OCT and Imaging in Central Nervous System Diseases: The Eye as a Window to the Brain

The second edition of OCT and Imaging in Central Nervous System Diseases offers updated state-of-the-art advances using optical coherence tomography (OCT) regrading neuronal loss within the retina. Detailed information on the OCT imaging and interpretation is provided for the evaluation of disease progression in numerous neurodegenerative disorders and as a biological marker of neuroaxonal injury. Covering disorders like multiple sclerosis, Parkinson’s disease, Alzheimer’s disease, intracranial hypertension, Friedreich’s ataxia, schizophrenia, hereditary optic neuropathies, glaucoma, and amblyopia, readers will given insights into effects on the retina and the and optic nerve. Individual chapters are also devoted to OCT technique, new OCT technology in neuro-ophthalmology, OCT and pharmacological treatment, and the use of OCT in animal models.

Similar to the first edition, this book is an excellent and richly illustrated reference for diagnosis of many retinaldiseases and monitoring of surgical and medical treatment. OCT allows to study vision from of the retina to the optic tracts. Retinal axons in the retinal nerve fiber layer (RNFL) are non-myelinated until they penetrate the lamina cribrosa. Hence, the RNFL is an ideal structure for visualization of any process of neurodegeneration, neuroprotection, or regeneration. By documenting the ability of OCT to provide key information on CNS diseases, this book illustrates convincingly that the eye is indeed the “window to the brain”.

• Language: English
• Publisher: Springer
• Release date: Jan 1, 2020
• ISBN: 9783030262693

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© Springer Nature Switzerland AG 2020

A. Grzybowski, P. Barboni (eds.)OCT and Imaging in Central Nervous System Diseaseshttps://doi.org/10.1007/978-3-030-26269-3_1

1. Introduction: Retina Imaging—Past and Present

Andrzej Grzybowski¹, ²   and Piero Barboni³, ⁴  

(1)

University of Warmia and Mazury, Olsztyn, Poland

(2)

Institute for Research in Ophthalmology, Poznań, Poland

(3)

Studio Oculistico d’Azeglio, Bologna, Italy

(4)

Scientific Institute San Raffaele, Milan, Italy

Andrzej Grzybowski (Corresponding author)

Piero Barboni

Email: [e-mail]

Keywords

RetinaImagingHistory of ophthalmologyFundusOptical coherent tomographyCentral nervous systemNeuro-ophthalmologyNeuro-degenerationCNS disorders

The retina is a mysterious structure. The first use of the term comes, as to our present knowledge, from Herophilos (335–280 or 255 BC), Greek anatomist, one of founders of Greek school in Alexandria. He used two different words, arachnoeides and amfiblesteroides, for retina. For many years, both meanings were related to casting net, and retiform, a word which the modern retina is derived. However, as it was nicely shown recently, there might be another explanation of these original terms [1]. Amfiblesteroides meant at that time also anything that is thrown around and encircling walls. For many years it was believed, however, that the lens, not retina is the reception organ of the eye responsible for vision and there was even no agreement as to whether the eye emanated light (extramission theory) or received it (intromission theory) [2, 3]. Leonardo da Vinci (1452–1519) and Johannes Kepler (1571–1630) questioned the role of the lens in light reception. Felix Plater (1536–1614), attributed that role to the retina, what was further experimentally supported by Christopher Scheiner (1575–1650) who, by removing part of the sclera and choroids, was able to notice the reversed picture projected onto the bottom of the eye [3–6].

For the next two centuries, it was disputable weather retina or choroid was a precise structure responsible for vision reception [7]. This was finally settled by Herman von Helmholtz (1821–1894), who also constructed and popularized the first ophthalmoscope in 1851 [8]. This revolutionized the development of retinology.

The first visualization of the eye fundus of the living animal, however, was conducted by Jean Mery (1654–1718) in 1704. By plunging the head of a cat in water, Mery was able to observe the retinal vessels, the optic nerve head and the choroid (Fig. 1.1) [9]. This was later confirmed by Adolf Kussmaul in 1845 [10], Johann Nepomuk Czermak in 1851 [11] and Adolf Ernst Coccius in 1852, who introduced a water-box named orthoscope, to neutralize the corneal curvature [12, 13]. It was, however, Johannes Purkinje (1787–1869) in 1823 who described the basics of ophthalmoscopy based on his observations living animal and human eye [14]. One of the pioneers in the use of ophthalmoscopy for the diagnosis of central nervous system disorders was Xavier Galezowski (1832–1907), who published one of early textbooks on this subject and coined a term of cerebroscopy for this examination (Fig. 1.2) [15].

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Fig. 1.1

Extract from the Proceedings of the Royal Academy of Sciences for the year 1709—Session of 20th March 1709. By this diagram, La Hire explains the visualization of the fundus of the submerged cat by the fact that the surface of the water having abolished the corneal dioptric power, the rays coming out of the eye would no longer be parallel, but would diverge and that would make the eye fundus visible to the observer. Source: Heitz RF. Earliest Visualizations of the Living Eye’s Fundus by Immersion in Water. Archiwum Historii I Filozofii Medycyny 2012; 75: 11–15

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Fig. 1.2

Cover page of the book Etude ophtalmoscopique sur les altérations du nerf optique et les maladies cérébrales dont elles dépenden by Xavery Gałęzowski, Paris, 1866

The microscopical structure of the retina was described in the nineteenth century, and by the end of the twentieth century it was believed that its histological and functional characteristics was largely recognized. Then, the discovery of intrinsically photosensitive ganglion cells, a novel class of retinal photoreceptors, which express melanopsin, are sensitive to short-wavelength blue light and project throughout the brain, have presented a completely unknown area of retina-brain possible interactions [16, 17]. It is quite clear today that other cellular components of the retina, namely amacrine cells, bipolar cells and microglial cells, although somehow neglected in the past, play important functions both in physiology and pathology of the retina. For example, it was proposed that microglia are involved in the pathogenesis of several degenerative conditions of the retina, including glaucoma, age-related macular degeneration, and inherited photoreceptor degeneration [18]. Moreover, recently the evidence of retinal astrocytopathy in neuromyelitis optica spectrum disorder was provided [19].

