Clinical OCT Angiography Atlas Bruno Lumbroso, Marco Rispoli, Maria Cristina Savastano, Yali Jia, David Huang
INDEX
Note: Page numbers in bold or italic refer to tables, box or figures respectively.
A
Alzheimer's disease 151, 152, 154
Angioid streaks 54
Anterior segment optical coherence tomography angiography 31
Arteries 28
Atrophy 63, 64, 112, 133
Autosomal-dominant neurodegenerative disorder 156
B
Behçet's disease 97, 118, 129
Best disease, color retinal fundus of 58
Best macular dystrophy 55
Birdshot chorioretinopathy 95, 97, 118, 125
Blood flow
velocity 7
visualization of 141
Brain 151, 152
Branch retinal artery occlusion 112, 114, 115
Branch retinal vein occlusion 42, 113
Bruch's membrane 51, 54, 71, 133
B-scan 31
optical coherence tomography 54
C
Central nervous system 151, 152
Central retinal artery occlusion 112
Central retinal vein occlusion 119
Central serous chorioretinopathy 51, 51, 93, 95, 96, 97
Central serous retinopathy 97
Chorioretinitis 125
macular serpiginous 129
scars 66
Chorioretinopathy, chronic central serous 51
Choroid, visualization of 17
Choroidal disorders 17
Choroidal hemangioma 142, 142
Choroidal melanoma 97, 141
Choroidal metastasis 143
Choroidal neovascularization 9, 17, 45, 46, 52, 55, 5658, 60, 61, 63, 64, 97, 126, 129, 133, 136, 139
Choroidal nevus 97, 141
Choroidal nonexudative neovascular membrane, optical coherence tomography angiography of 45
Choroidal osteoma 142
Choroiditis 95, 97, 117
multifocal 59, 95, 97
Circle of Zinn–Haller 133
Classic choroidal neovascularization, fluorescein angiography of 59
Coats’ disease 19, 20
Conjunctiva 32
Conjunctival vasculatures 31
Corneal adapter module 31
Coronavirus disease 2019 118
COVID-19 117, 118
Cross-section optical coherence tomography 93, 115
angiography 9
Cushing's syndrome 93
Cystic spaces 101
Cystoid edema 111, 125
D
Deep vascular complex 14, 15, 38, 42, 116
Deep vascular plexus 22, 27, 29, 110, 154
Dermatomyositis, juvenile 118
Diabetic fibrovascular membrane 66
Diabetic macular edema 81, 119
Diabetic maculopathy, ischemic 85
Diabetic retinopathy 19, 21, 81, 83, 84, 119
advanced 22
nonproliferative 11, 22, 23, 82, 84, 8486, 121
proliferative 22, 23, 85, 88, 8991, 118
Diffuse retinal pigment epitheliopathy 93, 96
Disk, neovascularization of 81
Dye angiography 46
E
Edematous branch vein occlusion 109, 110
En-face optical coherence tomography 93, 94, 99
angiography 47, 134, 145, 146
sequence of 107
Epiretinal membranes 17, 18
Epitheliopathy, chronic 93, 9597
Epstein–Barr infection 99
Expanded disability status scale 151
F
Fibrosis 63
Fibrotic neovascularization 66
Fibrotic punctate inner choroidopathy macular lesion 128
Fibrous scars 64
Fibrovascular pigment epithelium detachment 46
Fluid reaccumulation 61, 62
Fluorescein angiography 17, 27, 27, 39, 45, 56, 59, 81, 83, 93, 102, 109, 109, 110, 110, 111, 112, 113, 119, 133, 137, 141, 142
examinations 101
Fluorescein diffusion leakage 20
Focal choroidal excavation 95, 97, 98, 99
Foveal avascular zone 30, 81, 154
Fuchs’ lesion 54
Fuchs’ spot 133
Fundus
autofluorescence 118
fluorescein angiography 126
