Meshi A, Goldenberg D, Armarnik S, Segal O, Geffen N. Systematic review of macular ganglion cell complex analysis using spectral domain optical coherence tomography for glaucoma assessment. World J Ophthalmol 2015; 5(2): 86-98 [DOI: 10.5318/wjo.v5.i2.86]
Corresponding Author of This Article
Noa Geffen, MD, Glaucoma Consultant, Department of Ophthalmology, Meir Medical Center, 59 Tschernihovsky St., Kfar Saba 4428164, Israel. firstname.lastname@example.org
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Ophthalmol. May 12, 2015; 5(2): 86-98 Published online May 12, 2015. doi: 10.5318/wjo.v5.i2.86
Systematic review of macular ganglion cell complex analysis using spectral domain optical coherence tomography for glaucoma assessment
Amit Meshi, Dafna Goldenberg, Sharon Armarnik, Ori Segal, Noa Geffen
Amit Meshi, Sharon Armarnik, Ori Segal, Noa Geffen, Department of Ophthalmology, Meir Medical Center, Kfar Saba 4428164, Israel
Amit Meshi, Sharon Armarnik, Ori Segal, Noa Geffen, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6423906, Israel
Dafna Goldenberg, Department of Ophthalmology, Tel Aviv Medical Center, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6423906, Israel
ORCID number: $[AuthorORCIDs]
Author contributions: Meshi A and Geffen N contributed equally to this work; each one substantially contributed to study design and to writing, to acquisition, analysis and interpretation of the data and performed critical revisions; Goldenberg D participated in the acquisition of the data and in writing, contributed significantly to the analysis of the technical data and performed critical revisions; Armarnik S participated in the acquisition of the data, in writing and approved the final version of the article to be published; Segal O performed critical revision and participated in the acquisition of the data; all authors approved the final version of the article.
Conflict-of-interest: All authors have no conflict of interest related to this work.
Data sharing: No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Noa Geffen, MD, Glaucoma Consultant, Department of Ophthalmology, Meir Medical Center, 59 Tschernihovsky St., Kfar Saba 4428164, Israel. email@example.com
Telephone: +972-54-2211710 Fax: +972-77-5610362
Received: August 15, 2014 Peer-review started: August 17, 2014 First decision: October 14, 2014 Revised: February 9, 2015 Accepted: April 1, 2015 Article in press: April 7, 2015 Published online: May 12, 2015
AIM: To review the use of spectral domain optical coherence tomography (SD-OCT) for macular retinal ganglion cells (RGC) and ganglion cell complex (GCC) measurement in glaucoma assessment, specifically for early detection and detection of disease progression.
METHODS: A systematic review was performed by searching PubMed, Medline, and Web of Science for articles published in English through July 2014 describing the various macular SD-OCT scanning strategies developed for glaucoma assessment. The review focused on papers evaluating the use of macular RGC/GCC SD-OCT to detect early glaucoma and its progression. The search included keywords corresponding to the index test (macular ganglion cell/RGC/GCC/Spectral domain OCT), the target condition (glaucoma), and diagnostic performance. The RGC/GCC SD-OCT scanning strategies used to assess glaucoma of most commonly used SD-OCT instruments were described and compared. These included the Cirrus high definition-OCT (Carl Zeiss Meditec, Inc., Dublin, CA, United States), RTVue (Optovue, Inc., Fremont, CA, United States), Spectralis (Heidelberg Engineering, Heidelberg, Germany) and the 3D OCT 2000 (Topcon Corporation, Tokyo, Japan). Studies focusing on the ability of RGC/GCC SD-OCT to detect early glaucomatous damage and on the correlation between glaucomatous progression and RGC/GCC measurement by SD-OCT were reviewed.
RESULTS: According to the literature, macular RGC/GCC SD-OCT has high diagnostic power of preperimetric glaucoma, reliable discrimination ability to differentiate between healthy eyes and glaucomatous eyes, with good correlation with visual filed damage. The current data suggests that it may serve as a sensitive detection tool for glaucomatous structural progression even with mild functional progression as the rate of change of RGC/GCC thickness was found to be significantly higher in progressing than in stable eyes. Glaucoma assessment with RGC/GCC SD-OCT was comparable with and sometimes better than circumpapillary retinal nerve fiber layer thickness measurement.
CONCLUSION: An increasing body of evidence supports using macular RGC/GCC thickness as an indicator for early glaucoma. This might be a useful tool for monitoring disease progression.
