3D Optical Coherence Tomography Angiography Research Articles

Three-dimensional vascular graph construction from depth information of blood vessel centerlines in optical coherence tomography angiography

Optical coherence tomography angiography (OCTA) is a noninvasive imaging technique for visualizing high-resolution volumetric vascular networks. Although OCTA has been widely employed in vascular network analysis, most studies have been limited to the analysis of two-dimensional (2D) en-face projection images because leveraging the full potential of OCTA’s three-dimensional (3D) information has been challenging due to projection artifacts beneath blood vessels. In this study, we propose a semi-automatic method for constructing a 3D vascular graph from 3D OCTA images without relying on data-driven learning strategies such as deep learning. The proposed method estimates the depth information of blood vessel centerlines in 2D en-face images and constructs a 3D vascular graph by integrating the depth estimation results for all vessel centerline segments. We demonstrate the effectiveness of the proposed method through experiments conducted on both simulated datasets and real datasets acquired from the dorsal dermis of mice.

LA-Net: layer attention network for 3D-to-2D retinal vessel segmentation in OCTA images

Objective. Retinal vessel segmentation from optical coherence tomography angiography (OCTA) volumes is significant in analyzing blood supply structures and the diagnosing ophthalmic diseases. However, accurate retinal vessel segmentation in 3D OCTA remains challenging due to the interference of choroidal blood flow signals and the variations in retinal vessel structure. Approach. This paper proposes a layer attention network (LA-Net) for 3D-to-2D retinal vessel segmentation. The network comprises a 3D projection path and a 2D segmentation path. The key component in the 3D path is the proposed multi-scale layer attention module, which effectively learns the layer features of OCT and OCTA to attend to the retinal vessel layer while suppressing the choroidal vessel layer. This module also efficiently captures 3D multi-scale information for improved semantic understanding during projection. In the 2D path, a reverse boundary attention module is introduced to explore and preserve boundary and shape features of retinal vessels by focusing on non-salient regions in deep features. Main results. Experimental results in two subsets of the OCTA-500 dataset showed that our method achieves advanced segmentation performance with Dice similarity coefficients of 93.04% and 89.74%, respectively. Significance. The proposed network provides reliable 3D-to-2D segmentation of retinal vessels, with potential for application in various segmentation tasks that involve projecting the input image. Implementation code: https://github.com/y8421036/LA-Net.

Retinal vessel volume reference database derived from volume-rendered optical coherence tomography angiography

Optical coherence tomography angiography (OCTA) enables three-dimensional reconstruction of the functional blood vessels in the retina. Therefore, it enables the quantification of 3D retinal vessel parameters such as surface area and vessel volume. In spite of the widespread use of OCTA, no representative volume-rendered vessel volume (VV) data are published to date. In this study, OCTA 3 × 3 mm macular cubes were processed with volume-rendering techniques to measure VV in 203 eyes from 107 healthy volunteers. Generalized linear models (GLM) were constructed to assess the impact of age, gender, visual acuity (VA), spherical equivalent (SE), and axial length (AL) on VV. Overall mean VV was 0.23 ± 0.05mm3. Age and axial length showed a negative correlation with VV. However, GLM model analysis found that AL exerted the most pronounced influence on VV. No statistically significant associations were identified between gender or between left and right eyes. This is the first study to assess 3D OCTA VV and its naturally occurring variations in a large series of healthy subjects. It offers novel insights into the characterization of normal retinal vascular anatomy in healthy individuals, contributing to a valuable reference for future research in this field.

Axial Stretching of Vessels in the Retinal Vascular Plexus With 3D OCT-Angiography.