G
Ganglion cell 155
combined 14
complex 145, 152, 156
layer 27, 28, 81
plexus 14, 15
Geographic atrophy 48, 73
Giant cell arteritis 112
Glaucoma 145
H
Haller's layer 93, 95
Haller's vessel dilatation 97
Hemorrhage 65
intraretinal 119
macular 135, 136
subretinal 40
High myopia 133
Highly active antiretroviral therapy 125
Huntington's disease 152, 156, 156
Hypertension 118
Hyporeflective cavities 101
Hypotony 97
I
Idiopathic macular telangiectasia 101
Indocyanine green 17, 51
angiography 31, 45, 46, 53, 56, 66, 93, 117, 133, 142, 143
phases of 46
Inflammatory disorders 97, 125
Inflammatory vein occlusion 110
Inner nuclear layer 14, 28, 81
Inner plexiform layer 14, 29, 81
Inner retinal disorders 17, 18
Inner retinal layer
atrophy of 112
complex 155
Intermediate capillary plexus 14, 15, 27, 29
Iris 32
optical coherence tomography 32
angiography 31
Ischemia, retinal 22
Ischemic branch vein occlusion 109
Isolated retinal capillary ischemia 115
L
Lacquer cracks 133
Laser scars 66
Leber–Coats’ disease 19
Locus minoris resistentiae 133
Lymphoma 97
M
Macroaneurysm 19, 21
Macular degeneration
advanced 66
age-related 23, 45, 71, 74, 94, 97, 161
Macular geographical atrophy 84
Macular hole 133
Macular hole classification of Gass 45
Macular neovascularization 37, 41, 42, 45, 162
Macular neuroretinopathy, acute 113, 115, 117, 117
Macular vessel density, quantification of 147
Magnetic resonance angiography 151
Microphthalmia 97
Microvascular occlusions 117
Mixed edematous ischemic occlusions 109
Müller cell depletion 101
Multiple evanescent white dot syndrome 95, 97, 127, 129, 131
Multiple sclerosis 151, 152, 154
Myopia 133
degenerative 133
Myopic choroidal neovascularization 133, 136138
recurrence of 138
Myopic eye 25, 26
Myopic fibrous scars 66
Myopic maculopathy 133
atrophy, traction, and neovascularization classification system of 133
N
Neovascular age-related macular degeneration, pathogenic sequence of 37
Neovascular membranes 26
Neovascularization 64, 81
angioflow evolution sequence of 62
chronic 65
nonexudative 93, 94
vessel area of 15
Nerve fiber layer 14, 115
infarction 115
plexus 14, 15
Neurodegenerative diseases 151, 152
Nonexudative choroidal neovascularization, multimodal imaging of 46
Nonneovascular age-related macular degeneration 71
O
Obstruction, extent of 109
Ocular toxoplasmosis, bilateral 127
Ocular tumors 141
diagnosis of 141
management of 141
Ophthalmia, sympathetic 97, 125
Optic disk 28
Optic nerve
head 145, 151
optical coherence tomography angiography of 109
Optic neuritis 109, 151
Optical coherence tomography 3, 4, 10, 31, 45, 56, 65, 95, 101, 111, 111, 112, 114, 115, 117, 117, 125, 133, 145, 151, 161
angiography 3, 7, 8, 13, 17, 19, 23, 27, 32, 37, 46, 51, 5255, 5759, 66, 67, 72, 73, 7378, 81, 82, 8386, 88, 8891, 94, 9698, 103, 105, 106, 109111, 112114, 116, 117, 118, 121, 128, 135138, 141, 148, 151, 153156, 161
advantages of 17
applications 17
clinical use of 13
disadvantages of 17
examination 101, 133, 145, 151
features 94, 110
future developments in 159
interpretation of 7
principles of 3