One of the major developments in recent years in retinal imaging was the introduction of optical coherence tomography (OCT). OCT was firstly reported by Huang et al. in 1991 [20]. In vivo studies were first reported in 1993 [21, 22], and in 1995 imaging of the normal retina [23] and macular pathology [24] was presented. OCT delivers high-resolution cross-sectional or 3-dimensional images of the retinal and choroid structures, which are generated by an optical beam scanned across the retina (and choroid). OCT testing is quick, easy and noninvasive, and pupil dilation is typically not required. Moreover, OCT yields quantitative anatomical data and is related with low variation for repeated measurements, low intra-individual and inter-individual variation and low variability across different centers using the same device.

Retinal ganglion cells axons are nonmyelinated within the retina, thus retinal nerve fiber layer (RNFL) is an optimal structure to visualize the process of neurodegeneration, neuro-protection and neuro-repair [25]. Moreover, OCT enables evaluation of retinal ganglion cells (RGC). For example, it was reported in patients with MS a dropout of RGC in 79% of eyes and inner nuclear layer atrophy (including amacrine cells and bipolar cells) in 40% of eyes [26]. It was also argued that OCT might reveal RNFL abnormalities in many patients with no clinical symptoms [27].

Retina and optic nerve originates from diencephalon, thus are a part of central nervous system (CNS). RGC present the typical morphology of CNS neurons. Optic nerve, like all fiber tracts in CNS, is covered with myelin and is unsheathed in all three meningeal layers. Insult to the optic nerve, similar to CNS, lead to retrograde and anterograde degeneration of damaged axons [28]. Because of these many similarities, it has not been very surprising that many CNS diseases can be also detected on the retina level. They include multiple sclerosis, Alzheimer disease, Parkinson disease, and many others. Moreover, it was shown that there are some common degenerative mechanisms between Alzheimer disease and eye diseases, like glaucoma and age-related macular degeneration [29]. Thus, the aim of this book is to review all aspects of OCT retina studies in CNS diseases, and present some other novel and interesting techniques, including retinal amyloid imaging, retinal oximetry, and real-time imaging of single neuronal cell apoptosis.

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Daxecker F. Further studies by Christoph Scheiner concerning the optics of the eye. Doc Ophthalmol. 1994;86:153–61.

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Grzybowski A, Aydin P. Edme Mariotte (1620-1684): pioneer of neurophysiology. Surv Ophthalmol. 2007;52:443–51.

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Helmholtz HLFV. Beschreibung eines Augenspiegels zur Untersuchung der Netzhaut im lebenden Auge. Berlin: Forstner; 1851.

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Heitz RF. Earliest visualizations of the living eye’s fundus by immersion in water. Arch Hist Filoz Med. 2012;75:11–5.

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Kussmaul A. Die Farben-Erscheinungen im Grunde des menschlichen Auges. Heidelberg: Groos; 1845.

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Czermak JN. Ueber eine neue Methode zur genaueren Untersuchung des gesunden und kranken Auges. Vjschr prakt Heilk. 1851;8:154–65.

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Coccius AE. Ueber die Ernährungsweise der Hornhaut und die Serum führenden Gefässe im menschlichen Körper. Leipzig: Muller; 1852.

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Coccius AE. Ueber die Anwendung des Augen-Spiegels nebst Angabe eines neuen Instruments. Leipzig: Muller; 1853.

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Reese PD. The neglect of Purkinje’s technique of ophthalmoscopy prior to Helmholtz’s invention of the ophthalmoscope. Ophthalmology. 1986;93:1457–60.

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Gałęzowski X. Etude ophtalmoscopique sur les altérations du nerf optique et les maladies cérébrales dont elles dépendent. Paris: Librairie de L. Leclerc; 1866.

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Lucas RJ, Freedman MS, Munoz M, Garcia-Fernandez JM, Foster RG. Regulation of the mammalian pineal by non-rod, non-cone, ocular photoreceptors. Science. 1999;284:505–7.

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Schmidt TM, Chen SK, Hattar S. Intrinsically photosensitive retinal ganglion cells: many subtypes, diverse functions. Trends Neurosci. 2011;34:572–80.

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Silverman SM, Wong WT. Microglia in the retina: roles in development, maturity, and disease. Annu Rev Vis Sci. 2018;4:45–77.

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You Y, Zhu L, Zhang T, Shen T, Fontes A, Yiannikas C, Parratt J, Barton J, Schulz A, Gupta V, Barnett MH, Fraser CL, Gillies M, Graham SL, Klistorner A. Evidence of Müller glial dysfunction in patients with aquaporin-4 immunoglobulin G–positive neuromyelitis optica spectrum disorder. Ophthalmology. 2019; https://​doi.​org/​10.​1016/​j.​ophtha.​2019.​01.​016.

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Huang D, Swanson EZ, Lin CP, et al. Optical coherence tomography. Science. 1991;254:1178–81.

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Swanson EA, Izatt JA, Hee MR, et al. In vivo retinal imaging by optical coherence tomography. Opt Lett. 1993;18:1864–6.

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Fercher AF, Hitzenberger CK, Drexler W, et al. In vivo optical coherence tomography. Am J Ophthalmol. 1993;116:113–4.

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Hee MR, Puliafito CA, Wong C, et al. Optical coherence tomography of the human retina. Arch Ophthalmol. 1995;113:325–32.

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Puliafito CA, Hee MR, Lin CP, et al. Imaging of macular diseases with optical coherence tomography. Ophthalmology. 1995;102:217–29.

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Galetta KM, Calabresi PA, Frohman EM, Balcer LJ. Optical coherence tomography (OCT): imaging the visual. Pathway as a model for neurodegeneration. Neurotherapeutics. 2011;8:117–32.

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Green A, McQuaid S, Hauser SL, Allen IV, Lyness R. Ocular pathology in multiple sclerosis: retinal atrophy and inflammation irrespective of disease duration. Brain. 2010;133:1591–601.

