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In Humphrey visual field analyzer, the false-positive (FP) responses imply that the patient has pressed the response button despite no stimulus being seen at the time of response and FP rates >15 are flagged. The classical \"Trigger happy\" visual field has increased fixation loss, very high threshold retinal sensitivity with the values in supernormal range, \"white scotoma\" on grayscale map, high positive mean deviation (MD), glaucoma hemifield test (GHT) gives classification of \"abnormally high sensitivity, ‘Excessive high false positive' message is displayed,\" and pattern deviation probability plot has more defects than total deviation probability plot known as \"reverse cataract pattern.\" However, these classical findings are not seen in all the cases of FP as the same thumb rule cannot be applied to all the visual fields with high FP. This video emphasizes the significance of careful examination of all the parameters in a visual field printout of high FP to interpret the test results and the caution needed when an FP response is seen in a patient with advanced glaucoma. The video presents some interesting visual fields in normal and glaucoma patients and the effect of high FP responses on MD, the different classification messages displayed for GHT, patterns of total deviation probability plot and pattern deviation probability plot, and how to identify the hidden FP.

Purpose: To compare the retinal sensitivities between the blue-on-yellow perimetry (BYP)/short-wavelength automated perimetry (SWAP) and green-on-yellow perimetry (GYP) among patients with and without nuclear sclerosis among glaucoma suspects. Methods: After ophthalmic examination, patients were subjected to two perimetric tests: BYP and GYP. The visual field (VF) parameters were compared between the two perimeters (p < 0.05 was considered significant). Results: Fifty-five eyes of 39 patients with a mean age of 60.53 ± 9.70 years were included in the study. Twenty-one eyes had clear lens or pseudophakia. Twenty-six eyes had lower grades of nuclear sclerosis (NO2NC2, NO3NC3) and eight eyes had higher grades of cataract (NO4NC4, NO5NC5). The mean retinal sensitivity (RS) in BYP was 22.08 ± 5.02 (dB) and in GYP was 23.84 ± 5.50 (dB) (p = 0.08). The mean defect in BYP was -2.56 ± 4.40 (dB) and in GYP was -3.24 ± 5.05 (dB), pattern standard deviation (PSD) in BYP was 3.65 ± 1.91 (dB) and in GYP was 3.83 ± 1.99 (dB), and foveal threshold (FT) was 24.20 ± 4.32 (dB) in BYP and 28.10 ± 4.50 (dB) in GYP. The two perimeters showed good agreement by the Bland-Altman plot for all parameters. Fourteen eyes showed perimetric changes suggestive of glaucoma by BYP. In these, GYP had a sensitivity of 92.86% (95% CI of 66.13% to 99.82%) and specificity of 95.12% (95% CI of 83.47% to 99.40%). Conclusion: BYP and GYP show good agreement. They are comparable in clear media as well as in different grades of nuclear sclerosis. GYP showed good sensitivity and specificity compared to BYP.

Virtual reality-assisted visual field testing (VRVFT) is a novel modality for evaluating glaucoma progression, offering potential advantages over standard automated perimetry (SAP). To date, no narrative literature review has comprehensively discussed the benefits and drawbacks of VRVFT for glaucoma patients. A narrative literature review was conducted using PubMed and MEDLINE via EBSCOhost, covering articles published from 2014 to October 2023. The search terms used were \"virtual reality visual field\" AND \"glaucoma\". Filters applied included \"Free full text\", \"Full text\", and \"Peer Reviewed.\" Inclusion criteria encompassed studies evaluating VRVFT in relation to glaucoma. Exclusion criteria included duplicates, meta-analyses, literature not discussing glaucoma or VRVFT, and other literature reviews. Sixteen studies met the inclusion criteria, comprising various study designs. VRVFT showed comparable reliability and efficacy to SAP in detecting glaucomatous visual field defects. Benefits of VRVFT included improved accessibility, patient comfort, and resource optimization. Drawbacks included technical limitations such as restricted luminance range, lack of sophisticated eye-tracking in some devices, and implementation challenges like patient technology familiarity and access to equipment. VRVFT presents several benefits, making it a promising alternative or complement to conventional glaucomatous visual field testing in outpatient clinics and remote settings. Addressing technical limitations and standardizing protocols are essential for broader clinical adoption.

