Wavelet decomposition analysis in the two-flash multifocal ERG in early glaucoma: a comparison to ganglion cell analysis and visual field.
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ABSTRACT:
SUBMITTER: Brandao LM
PROVIDER: S-EPMC5532413 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:It is often said that substantial retinal ganglion cells are lost before glaucomatous damage is detected by standard automated perimetry. There are 4 key articles referenced to support this belief. To test the hypothesis that the 4 key articles are incorrectly cited, the publications in the first 6 months of 2019 that reference 1 or more of these 4 articles were examined. In particular, the degree to which the quotes from these 2019 publications accurately reflected the evidence in the 4 key articles was assessed. These quotes are inadequately supported by the data, and in some cases even by the conclusions found in the abstracts of the key articles. This is despite several review articles that have questioned the evidence in these key articles. Further, a case can be made that the evidence in the key articles better supports the opposite conclusion. That is, the data suggest that sensitivity loss can be seen on standard automated perimetry before retinal ganglion cells are missing.
| S-EPMC7343057 | biostudies-literature
Project description:To study the performance of multifocal-visual-evoked-potential (mfVEP) signals filtered using empirical mode decomposition (EMD) in discriminating, based on amplitude, between control and multiple sclerosis (MS) patient groups, and to reduce variability in interocular latency in control subjects.MfVEP signals were obtained from controls, clinically definitive MS and MS-risk progression patients (radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS)). The conventional method of processing mfVEPs consists of using a 1-35 Hz bandpass frequency filter (XDFT). The EMD algorithm was used to decompose the XDFT signals into several intrinsic mode functions (IMFs). This signal processing was assessed by computing the amplitudes and latencies of the XDFT and IMF signals (XEMD). The amplitudes from the full visual field and from ring 5 (9.8-15° eccentricity) were studied. The discrimination index was calculated between controls and patients. Interocular latency values were computed from the XDFT and XEMD signals in a control database to study variability.Using the amplitude of the mfVEP signals filtered with EMD (XEMD) obtains higher discrimination index values than the conventional method when control, MS-risk progression (RIS and CIS) and MS subjects are studied. The lowest variability in interocular latency computations from the control patient database was obtained by comparing the XEMD signals with the XDFT signals. Even better results (amplitude discrimination and latency variability) were obtained in ring 5 (9.8-15° eccentricity of the visual field).Filtering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies. This could be applied to assess visual cortex activity in MS diagnosis and evolution studies.
| S-EPMC5909914 | biostudies-literature
Project description:Background/aimsTo evaluate the association of macular vessel density (VD) and ganglion cell complex (GCC) thickness with 10-2 central visual field (CVF) progression in glaucoma.MethodsIn this retrospective cohort study, patients with glaucoma from Diagnostic Innovation in Glaucoma Study with≥five 10-2 visual field (VF) tests and 3-year follow-up before optical coherence tomography (OCT) and OCT angiography (OCTA) imaging were included. Whole-image GCC thickness (wiGCC) and superficial VD (wiVD) were obtained from 6*6 macula scans. The association of wiVD and wiGCC with past rate of 10-2 VF mean deviation worsening, and with past CVF progression (defined using clustered linear regression criteria) was evaluated using linear mixed models after adjusting for confounders.ResultsFrom 238 eyes (141 patients), 25 eyes (11%) of 16 patients were CVF progressors. In the multivariable analysis of the association between OCT/OCTA parameters and past rate of 10-2 CVF worsening, lower wiVD (β=-0.04 (-0.05, -0.02); p<0.001; R2=0.32) and wiGCC (β=-0.01 (-0.01, 0.00); p=0.004; R2=0.21) were significantly associated with faster CVF worsening. For the association between OCT/OCTA parameters and past CVF progression, the multivariable analysis showed that a lower wiVD was significantly associated with increased odds of past CVF progression (OR=1.23 (1.06, 1.44) per 1% lower; p=0.008), while wiGCC did not show correlation.ConclusionsLower macular VD and GCC were associated with faster worsening of CVF, and lower macular VD was associated with increased odds of CVF progression. Assessment of macular OCT and OCTA may help detect glaucoma eyes with CVF progression.
| S-EPMC10033463 | biostudies-literature
Project description:[This corrects the article DOI: 10.1371/journal.pone.0194964.].