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Cettomai D, Hiremath G, Ratchford J, et al. Associations between retinal nerve fiber layer abnormalities and optic nerve examination. Neurology. 2010;75:1318–25.

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© Springer Nature Switzerland AG 2020

A. Grzybowski, P. Barboni (eds.)OCT and Imaging in Central Nervous System Diseaseshttps://doi.org/10.1007/978-3-030-26269-3_2

2. OCT Technique: Past, Present and Future

Tigran Kostanyan¹, Maria de los Angeles Ramos-Cadena², Gadi Wollstein² and Joel S. Schuman²  

(1)

Department of Ophthalmology, University of Pittsburgh School of Medicine, UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Sciences Research Center, Pittsburgh, PA, USA

(2)

Department of Ophthalmology, NYU Langone Health, NewYork, NY, USA

Joel S. Schuman

Email: [e-mail]

Keywords

Time domain (TD-) OCTSpectral domain (SD-) OCTSwept source (SS-) OCTPolarization sensitive (PS-) OCTAdaptive optics (AO)OCT blood flowOCT angiography (OCTA)Visible light (Vis-) OCT

Abbreviations

2D

Two-dimensional

3D

Three-dimensional

AO

Adaptive optics

CCD

Charge-coupled device

EDI

Enhanced depth imaging

FD

Fourier domain

GCC

Ganglion cell complex

ILM

Internal limiting membrane

IPL

Inner plexiform layer

IS

Inner segment

LC

Lamina cribrosa

OCT

Optical coherence tomography

OCTA

Optical coherence tomography angiography

ONH

Optic nerve head

OS

Outer segment

PS

Polarization sensitive

RGC

Retinal ganglion cell

RNFL

Retinal nerve fiber layer

RPE

Retinal pigment epithelium

SD

Spectral domain

SS

Swept source

TD

Time-domain

Vis-OCT

Visible light optical coherence tomography

2.1 Introduction

Optical coherence tomography (OCT), first developed in the 1990s, is a diagnostic imaging technology that has gained a leading position in research and clinical practice due to its ability to obtain noncontact, in vivo, high-resolution, micron-scale images of tissue structures. OCT makes in situ imaging of tissue microstructure possible with a resolution approaching that of histology [1].

The technology uses the principle of low-coherence interferometry, which was originally applied to ophthalmology for in vivo measurements of the axial length of the eye [2].

At the time of introduction, the technology was used to acquire in vivo, cross-sectional images of the anterior segment [3], and retinal pathologies. Since then, OCT has evolved significantly, with improvements in both image acquisition methods and image analysis. The evolution of OCT began with the time domain (TD) technique, followed by spectral domain (SD) systems and later, newer iterations with faster acquisition speeds [4, 5] and improved axial resolution [6].

This chapter describes the basic principles of OCT techniques, its history, current status, major ophthalmic applications, and research that will determine the future of the technology.

2.2 Basic Principles

OCT provides cross-sectional and volumetric images of areas of interest by acquiring either the echo time delay or frequency information of back-reflected light. Differences in the optical properties of biological tissues allow the recognition of layered structures. The speed of light makes it impossible to analyze the acquired information directly, since it would be in the order of femtoseconds thus, OCT systems use the optical technique known as interferometry . Low-coherence interferometry enables the analysis of this information and the composition of a depth-resolved reflectivity profile (A-scan) of the scanned tissue by matching the light profiles from the scanning and reference arms.

Utilization of light provides OCT technology the ability to obtain images in a non-contact fashion and to achieve resolutions of 1–15 μm, which is 1–2 orders of magnitude finer than other conventional clinical imaging technologies such as ultrasound, computerized tomography, or magnetic resonance. Light is highly absorbed or scattered in most biological tissues, therefore the use of this technology is limited only to locations that are optically accessible or that can be imaged using devices such as endoscopes or catheters. The eye is the most optically accessible organ of the human body since the anterior and posterior segments can be visualized and imaged [7].

The key parameters that are typically used to characterize OCT technology are the wavelength of the light source, axial and transverse resolution, scanning speed, and imaging depth.

Axial resolution determines the smallest distance along the axial direction where two adjacent points are discernable, and it is inversely related to the bandwidth of the light source. Current commercial OCT devices achieve axial resolutions up to 4 μm, and research systems can achieve up to ~1 μm [8]. The penetration depth (in the axial direction) is approximately 2 mm in the various OCT iterations with the exception of Visible-light OCT that does not penetrate beyond the RPE layer.

Transverse resolution is determined by the spot size projected into the eye, which is limited by the optical properties of the eye. As such, the transverse resolution of OCT ranges between 15–20 μm among the different generations of the technology. Improving transverse resolution requires the correction of the optical aberrations of the eye using technologies such as adaptive optics.

Scanning speed is dictated by mechanical constrains and the sensitivity of the detector to the back-reflected light. As scanning speed increases, the time the detector remains in the same location is shorter, thus reducing the light that can be detected in each location. Since the power of the projected light is limited in order to be within safety limits, faster scans require a more sensitive detector that can function with a lower level of light.

The achievable imaging depth is related to the central wavelength of the light source, with longer wavelengths providing increased imaging depth [9, 10]. However, longer wavelengths are limited by the increased optical absorption of water [11].

Currently available OCT techniques are based on several iterations of the technology: spectral-domain (SD ; also known as Fourier or frequency domain), swept-source (SS), and visible-light (Vis-OCT). The earliest iteration of the technology, time-domain (TD), is no longer manufactured for ophthalmic use and therefore will not be discussed.