ratio analysis 3
signal generation 4
study 35
terminology 13
visualization 8
scans 3
system 82, 86, 87
techniques 46, 125
Optical microangiography 4, 31
Outer retinal atrophy 162
Outer retinal disorders 23
P
Pachychoroid
disorders 93
neovasculopathy 95, 98
pigment epitheliopathy 95, 98
spectrum 93, 95, 97
Paracentral acute middle maculopathy 17, 23, 113, 115, 116, 118, 143
Parkinson's disease 151153, 155
Pathologic myopia 54, 133
choroidal neovascularization of 54
Pearson test 147, 147
Peripapillary pachychoroid syndrome 95, 97
Peripapillary retinal flow index and vessel density, quantification of 145
Peripapillary retinal nerve fiber layer 145
Pigment epithelial detachment 38, 51, 93
Polypoidal choroidal vasculopathy 51, 52, 95, 97, 98
Projection-resolved optical coherence tomography angiography 14
Punctate outer retinal toxoplasmosis 126
Q
Quiescent choroidal neovascularization 45
R
Radial peripapillary capillary plexus 15
Ranibizumab, intravitreal injection of 55
Relapsing-remitting multiple sclerosis 151
Retina 145, 151
neovascularization of 81
Retinal angiomatous proliferation 9
Retinal anomalies 19
Retinal capillary ischemia, levels of 115
Retinal choroidal anastomosis, development of 104
Retinal detachment 94
serous 97
Retinal diseases 128
Retinal disorders study 17
Retinal edema 110
areas of 111
Retinal folds 18
Retinal ganglion cells 152
Retinal hemorrhages 110, 111
Retinal inner layers, disorganization of 113, 115, 119
Retinal microcirculation, pathology of 113
Retinal nerve fiber layer 27, 81, 146, 147, 147, 151, 152
Retinal pigment epithelium 24, 25, 29, 38, 51, 54, 56, 57, 64, 65, 71, 93, 95, 96, 117, 126, 127, 133, 161
Retinal vascular plexus 14, 28
Retinal vein 28
occlusion 42, 109
Retinitis, infectious 125
Retinopathy 17
acute central serous 94
S
Sarcoidosis 97, 125
Scaffold vessels 61
Sclera 32
Scleral optical coherence tomography angiography 31
Scleritis, posterior 97
Serpiginous 129
Sickle cell disease 117, 118
Signal-to-noise ratio 14
Spectral-domain optical coherence tomography 39, 40, 102, 103, 127, 142
angiography 41, 42, 152, 156
scan 135
Split-spectrum amplitude-decorrelation angiography 3, 14, 31
Subretinal macular neovascularization 85, 101
Subretinal pigment epithelium 45, 98
Superficial capillary plexus 27, 105
Superficial plexus 18, 29, 111
Superficial retinal optical coherence tomography angiography 154
Superficial vascular complex 10, 14, 15
Superficial vascular plexus 22, 27, 28, 29, 29, 110, 112, 112
angioflow of 113
T
Telangiectasia 19
macular serpiginous 19, 20, 101
Trauma 66
Tumors 97
U
Ultrahigh sensitive optical microangiography 5
Uveal effusion syndrome 97
Uveitis 95, 97, 125
V
Vascular endothelial growth factor 11, 37, 46, 54, 57, 60, 66, 67, 104, 106, 136, 138
Vascular plexuses 15
Vein occlusions 109
Vessel
arterialization 61
densities 15
metrics 15
Visual acuity 126
loss of 37, 38
Visual field damage 145
Vitrectomy 118
Vogt–Koyanagi–Harada
disease 95, 97, 100, 125
W
White dot syndromes 125
Z
Zinn–Haller ring 134
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Chapter Notes

