Predicting Progressive Glaucomatous Optic Neuropathy Using Baseline Standard Automated Perimetry Data

Abstract Objective To determine the diagnostic ability of isolated-check visual evoked potential (icVEP), pattern visual evoked potential (pVEP), and standard automated perimetry (SAP) between dysthyroid optic neuropathy (DON) and thyroid-associated ophthalmopathy (TAO) without DON (non-DON). Methods This is a case-control study, 49 bilateral patients (26 DON and 23 non-DON) were included. icVEP, pVEP, and SAP were conducted in all the subjects, icVEP parameters compared were signal-to-noise ratios (SNRs) under 8, 16, and 32% depth of modulation (DOM). pVEP parameters compared were amplitude and latency. SAP parameters were mean deviation (MD) and pattern standard deviation (PSD). The area under the receiver operating characteristic (ROC) curve (AUC), net reclassification index (NRI), integrated discrimination index (IDI), and decision curve analysis (DCA) were applied for analysis. Results In icVEP, values of SNR in DON were significantly smaller than non-DON (p < 0.05). In pVEP, P100 latent time in DON was significantly larger than non-DON (p = 0.0026). In SAP, value of PSD in DON was larger than non-DON (p = 0.0006), and value of MD in DON was smaller (p = 0.0007). AUC, NRI, and IDI among the three tests were not significantly different. DCA showed that SNR of icVEP under 8% DOM was the farthest from the two extreme curves. Conclusions icVEP, pVEP, and SAP have equal diagnostic capabilities to discern between DON and non-DON. In addition, icVEP may represent a significant ancillary diagnostic approach to DON detection, with more clinical benefit.

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Spatial Relationship of Motion Automated Perimetry and Optic Disc Topography in Patients with Glaucomatous Optic Neuropathy

Journal of Glaucoma ◽

10.1097/00061198-199910000-00002 ◽

1999 ◽

Vol 8 (5) ◽

pp. 281???289 ◽

Cited By ~ 11

Author(s):

Charles F. Bosworth ◽

Pamela A. Sample ◽

Julia M. Williams ◽

Linda Zangwill ◽

Brian Lee ◽

...

Keyword(s):

Optic Disc ◽

Optic Neuropathy ◽

Spatial Relationship ◽

Glaucomatous Optic Neuropathy ◽

Automated Perimetry ◽

Relationship Of

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The photopic negative response (PhNR): measurement approaches and utility in glaucoma

International Ophthalmology ◽

10.1007/s10792-020-01515-0 ◽

2020 ◽

Vol 40 (12) ◽

pp. 3565-3576

Author(s):

Matteo Prencipe ◽

Tommaso Perossini ◽

Giampaolo Brancoli ◽

Mario Perossini

Keyword(s):

Optic Neuropathy ◽

Negative Response ◽

Photopic Negative Response ◽

Diagnostic Process ◽

Glaucomatous Optic Neuropathy ◽

Specific Information ◽

Automated Perimetry ◽

Pattern Erg ◽

Glaucomatous Damage ◽

Additional Tool

Abstract Purpose Visual electrophysiological testing continues to generate interest among glaucoma experts because of its potential help in clarifying disease pathophysiology and promoting early detection of glaucomatous damage. The photopic negative response (PhNR) is a slow negative component of the full-field electroretinogram that has been shown to provide specific information about retinal ganglion cells (RGCs) activity. The purpose of this article is to review the literature to explore the currently available measurement methods and the utility of PhNR in glaucoma diagnostic process. Methods We gathered publications related to the origins, types of stimuli used, measurements methods and applications of the PhNR of ERG in animal models and humans through a search of the literature cited in PubMed. Search terms were: “PhNR”, “photopic negative response”, “glaucoma”, “glaucomatous optic neuropathy”, “ERG”, “electroretinogram”. Results The most reliable PhNR measurements are obtained using a red stimulus on a blue background, without requiring refractive correction, fixation monitoring, or ocular media transparency. Given its direct correlation with RGCs response, the PhNR measured as baseline-to-trough (BT) represents the most reliable parameter of evaluation. Glaucoma patients with evident perimetric defects show pathologic PhNR values. Even though the PhNR is promising in detecting early RGCs impairment, distinguishing between healthy subjects and suspect patients at risk of developing glaucomatous damage still remains challenging. Conclusion The PhNR is a useful additional tool to explore disorders that affect the innermost retina, including glaucoma and other forms of optic neuropathy. In particular, comparing reports of the standard examinations (optic disc assessment, OCT RNFL measurement, standard automated perimetry) with the results of electrophysiological tests may be helpful in solving clinical diagnostic and management dilemmas. On the one hand, the PhNR of the ERG can examine the parvocellular pathways; on the other hand, the steady-state pattern ERG optimized for glaucoma screening (PERGLA) can explore the magnocellular pathways. This could give ophthalmologists a useful feedback to identify early RGCs alterations suggestive of glaucoma, stratify the risk and potentially monitor disease progression.

