Pulsatile signals from the cutaneous blood flow could be informative for evaluating the health condition of an individual. One of the popular optical measuring devices, photoplethysmogram (PPG) is often used to detect the pulse signal from skin. However, the origin of the PPG signal still remains controversial. Benefiting from the non-invasive, label-free, 3D imaging tool, optical coherence tomography (OCT) is able to capture the intrinsic tissue signals at different penetration depth in high spatial and temporal resolution. Periodic pulse signal was observed by taking advantage of the optical microangiography (OMAG) algorithm which is sensitive to the motion of blood flow. The pulsatile pattern from the capillary and arteriole was successfully differentiated and their morphology showed distinct property at different local blood pressure. The pulse signal from the arteriole is more consistent and has similar waveform as the PPG signals. The result indicated that the PPG signal could be deceive by the mixing signal from the capillary bed and arterioles since it measures the total blood volume change in the plexuses. This study may shed some new light on understanding the mechanical property of how blood travel through different types of vasculature networks and elucidate its potential application in disease assessments.
Optical coherence tomography angiography (OCT-A) is a novel non-invasive imaging technique that provide the visualization of retinal microvasculature. However, the quantification and evaluation of OCT-A are still a challenge for the diagnosis for ophthalmology. Deep convolutional neural network (CNN) architectures were initially designed for the task of natural image classification, delivering promising precision in computer vision tasks and recent research has applied deep CNN to biomedical image processing tasks and produces impressive outcomes. However, so far, there is no report relating to the application of large deep neural networks on a small annotated OCT-A dataset. We collected and annotated OCT-A datasets that contain diabetic retinopathy (DR), uveitis, dry age-related macular degeneration (AMD) patients, and normal cases. We propose a transfer learning CNN model for automated disease classification using clinical OCT-A images. The CNN model is pre-trained on the ImageNet dataset and fine-tuned the top feedforward layers of the model to fit the classification task during the training process. The proposed approach can offer a real-time evaluation and discrimination of retinal pathologies with a depth-encoded OCT-A projected image. Our results show great accuracy of transfer learning CNN model on the classification task with the limited dataset. The CNN model with the pre-trained weights has better performance in comparison with an SVM using HOG feature approach.
KEYWORDS: Optical coherence tomography, Visualization, Amplitude modulation, Angiography, In vivo imaging, Signal to noise ratio, Photons, Tissues, Scattering, Imaging systems
The choriocapillaris (CC) plays an essential role in maintaining the normal functions of the human eye. There is increasing interest in the community to develop an imaging technique for visualizing the CC, yet this remains underexplored due to technical limitations. We propose an approach for the visualization of the CC in humans via a complex signal-based optical microangiography (OMAG) algorithm, based on commercially available spectral domain optical coherence tomography (SD-OCT). We show that the complex signal-based OMAG was superior to both the phase and amplitude signal-based approaches in detailing the vascular lobules previously seen with histological analysis. With this improved ability to visualize the lobular vascular networks, it is possible to identify the feeding arterioles and draining venules around the lobules, which is important in understanding the role of the CC in the pathogenesis of ocular diseases. With built-in FastTrac™ and montage scanning capabilities, we also demonstrate wide-field SD-OCT angiograms of the CC with a field of view at 9×11 mm2.