SD-OCT uses a broad-bandwidth, low-coherence superluminescent diode laser light that is divided into two arms by a partially reflecting mirror (beam splitter). In the first arm light is projected toward the sampling location, while in the second arm light is projected toward a reference mirror. The backscattered light from both arms travels back to a spectrometer and recombines to form an interference pattern. Light frequency information is analyzed by Fourier transformation to encode distances within tissue microstructure [12]. SD technology allows the acquisition of information from all points along each axial scan (A-scan) simultaneously at a scanning speed of ~25,000–100,000 A-scans/s [13, 14] and up to 20 million A-scans/s in research devices [5]. A cross-sectional image, also known as a B-scan, is generated by performing fast, subsequent A-scans at different transverse positions. Combining rapidly acquired subsequent cross-sectional scans allows the creation of three-dimensional (3D) datasets, enabling advanced post-processing analysis. The wide bandwidth of the SD-OCT light source also facilitates an axial resolution of 3–6 μm in commercially available systems and up to 1 μm in research systems [15, 16].

SS-OCT uses a tunable laser light source that sweeps through different frequencies in rapid succession to cover the entire broad spectrum. The reflectance of the light from the scanned area is captured by a photodetector, which allows a substantially faster acquisition rate (up to 400,000 A-scans/s) than the spectrometry of SD-OCT [4, 17]. Another important advantage of SS-OCT is an improved signal-to-noise ratio and reduction in the depth dependent signal drop-off observed with SD-OCT technology [18]. Most SS-OCT devices operate with light sources centered at around 1050 nm (compared with 840 nm in the commercially available SD-OCT devices), which reduces the axial resolution to approximately 8 μm but allows for better penetration into the tissue. This combination of improved tissue penetration and reduced signal attenuation allows detailed scanning of structures such as the choroid and the lamina cribrosa (LC) within the ONH.

Vis-OCT. Unlike other OCT iterations that use near infrared light sources (~800 and 1000 nm), Vis-OCT utilizes a light source with a shorter center wavelength of ~550 nm resulting in an improved axial resolution of <1 μm but with reduced achievable imaging depth [19, 20]. Using spectroscopic analysis, it is possible to quantify chromophore concentration from Vis-OCT images [19]. Retinal oximetry is one of its first applications, providing objective, functional information about retinal vasculature. Light absorbance for oxygenated and de-oxygenated hemoglobin peaks in separate wavelengths, both of which are within the spectrum of Vis-OCT. Tissue oxygen consumption can be determined by extracting the venous de-oxygenated level from the arterial oxygenated level. The oximetry information can be aligned to the structural location observed in the same images, opening a new venue for global and local functional assessment.

The major characteristics of these 3 different OCT techniques are presented in Table 2.1.

Table 2.1

Comparison of SD-OCT, SS-OCT, and Vis-OCT technologies

2.3 The Past

OCT technology was first described by Huang and colleagues in 1991 [21]. The authors scanned human retinas and atherosclerotic plaques ex vivo with a prototype device using infrared light at a ~800 nm wavelength. The axial resolution of cross-sectional images of the retina, optic nerve, and coronary artery wall was 15 μm, which allowed the visualization of some retinal layers, optic nerve head structures, and the composition of the coronary artery. In vivo retinal scanning was conducted using a prototype device based on a slit-lamp biomicroscope that was modified to provide a view of the fundus while scanning with OCT. The development of scan patterns that enabled the acquisition of reproducible measurements [22] led to the use of the technology in clinical practice. The first commercially available OCT, called OCT 1000, was marketed in 1996 by Zeiss (Dublin, CA). The technology went through 2 iterations, resulting in OCT 2000 in the year 2000 and then OCT 3 (Stratus), which became commercially available in 2002. Stratus OCT had an axial resolution of ~10 μm, a transverse resolution of 20 μm, and a scan speed of 400 A-scans/s [1, 23]. The typical cross-sectional scan was composed of 128–512 A-scans, comprising an image area of 4–6 mm.

Due to its ability to obtain quantitative and reproducible measurements of the macula [24, 25], retinal nerve fiber layer thickness [22, 26], and optic nerve head [27], OCT became the gold standard clinical imaging device for posterior segment pathologies in a relatively short period of time.

Early iterations of OCT had a relatively slow acquisition rate, and therefore the conventional scan patterns were comprised of 6 radial scans through the macula (6 mm diameter) or optic nerve (4 mm) with a circular 3.4 mm diameter scan centered on the ONH. Using automated segmentation, the total macular thickness (internal limiting membrane (ILM) to the photoreceptor inner segment-outer segment (IS–OS) junction), retinal nerve fiber layer (RNFL) thickness, and ONH structures were automatically quantified.

The introduction of SD-OCT added a dramatic increase in scanning speed and substantially extended the clinical utility of OCT. The faster scanning speed enabled new scanning patterns such as raster scans, where volumetric data is constructed with a rapidly acquired succession of adjacent B-scans. A 3D dataset allows a thorough sampling of the scanned region, advanced post-processing, and improved registration of consecutive scans. Another commonly used approach is the averaging of consecutive scans acquired at the same location that result in improved image quality.

The majority of commercial OCT systems applied SD technology for posterior eye imaging and visualization of the cross-sectional structures of the retina and optic disc [1] (Fig. 2.1). OCT has been used extensively in the diagnosis and management of a wide range of ocular pathologies including glaucoma, age-related macular degeneration, macular edema, macular holes, diabetic retinopathy, alterations in the vitreoretinal interface, papilledema, and others. In addition to acquiring tissue structural information, OCT has been incorporated into multimodal imaging systems that provide further insight into the functional characteristics of tissue [28–30].

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Fig. 2.1

OCT c ross-sectional image of a healthy optic disc (a) and a 3D volumetric scan (b)

OCT has become a key ophthalmic diagnostic imaging tool due to its ability to provide information about tissue microstructure. Over the years, it has continuously evolved with improved visualization, new retinal imaging locations, increased reliability, and enhanced longitudinal analysis.

2.4 The Present

Since the advent of OCT, 25 years ago, countless improvements have been implemented in an effort to acquire quantitative data with high reliability and sensitivity for precise evaluation of the structure and function of ocular structures.