Core tip: Glaucoma is an optic neuropathy characterized by structural changes followed by functional deficits. Diagnosing early signs of the disease and detecting its progression are challenging. This review focuses on the most common macular retinal ganglion cells/ganglion cell complex spectral domain optical coherence tomography (SD-OCT) scanning strategies developed for glaucoma assessment (Cirrus high definition-OCT, RTVue, Spectralis and 3D OCT 2000) described in the literature published through July 2014; specifically, studies that assessed the ability to diagnose early glaucoma and glaucoma progression. The findings highlight the central role of macular SD-OCT in identifying subjects with early and progressive anatomical and functional glaucomatous damage.
Citation: Meshi A, Goldenberg D, Armarnik S, Segal O, Geffen N. Systematic review of macular ganglion cell complex analysis using spectral domain optical coherence tomography for glaucoma assessment. World J Ophthalmol 2015; 5(2): 86-98
Glaucoma is the leading cause of irreversible loss of vision, globally. In 2013, glaucoma was estimated to affect 64.3 million people 40-80 years-of-age, with this number increasing to 76.0 million by 2020 and 111.8 million by 2040. Glaucoma is an optic neuropathy characterized by loss of retinal ganglion cells (RGC), thinning of the circumpapillary retinal nerve fiber layer (cpRNFL) and the neuroretinal rim, and increased cupping[2,3]. It is often asymptomatic until the later stages and structural alterations usually appear before functional changes and prior to repeatable visual field deficits[4-6]. Early detection of the disease can lead to earlier treatment that might improve prognosis. The primary challenges in glaucoma assessment are diagnosing early signs of the disease and detecting disease progression.
Various tools are used for glaucoma assessment. Optical coherence tomography (OCT) has become a main modality. OCT is a micron-level, diagnostic method that uses 800-840 nm wavelength infrared light to provide high-resolution, non-invasive neural imaging. It is based on the principal of Michelson interferometry. An interference pattern is produced by splitting a beam of light into two. The two bouncing beams, one beam from the targeted tissue and the other from a reference mirror, and then recombined through the use of semitransparent mirrors.
OCT has become a well-established tool for diagnosing and monitoring diseases of the retina, choroid[8-11] and optic nerve head (ONH)[12-14], as well as anterior-segment conditions[15,16]. Time-domain (TD) and more recently spectral-domain (SD) OCT have significantly improved the ability to manage patients with retinal diseases and glaucoma.
OCT is commonly used for glaucoma to assess ONH and retinal nerve fiber layer (RNFL) thickness. RNFL thickness measurements with OCT have good reproducibility, an established structural–functional relationship and can detect glaucoma progression[19,20]. OCT has improved the ability to discriminate healthy eyes from those with glaucoma[17,20,21]. However, cpRNFL thickness measurement with OCT is limited by significant variations in the shape and size of the ONH, refractive error, axial length and peripapillary atrophy. Healthy eyes sometimes have unusual anatomical features that confuse currently available diagnostic software, and they are mistakenly classified as abnormal. Myopia is a very good example of this problem, as it is commonly associated with high variability in RNFL. Several studies reported that the average RNFL becomes thinner as the degree of myopia increases[22-24]. Moreover, RNFL thickness frequently varies by sector in patients with myopia, as their temporal RNFL tends to be much thicker[25,26]. Thus, caution should be taken while observing RNFL thickness in eyes with various cpRNFL abnormalities and pathologies, such as myopia, as normative data provided by OCT may be unreliable in these cases.
Glaucoma evaluation by macular imaging was first suggested by Zeimer et al. The macula has several physiological and anatomical advantages. As the RNFL is comprised of RGC axons, assessing the RGC may be a more direct way to measure ocular damage due to glaucoma than measurement of the cpRNFL thickness. The macula is the only place where more than one RGC body is found in the ganglion cell layer of the retina and because the body of the cell is much larger than the soma, it might be easier to detect glaucoma related cellular damage[27,28]. Additionally, more than half of all the RGC in the retina are in the macula. Thus, macular scanning allows most of the RGC to be sampled. In general, the shape of the RGC layer in the macular area is more consistent among healthy individuals than the RNFL in the ONH area. The macular RGC might provide a more sensitive measure than the cpRNFL because variations in this layer are likelier be result from pathological changes rather than normal variations.
MATERIALS AND METHODS
A systematic review was performed by searching PubMed, Medline, and Web of Science for articles published in English through July 2014 describing the various macular SD-OCT scanning strategies developed for glaucoma assessment. The search included keywords corresponding to the index test macular/RGC/ganglion cell complex (GCC) SD-OCT, the target condition (glaucoma), and diagnostic performance. Studies were included if they met the following criteria: (1) the study assessed diagnostic performance of macular/RGC/GCC SD-OCT in glaucoma patients; (2) the study evaluated early detection of glaucoma; and (3) the study assessed glaucoma progression. Relevant references used in included studies were also evaluated.