Challenge persists in the field of optical coherence tomography (OCT) when it is required to quantify capillary blood flow within tissue beds in vivo. We propose a useful approach to statistically estimate the mean capillary flow velocity using a model-based statistical method of eigendecomposition (ED) analysis of the complex OCT signals obtained with the OCT angiography (OCTA) scanning protocol. ED-based analysis is achieved by the covariance matrix of the ensemble complex OCT signals, upon which the eigenvalues and eigenvectors that represent the subsets of the signal makeup are calculated. From this analysis, the signals due to moving particles can be isolated by employing an adaptive regression filter to remove the eigencomponents that represent static tissue signals. The mean frequency (MF) of moving particles can be estimated by the first lag-one autocorrelation of the corresponding eigenvectors. Three important parameters are introduced, including the blood flow signal power representing the presence of blood flow (i.e., OCTA signals), the MF indicating the mean velocity of blood flow, and the frequency bandwidth describing the temporal flow heterogeneity within a scanned tissue volume. The proposed approach is tested using scattering phantoms, in which microfluidic channels are used to simulate the functional capillary vessels that are perfused with the scattering intralipid solution. The results indicate a linear relationship between the MF and mean flow velocity. In vivo animal experiments are also conducted by imaging mouse brain with distal middle cerebral artery ligation to test the capability of the method to image the changes in capillary flows in response to an ischemic insult, demonstrating the practical usefulness of the proposed method for providing important quantifiable information about capillary tissue beds in the investigations of neurological conditions in vivo.
Optical microangiography (OMAG) is a powerful optical angiographic tool to visualize micro-vascular flow in vivo. Despite numerous demonstrations for the past several years of the qualitative relationship between OMAG and flow, no convincing quantitative relationship has been proven. In this paper, we attempt to quantitatively correlate the OMAG signal with flow. Specifically, we develop a simplified analytical model of the complex OMAG, suggesting that the OMAG signal is a product of the number of particles in an imaging voxel and the decorrelation of OCT (optical coherence tomography) signal, determined by flow velocity, interframe time interval, and wavelength of the light source. Numerical simulation with the proposed model reveals that if the OCT amplitudes are correlated, the OMAG signal is related to a total number of particles across the imaging voxel cross-section per unit time (flux); otherwise it would be saturated but its strength is proportional to the number of particles in the imaging voxel (concentration). The relationship is validated using microfluidic flow phantoms with various preset flow metrics. This work suggests OMAG is a promising quantitative tool for the assessment of vascular flow.
To investigate the application of wide field OCT angiography (OCTA) in living human eye. Normal and pathologic eyes
were recruited and imaged by a 1060 nm swept source OCTA system with A-line speed of 100 kHz provided by Carl
Zeiss Meditec. Inc.. Wide field OCTA images were generated in a single scan within 5 seconds based on the tracking
capability installed in the system with 9 x 9 mm2 and 12 x 12 mm2 field of view and sampled by 500 A-lines x 500 Bframes
with 2 repetitions in the same location for one 3D data. Complex optical microangiography (OMAG) algorithm
was used to extract the blood flow information. The en face maximum projection provided by the device was used to
generate 2-dimensional angiograms of different layers and color-code images. Wide field en face OCTA images of
different macular diseases showed a great agreement with fluorescein angiography (FA). Meanwhile, OCTA provides
depth-resolved information and detailed vascular images of venous occlusion and DR patients in far peripheral region,
and choroidal vessels imaging in serpiginous choroidopathy patient, providing a better visualization of vascular network
compared to FA.
Optical coherence tomography angiography (OCTA) is clinically useful for the qualitative assessment of the macular microvasculature. However, there is a need for comprehensive quantitative tools to help objectively analyze the OCT angiograms. Few studies have reported the use of a single quantitative index to describe vessel density in OCT angiograms. In this study, we introduce a five-index quantitative analysis of OCT angiograms in an attempt to detect and assess vascular abnormalities from multiple perspectives. The indices include vessel area density, vessel skeleton density, vessel diameter index, vessel perimeter index, and vessel complexity index. We show the usefulness of the proposed indices with five illustrative cases. Repeatability is tested on both a healthy case and a stable diseased case, giving interclass coefficients smaller than 0.031. The results demonstrate that our proposed quantitative analysis may be useful as a complement to conventional OCTA for the diagnosis of disease and monitoring of treatment.