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Perimetric Calculator

Ophthalmology in Russia ◽

10.18008/1816-5095-2020-3-459-464 ◽

2020 ◽

Vol 17 (3) ◽

pp. 459-464

Author(s):

O. L. Fabrikantov ◽

A. V. Sukhorukova ◽

S. V. Shutova

Keyword(s):

Computer Program ◽

Information Content ◽

Open Angle Glaucoma ◽

Diagnostic Information ◽

Glaucomatous Optic Neuropathy ◽

Automated Perimetry ◽

Standard Automated Perimetry ◽

Glaucoma Diagnosis ◽

Group I ◽

Sensitivity Specificity

The paper considers the problems of the early glaucoma diagnosis before the development of the marked glaucomatous optic neuropathy. Special attention is paid to the methods of computer perimetry, which are important in diagnosing the presence or progression of glaucoma.Purpose. To create the computer program “perimetric calculator” that performs mutual recalculation of perimeter data of HFA and HEP without additional perimetric studies, as well as calculation of diagnostic information content of perimeter parameters with different “cut-off points” of HFA and HEP parameters.Patients and methods. 56 patients (85 eyes), including 16 men and 40 women aged 55 to 84 years (mean age 64.9 ± 6.4 years). All patients were divided into 2 groups: group I — 23 healthy subjects (40 eyes) without any signs of glaucoma; group II — 33 patients (45 eyes) diagnosed with the initial stage of primary open-angle glaucoma.Results and discussion. The study revealed the comparability of the standard automated perimetry (HFA) results and Heidelberg edge perimetry (HEP), determined the most informative diagnostic criterion (MD/HEP). According to the obtained results, a computer program was created, it included two modules: the first — diagnostic information content of perimeter parameters with different “cut-off points”, the second-mutual recalculation of HFA and HEP parameters.Conclusions. This computer program allows calculating the main indices of diagnostic information content of the perimeter parameters (sensitivity and specificity) at different “cut-off points”, gives the results of calculating the values of sensitivity, specificity and accuracy for at least 150 threshold values, allows performing mutual recalculation of the parameters of the standard automated perimeter (HFA) and Heidelberg perimeter (HEP).

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An Objective Structural and Functional Reference Standard for Diagnostic Studies in Glaucoma

10.1101/2020.04.10.20057836 ◽

2020 ◽

Author(s):

Eduardo B. Mariottoni ◽

Alessandro A. Jammal ◽

Samuel I. Berchuck ◽

Ivan M. Tavares ◽

Felipe A. Medeiros

Keyword(s):

High Performance ◽

Characteristic Curve ◽

Glaucomatous Optic Neuropathy ◽

Automated Perimetry ◽

Reference Standard ◽

Standard Automated Perimetry ◽

Likelihood Ratios ◽

Cross Sectional ◽

Diagnostic Studies ◽

Definition Of

AbstractPurposeTo propose a reference standard for the definition of glaucomatous optic neuropathy (GON) consisting of objective parameters from spectral-domain optical coherence tomography (SDOCT) and standard automated perimetry (SAP), and to apply it to the development and evaluation of a deep learning (DL) algorithm to detect glaucomatous damage on fundus photographs.DesignRetrospective, cross-sectional study.MethodsData were extracted from the Duke Glaucoma Registry and included 2,927 eyes of 2,025 participants with fundus photos, SDOCT and SAP acquired within six months. Eyes were classified as GON versus normal based on a combination of objective SDOCT and SAP criteria. A DL convolutional neural network was trained to predict the probability of GON from fundus photos. The algorithm was tested on an independent sample with performance assessed by sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and likelihood ratios (LR).ResultsThe test sample included 585 eyes of 405 participants. The median DL probability of glaucoma in eyes with GON was 99.8% versus 0.03% for normal eyes (P < 0.001), with an AUC of 0.92 and sensitivity of 77% at 95% specificity. LRs indicated that the DL algorithm provided large changes in the post-test probability of disease for the majority of eyes.ConclusionsThe DL algorithm had high performance to discriminate eyes with GON from normal. The newly proposed objective definition of GON used as reference standard may increase the comparability of diagnostic studies of glaucoma across devices and populations, helping to improve the development and assessment of tests in clinical practice.

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An objective structural and functional reference standard in glaucoma

Scientific Reports ◽

10.1038/s41598-021-80993-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Eduardo B. Mariottoni ◽

Alessandro A. Jammal ◽

Samuel I. Berchuck ◽

Leonardo S. Shigueoka ◽

Ivan M. Tavares ◽

...

Keyword(s):

High Performance ◽

Characteristic Curve ◽

Test Sample ◽

Glaucomatous Optic Neuropathy ◽

Automated Perimetry ◽

Reference Standard ◽

Standard Automated Perimetry ◽

Likelihood Ratios ◽

Definition Of ◽

Sensitivity Specificity

AbstractThe current lack of consensus for diagnosing glaucoma makes it difficult to develop diagnostic tests derived from deep learning (DL) algorithms. In the present study, we propose an objective definition of glaucomatous optic neuropathy (GON) using clearly defined parameters from optical coherence tomography and standard automated perimetry. We then use the proposed objective definition as reference standard to develop a DL algorithm to detect GON on fundus photos. A DL algorithm was trained to detect GON on fundus photos, using the proposed objective definition as reference standard. The performance was evaluated on an independent test sample with sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and likelihood ratios (LR). The test sample had 2118 fundus photos from 585 eyes of 405 individuals. The AUC to discriminate between GON and normal was 0.92 with sensitivity of 77% at 95% specificity. LRs indicated that the DL algorithm provided large changes in the post-test probability of disease for the majority of eyes. A DL algorithm to evaluate fundus photos had high performance to discriminate GON from normal. The newly proposed objective definition of GON used as reference standard may increase the comparability of diagnostic studies of glaucoma across devices and populations.

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