Using RGC/GCC OCT to assess glaucoma is a relatively new concept. Systematic review of the literature revealed an increasing number of papers dealing with this subject. SD-OCT has enabled measurements of the RGC in the macula and the retinal GCC, including the RNFL[30,31]. GCC thickness is defined by the distance from the internal limiting membrane to the outer boundary of the inner plexiform layer (IPL), which comprises the inner 3 layers of the retina (RNFL, ganglion cell layer and inner plexiform layer). Glaucoma affects all of these three layers. Another way to evaluate glaucomatous macular damage is to measure the entire retinal thickness rather than ganglion cell layer alone, as is done by the Spectralis OCT (Heidelberg Engineering, Heidelberg, Germany). Kita et al introduced a new parameter, the ratio of macular GCC thickness divided by the corresponding total retinal thickness (G/T). In a study conducted on a Japanese population to differentiate between healthy eyes and those with open angle glaucoma, a decreased G/T ratio was found in the early stages of glaucoma. However, Holló et al showed that the diagnostic accuracy of the G/T ratio in Europeans was consistently lower than measurements of RNFL thickness and GCC parameters provided by several software.
Most commonly used SD-OCT instruments for glaucoma assessment
Various macular scanning strategies were developed for glaucoma assessment using SD-OCT. The most commonly used SD-OCT instruments are Cirrus HD-OCT (Carl Zeiss Meditec, Inc., Dublin, CA, United States), RTVue (Optovue, Inc., Fremont, CA, United States), Spectralis (Heidelberg Engineering, Heidelberg, Germany) and 3D OCT 2000 (Topcon Corporation, Tokyo, Japan).
The macular scanning methodology for glaucoma assessment employed by each of the devices is explained below. Table 1 compares the properties of the various SD-OCT instruments.
Table 1 Properties of the various spectral domain optical coherence tomography instruments.
Cirrus HD-OCT (Carl Zeiss Meditec, Inc., Dublin CA, United States)
Cirrus HD-OCT (Carl Zeiss Meditec, Inc., Dublin, CA, United States): The Cirrus HD-OCT evaluates the thickness of the ganglion cell and IPL combined (Figure 1A), using the Macular Cube 200 × 200 or 512 × 128 scan patterns. The scan generates data in a 6 mm × 6 mm grid that consists of 200 frames of horizontal linear B-scans with 200 A-scan lines per B-scan. The segmentation software calculates the thickness of the macular ganglion cell-inner plexiform layer from an elliptical annulus centered on the fovea (thickness map) (Figure 1B) and calculates the thicknesses of the combined ganglion cell and IPL. The results are compared to normative data (Deviation map) (Figure 1C). The ganglion cell analysis segmentation algorithm divides the elliptical annulus of the Thickness Map into 6 equal sectors expressed in micrometers. Each spoke represents the average number of pixels along that spoke that lie within the measurement annulus (Figure 1D)[29,35-38].
Figure 1 Cirrus HD-optical coherence tomography.
A: Segmentation. Horizontal and vertical B-scans. The purple line represents the inner boundary of the ganglion cell layer and the yellow line represents the outer boundary of the inner plexiform layer; B: Thickness map. Calculation of the ganglion cell layer (GCL) + inner plexiform layer (IPL) thickness data from an elliptical annulus, 6 mm × 6 mm grid, centered on the fovea; C: Deviation map. Comparison of the GCL + IPL thickness results to a normative database; D: Sectors. Ganglion cell analysis segmentation algorithm that divides the elliptical annulus of the thickness map into 6 equal sectors expressed in micrometers. Each spoke represents the average of the pixels along that spoke that lie within the measurement annulus.
RTVue (Optovue, Inc., Fremont, CA, United States): The RTVue measures the GCC by scanning 1 horizontal line and 15 vertical lines at 0.5 mm intervals covering a 7 mm2 region centered on the fovea. It obtains 14928 A-scans within 0.6 s. The OCT scans are processed to provide a map of the thickness of the GCC (Figure 2A). It also provides pattern-based parameters of focal loss volume (FLV) and global loss volume (GLV). GLV corresponds to the total deviation map and FLV to the pattern deviation map that is used with visual field tests. A deviation map is calculated by comparing the thickness map to the normative databases (Figure 2B)[39,40]. RTVue also provides a significance map that illustrates the areas where there is a statistically significant change from normal (Figure 2C).
Figure 2 RTVue.