2.4.1 Spectral-Domain OCT

Since the first FDA-approved SD-OCT became available in 2006, numerous improvements have enriched the capabilities of OCT. One application of advanced processing is the OCT enface image generated by integrating the information from all A-scans into an image of the surface of the retina [31]. The enface image is identical to the retinal fundus view and it can be used for subjective assessment of image quality and eye motion detection, comparison with clinical findings, and further focus on specific location within the region of interest.

Various scan patterns are available for ONH imaging from the different commercially available SD-OCT devices. This includes raster (also known as 3D or volumetric) scans, radial scans, circular scans, and a combination of radial and concentric scans. All of the devices can automatically detect the optic disc boundary as the location at which the photoreceptor layer, retinal pigment epithelium (RPE), and choriocapillaries terminate. The machine provides quantification of ONH structures such as the disc area, cup-to-disc ratio, and others along with the circumpapillary RNFL thickness measurement reported as global, quadrant, and sectoral thicknesses. Evaluation of the ONH provides important clinical information in multiple ocular and central nervous system pathologies like glaucoma and papilledema.

One of the most useful measurements provided by OCT is the circumpapillary RNFL thickness. Because the axons from the retinal ganglion cells gather to form the optic nerve, a circular scan around the ONH allows sampling of the axons from the entire retina. The limitation of this approach is that the sampling of the tissue is performed only along the circle, therefore any misplacement of the circle during consecutive scanning will result in increased measurement variability [32]. Another option is to extract the RNFL thickness from the raster scan pattern. This method can ensure that the tissue sampling location is consistent through multiple scans, as the repositioning of the circle is possible if needed during post-processing. Several devices also report the RNFL thickness as a color-coded thickness map of the peripapillary region. This map provides additive information to the circumpapillary RNFL thickness measurement, as it can highlight small, localized thinning or defects outside the circumpapillary sampling location. Furthermore, in many devices, the RNFL thickness is compared to population-derived normative data to highlight locations deviating from normal.

Figure 2.2A shows a Cirrus HD-OCT (Zeiss, Dublin, CA) ONH scan printout that provides the RNFL thickness map (a) and cross-section (c). The deviation map (b) compares the RNFL measurements at each superpixel with an age-matched normative database, and locations thinner than the lowest 95% of the normal range are highlighted. In the center panel, quantitative parameters are provided for ONH structures, along with RNFL thickness presented as a thickness profile around the ONH, in quadrants and in clock hours. The background coloring reflects the comparison with the normative database, with green representing the normal range, yellow representing <5% of the normal population, and red representing <1% of the normal population. The right eye shows an example of eye within the normal limits while the left eye shows a glaucomatous eye with thin average RNFL, superior, inferior, and temporal thin RNFL, enlarged cup-to-disc ratio and an inferior notch. OptoVue Avanti (Optovue, Redmont, CA) peripapillary scan (Fig. 2.2B) is created from 13 circular scans with diameters of 1.3–4.9 mm centered on the ONH. Comparison with a normative database is performed in 16 sectors and presented as the deviation map that surrounds the RNFL thickness map. Figure 2.2C shows the circumpapillary RNFL scans obtained with the Spectralis OCT (Heidelberg Engineering, Heidelberg, Germany). A retinal cross section image with delineation of RNFL boundaries is shown in (a). Note the visualization of fine details that is accomplished by averaging repetitive scans acquired in the same location while engaging eye motion tracking systems to reduce motion artifacts. Thickness measurements and color-coded comparison with normative data are presented for global average thickness, quadrants, and in six sectors (b).

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Fig. 2.2

SD-OCT optic nerve head and retinal nerve fiber layer analysis, (A) Cirrus, (B) Avanti, and (C) Spectralis OCT

The improvements introduced in SD-OCT also have a substantial impact on macular imaging. Thorough sampling of the macula, the improved visualization of the retina and choroid, and the ability to automatically segment the various layers of the retina substantially impacted clinical management. The scan patterns that are often used to image the macula include line, cross-line, raster, mesh, and radial scan patterns. Line scans are typically composed from the averaging of multiple scans at the same location. This is typically performed at a single linear location (Fig. 2.3A) or along several parallel lines (Fig. 2.3B). Line scans are clinically useful for obtaining retinal images with the highest level of detail. The principle of the volumetric cube scan is similar to the 3D ONH scan patterns described above. Volumetric macular scans are very helpful in clinical management of macular pathologies, such as macular edema, age related macular degeneration, and macular holes.

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Fig. 2.3

(A) Line scans of the macular region obtained with Spectralis OCT from a healthy eye (a), an eye with vitreomacular traction (b), and wet age-related macular degeneration (c). (B) Macular five-line raster scan of a healthy eye obtained with Cirrus HD-OCT

Some SD-OCT systems are capable of acquiring scans in horizontal and vertical orientations to provide a mesh scan pattern. The logic behind this scan pattern is that even at a fast scanning rate there is a relatively long temporal gap between adjacent points that are perpendicular to the scan orientation. For example, in a horizontal raster scan, the time gap between adjacent points in the horizontal direction is much shorter than the gap between adjacent points vertically. This can lead to image distortion along the slow axis of the scan. Registering the horizontal and vertical scans together can reduce the distortion in the slow axis and improve scan quality. Figure 2.4 shows the macula thickness map acquired by a retina map scanning pattern (left side of the report) with the correspondent cross-sectional image (right side of the report) obtained with Optovue Avanti (Optovue, Redmont, CA). The pattern consists of an inner, dense grid and outer grid, visible as white grid lines.

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Fig. 2.4

Macular thickness with a retina map scanning pattern obtained with Optovue Avanti

Radial scan protocols acquire multiple evenly spaced linear scans that intersect at the fovea. This pattern provides information from the entire macular region, with dense coverage near the fovea where the lines intersect and sparse coverage at the macula periphery. Figure 2.5 demonstrates a radial scanning pattern of the macula from two different healthy subjects using different commercial SD-OCT systems.

