Translational Vision Science & Technology

BackgroundStereopsis is a critical visual function, however clinical stereotests are time-consuming, coarse in resolution, suffer low test-retest repeatability, and poor agreement with other tests. We developed AIM Stereoacuity to address these limitations and asked whether it could deliver reliable, efficient, and precise stereo-thresholds across stimulus types and disparity signs. MethodsObservers reported the orientation of 5x1.25{degrees} bar defined by disparity of random dots embedded in a 6{degrees} diameter circular cell, presented in a 4*4 grid. Bar disparity was scaled from {+/-} 2{sigma} relative to a threshold and slope-estimate, initially set by the experimenter and adaptively updated. Orientation report errors (indicated vs. actual bar-orientation) were fit with a cumulative Gaussian function to derive stereo-thresholds. Twenty-one normally-sighted observers were tested with red-blue anaglyphs in crossed and uncrossed disparity signs across 4 element-types (8.5arcmin broadband dots, or band-pass difference of Gaussians with peak Spatial-Frequency (SF) of 2, 4, or 6 c/{degrees}). We analyzed stereoacuities, test durations, and the test-retest repeatability. ResultsAcross SFs and observers, test duration for a chart were 36 and 40 secs for measuring crossed and uncrossed disparity, respectively. There was no effect of disparity sign or SF (Kruskal-Wallis; p>0.05). Median log stereo-thresholds averaged across all SFs were 1.90 and 1.84 log arcsec for crossed and uncrossed disparities, respectively. Crossed and uncrossed disparities were moderately correlated across SFs(r=0.44 to 0.79; median=0.54). Test-retest biases were 0.01 arcsec (p=0.45) and 0.10 arcsec (p= 0.001) for crossed and uncrossed disparities, respectively. ConclusionsThe results for the response-adaptive, self-administered AIM Stereoacuity method showed no significant stereo-thresholds differences between broad- and narrow-band stimuli. The test delivers repeatable results for crossed disparity in approximately 80 seconds.

PurposeTo train and evaluate segmentation-free 3D convolutional neural network (3DCNN) models for estimating visual field (VF) from optical coherence tomography (OCT) images and to independently assess the longitudinal variability and progression detection capabilities of Humphrey Field Analyzer (HFA) measurements and OCT-based estimated VF (OCT-VF) in a diverse clinical population. DesignRetrospective multicenter study. Participants13,366 patients (24,313 eyes) underwent HFA tests (24-2, trimmed 30-2, or 10-2 test patterns) and macular OCT imaging at five ophthalmic institutions. The dataset included 129,007 paired OCT-VF data points representing various ocular conditions. MethodsWe trained segmentation-free 3DCNN models using comprehensive OCT datasets without disease-specific exclusions, employing 10-fold cross-validation to estimate VF thresholds and mean deviation (MD). Unlike previous studies, we independently assessed both OCT-VF and HFA measurements by creating separate longitudinal datasets with standardized measurement counts and observation periods for comparative analysis, enabling direct evaluation of clinical reliability. We analyzed absolute residual variability from regression lines using jackknife resampling, applied Bonferroni correction for multiple comparisons, and used Spearmans correlation for progression analysis. Main Outcome MeasuresOCT-VF and HFA VF agreement, residual variability, progression detection rates, and progression rate correlations. ResultsOCT-VF and HFA VF showed correlations (Pearsons r: 24-2 thresholds 0.863, MD 0.924; 10-2 thresholds 0.881, MD 0.939; all p < 0.001). OCT-VF demonstrated significantly lower residual variability than HFA for all parameters (OCT-VF vs. HFA: 0.58 vs. 1.12 dB for 24-2 MD; 0.70 vs. 1.12 dB for 10-2 MD; all p < 0.001). This advantage persisted across all test points (mean variability reduction: 60.4% for 24-2; 55.1% for 10-2), age groups, and most severity levels. OCT-VF identified more progression events (24-2 MD: 113% more, 10-2 MD: 48.6% more). MD slopes showed correlations between OCT-VF and HFA (Pearsons r: 24-2 MD 0.831, 10-2 MD 0.863; all p < 0.001). ConclusionsThe segmentation-free 3DCNN models objectively estimated VF from OCT images with significantly lower longitudinal variability than performance-dependent HFA measurements across diverse ocular conditions. The lower variability of OCT-VF enhances statistical power for progression detection, suggesting its clinical potential as a complementary tool derived from routine OCT data, decreasing measurement noise, and enabling more timely therapeutic interventions.