A: Thickness map. The thickness map is color coded where thicker regions of the ganglion cell complex are displayed in hot colors (yellow and orange), and thinner areas are displayed in cooler colors (blue and green); B: Deviation map. Calculated based on comparing the thickness map to the normative databases. The deviation map shows the percent loss from normal as determined by the normative database; C: Significance map. Shows regions where the change from normal reaches statistical significance. The significance map is color-coded where green represents values within the normal range (P = 0.05-0.95), yellow indicates borderline results (P < 0.05), and red represents outside normal limits (P < 0.01).
Spectralis (Heidelberg Engineering, Heidelberg, Germany): The Spectralis OCT measures the entire retinal thickness rather than ganglion cell layer. It uses 61 lines (30°× 25° OCT volume scan) to measure the retinal thickness in the posterior pole for each eye in a central 20° area. A color-coded thickness map for an 8 x 8 grid centered on the foveal pit is shown (Figure 3A). The grid is symmetrical to the fovea-to-disc axis of each eye. The Spectralis examines asymmetry between the eyes (Figure 3B). It also displays the asymmetry between the superior and the inferior hemisphere of each eye (hemisphere asymmetry) (Figure 3C)[41,42]. It also provides a mean thickness map (Figure 3D).
Figure 3 Spectralis.
A: Thickness map - the entire retinal thickness in the posterior pole displayed as a color coded thickness map for an 8 × 8 grid centered on the foveal pit positioned symmetrically to the fovea-disc axis; B: Asymmetry map - examination by grid of the asymmetry between the thicknesses in the corresponding cell of the fellow eye. Asymmetry color scale - darker grey indicates larger differences. The closer the value is to zero (white color), the better the symmetry; C: Hemisphere analysis - displays the asymmetry between the superior and the inferior hemisphere of each eye. The fovea-disc axis is the horizontal symmetry line. The lower half compares the inferior to the superior; D: Mean thickness - represents the mean retinal thickness for the superior and inferior hemisphere, as well as the total mean thickness over the entire 8 × 8 grid.
3D OCT 2000 (Topcon, Inc., Tokyo, Japan): The Topcon 3D OCT 2000 measures the RNFL thickness, the RGC with the IPL (GCIP), and the GCC. It uses raster scanning of a 7 mm2 area that is centered on the fovea with a scan density of 128 (horizontal) × 512 (vertical) scans (Figure 4A). The boundaries of the anatomical layers are determined by the program software (version 8.00; Topcon, Inc., Tokyo, Japan) using a validated, automated segmentation algorithm. The macular inner retinal layers (MIRL) analysis software detects the center of the fovea at the macular cube automatically, and selects a 6 mm × 6 mm region centered at the foveal center. The software divides the macular square into a 6 × 6 grid containing 100 cells of 0.6 mm × 0.6 mm, to assess regional abnormalities in MIRL thickness. Average regional thickness of GCC, GCIP and RNFL in each cell is calculated and compared to the normative database of the device[43,44] (Figure 4B).
Figure 4 Three dimensions optical coherence tomography 2000.
A: Segmentation: 7 mm2 area centered on the fovea with a scan density of 512 vertical × 128 horizontal scans; B: Thickness map. Average regional thickness is calculated for RNFL, GCL+ (GCL + IPL), GCL++ (RNFL + GCL + IPL). Each cell is calculated and compared to the normative database of the device; C: Significance map. From left to right, 10 × 10 grid comparison maps covering 6 mm × 6 mm area of RNFL, GCL+ and GCL++ are shown. The comparison result is displayed with the color in the legend on the right. The background image is red free image; D: Average thickness. From left to right, three average thicknesses of RNFL, GCL+ and GCL++. The top is “Superior” which means average in the upper half area, the middle is “Inferior” which means average in the lower half area, and the bottom is “Total’ which means average in the total area. Each average thickness is compared to the normative data and displayed according to color; E: Asymmetry map. From left to right, subtraction thickness maps covering 6 mm × 6 mm area of RNFL, GCL+ and GCL++ are shown. The subtraction is performed between two points which symmetrically lie with respect to the center horizontal line. In the upper half, the value in each point is calculated such that thickness of the point is subtracted from the thickness of the corresponding line-symmetry point below and vice versa. Blue indicates that the thickness of the point is thinner than that of the corresponding point. RNFL: Retinal nerve fiber layer; GCL: Ganglion cell layer; IPL: Inner plexiform layer.
Table 2 summarizes the characteristics of the major studies reviewed in this paper.
Table 2 Summary of major studies investigating macular spectral domain optical coherence tomography for glaucoma assessment.