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1Technology and interpretation
SECTION 1: Methods and techniques of OCT angiography examination
  • CHAPTER 1: Principles of OCT angiography
    Yali Jia, Tristan T Hormel, David Huang
  • CHAPTER 2: Interpretation of OCT angiography
    Tristan T Hormel, Yali Jia, David Huang
  • CHAPTER 3: OCT angiography: Terminology
    David Huang, Tristan Hormel, Yali Jia
  • CHAPTER 4: OCT angiography in everyday clinical practice
    Bruno Lumbroso, Marco Rispoli, Maria Cristina Savastano
  • CHAPTER 5: Retinal normal vascularization
    Maria Cristina Savastano, Marco Rispoli, Bruno Lumbroso
  • CHAPTER 6: Corneal and anterior segment OCT angiography
    Yan Li, David Huang, Yali Jia2

Principles of OCT angiographyChapter 1

Yali Jia,
Tristan T Hormel,
David Huang
 
ABSTRACT
Optical coherence tomography angiography (OCTA) data is generated by measuring motion contrast between sequential optical coherence tomography (OCT) scans. Here we review how the OCT data is collected and how flow signal can be measured using either amplitude, phase, or complex signals.
 
INTRODUCTION
Optical coherence tomography (OCT) uses interferometry to measure tissue reflectance.1 Interferometry relies on the interaction between a reference beam and light reflected from the sample arm after interaction with the tissue. The depths of tissue reflections are resolved by coherence gating, which refers to the mutual coherence between reference and sample reflections. Transverse scanning of the beam in the sample arm makes OCT a three-dimensional imaging modality. OCT usually employs invisible infrared light, which is advantageous for patient comfort in ophthalmic applications. The axial resolution of OCT systems ranges from 2 to 10 µm, depending on the spectral bandwidth and wavelength.2 This enables noninvasive visualization of the internal layers of thin structures such as the retina not possible with any other technology. These advantages have made OCT the most commonly performed imaging procedure in ophthalmology,3 where it is used to diagnose disease and assess treatment efficacy.4
In structural OCT, inherent variation in tissue reflectivity enables the identification of different structures. For instance, the inner nuclear layer of the retina has relatively low reflectivity, and can be distinguished from the more reflective inner and outer plexiform layers around it. However, this does not provide good contrast for capillaries, which usually have similar reflectivity to the tissues in which they are embedded. Structural OCT measurements are consequently incapable of achieving adequate detail to construct an angiogram at capillary-scale detail. Early attempts at OCT angiography (OCTA) uses the Doppler shift measured between adjacent axial scans, but this proved unreliable because the OCT beam often strikes retinal blood vessel at near perpendicular incidence, which makes the Doppler shift too small to measure.5,6 Reliable OCTA eventually emerged as more robust methods to detect motion between successive OCT cross-sectional scans (B-scans) were developed.
 
GENERATING OCTA DATA FROM MOTION CONTRAST
Optical coherence tomography angiography relies on motion contrast to highlight blood vessels down to the capillary level. Blood flow changes the OCT reflectance signal between sequential B-scans (Figures 1A to D). This change constitutes flow signal.
Because OCTA is based on OCT data, it has many of the characteristics of structural OCT imaging. OCTA is also a noninvasive, three-dimensional modality. OCTA data is automatically coregistered with the structural OCT data used to produce it. This can be useful for assessing the location of vasculature relative to the tissue in which it is embedded and for correlating the structural and vascular features to enhance the diagnosis of retinal pathologies.
 
METHODS FOR MEASURING MOTION CONTRAST
There are a number of ways to measure motion contrast. OCT signal is complex valued—including both amplitude and phase components. Consequently, OCTA can be either phase-based, amplitude-based, or complex-signal-based.
The first attempts to achieve angiography from OCT devices relied on Doppler phase shifts. Doppler OCT can measure the absolute blood flow velocity based on the phase shift between consecutive axial scans and the beam incidence angle. The Doppler shift is proportional to the off-perpendicular angle between the OCT beam and the direction of blood flow. Unfortunately, for retinal OCT scanning, this angular offset is often close to zero. To overcome this limitation, researchers next turned to phase variance (rather than phase shift) as the flow signal.79 However, phase-based OCTA is very susceptible to corruption by phase noise due to bulk tissue motion and OCT system noise (especially swept-source output).10 There are several methods that compensate for phase noise, which largely rely on the statistical properties (e.g., the mean or histogram) of the flow signal distribution within an OCTA volume.912 While no method can completely remove phase noise, a recent approach that relies on using the standard deviation of flow values within a line scan can reliably and efficiently compensate for phase shifts.12
To avoid the difficulties with phase noise, most commercial OCTA systems are amplitude-based. While amplitude-based OCTA lose some flow sensitivity compared to phase measurements, it is sensitive enough to measure capillary. Because it is less susceptible to noise from tissue bulk motion and other sources of phase variation, amplitude-based OCT is more reliable and easier to implement.
Optovue, Heidelberg, and Topcon instruments all rely on amplitude-based motion contrast. But the exact algorithm differs. Heidelberg OCTA measures the temporal amplitude distribution within a given voxel in order to estimate the probability that it belongs to static tissue or a vessel.13 To achieve enough information to adequately sample, these amplitude distributions require 4–7 consecutive B-frames at each scan location.13 Optovue systems employ the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm that requires only two consecutive B-frames for compute a high-quality angiogram. Topcon instruments use a ratio analysis approach [termed “OCTA ratio analysis (OCTARA)”] in which the ratio between the minimum and maximum voxel value 4at two different time points is compared in order to construct the OCTA signal.14 This algorithm also requires at least four repeated B-scans to achieve adequate results.
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Figures 1A to D: Optical coherence tomography angiography (OCTA) signal generation. (A) Two sequential cross-sectional structural OCT scans (scan A and scan B) are generated by collecting data from a sample beam at a detector. (B) When the sample beam (red and blue arrows) encounters a blood vessel, flowing blood imparts a change in the reflectance signal between scan A and scan B. (C) On the other hand, when the sample beam encounters static tissue, the reflectance signal in scan A and scan B will be essentially identical. (D) By measuring the change between scan A and scan B, blood flow can be identified.
Complex-signal-based OCTA uses both the phase and amplitude components of the OCT signal. It is highly susceptible to phase noise like phase-based OCTA. The most prominent complex-signal-based OCTA generation algorithm is “optical microangiography” (OMAG). This algorithm uses frequency modulation in the interferogram in order to separate the static signal from the flow signal. The specifics of how this offset is achieved have changed as the technique improved over time.1518 OMAG requires adequate phase compensation in order to remove noise from bulk motion. Zeiss instruments use the ultrahigh sensitive OMAG algorithm,19 which has recently achieved high-quality angiographic images from just two repeated B-scans on 100-kHz swept-source OCT prototype (Figures 2A to F).20,21
 