Optical coherence tomography angiography (OCTA) has increasingly become a clinically useful technique in ophthalmic imaging. We evaluate the repeatability and reproducibility of blood perfusion in the optic nerve head (ONH) measured using optical microangiography (OMAG)-based OCTA. Ten eyes from 10 healthy volunteers are recruited and scanned three times with a 68-kHz Cirrus HD-OCT 5000-based OMAG prototype system (Carl Zeiss Meditec Inc., Dublin, California) centered at the ONH involving two separate visits within six weeks. Vascular images are generated with OMAG processing by detecting the differences in OCT signals between consecutive B-scans acquired at the same retina location. ONH perfusion is quantified as flux, vessel area density, and normalized flux within the ONH for the prelaminar, lamina cribrosa, and the full ONH. Coefficient of variation (CV) and intraclass correlation coefficient (ICC) are used to evaluate intravisit and intervisit repeatability, and interobserver reproducibility. ONH perfusion measurements show high repeatability [CV≤3.7% (intravisit) and ≤5.2% (intervisit)] and interobserver reproducibility (ICC≤0.966) in all three layers by three metrics. OCTA provides a noninvasive method to visualize and quantify ONH perfusion in human eyes with excellent repeatability and reproducibility, which may add additional insight into ONH perfusion in clinical practice.
To investigate the application of optical microangiography (OMAG) in living human eye. Patients with different macular diseases were recruited, including diabetic retinopathy (DR), geographic atrophy (GA), retinitis pigmentosa (RP), and venous occlusion, et al. Wide field OCT angiography images can be generated by montage scanning protocol based on the tracking system. OMAG algorithm based on complex differentiation was used to extract the blood flow and removed the bulk motion by 2D cross-correlation method. The 3D angiography was segmented into 3 layers in the retina and 2 layers in the choroid. The en-face maximum projection was used to obtain 2-dimensional angiograms of different layers coded with different colors. Flow and structure images were combined for cross-sectional view. En face OMAG images of different macular diseases showed a great agreement with FA. Meanwhile, OMAG gave more distinct vascular network visions that were less affected by hemorrhage and leakage. The MAs were observed in both superficial and middle retinal layers based on OMAG angiograms in different layers of DR patients. The contour line of FAZ was extracted as well, which can be quantitative the retinal diseases. For GA patient, the damage of RPE layer enhanced the penetration of light and enabled the acquisition of choriocapillaries and choroidal vessels. The wide field OMAG angiogram enabled the capability of capturing the entire geographic atrophy. OMAG provides depth-resolved information and detailed vascular images of DR and GA patients, providing a better visualization of vascular network compared to FA.
Optical coherence tomography (OCT)-based angiography is increasingly becoming a clinically useful and important imaging technique due to its ability to provide volumetric microvascular networks innervating tissue beds in vivo without a need for exogenous contrast agent. Numerous OCT angiography algorithms have recently been proposed for the purpose of contrasting microvascular networks. A general literature review is provided on the recent progress of OCT angiography methods and algorithms. The basic physics and mathematics behind each method together with its contrast mechanism are described. Potential directions for future technical development of OCT based angiography is then briefly discussed. Finally, by the use of clinical data captured from normal and pathological subjects, the imaging performance of vascular networks delivered by the most recently reported algorithms is evaluated and compared, including optical microangiography, speckle variance, phase variance, split-spectrum amplitude decorrelation angiography, and correlation mapping. It is found that the method that utilizes complex OCT signal to contrast retinal blood flow delivers the best performance among all the algorithms in terms of image contrast and vessel connectivity. The purpose of this review is to help readers understand and select appropriate OCT angiography algorithm for use in specific applications.