PurposeTo determine the repeatability of a clinical pupillometer in healthy participants with a 5 and 30-minute test-retest break for both Swinging-Flashlight and Low-High Luminance approach. Methods20 healthy participants (mean age: 27 years {+/-}5; 9 females) placed their heads into the devices headrest and fixated a central spot. A Swinging-Flashlight approach evoked a pupillary light reflex, stimulating alternatingly 8 times each eye by a brief diffuse white light flash followed by a continuous measurement of constriction and dilation of the direct and consensual pupils. For the Low-High Luminance setting, continuous measurements of pupil diameters for a 5 second low luminance display followed by a 5 second high luminance white light. Pupillary light reflex parameters for each test and each eye were calculated by the device. Repeatability was investigated after a 5-minute break time and during a control experiment for 21 participants after a 30-minute break for each approach in counterbalanced order using Bland-Altman analysis. ResultsOverall, many parameters for both Swinging-Flashlight and Low-High Luminance approach showed retest biases for all pupil light reflex parameters after a 5-minute test-retest break. These biases were almost completely reduced after a 30-minute break between test and retest for both approaches. The test-retest variabilities as expressed using the Coefficient of Repeatability was reduced after 30-minutes for the majority of the Low-High Luminance results but not for results of the Swinging-Flashlight method. ConclusionsClinical pupillometry includes the Swinging Flashlight Test (SFL) and Low-High Luminance assays. In SFL, many pupillary dynamic metrics showed test-retest bias at a 5-minute interval, whereas relative afferent pupillary defect (RAPD) measurements remained unbiased at both 5 and 30-minute intervals. Similarly, Low-High Luminance testing showed minimal bias after 30 minutes but exhibited bias at the 5-minute interval. Thus, when evaluating multiple pupillary parameters in scientific or clinical settings, RAPD is less susceptible to bias, while other metrics require longer intervals between testing and retesting.

ObjectiveTo assess the efficacy and safety of the PRIMA subretinal neurostimulation system 48-months post-implantation for improving visual acuity (VA) in patients with geographic atrophy (GA) due to age-related macular degeneration (AMD) at 48-months post-implantation. DesignFirst-in-human clinical trial of the PRIMA subretinal prosthesis in patients with atrophic AMD, measuring best-corrected ETDRS VA (Clinicaltrials.gov NCT03333954). SubjectsFive patients with GA, no foveal light perception and VA of logMAR 1.3 to 1.7 in their worse-seeing "study" eye. MethodsIn patients implanted with a subretinal photovoltaic neurostimulation array containing 378 pixels of 100 m in size, the VA was measured with and without the PRIMA system using ETDRS charts at 1 meter. The systems external components: augmented reality glasses and pocket computer, provide image processing capabilities, including zoom. Main Outcome MeasuresVA using ETDRS charts with and without the system. Light sensitivity in the central visual field, as measured by Octopus perimetry. Anatomical outcomes demonstrated by fundus photography and optical coherence tomography up to 48-months post- implantation. ResultsAll five subjects met the primary endpoint of light perception elicited by the implant in the scotoma area. In one patient the implant was incorrectly inserted into the choroid. One subject died 18-months post-implantation due to study-unrelated reason. ETDRS VA results for the remaining three subjects are reported herein. Without zoom, VA closely matched the pixel size of the implant: 1.17 {+/-} 0.13 pixels, corresponding to mean logMAR 1.39, or Snellen 20/500, ranging from 20/438 to 20/565. Using zoom at 48 months, subjects improved their VA by 32 ETDRS letters versus baseline (SE 5.1) 95% CI[13.4,49.9], p<0.0001. Natural peripheral visual function in the treated eye did not decline after surgery compared to the fellow eye (p=0.08) during the 48 months follow-up period. ConclusionsSubretinal implantation of PRIMA in subjects with GA suffering from profound vision loss due to AMD is feasible and well tolerated, with no reduction of natural peripheral vision up to 48-months. Using prosthetic central vision through photovoltaic neurostimulation, patients reliably recognized letters and sequences of letters,and with zoom it provided a clinically meaningful improvement in VA of up to eight ETDRS lines.