Early-stage glaucoma diagnosis is crucial for preventing permanent structural damage and irreversible vision loss. While various machine-learning approaches have been developed for glaucoma diagnosis, only a few specifically address early-stage detection. Moreover, existing early-stage detection methods rely on unimodal information and exclude subjects with high myopia, which contradicts clinical practice and overlooks the adverse effect of high myopia on prediction performance. To develop a clinically practical tool, this study proposes a deep-learning-based, end-to-end early-stage glaucoma detection framework designed for a cohort likely with high myopia. This framework uniquely integrates functional information from visual field (VF) parameters of standard automated perimetry (SAP) and Pulsar perimetry (PP) with structural information derived from optical coherence tomography (OCT) thickness maps. It comprises three key components: 3D OCT ganglion cell complex (GCC) layer segmentation, thickness map generation, and early-stage glaucoma detection. Evaluated on 394 subjects using five-time, 10-fold cross-validation, the proposed system achieved a mean area under the receiver operating characteristic (ROC) curve of 0.887 ± 0.006, outperforming the Asaoka method without transfer learning and nine models based solely on VF parameters. Results further confirmed that incorporating SAP and PP parameters was essential for mitigating the adverse effects of high myopia.

Purpose: The aim of this study was to compare the diagnostic ability of macular ganglion cell layer (GCL) analysis using spectral domain optical coherence tomography against retinal nerve fiber layer analysis (RNFL), short-wavelength automated perimetry (SWAP), and standard automated perimetry (SAP) in early detection of glaucoma. Methods: Participants fulfilling the inclusion criteria were consecutively enrolled from the glaucoma clinic of tertiary care eye hospital in Western India from November 2015 to October 2016. The subjects underwent a detailed evaluation by trained glaucoma specialists. On suspicion of glaucoma, the patients underwent SAP, SWAP, and SD-OCT for GCL and RNFL analysis. Results: There were 91 patients in total of which experts classified 54 eyes into GON and 37 eyes into nonglaucomatous group. Sensitivity of SAP (42.59%) was significantly lower (P < 0.05) than that of average GCL thickness (79.63%) and average RNFL thickness (72.22%). Specificity and positive LR of SWAP (97.3% and 19.19, respectively) and SAP (94.6% and 7.88, respectively) were greater than those of GCL (81.08% and 4.21) and RNFL (67.57% and 2.23) parameters. Negative LR of average GCL thickness (0.25) was superior to that of average RNFL thickness (0.411), SWAP (0.495), and SAP (0.607). Conclusion: Macular GCL parameters perform better than RNFL parameters in patients with early glaucomatous damage. There is superior ability of SWAP over SAP in detecting glaucomatous changes in glaucoma suspect group. GCL thickness analysis has higher sensitivity and negative likelihood ratio, whereas SWAP had higher specificity and positive likelihood ratio. Thus, combining both tests can lead to better diagnostic ability for early glaucomatous damage.

PurposeTo evaluate the screening accuracy of an Eye Movement Perimetry (EMP) in comparison with Frequency Doubling Perimetry (FDP) and to investigate the patient preference and perception towards these visual field screening methods.MethodsA total of 104 healthy subjects (mean age (SD) of 48 (14) years) and 73 glaucoma patients (mean age (SD) of 52 (13) years) were recruited. All the participants underwent a comprehensive ophthalmic evaluation including the 24-2 SITA standard protocol on the Humphrey Field Analyzer (HFA). This was followed by the 26-point protocol in EMP and the C-20-1 protocol in FDP. During EMP, all subjects were instructed to fixate a central target and to look at the detected peripheral target, followed by refixation of the central target and Saccadic Reaction Time (SRT) towards each of the “seen” stimuli was calculated. Next, a questionnaire was administered to evaluate the patient preference and perception towards the perimetry techniques. Mean SRTs and Robin scores were used to plot Receiver Operating Characteristics (ROC) curves to determine the screening accuracies. From the questionnaire survey, the frequency distributions of the responses were calculated.ResultsRobin score and SRT were significantly increased in glaucoma patients in comparison with the age-matched healthy subjects (p < 0.001). The ROC analysis revealed comparable Area Under the Curve (AUC) values (0.95, p = 0.81) with a specificity of 95.2% for FDP and 96.2% for EMP with a sensitivity of 87.7%. Thirty-seven percent of the older age group (≥ 40 years) and 65% of severe glaucoma patients showed preference for EMP over FDP.ConclusionsThis study results indicate that the customized protocol in EMP provides efficient and rapid means of screening visual field defects in glaucoma, which compared well with FDP. Elderly healthy participants and patients with moderate and severe glaucomatous defects preferred EMP as it permitted natural reflexive eye movements thereby resembling a real-life test setting.