Optical coherence tomography (OCT)-based optical microangiography (OMAG) is a high-resolution, noninvasive imaging technique capable of providing three-dimensional in vivo blood flow visualization within microcirculatory tissue beds in the eye. Although the technique has demonstrated early clinical utility by imaging diseased eyes, its limited field of view (FOV) and the sensitivity to eye motion remain the two biggest challenges for the widespread clinical use of the technology. Here, we report the results of retinal OMAG imaging obtained from a Zeiss Cirrus 5000 spectral domain OCT system with motion tracking capability achieved by a line scan ophthalmoscope (LSO). The tracking LSO is able to guide the OCT scanning, which minimizes the effect of eye motion in the final results. We show that the tracking can effectively correct the motion artifacts and remove the discontinuities and distortions of vascular appearance due to microsaccade, leading to almost motion-free OMAG angiograms with good repeatability and reliability. Due to the robustness of the tracking LSO, we also show the montage scan protocol to provide unprecedented wide field retinal OMAG angiograms. We experimentally demonstrate a 12×16 mm2 retinal OMAG angiogram acquired from a volunteer, which is the widest FOV retinal vasculature imaging up to now in the community.
In ophthalmology, a reliable means of diagnosing glaucoma in its early stages is still an open issue. Past efforts, including forays into fluorescent angiography (FA) and early optical coherence tomography (OCT) systems, to develop a potential biomarker for the disease have been explored. However, this development has been hindered by the inability of the current techniques to provide useful depth and microvasculature information of the optic nerve head (ONH), which have been debated as possible hallmarks of glaucoma progression. We reasoned that a system incorporating a spectral-domain OCT (SD-OCT) based Optical Microangiography (OMAG) system, could allow an effective, non-invasive methodology to evaluate effects on microvasculature by glaucoma. SD-OCT follows the principle of light reflection and interference to produce detailed cross-sectional and 3D images of the eye. OMAG produces imaging contrasts via endogenous light scattering from moving particles, allowing for 3D image productions of dynamic blood perfusion at capillary-level resolution. The purpose of this study was to investigate the optic cup perfusion (flow) differences in glaucomatous and normal eyes. Images from three normal and five glaucomatous subjects were analyzed our OCT based OMAG system for blood perfusion and structural images, allowing for comparisons. Preliminary results from blood flow analysis revealed reduced blood perfusion within the whole-depth region encompassing the Lamina Cribrosa in glaucomatous cases as compared to normal ones. We conclude that our OCT-OMAG system may provide promise and viability for glaucoma screening.
Qinshan Nuclear Power Station is located in the Haiyan County of Zhejiang Province in east China. The warm water
from their cooling systems is discharged into the Hangzhou Bay directly which will affect the ecosystem of coastal area
in the bay. To study the influence of warming effect from the thermal discharge of the Qinshan Nuclear Power Station
Phase2 and Phase3, the remote sensing image of the marine airborne multi-spectrum scanner (MAMS), the numerical
modeling based COHERENS (A coupled Hydrodynamical Ecological Model for Regional Shelf seas) and shipboard
water column measurements are all applied to explore the spatial and temporal distribution of the warm water. In order to
get accurate boundary conditions, a larger area was simulated firstly to provide hydrodynamic parameter for the
modeling area in the numerical simulation. From the remote sensing image, the numerical simulation and field
observations, we can conclude that the thermal effluent from the Qinshan Phase2 and Phase3 cooling systems just
influences coastal water on a small scale.
Hangzhou Bay in China is an important conveyor transporting contaminants from surrounding cities in Yangtze Delta. A
numerical hydrodynamic model based on COHERENS (Coupled Hydrodynamical Ecological model for Regional Shelf
seas) has been employed to simulate the pollutant transport trajectory and to obtain the retention ratio in the Bay. The
forcing of the model include tides and freshwater. The influence of wind was explored by imposing the QSCAT/NCEP
Blend Wind data into the numerical simulation.
The bay was divided into 8 subdomains (S1-S8) and the simulation was performed in two months: March (the dry
season) and July (the wet season). Two sets of numerical experiment were carried out with or without wind. Results
indicated that wind plays a more important role on pollutant transport in the wet season than in the dry season. The
influences of wind on the pollutant transport in 8 subdomians are different, especially in wet season. The retention ratio
of S1 is most significantly affected by wind compared with other subdomains.
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