PurposeTo assess accuracy and adherence of visual field (VF) home-monitoring in a pilot sample of glaucoma patients. DesignProspective longitudinal observation. MethodsTwenty adults (median 71 years) with an established diagnosis of glaucoma were issued a tablet-perimeter (Eyecatcher), and were asked to perform one VF home-assessment per eye, per month, for 6 months (12 tests total). Before and after home-monitoring, two VF assessments were performed in-clinic using Standard Automated Perimetry (SAP; 4 tests total, per eye). ResultsAll 20 participants could perform monthly home-monitoring, though one participant stopped after 4 months (Adherence: 98%). There was good concordance between VFs measured at home and in the clinic (r = 0.94, P < 0.001). In 21 of 236 tests (9%) Mean Deviation deviated by more than {+/-}3dB from the median. Many of these anomalous tests could be identified by applying machine learning techniques to recordings from the tablets front-facing camera (Area Under the ROC Curve = 0.78). Adding home-monitoring data to 2 SAP tests made 6 months apart reduced measurement error (between-test measurement variability) in 97% of eyes, with mean absolute error more than halving in 90% of eyes. Median test duration was 4.5mins (Quartiles: 3.9-5.2mins). Substantial variations in ambient illumination had no observable effect on VF measurements (r = 0.07, P = 0.320). ConclusionsHome-monitoring of VFs is viable for some patients, and may provide clinically useful data.

PurposeThis proof-of-concept aimed to evaluate the feasibility of targeted, image-guided microperimetry (IGMP) by integrating Optical Coherence Tomography (OCT) and Fundus Autofluorescence (FAF) for lesion mapping and functional assessment in retinal atrophic diseases. Methods22 eyes were identified, of which 17 had early geographic atrophy (GA) while 5 had Stargardt Disease (SD). Disease transition zones (TZs) on OCT and FAF were annotated onto enface infrared images. These were then exported with microperimetry assessments to custom MATLAB applications. IGMP patterns were thereafter created and imported using MAIA and Nidek microperimeters for subsequent scans. Mean procedure and examination times (mins), retinal sensitivity (dB), approach feasibility, and algorithm compatibility of targeted IGMP were reported as outcomes. ResultsTargeted IGMP was quicker than the standard 10-2 grid for both SD and GA lesion assessments. SD cases showed longer mean procedure and examination times and lower mean retinal sensitivity in all zones compared to GA lesions. Targeted IGMP procedure was lengthier for Nidek (29.2{+/-}7.1 mins) than MAIA (17.4{+/-}4.3 mins) although examination took longer on MAIA (4.0{+/-}1.0 mins) than on Nidek (3.6{+/-}1.2 mins). Overall, IGMP approach is feasible (100.0%) and the algorithm is compatible (100.0%) on both MP devices for all subjects tested. ConclusionsThis study establishes the feasibility of an IGMP workflow in providing targeted functional assessments in retinal degenerative diseases. Our approach may help enhance structure- function correlation and optimize the efficiency of microperimetry integration for clinical trials. Further validation in larger cohorts is needed to assess its broader clinical applicability.

PurposeFluorescein staining (FS) is a standard method of assessing corneal epithelium (CE) integrity. However, the equipment and personnel required for FS may be unavailable in low-resource environments. We developed and validated a low-cost, noninvasive, and quantitative CE evaluation pipeline using a custom smartphone attachment and convolutional neural networks (CNNs). MethodsA 3D-printed smartphone attachment and placido disk illumination module was attached to a OnePlus 7 Pro smartphone. 26 smartphone-acquired images were obtained from 15 subjects, comprising a dataset including healthy eyes and corneal epitheliopathies of Oxford grade I-V. A classifier CNN was trained on 8 subjects (23,173 image patches) to identify areas of suspected epithelial disruption, and validated on 7 subjects (10,883 image patches). The fraction of disrupted corneal surface area (FDSA) was computed for each subject from the model output. Results were compared with FS slit lamp photos which were independently graded by two clinicians using the Oxford scheme. ResultsFDSA showed promise as a non-invasive marker of CE integrity, with mean FDSA in the Oxford >II cohort being higher than the Oxford [&le;]II cohort (p = 0.04 and p = 0.09 using Oxford scores from each clinician, respectively). Additionally, areas of CE disruption identified by our smartphone-based technique showed qualitative concordance with those revealed by FS. ConclusionsOur technique for smartphone-based CE imaging and automated analysis is a promising low-cost, noninvasive method to quantitatively evaluate the CE. Translational RelevanceThis tool can be used to evaluate ocular surface disease in low-resource regions.