PurposeThe purpose of this study is to describe and quantify the nonpathological axial stretching in the retinal vascular plexus in three-dimensional (3D) optical coherence tomography angiography (OCTA) images.MethodsThe 3D vascular network underneath the inner limiting membrane of OCTA volumes was labeled as ground truth (GT) data. To analyze the cross-section area of the vessels the width and depth of the vessels in the GT data were computed and an elliptical quotient was proposed to quantify the axial stretching.ResultsA total of 21 3D OCTA volumes were labeled. It was found that the vessels in 3D OCTA images are stretched in the direction of the A-Scan by a factor of 2.46 ± 1.82 with a median of 2.24. Furthermore, a larger cross-section area leads to higher axial stretching.ConclusionsThe elliptical shape of the cross-section area of the vessel does not match with the expected pathology of the vascular network in the human eye. Therefore a correction of the volume data before a 3D analysis is recommended.Translational RelevanceThis work gives a systematic insight to the stretched shape of vessels in 3D OCTA images and is relevant for further clinical research analyzing the 3D vascular network.

Diabetic macular ischemia.

Since its relevance on diagnosis and prognosis of diabetic retinopathy (DR), this review will examine a multimodal imaging approach to detect diabetic macular ischemia (DMI). A PubMed engine search was carried out using the term "macular ischemia" paired with "diabetes," and "diabetic macular ischemia" paired to "fluorescein angiography," "ultra-wide field fluorescein angiography," "optical coherence tomography angiography," "octa," "2D octa," "ultra-wide field octa," "3D octa," "visual acuity." All studies published in English up to October 2021 irrespective of their publication status were reviewed, and relevant publications were included in this review. Recently, new technologies have been proposed as an alternative to fluorescein angiography (FA), which is an actual diagnostic gold standard technique. Nowadays, optical coherence tomography angiography (OCTA) has emerged as the most promising and reliable procedure able to provide a qualitative and quantitative description of DMI. Newer three-dimensional (3D) OCTA approach will be discussed too. Moreover, we will discuss how OCTA might identify preclinical alterations before the onset of DR and allow prediction about the progression of disease. OCTA has significantly expanded our knowledge on diabetic macular ischemia.

Blood vessel tail artifacts suppression in optical coherence tomography angiography.

.SignificanceA long-standing challenge of the blood vessel tail artifacts along the axial direction prevents optical coherence tomography angiography (OCTA) for a comprehensive three-dimensional (3D) vascular mapping. Addressing the blood vessel tail artifacts issue will make OCTA to be a real 3D blood vessel structural imaging technique, which in combination with OCT-based blood flow velocity measurements will pave the way for a simpler and robust 3D imaging of the capillary transit time, one important parameter for the evaluation of micro circulation.ApproachWe first described the basic principles of OCTA imaging, discussed the origin of blood vessel tail artifacts in an OCTA image, then reviewed the existing OCTA techniques for tail artifacts suppression, and at last we envisioned the potential solutions for effective OCTA tail artifacts suppression.ResultsThe origin of blood vessel tail artifacts is due to the multiple scattering of photons with flowing red blood cells, which elongates the light path of the dynamic signal from vessel lumen to the tail regions. High numerical aperture implementation, subtraction-based post-data processing, Hessian filtering, and high acquisition rate-based dynamic analysis methods have been proposed to address the blood vessel tail artifacts issue in OCTA.ConclusionsHigh acquisition rate-based dynamic analysis in combination with Hessian filtering have the potential to effectively suppress the blood vessel tail artifacts and in the meantime preserve flows in small vessels within the tail region, providing real 3D OCTA imaging of blood vessel structures.

Volume rendered 3D OCTA assessment of macular ischemia in patients with type 1 diabetes and without diabetic retinopathy

The aim of this study was to measure macular perfusion in patients with type 1 diabetes and no signs of diabetic retinopathy (DR) using volume rendered three-dimensional (3D) optical coherence tomography angiography (OCTA). We collected data from 35 patients with diabetes and no DR who had OCTA obtained. An additional control group of 35 eyes from 35 healthy subjects was included for comparison. OCTA volume data were processed with a previously presented algorithm in order to obtain the 3D vascular volume and 3D perfusion density. In order to weigh the contribution of different plexuses’ impairment to volume rendered vascular perfusion, OCTA en face images were binarized in order to obtain two-dimensional (2D) perfusion density metrics. Mean ± SD age was 27.2 ± 10.2 years [range 19–64 years] in the diabetic group and 31.0 ± 11.4 years [range 19–61 years] in the control group (p = 0.145). The 3D vascular volume was 0.27 ± 0.05 mm3 in the diabetic group and 0.29 ± 0.04 mm3 in the control group (p = 0.020). The 3D perfusion density was 9.3 ± 1.6% and 10.3 ± 1.6% in diabetic patients and controls, respectively (p = 0.005). Using a 2D visualization, the perfusion density was lower in diabetic patients, but only at the deep vascular complex (DVC) level (38.9 ± 3.7% in diabetes and 41.0 ± 3.1% in controls, p = 0.001), while no differences were detected at the superficial capillary plexus (SCP) level (34.4 ± 3.1% and 34.3 ± 3.8% in the diabetic and healthy subjects, respectively, p = 0.899). In conclusion, eyes without signs of DR of patients with diabetes have a reduced volume rendered macular perfusion compared to control healthy eyes.