SPECTRAL SPLITTING
Optical coherence tomography phase, amplitude, and complex signals can all be enhanced using spectral splitting, in which the OCT signal is processed separately in different frequency sub-bands and then averaged to produce the OCTA angiogram. Spectral splitting improves the flow detection signal-to-noise ratio (SNR) (and, consequently, downstream measurements such as vessel density or connectivity). The enhanced signal comes at the cost of reduced axial resolution, since each of the constituent frequency bands must be narrower than the full spectrum (which achieves optimal resolution). In ophthalmic imaging, this is not problematic since even at reduced axial resolution, spectrally split OCTA measurements can still unambiguously separate the vascular plexuses. Lowering axial resolution by spectral splitting reduces susceptibility to noise due to cardiac pulsation and other axial bulk motion, which further enhances the SNR of flow detection.
The first commercial OCTA instruments were developed by Optovue and made use of SSADA.22 SSADA is a purely amplitude-based OCTA processing algorithm, but research studies have made use of spectral splitting for phase- and complex-based processing as well.23 In each case, improvements in image SNR and contrast have been measured. Optovue instruments employing the SSADA algorithm require just two repeated B-scans in order to construct OCTA volumes.24 Due to this efficiency, recently SSADA has been able to achieve 12 × 12-mm field of view in a single scan (Figure 3) using the latest 120-kHz Solix system (Optovue, Inc.).
 
CONCLUSION
Optical coherence tomography angiography uses motion contrast to detect flow down to the capillary level. Flow signal is computed from the change in OCT reflectance between consecutive B-scans. Several different approaches can be used to compute the flow signal. The most efficient algorithms can obtain adequate flow SNR and image quality using only two consecutive B-scans at each location.5
zoom view
Figures 2A to F: Ultrahigh sensitive optical microangiography (OMAG) images of retinal vasculature at several scales compared to fundus photography. (A) A fundus photography image of a healthy retina. (B) A montaged OMAG en face image of the nerve fiber layer. (C) A superficial retinal slab shows the vascular network in the ganglion cell layer and outer plexiform layer. (D) Retinal slab corresponding to the deep vascular complex. (E) Image showing the vasculature in both (C) and (D), with vessels color-coded according to depth (red: superficial; green: intermediate; blue: deep). (F) Magnified image detailing the blue box in (E), along with a structural cross-section with flow overlaid at the position indicated by the dotted dashed line. Capillary details are clearly visible in the magnified version.Source: Reprinted with permission from Zhang Q, Lee CS, Chao J, et al. Wide-field optical coherence tomography based microangiography for retinal imaging. Sci Rep 2016; 6:22017.
zoom view
Figure 3: 12 × 12-mm, 600 × 600-pixel resolution image of a normal retina from a commercial instrument (Solix, Optovue, CA) employing SSADA OCTA processing. This efficient algorithm requires only two sequential scans to capture the detail shown here.
6
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