GCC thickness steadily decreased from normal to PPG to early glaucoma. GCIP and GCC, but not mNFL were significantly different between PPG and controls and had similar discrimination ability as cpRNFL analysis
GCC thickness of the inner or outer sector of the parafovea decreased as the corresponding hemifield defect increased. GCC thickness changes in apparently normal hemifield correlated with progression of the glaucomatous defects
MIRL thickness was strongly correlated and glaucoma discrimination ability was comparable with cpRNFL thickness in early VF defects. cpRNFL had better diagnostic ability than MIRL in eyes with advanced or peripheral VF defects
Baseline GCC (average and inferior hemifield) were significantly thinner in fast progressors compared to slow progressors
SD-OCT: Spectral-domain optical coherence tomography; PPG: Pre-perimetric glaucoma; PG: Perimetric glaucoma; GCC: Ganglion cell complex; GCIP: Combined retinal ganglion cell and inner plexiform layer; mNFL: Macular nerve fiber layer; cpRNFL: Circumpapillary retinal nerve fiber layer; VF: Visual fields; MIRL: Macular inner retinal layers; AROC: Area under the receiver operating characteristics curve; POAG: Primary open-angle glaucoma; GLV: Global loss volume; VFS: Visual field sensitivity; MRT: Mean retinal thickness; NTG: Normal tension glaucoma; FLV: Focal loss volume.
Comparing results between different SD-OCT devices
The literature comparing results between different SD-OCT devices is relatively sparse. Previous studies revealed that cpRNFL measurements from healthy controls using several devices varied and could not be interchanged[45,46]. Nonetheless, the diagnostic performance of most devices was similar when measuring cpRNFL thickness for glaucoma detection. The Cirrus OCT and 3D OCT devices demonstrated similar accuracy when detecting a localized RNFL defect. Furthermore, review of the literature revealed only a few papers that compared RGC/GCC SD-OCT measurements from different OCT devices in glaucoma patients. Kim et al compared the GCC parameters between Cirrus OCT and 3D OCT. Among the macular GCC parameters of the 3D OCT device, inferior macular RNFL thickness had the highest sensitivity (81.2% at a specificity of 80%) and the largest area under the curve (AUC) (0.89).
Akashi et al compared the macular analysis results of the Cirrus, RTVue and 3D OCT in glaucoma patients. They found that the use of average GCC thickness for diagnosing glaucoma stages did not differ significantly among the three SD-OCT instruments. However, the RTVue provided better measurement of the superior hemi-field GCC thickness than did Cirrus and 3D-OCT.
Early detection of glaucoma using macular SD-OCT
Diagnosing the early signs of the disease can be challenging and macular analysis with SD-OCT for this purpose has recently received much attention. Tan et al measured macular retinal thickness and GCC thickness with the RTVue OCT. They reported that the mean GCC had significantly higher diagnostic power than the macular retinal thickness for both SD-OCT and TD-OCT for discriminating between normal eyes and those with perimetric glaucoma. They also found that the diagnostic powers of the best GCC parameters were equal to that of the mean TD-OCT RNFL.
Kim et al compared the GCC thickness measured by 3D OCT 2000 in three groups: healthy eyes, eyes with pre-perimetric glaucoma (PPG) and eyes with early glaucoma. They found that all GCC parameters decreased from normal to PPG and from PPG to early glaucoma. The values of the GCIP and GCC parameters differed significantly among the three groups (P < 0.001). However, the RNFL thickness of the macula between the healthy eyes and those with PPG was not significantly different (P > 0.05).
Rolle et al used RTVue OCT to study early structural changes of RNFL and GCC in patients with a family history of primary open angle glaucoma (POAG). They included 163 eyes of first and second degree relatives (85 healthy, 40 with ocular hypertension and 38 with PPG) and 108 eyes of subjects with no family history (60 healthy and 48 PPG). They found that RNFL superior, GCC average, GCC superior, and GCC inferior were thinner (P < 0.05) in healthy eyes of patients with a family history of glaucoma than in normal eyes with no such history. They also showed that subjects with a glaucomatous sibling had significantly thinner RNFL and GCC than those with a single parent affected by the disease. These findings highlight the central role of SD-OCT in identifying individuals with early anatomical damage from glaucoma, even in eyes that appear normal.