USING THREE-DIMENSIONAL OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY METRICS IMPROVES REPEATABILITY ON QUANTIFICATION OF ISCHEMIA IN EYES WITH DIABETIC MACULAR EDEMA.

Two-dimensional (2D) optical coherence tomography angiography (OCTA) is known to be prone to segmentation errors, especially in pathologic eyes. Therefore, our aim was to systematically compare intrasession repeatability between repeated scans for 2D and three-dimensional (3D) OCTA metrics in quantifying retinal perfusion in eyes with diabetic macular edema. Diabetic patients with diabetic retinopathy and diabetic macular edema who had two consecutive OCTA imaging scans obtained during the same visit were retrospectively included. A previously validated algorithm was applied to OCTA volume data to measure the 3D vascular volume and perfusion density. Optical coherence tomography angiography en face images were also processed to obtain 2D perfusion density metrics. Twenty patients (20 eyes) with diabetic retinopathy and diabetic macular edema were included. The intraclass correlation coefficient ranged from 0.591 to 0.824 for 2D OCTA metrics and from 0.935 to 0.967 for 3D OCTA metrics. Therefore, compared with the 2D OCTA analysis, the intraclass correlation coefficients of the 3D OCTA analysis were higher (without overlapping of the 95% confidential intervals). Similarly, the coefficient of variation (ranging from 2.2 to 4.2 for 2D OCTA metrics and from 1.9 to 2.0 for 3D OCTA metrics) indicated that the 3D OCTA-based quantifications had the highest interscan intrasession agreements. Differences in interscan 2D OCTA metrics' values were associated with average macular volume. Three-dimensional OCTA metrics have higher values of intrasession repeatability, as compared with 2D OCTA metrics. The latter finding seems to be related to the high rate of segmentation errors occurring in diabetic macular edema eyes.

Longitudinal assessment of type 3 macular neovascularization using 3D volume-rendering OCTA

ObjectiveTo investigate the evolution of treatment-naive type 3 macular neovascularization (MNV) undergoing anti-vascular endothelial growth factor (VEGF) treatment through volume rendered three-dimensional (3D) optical coherence tomography angiography (OCTA). DesignRetrospective observational study. ParticipantsPatients with type 3 MNV and age-related macular degeneration (AMD). MethodsIncluded subjects had three loading injections of an anti-VEGF agent. The OCTA volume data at baseline and follow-up were processed with a previously published algorithm in order to obtain a volume-rendered representation of type 3 MNV. Progressive changes in type 3 lesions were analyzed via 3D OCTA volume rendering. ResultsA total of 14 treatment-naive eyes with type 3 MNV from 11 AMD patients (7 females) were included. At both baseline and follow-up visits, a type 3 MNV complex was identifiable. Each complex was composed of a mean number of 2.5 ± 0.7 vascular branches at baseline and 1.4 ± 0.6 at the follow-up visit (p < 0.0001). The mean changes in central macular thickness and visual acuity were significantly correlated with modifications in the number of type 3 MNV branches (ρ = –0.533, p = 0.049, and ρ = –0.581, and p = 0.040, respectively). ConclusionsThis study demonstrated that type 3 lesions do not disappear completely after loading treatment, as indicated previously by histopathologic studies. Importantly, quantitative volume changes in type 3 lesions are directly associated with treatment response.