| S-EPMC5929517 | biostudies-literature
Project description:(1) Background: to investigate the correlation between structural (retinal ganglion cells and retinal nerve fibers) and functional alterations analyzed point-by-point in the central 10 degrees of the visual field of patients with advanced glaucoma using Humphrey 10-2 visual field tests. (2) Methods: Single-center prospective cohort study carried on from October 2018 to February 2019 at the Croix-Rousse hospital, Lyon, France. The primary outcome measure was the point-by-point correlation between retinal sensitivity (Humphrey 10-2) and retinal ganglion cell complex (GCC) thickness. (3) Results: 29 eyes of 27 patients were examined. Of these, 15 eyes had a mean deviation (MD) less than -20 dB. There were statistically significant linear relationships between GCC thickness and 10-2 visual field sensitivity for several points in the lower part of the visual field, with lower retinal sensitivity being associated with thicker GCC layers. There were no strong linear relationships or statistically significant correlations in the other regions of the visual field. For the patients with MD < -20 dB, there were statistically significant linear relationships between GCC thickness and 10-2 visual field sensitivity for several points in the superior nasal region. Retinal sensitivity was not correlated with retinal nerve fibre layer thickness. (4) Conclusions: In this study of patients with advanced glaucoma, GCC thickness was linearly associated with 10-2 visual field sensitivity in certain regions, negatively for patients with less-severe glaucoma. The initial thickening raises questions about the apoptosis mechanism, while the thinning observed in the most severe cases is consistent with the ganglion cell death identified on visual field tests.
| S-EPMC9409684 | biostudies-literature
Project description:Purpose:To quantify visual field (VF) variability as a function of threshold sensitivity and location, and to compare weighted pointwise linear regression (PLR) with unweighted PLR and pointwise exponential regression (PER) for data fit and prediction ability. Methods:Two datasets were used for this retrospective study. The first was used to characterize and estimate VF variability, and included a total of 4,747 eyes of 3,095 glaucoma patients with six or more VFs and 3 years or more of follow-up. After performing PER for each series, standard deviation of residuals was quantified for each decibel of sensitivity as a measure of variability. A separate dataset was used to test and compare unweighted PLR, weighted PLR, and PER for data fit and prediction, and included 261 eyes of 176 primary open-angle glaucoma patients with 10 or more VFs and 6 years or more of follow-up. Results:The degree of variability changed as a function of threshold sensitivity with a zenith and a nadir at 33 and 11 dB, respectively. Variability decreased with eccentricity and was higher in the central 10° (P < 0.001). Differences among the methods for data fit were negligible. PER was the best model to predict future sensitivity values in the mid term and long term. Conclusions:VF variability increases with the severity of glaucoma damage and decreases with eccentricity. Weighted linear regression neither improves model fit nor prediction. PER exhibited the best prediction ability, which is likely related to the nonlinear nature of long-term glaucomatous perimetric decay. Translational Relevance:This study suggests that taking into account heteroscedasticity has no advantage in VF modeling.
| S-EPMC6798312 | biostudies-literature
Project description:BackgroundTo develop a deep neural network able to differentiate glaucoma from non-glaucoma visual fields based on visual filed (VF) test results, we collected VF tests from 3 different ophthalmic centers in mainland China.MethodsVisual fields obtained by both Humphrey 30-2 and 24-2 tests were collected. Reliability criteria were established as fixation losses less than 2/13, false positive and false negative rates of less than 15%.ResultsWe split a total of 4012 PD images from 1352 patients into two sets, 3712 for training and another 300 for validation. There is no significant difference between left to right ratio (P?=?0.6211), while age (P?=?0.0022), VFI (P?=?0.0001), MD (P?=?0.0039) and PSD (P?=?0.0001) exhibited obvious statistical differences. On the validation set of 300 VFs, CNN achieves the accuracy of 0.876, while the specificity and sensitivity are 0.826 and 0.932, respectively. For ophthalmologists, the average accuracies are 0.607, 0.585 and 0.626 for resident ophthalmologists, attending ophthalmologists and glaucoma experts, respectively. AGIS and GSS2 achieved accuracy of 0.459 and 0.523 respectively. Three traditional machine learning algorithms, namely support vector machine (SVM), random forest (RF), and k-nearest neighbor (k-NN) were also implemented and evaluated in the experiments, which achieved accuracy of 0.670, 0.644, and 0.591 respectively.ConclusionsOur algorithm based on CNN has achieved higher accuracy compared to human ophthalmologists and traditional rules (AGIS and GSS2) in differentiation of glaucoma and non-glaucoma VFs.