ObjectivesTo optimize stimulation parameters for electroretionographic recordings of the multifocal photopic negative response (mfPhNR) for the detection of glaucoma and to compare the diagnostic accuracy of electrophysiological, structural and functional measures of glaucoma. MethodsIn 24 healthy controls, 10 glaucoma suspects (GLAS) and 16 glaucoma participants (GLAG), mfPhNR for 6 different stimulation rates were assessed to compare their discrimination performance. Subsequently, a cross-modal comparison of the mfPhNR/b-wave ratio was performed with pattern electroretinogram (PERG), and peripapillary retinal nerve fiber layer (pRNFL) thickness. These analyses were based on area under curves (AUC) obtained from receiver-operating-characteristics (ROC) analyses and step-wise regression analyses. ResultsCompared to the other mfPhNR-conditions, the PhNR/b-wave ratio for the fastest stimulation condition had the highest AUC for GLAS(0.84, P = 0.008, 95%CI: 0.71-0.98); the other modalities, i.e., PERG-amplitude and pRNFL had AUCs of 0.77, and 0.74 respectively. pRNFL was the significant predictor for mfPhNR/b-wave ratio [t (48) = 4, P 0.0002]. ConclusionsFast mfPhNR protocols outperform other mf-protocols in the identification of glaucomatous damage especially for GLAS and thus aid the early detection of glaucoma. SignificancemfPhNR recordings might serve as surrogate marker of ganglion cell dysfunction especially in glaucoma suspects.

Background/ObjectivesVirtual Reality (VR) eye trackers offer portable, objective tools for neuro-ophthalmic testing. This study evaluated the feasibility, reproducibility and reliability of a VR eye tracker (BulbiCAM) compared to wearable eye-tracking glasses (PupilLabs Neon glasses), highlighting its potential clinical utility and feasibility. Subjects/MethodsA prospective study involving 39 healthy participants (mean age{+/-}SD = 30.0 {+/-} 9.5 years) assessed inter-visit reproducibility of BulbiCAM tests across two visits. Pupillary light reflex tests were conducted with both BulbiCAM and PupilLabs Neon, enabling paired assessments. Reproducibility was analysed using intra-class correlation coefficients (ICC), reliability via Bland-Altman analysis, and participant experience through a survey evaluating test comfort and usability. ResultsParticipants feedback (n=27) highlighted high acceptability for BulbiCAM: 89% found the test comfortable, 92.6% felt the testing duration was appropriate, and 81.5% reported no eye strain or fatigue. Inter-visit reproducibility of Bulbicam tests showed high reproducibility for pursuit and pupil tests (ICC= 0.88-0.76), while saccadic tasks showed lower reproducibility (best ICC at 0.62). Paired assessments between devices showed close agreement for key pupillometer metrics: baseline diameter (bias: -0.48 {+/-} 0.47 mm), peak constriction diameter (bias: -0.56 {+/-} 0.36 mm), constriction velocity (bias: 0.22 {+/-} 0.58 mm/s), and duration of constriction (bias: -0.052 {+/-} 0.15 s). ConclusionsThis study highlights the clinical feasibility of BulbiCAM, with high patient acceptability and reproducibility for pursuit and pupil tests. Paired assessments confirmed its accuracy for key pupillometric parameters, validating its reliability for clinical and research use.