The correlation between early glaucomatous visual field (VF) defects and macular ganglion cell layer assessment by OCT was investigated. Kim et al evaluated the point-wise relationships between visual field sensitivity (VFS), measured by standard automated perimetry (SAP) and macular thickness, as determined by Spectralis-OCT, in glaucoma patients. They examined the correlation between the retinal sensitivities of 16 central test points from the SAP (Humphrey field analyzer) and Spectralis macular volume scans. They measured the macular thickness in 4 square cells in an 8 × 8 posterior pole retinal thickness map. The values were averaged for a mean retinal thickness (MRT) value, which corresponded to the 16 central test points in the SAP. A significant relationship between the MRT values and the corresponding VFS of each 16 central test point was found. They also showed that the level of the relationship varied among different sectors of the macula, showing the most significant relationship in the arcuate region. The study revealed that substantial structural loss (approximately 17%) appears to be necessary for detection of functional loss, using SD-OCT. Kim et al concluded that from a clinical point of view, structural evaluation may be a more sensitive measure of ocular health in early stage glaucoma, whereas the functional evaluation may be a more sensitive and accurate measure of glaucoma progression at moderate-to-advanced stages. Inuzuka et al examined the relationship between GCC thickness and its corresponding superior or inferior visual hemifield defects. They found that the thickness of the GCC at the inner and outer sectors of the parafovea decreased significantly as the corresponding hemifield defect increased. They also demonstrated that the GCC thickness correlated with changes in the corresponding hemifield that seemed normal. Their findings suggest that in glaucoma patients, changes in the GCC thickness occur before the VF worsens, even when the hemifield appears normal. This correlated with the severity of the disease. Thus, macular GCC thickness is an important indicator for glaucoma risk and may be a useful parameter for monitoring changes in patients with early or pre-perimetric glaucoma.
There is an increasing body of evidence to support the hypothesis that MIRL parameters are comparable to those of cpRNFL thickness in terms of the ability to diagnose glaucoma early. This is especially useful when cpRNFL measurements are not reliable, such as in eyes with extremely small or large optic discs, in tilted optic discs or peripapillary atrophy. Seong et al used the RTVue OCT to compare the ability of MIRL thickness and cpRNFL thickness measurements to detect glaucoma. They showed that MIRL thickness was strongly correlated with cpRNFL thickness, and that MIRL thickness was able to discern glaucoma similar to cpRNFL thickness with early VF defects. However, cpRNFL measurement was better at diagnosing glaucoma than MIRL measurements in eyes with advanced or peripheral VF defects. Similar correlations between VF mean sensitivity, GCC, and cpRNFL thickness in glaucomatous eyes were reported by Cho et al. Na et al showed that pre-perimetric glaucoma patients with localized RNFL defects observed in red-free fundus photography had significantly thinner GCC measured by RTVue OCT, in all sectors compared to healthy individuals. The superior average GCC thickness was the best GCC parameter for detecting localized RNFL defects. It had similar area under receiver operating characteristic curve (AROC) values (0.84) to that of cpRNFL average thickness (0.89). Lee at al compared MIRL and cpRNFL measurements in discriminating between eyes with and without paracentral scotoma. They included 63 eyes with early glaucoma with (33 eyes) or without (30 eyes) paracentral VF defects. Differences between the groups were significant in all of the MIRL parameters, but only in some cpRNFL parameters. The AROC for discriminating between groups was better for MIRL (0.77) than for cpRNFL (0.644) parameters. This study suggested that regional structural assessment of MIRL was a stronger indicator of scotoma in the paracentral area than cpRNFL measurements. On the other hand, using various scanning protocols of the RTVue OCT, including GCC parameters, Rao et al found only moderate diagnostic abilities in differentiating PPG eyes from eyes with large physiologic cups. The GCC parameter with best AUC was inferior quadrant GCC thickness (0.75). Including subjects with large physiologic cups as the control group in this study might have obscured the differences between normal and abnormal eyes.
High specificity of macular analysis is needed to avoid false positive identification of glaucoma among healthy eyes. Iverson et al conducted a prospective, longitudinal study and found a high specificity (91%) for GCC thickness parameters in normal eyes, but only moderate specificity (77%) in glaucoma suspects, during the course of 43 mo of follow-up. Approximately half of the GCC measurements classified as outside normal limits were not replicable on subsequent scans. Mwanza et al examined the diagnostic performance of GCIP thickness (Cirrus HD-OCT) between early glaucoma patients and normal controls. GCIP parameters were significantly thinner in the glaucoma group compared with controls. The best discriminant was the minimum, with 82% sensitivity and 87.8% specificity. Its performance was similar to that of the best RNFL and ONH parameters. The diagnosis was based on at least 1 abnormal GCIP parameter and yielded sensitivity and specificity values of 88% and 81.6%, respectively. Thus, confirmation of suspected SD-OCT abnormalities is essential for differentiating long-term variability from reproducible loss.