| S-EPMC6172715 | biostudies-literature
Project description:PURPOSE:To develop a visual field (VF) feature model to predict the reversal of glaucoma hemifield test (GHT) results to within normal limits (WNL) after 2 consecutive outside normal limits (ONL) results. DESIGN:Retrospective cohort study. PARTICIPANTS:Visual fields of 44?503 eyes from 26?130 participants. METHODS:Eyes with 3 or more consecutive reliable VFs measured with the Humphrey Field Analyzer (Swedish interactive threshold algorithm standard 24-2) were included. Eyes with ONL GHT results for the 2 baseline VFs were selected. We extracted 3 categories of VF features from the baseline tests: (1) VF global indices (mean deviation [MD] and pattern standard deviation), (2) mismatch between baseline VFs, and (3) VF loss patterns (archetypes). Logistic regression was applied to predict the GHT results reversal. Cross-validation was applied to evaluate the model on testing data by the area under the receiver operating characteristic curve (AUC). We ascertained clinical glaucoma status on a patient subset (n = 97) to determine the usefulness of our model. MAIN OUTCOME MEASURES:Predictive models for GHT results reversal using VF features. RESULTS:For the 16?604 eyes with 2 initial ONL results, the prevalence of a subsequent WNL result increased from 0.1% for MD < -12 dB to 13.8% for MD ?-3 dB. Compared with models with VF global indices, the AUC of predictive models increased from 0.669 (MD ?-3 dB) and 0.697 (-6 dB ? MD < -3 dB) to 0.770 and 0.820, respectively, by adding VF mismatch features and computationally derived VF archetypes (P < 0.001 for both). The GHT results reversal was associated with a large mismatch between baseline VFs. Moreover, the GHT results reversal was associated more with VF archetypes of nonglaucomatous loss, severe widespread loss, and lens rim artifacts. For a subset of 97 eyes, using our model to predict absence of glaucoma based on clinical evidence after 2 ONL results yielded significantly better prediction accuracy (87.7%; P < 0.001) than predicting GHT results reversal (68.8%) with a prescribed specificity 67.7%. CONCLUSIONS:Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.
| S-EPMC6706864 | biostudies-literature
Project description:PurposeTo design a mathematical model that can predict the relationship between the ganglion cell complex (GCC) thickness and visual field sensitivity (VFS) in glaucoma patients.DesignRetrospective cross-sectional case series.MethodWithin 3 months from VFS measurements by the Humphrey field analyzer 10-2 program, 83 eyes underwent macular GCC thickness measurements by spectral-domain optical coherence tomography (SD-OCT). Data were used to construct a multiple logistic model that depicted the relationship between the explanatory variables (GCC thickness, age, sex, and spherical equivalent of refractive errors) determined by a regression analysis and the mean VFS corresponding to the SD-OCT scanned area. Analyses were performed in half or 8 segmented local areas as well as in whole scanned areas. A simple logistic model that included GCC thickness as the single explanatory variable was also constructed. The ability of the logistic models to depict the real GCC thickness/VFS in SAP distribution was analyzed by the ?2 test of goodness-of-fit. The significance of the model effect was analyzed by analysis of variance (ANOVA).ResultsScatter plots between the GCC thickness and the mean VFS showed sigmoid curves. The ?2 test of goodness-of-fit revealed that the multiple logistic models showed a good fit for the real GCC thickness/VFS distribution in all areas except the nasal-inferior-outer area. ANOVA revealed that all of the multiple logistic models significantly predicted the VFS based on the explanatory variables. Although simple logistic models also exhibited significant VFS predictability based on the GCC thickness, the model effect was less than that observed for the multiple logistic models.ConclusionsThe currently proposed logistic models are useful methods for depicting relationships between the explanatory variables, including the GCC thickness, and the mean VFS in glaucoma patients.
| S-EPMC4136731 | biostudies-literature
Project description:BackgroundAcute angle-closure glaucoma (AACG) is an ophthalmic emergency that occurs over the course of hours or days and may cause irreversible blindness if not treated immediately. In most cases, optic nerve damage is the cause of visual field (VF) loss in AACG. There has been no reliable biomarker found to evaluate optic nerve damage to date. Aqueous humor (AH) proteome analysis might reveal the proteomic alterations in AACG and provide helpful clues in the search for an AH biomarker of optic nerve damage and VF loss.MethodsIn this study, we used the AH proteome to explore the functions of differentially expressed proteins (DEPs) during disease progression. The AH proteins from the early-stage group and late-stage group were extracted and analyzed by the data-independent acquisition (DIA) method. The DEPs functions were annotated, and parallel reaction monitoring (PRM) was used to validate the key DEPs.ResultsA total of 87 DEPs were found. Gene Ontology analysis showed that most DEPs were enriched in immunology, hemodynamics, and apoptosis. Ingenuity pathway analysis found that vascular endothelial growth factor (VEGF) signaling, the production of reactive oxygen species (ROS) in macrophages, and the nuclear factor erythroid 2-related factor 2 (NRF2)-mediated oxidative stress response were active pathways in the late stage of AACG. The mechanism of retinal ganglion cell (RGC) death was hypothesized on the basis of DEP functional analysis. A total of 20 DEPs were validated by using PRM, and prostaglandin-H2 D-isomerase was found to have the potential to evaluate optic nerve damage.ConclusionsThis study showed that AH proteomic analysis could reveal the proteomic alterations in the pathogenesis of VF loss in AACG and help to provide objective protein biomarkers to evaluate VF loss. These findings will benefit the application of the AH proteome to clinical research.
| S-EPMC8640911 | biostudies-literature