Deep learning toolbox for automated enhancement, segmentation, and graphing of cortical optical coherence tomography microangiograms.

Optical coherence tomography angiography (OCTA) is becoming increasingly popular for neuroscientific study, but it remains challenging to objectively quantify angioarchitectural properties from 3D OCTA images. This is mainly due to projection artifacts or "tails" underneath vessels caused by multiple-scattering, as well as the relatively low signal-to-noise ratio compared to fluorescence-based imaging modalities. Here, we propose a set of deep learning approaches based on convolutional neural networks (CNNs) to automated enhancement, segmentation and gap-correction of OCTA images, especially of those obtained from the rodent cortex. Additionally, we present a strategy for skeletonizing the segmented OCTA and extracting the underlying vascular graph, which enables the quantitative assessment of various angioarchitectural properties, including individual vessel lengths and tortuosity. These tools, including the trained CNNs, are made publicly available as a user-friendly toolbox for researchers to input their OCTA images and subsequently receive the underlying vascular network graph with the associated angioarchitectural properties.

Image Projection Network: 3D to 2D Image Segmentation in OCTA Images.

We present an image projection network (IPN), which is a novel end-to-end architecture and can achieve 3D-to-2D image segmentation in optical coherence tomography angiography (OCTA) images. Our key insight is to build a projection learning module (PLM) which uses a unidirectional pooling layer to conduct effective features selection and dimension reduction concurrently. By combining multiple PLMs, the proposed network can input 3D OCTA data, and output 2D segmentation results such as retinal vessel segmentation. It provides a new idea for the quantification of retinal indicators: without retinal layer segmentation and without projection maps. We tested the performance of our network for two crucial retinal image segmentation issues: retinal vessel (RV) segmentation and foveal avascular zone (FAZ) segmentation. The experimental results on 316 OCTA volumes demonstrate that the IPN is an effective implementation of 3D-to-2D segmentation networks, and the uses of multi-modality information and volumetric information make IPN perform better than the baseline methods.

Optical coherence tomography angiography measures blood pulsatile waveforms at variable tissue depths.

Photoplethysmography (PPG) is routinely used to detect the blood pulse signal from skin tissue beds in clinics. However, the origin of the PPG signal remains controversial. The purpose of this study is to explore optical coherence tomography angiography (OCTA) to indicate pulsatile waveforms in the papillary plexus and dermal plexus separately under different hand elevations. Optical microangiography (OMAG) algorithm was used to obtain a 3D OCTA signals, from which the depth-resolved pulsatile blood flow signals were extracted from different skin vascular plexus. The systolic amplitude, crest time, and delta T were measured from the OCTA pulsatile signals when the hand was placed at the positions of 50 cm below, 0 cm, and 50 cm above the heart level. The pulse signal integrated from all the depths has a similar waveform to that of the PPG and showed the same morphological change at different hand elevations. The pulsatile patterns from the papillary plexus and dermal plexus showed distinct morphological changes at different local blood pressure. Less amplitude difference was found from papillary plexus comparing to that of the dermal plexus. Crest time was found in an increasing trend in the OCTA pulsatile waveform from both plexuses when the arm was raised from the position below to above the heart level. In contrast, a decreasing trend of Delta T was detected in the dermal pulsatile but was not observed from that of the papillary plexus, indicating that vascular resistance associated with the arm elevations does not necessarily have the same effect on the two plexuses. OCTA can provide depth-resolved pulsatile waveforms within different microvascular plexus within tissue skin beds. This technique could open doors to understanding the mechanisms of how blood flow changes at different skin circulatory plexus.