PurposeAspheric planning in laser refractive surgery remains difficult: surgeons often rely on empirical nomo-grams or simple linear regression for defocus and astigmatism, while console Q-factor modulation yields a variably predictable effect on asphericity and an inconsistent cross-effect on defocus. This translational methods proof-of-concept frames planning as supervised prediction of console-programmable inputs (de-focus, astigmatism, Q-factor) and evaluates competing models; it is not a clinical effectiveness study. MethodsWe analyzed an anonymized, retrospective, single-platform dataset of 2,448 complete-case treatments. Multi-output regressors (linear and nonlinear) were trained and compared using prespecified metrics (R2, MAE/MSE) and residual-distribution visualization/calibration. Actuator-response checks related programmed inputs to changes in defocus (Z20) and primary spherical aberration (Z40). External validation used a temporally later, device-shift cohort (n=147). ResultsLinear regression predicted defocus and astigmatism well (e.g., defocus R2=0.98) but degraded for Q-factor (R2=0.47), whereas nonlinear models improved Q-factor error and calibration. Actuator-response analyses showed strong coupling for defocus input (R2=0.97), moderate coupling of Q-factor to {Delta}Z40 (R2=0.51), and a weak Q[-&gt;]defocus cross-effect (R2=0.12). On external validation, the best model generalized: Defocus MAE 0.22 D (R2=0.98) and Q-factor MAE 0.21 (R2=0.81). ConclusionsSupervised nonlinear multi-output models achieve lower error and better calibration for Q-factor than linear baselines, supporting a metric-driven pathway toward more reliable control of low-order refractive targets and primary asphericity. Potential clinical implications include tissue sparing, improved contrast, and near-vision gains. Prospective, human-in-the-loop evaluation with safety and patient-reported endpoints is warranted.

ObjectiveStandard automated perimetry (SAP) visual field (VF) results are more repeatable using Goldmann stimulus size V (stimV) in eyes with moderate/severe deficits due to glaucoma. There are few reports relating VFs using stimulus size V and III, typically used in the clinic for glaucoma, and none for non-arteritic anterior ischemic optic neuropathy (NAION). We hypothesized that we could compare and relate the VFs with both stimuli for glaucoma and NAION. MethodsWe utilized 1992 same-day pairs of stimIII and stimV SAP VFs using the 24-2 strategy for eyes with glaucoma or NAION. We explored the optimal threshold to censor the raw sensitivities, prior to calculating age-standardized total deviations (TD). We determined the mean and standard deviation of the differences among all TD pairs. We computed a line of best fit to determine closeness to the line of unity. ResultsThe ideal censoring conversion threshold was 21 dB for stimIII and 24 dB for stimV. The difference between stimV and stimIII censored (0.0 {+/-} 1.9 dB) and uncensored (0.4 {+/-} 2.6 dB) TD pairings strongly correlate with each other (r2 = 0.70, p < 0.001). The line of best fit from these pairings has a slope of 0.92, which is similar to that of the line of unity (m = 1). ConclusionCensoring plus age correction is a valid method of comparison between stimIII and stimV SAP VFs with moderate to severe VF loss due to optic nerve disorders. Translational RelevanceStimIII and stimV TDs are interchangeable in clinical practice.

PurposeTo evaluate the intra- and inter-grader concordance of anterior segment optical coherence tomography (ASOCT) grading for detection of endothelial plaque in microbial keratitis, and to compare endothelial plaque detection via ASOCT grading versus in-person slit lamp examination. MethodsDiagnostic concordance study of 150 consecutive patients with microbiologically confirmed bacterial or fungal keratitis at a high-volume tertiary eye hospital in India. Two masked ophthalmologist graders independently evaluated ASOCT images for presence of two morphologically distinct endothelial plaque subtypes noted during image review (round and flat plaques). We assessed intra-grader and inter-grader concordance for each endothelial plaque morphology and for presence of either morphology. Diagnostic agreement between ASOCT and in-person slit lamp examination was evaluated using percent agreement, Cohens kappa, sensitivity, and specificity. Univariable and multivariable logistic regression was used to assess odds of disagreement between ASOCT and slit lamp examination for endothelial plaque detection. ResultsASOCT detection showed near perfect inter-grader agreement for round endothelial plaques (kappa 0.88, 94.7% agreement), flat endothelial plaques (kappa 0.84, 92.0% agreement), and either plaque (kappa 0.88, 94.0% agreement). Intra-grader agreement was substantial to near perfect for both graders across all plaque types (kappa 0.70-0.86). Ophthalmologist slit lamp examination identified endothelial plaque in 6.0% eyes, while ASOCT detected round plaques in 32.7%, flat plaques in 43.3%, and either plaque in 55.3% of eyes. Using ASOCT as reference, slit lamp examination demonstrated sensitivity of 16.3% for round plaques, 6.2% for flat plaques, and 9.6% for either plaque, with specificity exceeding 94% for all. Poor visual acuity (logMAR [&ge;]1.0) was associated with increased disagreement for round plaques (adjusted OR 5.04), flat plaques (adjusted OR 3.63), and either plaque (adjusted OR 3.98). Bacterial infection was associated with increased disagreement for any endothelial plaque (adjusted OR 4.56). ConclusionSlit lamp examination substantially under-detects endothelial plaque compared to ASOCT, while ASOCT enables reproducible detection with excellent intra- and inter-grader agreement. These findings support incorporation of ASOCT imaging into microbial keratitis evaluation protocols. Differences in round and flat endothelial plaque morphologies warrant further investigation.