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Fig. 2.5

Macular radial scanning pattern obtained with Spectralis OCT (a) and RTVue Premier (b)

The high resolution of SD-OCT enables automated segmentation and the analysis of individual macular layers that are of particular diagnostic interest in many ocular diseases including glaucoma and diabetic retinopathy [33–35]. Cirrus HD-OCT extracts the information from an ellipse (vertical radius of 2 mm, horizontal radius of 2.4 mm) centered on the fovea and provides a combined measurement of the retinal ganglion cell (RGC) layer and the inner plexiform layer (IPL), called the ganglion cell inner plexiform layer (GCIPL) analysis (Fig. 2.6). The macula protocol of RTVue Premier provides the ganglion cell complex (GCC), which includes the macular nerve fiber layer, RGC layer, and IPL. The data is captured from a 7 mm² area centered 1 mm temporal to the fovea.

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Fig. 2.6

Cirrus HD-OCT ganglion cell analysis (a) and RTVue Premier GCC analysis (b)

2.4.2 Retinal and Macular Guided Progression Analysis

The ability of OCT to provide highly reproducible, quantitative, micron-scale measurements is useful in tracking small structural changes that occur over time due to disease deterioration. Several commercial SD-OCT devices include a progression analysis tool. Automatic progression algorithms utilize trend-based analysis methods, primarily linear regression analysis, for computing the rate of change in structural parameters over time. The computed rate is compared to a no-change slope to determine if the rate is statistically significant. This rate of change is also used to predict future progression beyond the most recent visit. This prediction can be useful when discussing disease forecast with a patient or to assess the effect of treatment modification. Several commercial devices also provide event-based analysis, where a series of follow-up measurements are compared with baseline measurements and progression is defined as measurements changing by exceeding a predetermined threshold from baseline.

It has been described that the peripapillary and macular regions are both capable of detecting glaucoma progression. Glaucoma progression identification has only moderate agreement when looking at these two retinal locations, and different causal theories have been suggested, such as varying dynamic ranges of thickness measurements and minimal measurable thickness (floor effect) with different residual thickness composition (i.e., blood vessels and glial cells), or because one region is affected prior to the other [36–38] .

Figure 2.7 shows the Cirrus HD-OCT guided progression analysis (GPA) for RNFL (A) and GCIPL (B). It provides RNFL and GCIPL event and trend analyses showing a visual display of the location of structural change. In event analysis (a), baseline values are obtained by averaging the data from the first two exams. At least 20 adjacent superpixels must be flagged in the RNFL or GCIPL thickness change maps for a change to be classified as significant. If the difference from baseline is confirmed to be outside the range of test-retest variability, it is classified as possible loss and is color-coded in yellow; if the change is confirmed in the subsequent follow-up examination it is classified as likely loss and is marked in red. Trend analysis (b) evaluates the rate of change over time using linear regression in the GCIPL, RNFL, and ONH parameters (rim area, average cup-to-disc ratio, vertical cup-to-disc ratio, and cup volume) .

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Fig. 2.7

RNFL (A) and GCIPL (B) guided progression analysis

Lately, it was described that macular (GCIPL average, superior, and inferior) and ONH parameters (rim area, cup volume, and cup-to-disc ratio) are sensitive biomarkers to detect glaucoma progression, even in eyes with structural glaucomatous damage, that have reached the floor effect level of RNFL OCT parameters [39] .

2.4.3 Swept Source OCT

At the time of this writing, several SS-OCT devices have been recently approved for use in the USA and worldwide. The major advantages of this OCT iteration compared to earlier ones are the faster scanning speed, deeper penetration into the tissue, and reduced signal attenuation within the scanned window. The counter-effect is a reduced resolution. These properties improve visualization of choroid, sclera, and retinal sub-RPE pathologies such as central serous chorioretinopathy, AMD, choroidal tumors, and retinitis pigmentosa [40, 41]. Examination of the LC and posterior sclera will improve the understanding of the mechanical aspects of glaucoma pathogenesis. Significant differences were documented in the 3D LC microstructure between healthy and glaucomatous eyes [42, 43] as well as a more tortuous pathway of the pores in glaucomatous eyes as a potential mechanism for axonal flow obstruction and subsequent damage [44] (Figs. 2.8, 2.9, and 2.10).

../images/324960_2_En_2_Chapter/324960_2_En_2_Fig8_HTML.jpg

Fig. 2.8

SS-OCT cross section where retinal layers (red arrows), lamina cribrosa (yellow arrows), and choroidal vessels (blue arrows) are all captured in the same scan because this technology is less prone to signal drop-off in comparison with other OCT iterations

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Fig. 2.9

Upper panel demonstrates enface images of SS-OCT of choriocapillaries (a) and the large vessels of the choroid (b). Bottom panel shows the corresponding cross-sectional scans with the turquoise lines marking the plane where the enface image was acquired

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Fig. 2.10

Swept-source OCT cross-section image of the optic nerve head region (a). Enface image at the lamina cribrosa level demonstrating the intricate structure of the hyper-reflective beams (white) and hypo-reflective pores (black) (b)

2.4.4 Optical Coherence Tomography Angiography (OCTA)

OCTA is an in-vivo, non-invasive, dye-free OCT-based imaging of the blood vessels that provides volumetric vascular analysis [45]. Multiple sequential B-scans are acquired in rapid succession and then compared [41]. The dynamic motion of red blood cells from one image to the other causes a decorrelation signal which is detected by the machine to generate three-dimensional angiograms of the retinal, ONH and choroidal vasculature [41, 45]. It should be noted that this method only provides the anatomical location of blood vessels with flow within a predefined range. Vessels with fast or slow flow outside of this range will not be detected. Furthermore, the device does not report the actual flow within the vessels. The device provides the visualization of blood vessel networks and quantitative analysis of the blood vessel density in the scanned region. OCTA can be performed using both SD-OCT and SS-OCT technologies. At the time of this writing, a few different OCTA are commercially available.

Figure 2.11 shows the SD-OCTA Angioplex report of both ONH and macula angiography scans. The report includes the enface angiography images at different depths on the left, the superficial vascular network and cross-sectional scan overlaid with the location of detected vessels in the middle, and the vessel density analysis by region in the inferior right corner.