Rotational Three-dimensional OCTA: a Notable New Imaging Tool to Characterize Type 3 Macular Neovascularization

This study explored whether rotational three-dimensional (3D) visualization of optical coherence tomography angiography (OCTA) volume data may yield valuable information regarding type 3 macular neovascularization (MNV). In this retrospective, cross-sectional study, we collected data from 15 eyes (13 patients) with treatment-naïve type 3 MNV in their post-nascent stage and age-related macular degeneration (AMD). Subjects were imaged with the SS-OCT system (PLEX Elite 9000, Carl Zeiss Meditec Inc., Dublin, CA, USA). The OCTA volume data were processed with a prototype volume projection removal algorithm and then analyzed using volumetric visualization techniques in order to obtain a 3D visualization of the region occupied by type 3 MNV. The two-dimensional and three-dimensional OCTA images were investigated. Mean ± SD age was 75.1 ± 7.4 years. BCVA was 0.42 ± 0.21 LogMAR in the study eyes. Considering the cohort of analyzed eyes, on rotational 3D OCTA images, a total of 35 neovascular lesions (vs 22 lesions detected on 2D OCTA images) rising from the deep vascular complex and variably spanning the outer retinal layers and eventually reaching the RPE/sub-RPE space were detected. Nine of 35 lesions had a saccular shape, while the remaining cases had a filiform shape. On rotational 3D OCTA images, these lesions were inclined on the three planes, instead of perpendicular to the RPE/Bruch’s membrane. In conclusion, this study used an algorithm to obtain rotational three-dimensional visualization of type 3 MNV. This approach seems to increase the detection rate for these lesions and to be useful to offer new insight into type 3 MNV.

In vivo rotational three-dimensional OCTA analysis of microaneurysms in the human diabetic retina

The aim of this study was to explore whether rotational three-dimensional (3D) visualization of optical coherence tomography angiography (OCTA) volume data may yield valuable information regarding diabetic retinal microaneurysm (MA) characteristics. In this retrospective, observational study, we collected data from 20 patients (20 eyes) with diabetic retinopathy. Subjects were imaged with the SS-OCTA system (PLEX Elite 9000, Carl Zeiss Meditec Inc., Dublin, CA, USA). The OCTA volume data were processed with a volume projection removal algorithm and then exported to imageJ in order to obtain a 3D visualization of the analyzed MAs. The rotational three-dimensional OCTA images were qualitatively and quantitatively investigated. A total of 52 MAs were included in the analysis. On rotational 3D OCTA images, the number of vessels associated with each MA varied between 1 and 4, and most MAs (59.6%) were associated with 2 vessels. Moreover, in 20 MAs (38.4%) these vessels seem to originate from the SCP, while 26 MAs (50.0%) had associated vessels originating from the DVC, and 6 MAs had associated vessels arising from both the SCP and DVC (11.6%). Most MAs (31/52) had a ‘saccular’ shape. The number of retinal layers occupied by each MA ranged between 1 and 3 and the inner nuclear layer was the retinal layer most frequently occupied by MAs. In conclusion, this study used an algorithm to obtain rotational three-dimensional visualization of retinal MAs. The MAs’ architecture is complex and 3D visualization may clarify the true vascular origin of these lesions, which is often mistaken using en face OCTA images.

3D Shape Modeling and Analysis of Retinal Microvasculature in OCT-Angiography Images.

3D optical coherence tomography angiography (OCT-A) is a novel and non-invasive imaging modality for analyzing retinal diseases. The studies of microvasculature in 2D en face projection images have been widely implemented, but comprehensive 3D analysis of OCT-A images with rich depth-resolved microvascular information is rarely considered. In this paper, we propose a robust, effective, and automatic 3D shape modeling framework to provide a high-quality 3D vessel representation and to preserve valuable 3D geometric and topological information for vessel analysis. Effective vessel enhancement and extraction steps by means of curvelet denoising and optimally oriented flux (OOF) filtering are first designed to produce 3D microvascular networks. Afterwards, a novel 3D data representation of OCT-A microvasculature is reconstructed via advanced mesh reconstruction techniques. Based on the 3D surfaces, shape analysis is established to extract novel shape-based microvascular area distortion via the Laplace-Beltrami eigen-projection. The extracted feature is integrated into a graph-cut segmentation system to categorize large vessels and small capillaries for more precise shape analysis. The proposed framework is validated on a dedicated repeated scan dataset including 260 volume images and shows high repeatability. Statistical analysis using the surface area biomarker is performed on small capillaries to avoid the effect of tailing artifact from large vessels. It shows significant differences ( ) between DR stages on 100 subjects in a OCTA-DR dataset. The proposed shape modeling and analysis framework opens the possibility for further investigating OCT-A microvasculature in a new perspective.