PurposeTo describe and demonstrate a more efficient (Maximum Likelihood) method for quantifying visual field progression. DesignMonte Carlo simulation. MethodsTrial-by-trial response data were simulated using a stochastic psychometric model (a "simulated observer"). Simulated Differential Light Sensitivity (DLS) decreased between tests to mimic long-term visual field progression. Progression slopes were fitted, either by fitting a regression slope to independent DLS estimates from each test (conventional method), or by fitting all the raw data combined in a single model (proposed maximum likelihood method). ResultsThe proposed ML method seldom performed worse than a conventional, regression-based approach, and often performed better. For an idealized observer with a lapse (false negative) rate of 0 and a guess (false positive) rate of 0, both methods were equally precise. However, as lapse rate increased, the ML method exhibited less random measurement error. For small numbers of trials this increase in precision translated to a negative progression slope being detected with 95% confidence at least one year/assessment sooner. The only time the ML method was observed to perform worse was when very few trials (N = 4) were combined with very high lapse rates ({lambda} = 0.3): an unlikely but not inconceivable scenario. ConclusionsCombining raw, trial-by-trial response data in a single ML model can provide a more robust estimate of visual field progression than conventional methods (e.g., linear regression), at no additional cost to the patient or clinician (i.e., no additional trials).

PurposeTo compare the diagnostic performance and to evaluate the interrelationship of electroretinographical and structural and vascular measures in glaucoma. MethodsFor 14 eyes of 14 healthy controls and 15 eyes of 12 patients with glaucoma ranging from preperimetric to advanced stages OCT, OCT-A and electrophysiological measures [multifocal photopic negative response ratio (mfPhNR) and steady state pattern electroretinogram (ssPERG)] were applied to assess changes in retinal structure, microvasculature, and function, respectively. The diagnostic performance was assessed via area-under-curve (AUC) measures obtained from ROC analyses. The interrelation of the different measures was assessed with correlation analyses. ResultsmfPhNR and ssPERG amplitudes, parafoveal (pfVD) and peripapillary vessel density (pVD), macular ganglion cell inner plexiform layer thickness (mGCIPL) and peripapillary retinal nerve fibre layer thickness (pRNFL) were significantly reduced in glaucoma. The AUC for mfPhNR was highest among diagnostic modalities (AUC: 0.88, 95%-CI: 0.75-1.0, P< 0.001), albeit not statistically different from that for macular (mGCIPL: 0.76, 0.58-0.94, P< 0.05; pfVD: 0.81, .65-.97, P< 0.01) or peripapillary imaging (pRNFL: 0.85, 0.70-1.0, P< 0.01; pVD: 0.82, 0.68-0.97, P < 0.01). Combined functional/vascular measures yielded the highest AUC (mfPhNR-pfVD: 0.94, 0.85-1.0, P<0.001). The functional/structural measure correlation (mfPhNR-mGCIPL correlation coefficient (rs): 0.58, P = 0.001; mfPhNR-pRNFL rs: 0.66, P < 0.0001) was stronger than the functional-vascular correlation (mfPhNR-pfVD rs: 0.29, P = 0.13; mfPhNR-pVD rs: 0.54, P = 0.003). ConclusionsThe combination of ERG measures and OCT-A improved diagnostic performance in glaucoma. Combing ERG, structural and OCT-A parameters provides an enhanced understanding of the pathophysiology of glaucoma.