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Fig. 2.11

Angioplex angiography with the 3 × 3 ONH (a) and 6 × 6 macula (b) report

Figure 2.12 shows the ONH SS-OCT Triton angiography report. The top row of the report shows the angiography analysis in different depths starting with the innermost section closest to the ILM (labeled as the nerve head), followed by an intermediary depth (vitreous), then the analysis at the level of retinal photoreceptor cells (RPC), and ending closest to the choroid (choroid disc). The inferior row shows on the left a cross-sectional image of the optic nerve and in the middle a color-coded vessel density map.

../images/324960_2_En_2_Chapter/324960_2_En_2_Fig12_HTML.jpg

Fig. 2.12

Triton ONH angiography report

2.5 Doppler Optical Coherence Tomography

This technique allow determining arterial and venous blood flow through spectral-domain and swept-source based Doppler OCT [46]. Based on the Doppler shift detected in the OCT signal, this method can determine depth-resolved retinal vessels flow without the use if dye [47]. However, notable drawback of this method are that it cannot detect flow if the vessels are perpendicular to the incident OCT beam or in smaller size vessels [48]. While Doppler OCT retinal blood flow measurements showed good repeatability and excellent correlation with clinical presentations of retinal diseases, the role of this technique in disease detection and monitoring is yet to be determined [48].

2.6 The Future

As technology keeps evolving, several innovative OCT technologies are being tested. The following sections will provide a brief description of some of the most promising developments.

2.7 Adaptive Optics

Adaptive optics (AO) is an optical method designed to dynamically adjust monochromatic aberrations in optical systems. AO was initially used in astronomy for correcting distortions of light passing through the atmosphere. The first in vivo examination of the retina with an AO fundus camera using a wave front sensor and a deformable mirror was introduced in 1997 [49]. A few years later, AO was combined with scanning laser ophthalmoscope [50] and OCT systems [51]. As discussed above, the transverse resolution of all conventional OCT systems is limited to the range of 15–20 μm due to the optical aberrations of light beams when passing through various media in the eye. AO measures and corrects the optical aberrations, reduces the projected spot size, and improves the transverse resolution from 20 μm to the range of 5–10 μm [51]. This resolution allows the acquisition of highly detailed images, enabling the visualization of fine details such as the retinal microvasculature, photoreceptor mosaic [52], LC, and microstructures within the RNFL [6, 53] and ganglion cell layer. The ability to acquire highly detailed in vivo images of these structures allow further insight into ocular anatomy in health and disease, providing the opportunity to expand the understanding of pathologic processes in the eye.

The major limitation of the AO technique is the small field of view, which is restricted to approximately 1°–3°. The use of an eye-tracking system to acquire a series of neighboring scans to cover a larger volume can resolve this limitation, though the longer scanning time might prohibit large scale clinical use [54]. Similarly, the focusing depth of the AO technique is also limited, and therefore acquiring high quality images of thick structures such as the choroid and retina in the same image is difficult to obtain. It may be possible to address this limitation by varying the focal plane while scanning in depth [55]. The volume of data, needed for image processing, and advanced analysis requirements are also a limiting factors for commercialization of the technology. Datasets are 100 times larger than the conventional OCT counterparts, and therefore storage and accessibility of the information are challenging [56].

2.8 Visible-Light OCT

Switching to light sources in the visible light wavelength (~550 nm), instead of near infrared wavelengths, allows further improvement in axial resolution to the level of <1 μm and the extraction of spectroscopic information that is registered to the structural information. The higher scattering coefficients of biological tissue with visible light improves imaging contrast, but at the expense of reduced imaging depth (Fig. 2.13) [19]. Speckle noise reduction techniques can be applied to reduce background noise level and further improve image quality.

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Fig. 2.13

Macula scan of the same subject with Vis-OCT with speckle reduction (a) Cirrus OCT (b), and Spectralis OCT (c). Note the improved visualization with the Vis-OCT and the distinct interface between retinal layers without the need of averaging of multiple images

The evaluation of oxygen saturation through spectroscopy analysis is one of the most promising applications of the Vis-OCT system [19]. By taking advantage of the distinct light absorption of oxygenated and de-oxygenated hemoglobin within the visible spectral range it is possible to determine the oxygen consumption of tissue in a given region [20]. The role of oxygen saturation and consumption by the ocular tissue for diagnosing and monitoring various ophthalmic disease is currently being examined. Other chromatophores indicating metabolic and biochemical tissue activity are also being initially evaluated.

2.9 Polarization Sensitive OCT

Polarization sensitive OCT (PS-OCT) uses the polarization state of polarized light for the assessment of tissue function. Different ocular structures and tissues alter the polarization state of light in different ways, such as through birefringence (sclera, RNFL), polarization-preservation (photoreceptors), and depolarization (RPE) (Fig. 2.14). PS-OCT estimates these light state alterations by simultaneously measuring intensity, retardation, and optic axis information, thus providing both tissue structural and functional information. The technology was initially incorporated into TD-OCT system, with subsequent introduction into all known OCT iterations such as SD-OCT [57], SS-OCT [30], and AO-OCT [58]. A few studies demonstrated that alteration in the polarization of ocular tissues might precede the occurrence of structural alteration, thus evaluation of the functional properties of the RNFL [59], sclera, and RPE [60] using PS-OCT technology could be an attractive candidate for improving the detection of ocular pathologies such as glaucoma and age-related macular degeneration.

