRIAL REGISTRATION NUMBER: NCT02391558, Pre-results.info:eu-repo/semantics/publishedVersio

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.R01 CA224911 - NCI NIH HHS; R01 CA232015 - NCI NIH HHS; R01 NS108464 - NINDS NIH HHS; R21 EY029412 - NEI NIH HHSAccepted manuscrip