IntroductionClinical tools are neither standardized nor ubiquitous to monitor volumetric or morphological changes in the periorbital region and ocular adnexa due to pathology such as oculofacial trauma, thyroid eye disease, and the natural aging process. We have developed a low-cost, three dimensionally printed PHotogrammetry for Automated CarE (PHACE) system to evaluate three-dimensional (3D) measurements of periocular and adnexal tissue. MethodsThe PHACE system uses two Google Pixel 3 smartphones attached to automatic rotating platforms to image a subjects face through a cutout board patterned with registration marks. Photographs of faces were taken from many perspectives by the cameras placed on the rotating platform. Faces were imaged with and without 3D printed hemispheric phantom lesions (black domes) affixed on the forehead above the brow. Images were rendered into 3D models in Metashape (Agisoft, St. Petersburg, Russia) and then processed and analyzed in CloudCompare (CC) and Autodesks Meshmixer. The 3D printed hemispheres affixed to the face were then quantified within Meshmixer and compared to their known volumes. Finally, we compared digital exophthalmometry measurements with results from a standard Hertel exophthalmometer in a subject with and without an orbital prosthesis. ResultsQuantification of 3D printed phantom volumes using optimized stereophotogrammetry demonstrated a 2.5% error for a 244L phantom, and 7.6% error for a 27.5L phantom. Digital exophthalmometry measurements differed by 0.72mm from a standard exophthalmometer. ConclusionWe demonstrated an optimized workflow using our custom apparatus to analyze and quantify oculofacial volumetric and dimensions changes with a resolution of 244L. This apparatus is a low-cost tool that can be used in clinical settings to objectively monitor volumetric and morphological changes in periorbital anatomy.

PurposeTo assess the impact of lens autofluorescence on adaptive optics fluorescence lifetime imaging ophthalmoscopy (AOFLIO). MethodsEighteen subjects (n = 18) aged 23 to 68 years with normal chorioretinal health and phakic lenses were imaged using a research-grade AOFLIO instrument. Retinal autofluorescence was excited with a pulsed diode laser ({lambda} = 473 nm) and detected in two spectral channels (500-560 nm and 560-720 nm). AOFLIO images were acquired at locations from the foveal center to 10{degrees} of the nasal retina. Autofluorescence decay was modeled using bi-exponential and tri-exponential functions, with and without accounting for the early arrival of the lens signal. The contribution of lens autofluorescence was evaluated in relation to age and retinal location. ResultsThe tri-exponential model that accounted for the early arrival of lens autofluorescence demonstrated superior conformity to the measured autofluorescence decay. The amplitude coefficient of lens contribution was 3 - 4%. However, this component accounted for 19.4 - 29.0% of photon-weighted signals and resulted in a 22.8 - 42.9% overestimation of the mean retinal fluorescence lifetime when uncorrected. Len effect was more pronounced in the short spectral channel. The time shift parameter of lens signal was associated with axial length and age (p = 0.023) and negatively correlated with axial length (p = 0.036). ConclusionsAOFLIO substantially suppresses lens autofluorescence; however, residual lens signal persists and can disproportionately bias retinal autofluorescence lifetime estimates. Accurate correction of the lens component are essential for reliable AOFLIO measurements. Translational RelevanceMinimizing the impact of lens autofluorescence in AOFLIO ensures accurate assessments of metabolic status in the retina and retinal pigment epithelium.

PurposeStandard automated perimetry (SAP) is the gold standard for functional assessment in glaucoma. SAP can be too demanding for some groups of patients. Continuous visual stimulus tracking (SONDA: Standardized Oculomotor and Neurological Disorders Assessment) simplifies the perimetric task to following a moving stimulus on a screen. In this study we evaluated the screening performance of SONDA-based eye movement perimetry (SONDA-EMP) in glaucoma. To explore generalizability, we evaluated an experimental setup (SONDA-Eyelink) and a clinic-ready version (SONDA-Neon). MethodsSONDA-Eyelink and SONDA-Neon measurements were performed in 100 cases with glaucoma (36, 36, and 28 with early, moderate, and severe glaucoma, respectively) and 100 age-similar controls. Participants monocularly tracked a moving stimulus (Goldmann size III) at 40% contrast (both setups) and 160% (SONDA-Eyelink). Eye movements were continuously recorded. Outcome was the agreement between gaze and stimulus position. We used previously collected glaucoma case-control data to build a continuous glaucoma screening score. This score was used for an ROC-analysis applied to the current, independently collected dataset. We predefined good screening performance as: at 95% specificity, a sensitivity of at least 50%, 90%, and 100% for early, moderate, and severe glaucoma, respectively. ResultsAt 95% specificity, the sensitivity of SONDA-Eyelink was 58, 94, and 100% at 40% contrast and 56, 97, and 100% at 160% contrast for early, moderate, and severe glaucoma, respectively. Sensitivity was 53, 94, and 100% for SONDA-Neon. ConclusionsSONDA-EMP is a novel, fast, and intuitive method to screen for visual function loss in glaucoma.