../images/324960_2_En_2_Chapter/324960_2_En_2_Fig14_HTML.jpg

Fig. 2.14

PS-OCT optic nerve head and retinal imaging in healthy subjects. (a) A cross-sectional intensity image with two depth-encoded copies of the optic nerve head region. (b) Corresponding PS-OCT image shows high retardance in the RNFL and sclera. (c) OCT fundus image. (d) Corresponding PS-OCT map shows high retardance around the optic nerve head region. (e) A cross-sectional intensity image at the fovea region. (f) Corresponding PS-OCT image shows low retardance in the retinal layers

2.10 Phase Sensitive OCT

The Phase Sensitive OCT technique is able to provide in vivo information on micron scale movements or vibrations within the tissue [61]. The technology analyzes the phase information of the back-reflected light beam, which is typically ignored in conventional OCT systems. OCT phase imaging has been demonstrated with SD-OCT [62] and SS-OCT [63] technologies. Phase sensitive OCT offers the advantage of simultaneously assessing both the structural and functional information of the scanned tissue. The device has been shown to capture the retinal pigment epithelium layer, Henle’s loop of the macula and retinal nerve fiber layer [64–67]. PS-OCT might be clinically useful in the context of glaucoma, AMD and potentially multiple sclerosis [64, 66, 68], but the clinical application is challenging because it is very sensitive to eye motion.

In conclusion, OCT has an important clinical role in the diagnosis of ocular diseases and in tracking changes overtime, leading to improved clinical management and better insight into pathophysiology of diseases. The constant enhancement of this technology ensures that clinicians will have an indispensable diagnostic tool in their armament.

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© Springer Nature Switzerland AG 2020

A. Grzybowski, P. Barboni (eds.)OCT and Imaging in Central Nervous System Diseaseshttps://doi.org/10.1007/978-3-030-26269-3_3

3. The APOSTEL Recommendations

Aykut Aytulun¹  , Andrés Cruz-Herranz²  , Lisanne Balk³  , Alexander U. Brandt⁴, ⁵, ⁶, ⁷, ⁸, ⁹   and Philipp Albrecht¹  

(1)

Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

(2)

Department of Neurology, University of California, San Francisco, CA, USA

(3)

Departments of Neurology and Ophthalmology, VU University Medical Centre, Amsterdam, The Netherlands

(4)

NeuroCure Clinical Research Center, Berlin, Germany

(5)

Charité-Universitätsmedizin Berlin, Berlin, Germany

(6)

Freie Universität Berlin, Berlin, Germany

(7)

Humboldt-Universität zu Berlin, Berlin, Germany

(8)

Berlin Institute of Health, Berlin, Germany

(9)

Department of Neurology, University of California, Irvine, CA, USA

Aykut Aytulun

Email: [e-mail]

Andrés Cruz-Herranz

Email: [e-mail]

Lisanne Balk

Email: [e-mail]

Alexander U. Brandt

Email: [e-mail]

Philipp Albrecht (Corresponding author)

Email: [e-mail]

Keywords

Reporting recommendationsQuantitative OCT studiesNeurodegenerationStandardizationQuality assurance

As the number of quantitative OCT studies rapidly increases, there is an obvious need for standardization on how these studies should be performed and reported. Important steps for standardization were the development of quality control criteria and of a consensus on the nomenclature of retinal structures accessible to OCT imaging. The OSCAR-IB Consensus Criteria for Retinal OCT Quality Assessment [1] were developed to validate the accuracy and quality of peripapillary ring scans assessing the retinal nerve fiber layer (RNFL) in multiple sclerosis (MS). The majority of these criteria not only apply to imaging of the peripapillary RNFL in MS but can also be used to rate e.g. macular scans or be applied in other conditions associated with quantitative changes of retinal layers (e.g. neurodegenerative disorders). The International Nomenclature for Optical Coherence Tomography (INOCT) Panel has proposed a consensus nomenclature for the classification of retinal and choroidal layers and bands visible on spectral-domain optical coherence tomography (SD-OCT) images of a normal eye [2].

However, despite these recommendations, imprecise reporting of quantitative OCT studies has sometimes led to uncertainty about methodological aspects, such as scan protocols, analysis software, the use of quality control criteria and inclusion or exclusion of patients and/or eyes. This impacts the interpretability and generalizability of these reports. Therefore, a panel of experts from the International MS Visual (IMSVISUAL) consortium convened at two international meetings in 2015 to develop the Advised Protocol for OCT Study Terminology and Elements recommendations (APOSTEL recommendations). These recommendations include a checklist of nine items of particular relevance when reporting quantitative OCT studies.

In the following, a short overview of the nine items is provided:

3.1 Describe the Study Protocol

The study design should be reported in line with the applicable guidelines STROBE, CONSORT or CARE [3]. Additionally, for OCT studies, authors should define if inclusion and exclusion criteria were applied at the eye or patient level and if/how confounding ocular pathologies, e.g. as listed in the OSCAR-IB criteria [1], were ruled out. Reporting the history of and time span from events of particular relevance for the OCT outcomes at study, i.e. optic neuritis (ON) in neuroinflammatory diseases or first symptoms in Leber’s hereditary optic neuropathy, is of major importance.

3.2 State the Acquisition Device Type, Name and Version

As OCT technology is continuously evolving, it is important to provide not only the specifications of the devices used (manufacturer, model, interferometric technique) but also the exact version of the software used for the acquisition.

3.3 Define the Acquisition Setting

The exact conditions, under which and how OCT measurements were performed, should be reported, including the use of methods to facilitate imaging such as the use of device-specific control for movement artifacts or pupil dilation.

3.4 Define the OCT Scanning Protocol

It is essential to report the target structures imaged and the exact acquisition parameters of the full measurement protocol, including a detailed description of all scan types employed in a study.

3.5 Define Fundoscopic Imaging

In case additional fundus imaging modalities such as confocal scanning laser ophthalmoscopy (cSLO), retinal angiography and auto-fluorescence imaging are reported, these should be described. Likewise, the acquisition protocol, including the excitation wavelength, filter sets and the number of frames averaged (if applicable), should be indicated.

3.6 Describe Post-acquisition Data Selection

A crucial point of all studies is the quality of the scans, which can have a major impact on the results and their interpretation. If strategies to select or exclude scans from analyses were applied, these should be described in detail. In order to ensure a high quality of scans and interpretability of the results, the use of quality control criteria is recommended. For example, an extensive set of quality control criteria has been published in the form of the OSCAR-IB criteria [1, 4].

3.7 Describe Post-acquisition Data Analysis

Authors should precisely report how the post-processing analysis (e.g. intraretinal layer