To investigate the prevalence of visual field defects in glaucomatous eyes, glaucoma suspects, and ocular hypertensives with 24-2 and 10-2 visual fields.
Prospective, cross-sectional study.
Patients ...with or suspected glaucoma tested with 24-2 and 10-2. Patients were classified into 3 groups on the basis of the presence of glaucomatous optic neuropathy (GON) and 24-2 visual field abnormalities: early glaucoma (GON and abnormal visual field, mean deviation >-6 decibels dB), glaucoma suspects (GON and normal visual field), and ocular hypertensives (normal disc, normal visual field, and intraocular pressure >22 mmHg). For the classification of visual field abnormalities, 24-2 and 10-2 tests performed on the same visit were analyzed.
Comparison of the prevalence of abnormal 24-2 versus 10-2 visual field results based on cluster criteria in each diagnostic group.
A total of 775 eyes (497 patients) were evaluated. A total of 364 eyes had early glaucoma, 303 eyes were glaucoma suspects, and 108 eyes were ocular hypertensives. In the glaucoma group, 16 of the 26 eyes (61.5%) classified as normal based on cluster criteria on 24-2 tests were classified as abnormal on 10-2 visual fields. In eyes with suspected glaucoma, 79 of the 200 eyes (39.5%) classified as normal on the 24-2 test were classified as abnormal on 10-2 visual fields. In ocular hypertensive eyes, 28 of the 79 eyes (35.4%) classified as normal on the 24-2 were classified as abnormal on the 10-2. Patients of African descent were more likely to have an abnormal 10-2 result (67.3 vs. 56.8%, P = 0.009).
Central visual field damage seen on the 10-2 test is often missed with the 24-2 strategy in all groups. This finding has implications for the diagnosis of glaucoma and classification of severity.
To develop and evaluate a deep learning system for differentiating between eyes with and without glaucomatous visual field damage (GVFD) and predicting the severity of GFVD from spectral domain OCT ...(SD OCT) optic nerve head images.
Evaluation of a diagnostic technology.
A total of 9765 visual field (VF) SD OCT pairs collected from 1194 participants with and without GVFD (1909 eyes).
Deep learning models were trained to use SD OCT retinal nerve fiber layer (RNFL) thickness maps, RNFL en face images, and confocal scanning laser ophthalmoscopy (CSLO) images to identify eyes with GVFD and predict quantitative VF mean deviation (MD), pattern standard deviation (PSD), and mean VF sectoral pattern deviation (PD) from SD OCT data.
Deep learning models were compared with mean RNFL thickness for identifying GVFD using area under the curve (AUC), sensitivity, and specificity. For predicting MD, PSD, and mean sectoral PD, models were evaluated using R
and mean absolute error (MAE).
In the independent test dataset, the deep learning models based on RNFL en face images achieved an AUC of 0.88 for identifying eyes with GVFD and 0.82 for detecting mild GVFD significantly (P < 0.001) better than using mean RNFL thickness measurements (AUC = 0.82 and 0.73, respectively). Deep learning models outperformed standard RNFL thickness measurements in predicting all quantitative VF metrics. In predicting MD, deep learning models based on RNFL en face images achieved an R
of 0.70 and MAE of 2.5 decibels (dB) compared with 0.45 and 3.7 dB for RNFL thickness measurements. In predicting mean VF sectoral PD, deep learning models achieved high accuracy in the inferior nasal (R
= 0.60) and superior nasal (R
= 0.67) sectors, moderate accuracy in inferior (R
= 0.26) and superior (R
= 0.35) sectors, and lower accuracy in the central (R
= 0.15) and temporal (R
= 0.12) sectors.
Deep learning models had high accuracy in identifying eyes with GFVD and predicting the severity of functional loss from SD OCT images. Accurately predicting the severity of GFVD from SD OCT imaging can help clinicians more effectively individualize the frequency of VF testing to the individual patient.
The ability of deep learning architectures to identify glaucomatous optic neuropathy (GON) in fundus photographs was evaluated. A large database of fundus photographs (n = 14,822) from a racially and ...ethnically diverse group of individuals (over 33% of African descent) was evaluated by expert reviewers and classified as GON or healthy. Several deep learning architectures and the impact of transfer learning were evaluated. The best performing model achieved an overall area under receiver operating characteristic (AUC) of 0.91 in distinguishing GON eyes from healthy eyes. It also achieved an AUC of 0.97 for identifying GON eyes with moderate-to-severe functional loss and 0.89 for GON eyes with mild functional loss. A sensitivity of 88% at a set 95% specificity was achieved in detecting moderate-to-severe GON. In all cases, transfer improved performance and reduced training time. Model visualizations indicate that these deep learning models relied on, in part, anatomical features in the inferior and superior regions of the optic disc, areas commonly used by clinicians to diagnose GON. The results suggest that deep learning-based assessment of fundus images could be useful in clinical decision support systems and in the automation of large-scale glaucoma detection and screening programs.