Retinal Blood Vessel Caliber Estimation for Optical Coherence Tomography Angiography Images Based on 3D Superellipsoid Modeling

Changes of retinal blood vessel calibers may reflect various retinal diseases and even several non-retinal diseases. We propose a new method to estimate retinal vessel calibers from 3D optical coherence tomography angiography (OCTA) images based on 3D modeling using superellipsoids. Taking advantage of 3D visualization of the retinal tissue microstructures in vivo provided by OCTA, our method can detect retinal blood vessels precisely, estimate their calibers reliably, and show the relative flow speed visually.

Automated motion-artifact correction in an OCTA image using tensor voting approach.

Optical coherence tomography angiography (OCTA) is a promising tool for imaging subsurface microvascular networks owing to its micron-level resolution and high sensitivity. However, it is not uncommon that OCTA imaging suffers from strip artifacts induced by tissue motion. Although various algorithms for motion correction have been reported, a method that enables motion correction on a single en face OCTA image remains a challenge. In this study, we propose a motion correction approach based on microvasculature detection and broken gap filling. Unlike previous methods using registration to restore disturbed vasculature during motion artifact removal, tensor voting is performed in an individual projected image to connect the broken vasculature. Both simulation and in vivo 3D OCTA imaging of the mouse bladder are performed to validate the effectiveness of this method. A comparison of in vivo images before and after motion correction shows that our method effectively corrects tissue motion artifacts while preserving the continuity of vasculature network. Furthermore, in vivo results of this technique are presented to demonstrate its utility for imaging tumor angiogenesis in the mouse bladder.

Enhanced resolution and speckle-free three-dimensional printing of macular optical coherence tomography angiography.

Enhanced resolution and speckle-free three-dimensional printing of macular optical coherence tomography angiography.

System of label-free three-dimensional optical coherence tomography angiography with high sensitivity and motion contrast and its applications in brain science

Combining three-dimensional (3D) imaging ability of optical coherence tomography (OCT) with movement recognition ability of dynamic scattering technique, label-free 3D OCT angiography can be realized, which has a wide range of applications in basic science research and clinical diagnosis. At no expense of line scanning speed, the scale of capillaries can be detected by improving the sensitivity through the interframe analysis. However, there exists a certain residual overlap between dynamic flow signals and static tissue beds due to a series of reasons, thus making it difficult to completely distinguish dynamic flow signals from static tissue beds. Thus, when it comes to threshold segmentation for the blood flow signal extraction, classification error rate is inevitable, resulting in the decrease of the motion contrast of angiogram. In order to reduce classification error rate between static tissue beds and dynamic flow signals for high motion-contrast angiography, we propose a method of component compounding in wavelet domain. Three main steps are needed for this method. Firstly, on the basis of two-dimensional (2D) discrete static wavelet transform, a frame image can be decomposed into multiple levels. Each level has four components, i.e., approximation component, horizontal detail component, vertical detail component and diagonal detail component. Different decomposition levels and types of wavelet can be selected according to the demand. Secondly, the algorithm of inverse iteration compounding is used, which contains the arithmetic mean and the geometric mean of the components of adjacent decomposition levels. The adopted order for inverse iteration compounding is from the last level to the first one. The weight of the arithmetic mean to the geometric mean is one to one. In this way, four compounding components can be obtained. Thirdly, a new frame image with higher motion contrast can be obtained by using 2D discrete static wavelet inverse transform of the four compounding components. Both flow phantom and live animal experiments are performed. The results show that classification error rate decreases by 83% and 71% respectively after component compounding in wavelet domain. Besides, the angiogram has an improved motion contrast and a better vessel connectivity, which may contribute to better and wider applications of OCT angiography. Furthermore, based on the developed system, the preliminary imaging studies on the model of local stroke are conducted. In this experiment, we record the 3D data of SD mouse brain before and after the local stroke and on the tenth day. As a consequence, a clear presentation for the whole process of stroke model formation, vessel damage and vessel recovery is achieved, which may be beneficial to studying the mechanism of local stroke model.