Quantitative OCT angiography of optic nerve head blood flow

Jia, Yali; Morrison, John C.; Tokayer, Jason; Tan, Ou; Lombardi, Lorinna; Baumann, Bernhard; Chen, Lu; Choi, WooJhon; Fujimoto, James G.; Huang, David

doi:10.1364/boe.3.003127

Cited by 435 publications

(355 citation statements)

References 34 publications

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“…Motivated by the fact that pixels from static tissue yield small decorrelation values while pixels from the faster moving tissue yield high decorrelation values [7][8], we propose to compute decorrelations from overlapping scans and use the en face decorrelation image. This implies that the proposed method is not suitable to data without any overlapping scan.…”

Section: Motion Detectionmentioning

confidence: 99%

Motion Correction in Optical Coherence Tomography for Multi-modality Retinal Image Registration

Cheng

Lee

et al. 2016

Proceedings of the Ophthalmic Medical Image Analysis Third International Workshop

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Abstract. Optical coherence tomography (OCT) is a recently developed non-invasive imaging modality, which is often used in ophthalmology. Because of the sequential scanning in form of A-scans, OCT suffers from the inevitable eye movement. This often leads to mis-alignment especially among consecutive B-scans, which affects the analysis and processing of the data such as the registration of the OCT en face image to color fundus image. In this paper, we propose a novel method to correct the mis-alignment among consecutive B-scans to improve the accuracy in multi-modality retinal image registration. In the method, we propose to compute decorrelation from overlapping B-scans and to detect the eye movement. Then, the B-scans with eye movement will be re-aligned to its precedent scans while the rest of B-scans without eye movement are untouched. Our experiments results show that the proposed method improves the accuracy and success rate in the registration to color fundus images.

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Section: Motion Detectionmentioning

confidence: 99%

Motion Correction in Optical Coherence Tomography for Multi-modality Retinal Image Registration

Cheng

Lee

et al. 2016

Proceedings of the Ophthalmic Medical Image Analysis Third International Workshop

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“…In [6], the authors postulated that optic nerve head (ONH) blood flow may be associated with glaucoma development and proposed the use of Split-spectrum amplitude-decorrelation angiography (SSADA) method [7] together with flow index and vessel density for glaucoma detection. The split-spectrum amplitude-decorrelation angiography method [7] detects motion of blood flow as decorrelation of signals' amplitude between multiple sequential OCT B-scans taken at the same cross-section to construct a map of blood flow.…”

Section: Introductionmentioning

confidence: 99%

Artefacts Removal from Optical Coherence Tomography Angiography

Ong

Cheng

Qian

et al. 2016

Proceedings of the Ophthalmic Medical Image Analysis Third International Workshop

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“…Using OCT-A the vascular density in the optic nerve head (ONH) and peripapillary area was measured. [19][20][21] The authors found reduced ONH blood vessel density that was associated with structural and functional glaucomatous damage. [22][23][24][25] The purpose of the present study was to assess vascularity of the macular area in patients with glaucoma by means of OCT-A.…”

mentioning

confidence: 97%

“…A new 3D angiography algorithm (split-spectrum amplitude-decorrelation angiography, (SSADA)) was developed for imaging retinal microcirculation. 19 This method is based on ultrahigh-speed optical coherence tomography (OCT), and was called OCT-angiography (OCT-A). Using OCT-A the vascular density in the optic nerve head (ONH) and peripapillary area was measured.…”

mentioning

confidence: 99%

“…[19][20][21][22][23][24][25] For example, Jia et al 19 studied the percentage area occupied by vessels (vessel density) in the optic disc and revealed that preperimetric glaucoma (PPG) patients had significant reductions of ONH perfusion compared to normal: the vessel density was reduced by 34% in the PPG group (p<0.05) with the repeatability 6.2%. The authors concluded that OCT angiography could detect the abnormalities of ONH perfusion and reveal the ONH blood flow mechanism related to glaucoma.…”

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confidence: 99%

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Does OCT Angiography of Macula Play a Role in Glaucoma Diagnostics?

Курышева¹

2017

Ophthalmol Open J

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CitationKurysheva NI. Does OCT angiography of macula play a role in glaucoma diagnostics? Ophthalmol Open J. 2016; 2(1): 1-11. doi: 10.17140/OOJ-2-107 Copyright ©2016 Kurysheva NI. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. To assess vascularity of the macular area in patients with glaucoma using optical coherence tomography angiography (OCT-A) and evaluate the role of its examination in early glaucoma diagnosis. Materials and Methods: Thirty-eight eyes of patients with the early stage of primary open-angle glaucoma (POAG), 27 eyes of patients with the advanced and far-advanced stages of POAG, and 22 eyes of age-matched healthy subjects were examined using spectral-domain OCT-A (SD-OCT-А) (RtVue xR Avanti with the AngioVue software, San Jose, CA, USA) in order to measure retinal thickness and angio flow density (AFD) retina in macula (an area bounded by a circle with a diameter of 3 mm), inсluding fovea and parafovea regions (superficial and deep) of the inner retinal layers. The AFD disc and peripapillary flow density were measured in optic nerve head (ONH) and 750-μm-wide elliptical annulus extending from the optic disc boundary. Retrobulbar blood flow parameters, including ophthalmic artery (OA), central retinal artery (CRA), short posterior ciliary arteries (PCAs), central retinal vein (CRV), and vortex veins (VV), were measured by color doppler imaging (CDI). The average thickness of the ganglion cell complex (avg GCC), retinal nerve fiber layer (RNFL), and choroid, as well as the focal loss volume (FLV) and global loss volume (GLV) of GCC were measured by means of SD-OCT. Automated perimetry was performed using Humphrey perimeter (Carl Zeiss Meditec, Dublin, CA, USA). Corneal-compensated intraocular pressure (IOPcc) and corneal hysteresis (CH) were determined using ocular response analyzer. Mean ocular perfusion pressure (MOPP) was calculated by measuring IOP and arterial blood pressure (BP) immediately prior to OCT and using formula: MOPP = (2/3 diastolic BP + 1/3 systolic BP) × 2/3 -IOP. Statistical analysis was performed using SPSS version 21 and MASS library in the R language. As a measure of the parameter's importance in distinguishing patient groups, a value of the adjusted standardized statistic of the Mann-Whitney test (z-value) and an area under the receiver operating characteristic (ROC) curve (AUC) were used. Results: Although all structural parameters and indices of retrobulbar blood flow were reduced in early glaucoma as compared to the normal controls, the following parameters were the main discrepancy criteria when discriminating these patient groups: macular vascular density-AFD Retina Superficial Whole En Face (z=3.86, p<0.0001;) and macular thickness in the inferior sector p<0.0001;). In discriminating early glaucoma from the advanced and far advanced stages of the disease, the most usefu...

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Quantitative OCT angiography of optic nerve head blood flow

Cited by 435 publications

References 34 publications

Motion Correction in Optical Coherence Tomography for Multi-modality Retinal Image Registration

Motion Correction in Optical Coherence Tomography for Multi-modality Retinal Image Registration

Artefacts Removal from Optical Coherence Tomography Angiography

Does OCT Angiography of Macula Play a Role in Glaucoma Diagnostics?

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