ObjectiveTo assess the feasibility of remotely training glaucoma patients to take a ten-session clustered virtual reality (VR) visual field test (VVP-10) at home, analyze results for test-retest variability, and assess correspondence with conventional perimetry. DesignCross-sectional study. Subjects21 subjects with glaucoma were enrolled and included in the feasibility assessment of remote training. 36 eyes were used for test-retest analysis and determination of concordance with Humphrey Visual Field (HVF) testing. MethodsSubjects were provided with a mobile VR headset containing the VVP-10 test software and trained remotely via video conferencing. Subjects were instructed to complete ten sessions over a 14-day period. Main Outcome MeasuresFeasibility was determined by the number of subjects who were able to independently complete VVP-10 over the 14-day period after one remote training session. Intraclass correlation coefficient (ICC) of average fraction seen across ten sessions and standard error (SE) for the mean were primary outcome measures for assessing test-retest variability. Correlation with HVF mean sensitivity (MS) across eyes, was a secondary outcome measure. Results20 subjects (95%) successfully completed the VVP-10 test series after one training session. ICC of VVP-10 was 0.95 (95% CI [0.92, 0.97]). Mean SE in units of fraction seen was 0.012. The Spearman correlations of VVP-10 average fraction seen versus HVF MS were 0.88 (95% CI [0.66, 0.99]) for moderate to advanced glaucoma eyes, and decreased to 0.68 (95% CI [0.29, 0.94]) when all eyes were included. ConclusionsRemote training of patients at home is feasible and subsequent remote clustered visual field testing using VVP-10 by patients on their own without any further interactions with caregivers or study staff was possible. At-home VVP-10 results demonstrated low test-retest variability. Future studies must be conducted to determine if VVP-10, taken at home as convenient for the patient, may be a viable supplement to provide equivalent or complementary results to that of standard in-clinic assessment of visual function in glaucoma.

PurposeTo 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.

PurposeTo evaluate the repeatability and reproducibility of a novel automated method compared with manual segmentation for measuring decreased autofluorescence (DAF) and definitely decreased autofluorescence (DDAF) in fundus autofluorescence (FAF) images of patients with Stargardt disease. DesignCross-sectional reproducibility and agreement study. ParticipantsA total of 316 eyes from 158 genetically confirmed Stargardt patients were analyzed. For intra-grader repeatability, 114 FAF images were reassessed in a masked, repeated-measures design. MethodsDAF and DDAF lesion areas were independently quantified by five certified graders using either manual delineation with Heidelberg RegionFinder or a threshold-based automated algorithm. Agreement and repeatability were assessed using intraclass correlation coefficients (ICC), standard error of measurement (SEM), minimal detectable change (MDC), Lins concordance correlation coefficient (CCC), Bland-Altman plots, and Passing-Bablok regression. Both raw and square-root-transformed lesion areas were evaluated. Main Outcome MeasuresRepeatability (intra-grader ICC, SEM, MDC), reproducibility (inter-grader ICC), and agreement (CCC, bias in regression analysis) between and within manual and automated methods. ResultsThe automated method achieved excellent intra-grader repeatability for both DAF and DDAF (ICCs [&ge;]0.988, SEM [&le;]0.71 mm{superscript 2}, MDC [&le;]1.98 mm{superscript 2}), with minimal operator influence. Manual measurements showed variable repeatability (DAF ICCs 0.909-0.974; DDAF ICCs as low as 0.837), with square-root transformation reducing SEM and MDC. Inter-grader reproducibility was highest for automated methods (ICC = 0.989-0.992), whereas manual methods ranged from 0.764-0.939 (raw) and 0.867-0.922 (transformed). Cross-method agreement was strong (CCC = 0.91-0.96), though minor proportional and constant bias was observed in raw DAF data. ConclusionsThe automated approach provides near-perfect repeatability and high agreement with manual grading, offering a scalable, objective alternative for quantifying hypo-autofluorescent lesions in Stargardt disease. Manual methods are generally reliable but more variable, especially for DDAF, and benefit from square-root transformation.