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Glaucomatous visual field progression has both personal and societal costs and therefore has a serious impact on quality of life. At the present time, intraocular pressure (IOP) is considered to be ...the most important modifiable risk factor for glaucoma onset and progression. Reduction of IOP has been repeatedly demonstrated to be an effective intervention across the spectrum of glaucoma, regardless of subtype or disease stage. In the setting of approval of IOP-lowering therapies, it is expected that effects on IOP will translate into benefits in long-term patient-reported outcomes. Nonetheless, the effect of these medications on IOP and their associated risks can be consistently and objectively measured. This helps to explain why regulatory approval of new therapies in glaucoma has historically used IOP as the outcome variable. Although all approved treatments for glaucoma involve IOP reduction, patients frequently continue to progress despite treatment. It would therefore be beneficial to develop treatments that preserve visual function through mechanisms other than lowering IOP. The United States Food and Drug Administration (FDA) has stated that they will accept a clinically meaningful definition of visual field progression using Glaucoma Change Probability criteria. Nonetheless, these criteria do not take into account the time (and hence, the speed) needed to reach significant change. In this paper we provide an analysis based on the existing literature to support the hypothesis that decreasing the rate of visual field progression by 30% in a trial lasting 12–18 months is clinically meaningful. We demonstrate that a 30% decrease in rate of visual field progression can be reliably projected to have a significant effect on health-related quality of life, as defined by validated instruments designed to measure that endpoint.
•A 30% decrease in rate of visual field progression can be projected to have a significant effect on health-related quality of life.•The US FDA definition of clinically-meaningful progression corresponds to a slope ≤−0.5 dB/yr in ≥5 abnormal test locations.•A 30% decrease in visual field progression with trend analysis is equivalent to a 2-3 mmHg decrease in intraocular pressure.
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Glaucomatous damage of the macula Hood, Donald C.; Raza, Ali S.; de Moraes, Carlos Gustavo V. ...
Progress in retinal and eye research,
01/2013, Volume:
32
Journal Article
Peer reviewed
Open access
There is a growing body of evidence that early glaucomatous damage involves the macula. The anatomical basis of this damage can be studied using frequency domain optical coherence tomography (fdOCT), ...by which the local thickness of the retinal nerve fiber layer (RNFL) and local retinal ganglion cell plus inner plexiform (RGC+) layer can be measured. Based upon averaged fdOCT results from healthy controls and patients, we show that: 1. For healthy controls, the average RGC+ layer thickness closely matches human histological data; 2. For glaucoma patients and suspects, the average RGC+ layer shows greater glaucomatous thinning in the inferior retina (superior visual field (VF)); and 3. The central test points of the 6° VF grid (24-2 test pattern) miss the region of greatest RGC+ thinning. Based upon fdOCT results from individual patients, we have learned that: 1. Local RGC+ loss is associated with local VF sensitivity loss as long as the displacement of RGCs from the foveal center is taken into consideration; and 2. Macular damage is typically arcuate in nature and often associated with local RNFL thinning in a narrow region of the disc, which we call the macular vulnerability zone (MVZ). According to our schematic model of macular damage, most of the inferior region of the macula projects to the MVZ, which is located largely in the inferior quadrant of the disc, a region that is particularly susceptible to glaucomatous damage. A small (cecocentral) region of the inferior macula, and all of the superior macula (inferior VF), project to the temporal quadrant, a region that is less susceptible to damage. The overall message is clear; clinicians need to be aware that glaucomatous damage to the macula is common, can occur early in the disease, and can be missed and/or underestimated with standard VF tests that use a 6° grid, such as the 24-2 VF test.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
PURPOSE:Existing summary statistics based upon optical coherence tomographic (OCT) scans and/or visual fields (VFs) are suboptimal for distinguishing between healthy and glaucomatous eyes in the ...clinic. This study evaluates the extent to which a hybrid deep learning method (HDLM), combined with a single wide-field OCT protocol, can distinguish eyes previously classified as either healthy suspects or mild glaucoma.
METHODS:In total, 102 eyes from 102 patients, with or suspected open-angle glaucoma, had previously been classified by 2 glaucoma experts as either glaucomatous (57 eyes) or healthy/suspects (45 eyes). The HDLM had access only to information from a single, wide-field (9×12 mm) swept-source OCT scan per patient. Convolutional neural networks were used to extract rich features from maps derived from these scans. Random forest classifier was used to train a model based on these features to predict the existence of glaucomatous damage. The algorithm was compared against traditional OCT and VF metrics.
RESULTS:The accuracy of the HDLM ranged from 63.7% to 93.1% depending upon the input map. The retinal nerve fiber layer probability map had the best accuracy (93.1%), with 4 false positives, and 3 false negatives. In comparison, the accuracy of the OCT and 24-2 and 10-2 VF metrics ranged from 66.7% to 87.3%. The OCT quadrants analysis had the best accuracy (87.3%) of the metrics, with 4 false positives and 9 false negatives.
CONCLUSIONS:The HDLM protocol outperforms standard OCT and VF clinical metrics in distinguishing healthy suspect eyes from eyes with early glaucoma. It should be possible to further improve this algorithm and with improvement it might be useful for screening.