Purpose of ReviewIn this review, we will describe current methods for visual field testing in neuro-ophthalmic clinical practice and research, develop terminology that accurately describes patterns of field deficits, and discuss recent advances such as augmented or virtual reality-based perimetry and the use of artificial intelligence in visual field interpretation.Recent FindingsNew testing strategies that reduce testing times, improve patient comfort, and increase sensitivity for detecting small central or paracentral scotomas have been developed for static automated perimetry. Various forms of machine learning-based tools such as archetypal analysis are being tested to quantitatively depict and monitor visual field abnormalities in optic neuropathies. Studies show that the combined use of optical coherence tomography and standard automated perimetry to determine the structure-function relationship improves clinical care in neuro-ophthalmic disorders.SummaryVisual field assessment must be performed in all patients with neuro-ophthalmic disorders affecting the afferent visual pathway. Quantitative visual field analysis using standard automated perimetry is critical in initial diagnosis, monitoring disease progression, and guidance of therapeutic plans. Visual field defects can adversely impact activities of daily living such as reading, navigation, and driving and thus impact quality of life. Visual field testing can direct appropriate occupational low vision rehabilitation in affected individuals.

Myopic eyes have an increased risk of glaucoma. However, glaucomatous changes in a myopic eye are often difficult to detect. Classic structural and functional investigations to diagnose glaucoma may be confounded by myopia. Here, we identify some of the common pitfalls in interpreting these structural parameters, and the possible solutions that could be taken to overcome them. For instance, in myopic eyes, we discuss the limitations and potential sources of error when using neuroretinal rim parameters, and retinal nerve fibre layer and ganglion cell-inner plexiform layer thickness measurements. In addition, we also review new developments and potential adjuncts in structural imaging such as the assessment of the retinal nerve fibre layer texture, and the examination of the microcirculation of the optic nerve head using optical coherence tomography angiography. For the functional assessment of glaucoma, we discuss perimetric strategies that may aid in detecting characteristic visual field defects in myopic glaucoma. Ultimately, the evaluation of glaucoma in myopia requires a multimodal approach, to allow correlation between structural and functional assessments. This review provides overview on how to navigate this diagnostic dilemma.

To compare virtual reality (VR) perimetry with perimetry conducted using the Humphrey visual field (HVF). A retrospective, single-center study was conducted on patients with diagnoses of: ocular hypertension, glaucoma suspect, or glaucoma who had both HVF and VR 24-2 visual field testing performed as a part of their routine eye examination. Results from both devices were compared on: test duration, test preference, mean deviation (MD), pattern standard deviation (PSD), and point-by-point sensitivity. Seventy-nine eyes were evaluated from 50 patients with a mean age of 72.1 ± 11.8 years. Of the 79 eyes, 8 had ocular hypertension or were glaucoma suspects, 24 had mild glaucoma, 28 had moderate glaucoma, and 19 had severe glaucoma. The average test duration by HVF was significantly greater (HVF: 253 ± 65 sec vs. VR: 122 ± 6 sec, p < 0.001). Strong correlations for both MD (r = 0.82, p < 0.001) and PSD (r = 0.85, p < 0.001) were observed between HVF and VR perimetry. Point-by-point evaluation did not detect systematic differences in sensitivity between HVF and VR perimetry. Of the 48 patients who completed both tests, 41 (85.4%) indicated a preference for VR perimetry and 7 (13.6%) felt neutral between VR perimetry and HVF. These findings demonstrate that results from HVF and VR perimetry may be comparable. While a majority of the patients preferred VR perimetry, additional studies will be necessary to assess whether VR perimetry can serve as a useful adjunct in monitoring glaucoma.