Macular SD-OCT has also a role in advanced glaucoma patients, although the evidence is sparse. Delbarre et al used the Cirrus HD-OCT to evaluate the diagnostic ability of segmentation of the various internal macular layers compared to cpRNFL with the various stages of glaucoma disease: early, moderate and advanced. For the entire study population, the minimum GCIPL index provided greater diagnostic ability than the other parameters. There was no statistically significant difference with the cpRNFL parameter in the early POAG group, whereas in the advanced POAG group, minimum GCILP and GCC gave the largest AUC indices. Kim et al assessed the relationship between visual acuity and mGCC thickness, as measured by RTVue, in open-angle glaucoma patients. They noted significant correlations only in eyes with severe glaucoma. In the severe glaucoma group all GCC parameters significantly correlated with best corrected visual acuity, however no correlation was found in the early-to-moderate disease group.
Detection of glaucoma progression with macular SD-OCT
The average cpRNFL thickness was evaluated in the first study that reported using OCT for glaucoma progression analysis. Clinicians were able to evaluate disease progression using specially designed statistical software. Guided Progression Analysis first became available in 2008, with the introduction of time-domain OCT (version 5.0, Stratus OCT, Carl Zeiss Meditec). The use of eye tracking (Spectralis OCT, Heidelberg Engineering) and cpRNFL thickness profiles from the same location in RNFL thickness maps (Cirrus HD-OCT, Carl Zeiss Meditec) are some of the strategies used to enhance the ability to detect changes with SD-OCT.
The macula has the highest density of ganglion cells in the retina. Measurements of the macular nerve fibers and ganglion cell and inner plexiform layer thicknesses are useful for monitoring glaucoma progression. However, most OCT progression studies conducted to date were limited to cpRNFL measurements; few evaluated measurements of macular thickness.
Both time-domain and SD-OCT instruments have been used to obtain macular measurements for the detection of glaucomatous damage. Repeatability of measurements is very important when evaluating progression. Mwanza et al found higher reproducibility of macular ganglion cell layer thickness measurements with the SD-OCT than with the TD-OCT. Although the TD-OCT did not show significant differences in the rate of change of average macular thickness (an average of six radial scan lines, each 6 mm long) between eyes with and without evidence of progression in the VF and/or optic disc stereophotographs (defined as progressors and nonprogressors, respectively), a study that used the SD-OCT had different results. Using similar definitions of progressors and non-progressors, Sung et al followed 98 patients with advanced glaucoma for a mean of 2.2 years and reported a significant difference in the rate of change of average macular thickness, but not in average cpRNFL thickness, between the two groups. However, in a study evaluating 162 patients with mild glaucoma followed for the same period, significant differences in the rates of change of cpRNFL and macular thicknesses between progressors and nonprogressors were found. In terms of progression as determined by optic disc/RNFL photographic or VF assessment, the thickness of the ganglion cell layer had similar sensitivity to RNFL and to total macular thickness. The enhanced measurement reproducibility and denser scanning afforded by SD-OCT may increase detection of structural progression. However, additional studies confirming this hypothesis have yet to be published.
As mentioned above, the RTVue GCC map includes FLV and GLV patterns, based on parameters. Naghizadeh et al found that compared to ONH, RNFL thickness, or average GCC parameters, GLV and FLV provide better detection of early structural changes due to glaucoma progression. They reported that these parameters detected structural progression even with mild functional progression and that both parameters demonstrated different progression rates between stable and progressing eyes.
Anraku et al investigated the functional impact of the baseline mGCC thickness. They assessed the association of the baseline mGCC thickness with the progression of VF loss in 56 POAG patients who were followed for more than 2 years after baseline OCT measurements. They found that the baseline mGCC thickness (average and inferior hemifield) was significantly thinner in the fast progressors than in the slow progressors. In a multivariate analysis, only mGCC thickness of the inferior hemifield was associated with disease progression (P = 0.007). They concluded that baseline mGCC thickness can be predictive of progressive VF loss in POAG.
However, using OCT parameters to track disease progress is somewhat limited. Some changes to the optic disc, RNFL and macular thicknesses detected by the OCT may not be due to glaucoma. Prospective studies have reported age-related RNFL and thinning of the macula as additional causes.
Detecting a decrease in macular thickness is not necessarily a sign of glaucoma progression. A prospective study followed 150 eyes in 90 glaucoma patients 3 times a year for an average of 3.8 years. Trend analyses showed progression of the inner macular thickness in 50% and in total macular thickness, in 30% of eyes. After considering changes due to age, progression decreased to 20.0% and 16.0% for inner retinal thickness and total macular thickness, respectively. These findings underscore the affects of changes due to aging on macular and RNFL measurements.
In cases of advanced optic neuropathy, OCT also has limitations related to detecting RNFL thinning. Changes in RNFL thickness are associated with initial measurements (the rate of decrease in RNFL thickness is increased when the eye has a thicker RNFL). RNFL thickness is not less than 30 µm even when the eye has end-stage optic neuropathy and no light perception.