The purpose of this retrospective, longitudinal study is to evaluate the relationship between MD slope from visual field tests collected over a short period of time (2 years) and the current United ...States' Food and Drug Administration (FDA) recommended endpoints for visual field outcomes. If this correlation is strong and highly predictive, clinical trials employing MD slopes as primary endpoints could be employed in neuroprotection clinical trials with shorter duration and help expedite the development of novel IOP-independent therapies. Visual field tests of patients with or suspected glaucoma were selected from an academic institution and evaluated based on two functional progression endpoints: (A) five or more locations worsening by at least 7 dB, and (B) at least five test locations based upon the GCP algorithm. A total of 271 (57.6%) and 278 (59.1%) eyes reached Endpoints A and B, respectively during the follow up period. The median (IQR) MD slope of eyes reaching vs. not reaching Endpoint A and B were -1.19 (-2.00 to -0.41) vs. 0.36 (0.00 to 1.00) dB/year and -1.16 (-1.98 to -0.40) vs. 0.41 (0.02 to 1.03) dB/year, respectively (P < 0.001). It was found that eyes experiencing rapid 24-2 visual field MD slopes over a 2-year period were on average tenfold more likely to reach one of the FDA accepted endpoints during or soon after that period.
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The objective of this prospective, longitudinal study of patients with normal-tension glaucoma (NTG) was to determine whether patients with nocturnal hypotension are at greater risk for visual field ...(VF) loss over 12 months than those without nocturnal hypotension.
Prospective, longitudinal study.
Consecutive patients with NTG with at least 5 prior VF tests were screened for eligibility.
The baseline evaluation assessed demographic and clinical characteristics, covering systemic comorbid conditions, including systemic hypertension. All oral and ophthalmologic medications were recorded. A complete ophthalmological examination was performed at baseline and follow-up. Patients had their blood pressure (BP) monitored every 30 minutes for 48 hours with an ambulatory recording device at baseline and 6 and 12 months.
The primary outcome was based on the global rates of VF progression by linear regression of the mean VF threshold sensitivity over time (decibels/year).
Eighty-five patients with NTG (166 eyes; mean age, 65 years; 67% were women) were included. Of the 85 patients, 29% had progressed in the 5 VFs collected before study enrollment. The nocturnal mean arterial pressure (MAP) was compared with the daytime MAP. Multivariate analysis showed that the total time that sleep MAP was 10 mmHg below the daytime MAP was a significant predictor of subsequent VF progression (P<0.02).
Cumulative nocturnal hypotension predicted VF loss in this cohort. Our data suggest that the duration and magnitude of decrease in nocturnal blood pressure below the daytime MAP, especially pressures that are 10 mmHg lower than daytime MAP, predict progression of NTG. Low nocturnal blood pressure, whether occurring spontaneously or as a result of medications, may lead to worsening of VF defects.
To assess the usefulness of enhanced depth imaging (EDI) optical coherence tomography (OCT) for evaluating deep structures of the optic nerve complex (ONC; optic nerve head and peripapillary ...structures) in glaucoma.
Prospective, observational study.
Seventy-three established glaucoma patients (139 eyes) with a range of glaucomatous damage.
Serial horizontal and vertical EDI OCT images of the ONC were obtained from both eyes of each participant. Deep ONC structures, including the lamina cribrosa (LC), short posterior ciliary artery (SPCA), central retinal artery (CRA), central retinal vein (CRV), peripapillary choroid and sclera, and subarachnoid space around the optic nerve, were investigated for their visibility and morphologic features.
Deep ONC structures identified in EDI OCT images.
Visual field mean deviation of 139 included eyes was -11.8 ± 8.6 dB (range, -28.70 to -2.01 dB). The anterior laminar surface was identified in all eyes in the central laminar area and in 91 (65%) eyes in the periphery beneath the neuroretinal and scleral rims or vascular structures. The LC pores with various shapes and sizes were visualized in 106 (76%) eyes, mainly in the central and temporal areas of the LC. Localized LC lesions seen on optic disc photographs were identified as focal LC defects (partial loss of LC tissue) in the EDI OCT images. The locations of the CRA and CRV were identified in all eyes. In the LC, the CRA maintained a straight shape with a consistent caliber, but the CRV (and tributaries) assumed a more irregular shape. The SPCAs, their branches through the emissary canals in the sclera, or both were visualized in 120 (86%) eyes. The subarachnoid space around the optic nerve was identified with varying degrees of clarity in 25 eyes (18%): 17 had high myopia and extensive parapapillary atrophy. Intrachoroidal cavitation or choroidal schisis, which had been unrecognized clinically, was identified in 2 eyes (1%) with high myopia.
Enhanced depth imaging OCT was able to visualize a wide variety of deep ONC structures in glaucoma patients and may be helpful in detecting, conceptualizing, and understanding basic and complicated in vivo anatomic and pathologic features of the ONC in glaucoma.
Proprietary or commercial disclosure may be found after the references.
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