Measurements of OCT are related to the signal-to-noise ratio (or signal strength) of OCT images[56,70,71]. The signal strength of OCT images may decrease over time if cataract, vitreous opacities or other entities that may affect the opacity of the media. Rao et al investigated the relationship between scan quality and diagnostic accuracy with SD-OCT using the RTVue OCT in glaucoma patients. The diagnostic ability was dependent on the scan quality even when the signal strength index (SSI) values were within the manufacturer-recommended limits. Scan quality had a greater effect on the diagnostic accuracy of ONH and cpRNFL than on GCC parameters. The sensitivity of all SD-OCT parameters, including GCC, for diagnosing glaucoma increased as the SSI increased. Thus, when interpreting a diagnosis of glaucoma and disease progression, the possible effect of the signal-to-noise ratio of the image series should always be considered.
Changes in the GCC demonstrated by OCT may also reflect pathologies other than glaucoma. The technology was found to be beneficial for detecting toxic effects of oral isotretinoin therapy and for demonstrating macular retinopathy related to sickle cell anemia. GCC OCT was used to detect optic chiasmal compression neuropathy, early macular retinal ganglion cell loss related to dominant optic atrophy and was also used in migraine patients with aura. Bayhan et al used it to follow patients with Parkinson’s disease, whereas Narayanan et al found it beneficial in multiple sclerosis especially with prolonged disease duration and in relapsing remitting eyes.
Future research directions
OCT is a relatively new, evolving technology. It continue to undergo improvements that will enhance our ability to understand the structural pathogenesis of glaucoma and to offer more objective and accurate detection of structural glaucomatous damage and changes over time.
A variety of OCT devices are used to capture the retinal layers. Finding a tool that allows comparison between the results of different GCC OCT devices may be beneficial. We should aspire to develop an algorithm that allows combining the visual field test points with the GCC sectors demonstrated by OCT in order to better investigate the structural-functional aspects of glaucoma progression.
A normative database that incorporates age, sex, axial length and population origin will be required to take full advantage of this technology.
An increasing body of evidence supports using RGC/GCC macular GCC thickness as an indicator for early glaucoma and a valuable tool for monitoring disease progression.
Optical coherence tomography (OCT) has become a well-established tool for diagnosing and monitoring glaucoma. Limitations in optic nerve head assessment with OCT have driven investigators to look for novel OCT scanning strategies for glaucoma evaluation. Spectral domain (SD) OCT has enabled measurements of the retinal ganglion cells (RGC) in the macula and the retinal ganglion cell complex (GCC), including the retinal nerve fiber layer (RNFL), which are primarily affected in glaucoma and can be directly assessed by this method. Using RGC/GCC SD-OCT in glaucoma is a relatively new concept and the aim of this study was to systematically review the current literature published on this subject.
New macular segmentation strategies using SD-OCT were developed in recent years for glaucoma assessment, focusing on the measurement of RGC and GCC thickness. Several SD-OCT instruments, including Cirrus HD-OCT (Carl Zeiss Meditec, Inc., Dublin, CA, United States), RTVue (Optovue, Inc., Fremont, CA, United States), Spectralis (Heidelberg Engineering, Heidelberg, Germany) and 3D OCT 2000 (Topcon Corporation, Tokyo, Japan), incorporate sophisticated glaucoma evaluation tools based on these parameters.
Innovations and breakthroughs
To the best of our knowledge, this is the first systematic review of the current data regarding the use of macular RGC/GCC SD-OCT for glaucoma assessment and no published paper thus far has summarized the current data in this field.
This systematic review may support clinicians to use macular RGC/GCC SD-OCT measurements as a routine adjunctive test to detect early glaucoma and to monitor glaucoma progression in established glaucoma patients.
Glaucoma is an optic neuropathy characterized by loss of RGC, thinning of the RNFL and the neuroretinal rim, and increased cupping. RGC layer is an inner retinal layer which is thicker at the macula. GCC thickness is defined by the distance from the internal limiting membrane, the inner most retinal layer, to the outer boundary of the inner plexiform layer (IPL), which comprises the inner 3 layers of the retina (retinal nerve fiber layer, ganglion cell layer and IPL. Glaucoma affects all of these three layers. OCT is a micron-level, diagnostic method that uses 800-840 nm wavelength infrared light to provide high-resolution, non-invasive neural imaging.
This manuscript is very good and well summarized about macular GCC analysis by various kinds of SD-OCT.
P- Reviewer: Bhattacharya SK, Hong YJ, Tzamalis A S- Editor: Ji FF L- Editor: A E- Editor: Wu HL
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