Citations

Background This study aimed to provide methodology to create a facial contour-informed normative 60-4 visual field and to apply the reference field to a glaucoma cohort to derive facial contour-informed 60-4 global indices. Methods Participant recruitment was completed at a tertiary medical centre. 60 eyes from 30 participants with no ocular pathology by clinical exam or optical coherence tomography were recruited for the healthy cohort. For the glaucoma cohort, 86 eyes from 43 patients diagnosed with glaucoma by clinical exam were recruited, with 30-2 visual field mean deviation used to stratify glaucoma severity. Results The median (range) age of the healthy participants was 33 (24–61) years old. A facial contour-informed 60-4 visual field reference field was developed. 43 glaucoma patients were recruited with a resulting median (range) age of 65 (30–84). Three algorithms compensating for facial contour were used for the derivation of 60-4 mean deviation and pattern SD. All mean deviation algorithms correlated with 30-2 mean deviation severity (ρ≤−0.62, p<0.0001) and retinal nerve fibre layer thickness (ρ≥0.36, p<0.05). For pattern SD, consideration of inferior nasal defects allowed correlation with both 30-2 mean deviation severity (ρ≥0.49, p<0.001) and retinal nerve fibre layer thickness (ρ≤−0.47, p<0.01). Conclusion This study provides methodology for deriving a facial contour-informed 60-4 reference field and illustrates the feasibility of applying facial contour information to refine global indices of the 60-4 visual field. Obtained metrics compensated for facial contour and correlated with functional and structural disease metrics.

AbstractPurpose: Evaluation of an adjustable chin rest apparatus for visual field machine.Methods: The HFA 60‐4 visual field test was performed in the primary position and then repeated in the optimum head turn angle using an adjustable chin rest to maximize a visual field for each subject. The optimum head turn angle was calculated using a 3D face model. A 3D model of the face of the subjects was reconstructed using a single facial photo and a Convolutional Neural Networks (CNN), which is a deep learning algorithm. The angles between visual axis and all points around it on the face surface were calculated and the points on the 3D face model with the angle less than 60 degrees was used to predict the optimal head turn angle. A chin rest apparatus for a visual field system was made by 3D printing. The chin rest apparatus includes a moveable chin rest insert coupled to the base and configured to be adjusted to one of a plurality of head turn angles.Results: Three eyes from three healthy subjects (2 female and 1 male) with the mean age of 27.33, CI: 7.37 were enrolled. The visual field defects cause by the facial contour of the subject was decreased by turning the subject's head relative to a vertical axis away from (nasally) the eye being tested using a visual field system with the adaptive chin rest. The mean threshold of the visual field tests of all eyes in the primary angle and optimized angle was 1496, CI: 380.22 and 1567.67, CI: 295.37 respectively. Mean of the degree of head turn to maximize the visual field for all individuals was 6.67 degrees, CI: 2.88.Conclusions: The described adaptive chin rest can be used to position a subject's head at an optimal head turn angle that minimizes the visual field defects caused by the facial contours and maximizes the measured visual field of the subject. This technology can be used in far peripheral visual field tests for early detection of glaucoma as well as accurate follow up of disease progression.

Background Despite, the potential clinical utility of 60–4 visual fields, they are not frequently used in clinical practice partly, due to the purported impact of facial contour on field defects. The purpose of this study was to design and test an artificial intelligence-driven platform to predict facial structure-dependent visual field defects on 60–4 visual field tests. Methods Subjects with no ocular pathology were included. Participants were subject to optical coherence tomography, 60–4 Swedish interactive thresholding algorithm visual field tests and photography. The predicted visual field was compared with observed 60–4 visual field results in subjects. Average and point-specific sensitivity, specificity, precision, negative predictive value, accuracy, and F1-scores were primary outcome measures. Results 30 healthy were enrolled. Three-dimensional facial reconstruction using a convolution neural network (CNN) was able to predict facial contour-dependent 60–4 visual field defects in 30 subjects without ocular pathology. Overall model accuracy was 97%±3% and 96%±3% and the F1-score, dependent on precision and sensitivity, was 58%±19% and 55%±15% for the right eye and left eye, respectively. Spatial-dependent model performance was observed with increased sensitivity and precision within the far inferior nasal field reflected by an average F1-score of 76%±20% and 70%±29% for the right eye and left eye, respectively. Conclusions This pilot study reports the development of a CNN-enhanced platform capable of predicting 60–4 visual field defects in healthy controls based on facial contour. Further study with this platform may enhance understanding of the influence of facial contour on 60–4 visual field testing.

Précis: In this longitudinal study of patients with open-angle (OAG), pseudoexfoliative (PXE), or neovascular glaucoma (NVG) receiving glaucoma drainage devices (GDD), posttube cumulative rates of reoperation, corneal graft, and visually threatening complications (VT-complications) increased beyond 5 years and were not significantly affected by glaucoma type. Purpose: To study the need for additional glaucoma surgery and development of complications after first GDD surgery in eyes with primary OAG, PXE, or NVG glaucoma. Patients and Methods: There were 306 eyes with OAG (n=185), PXE (n=60), or NVG (n=61) glaucoma who received a first GDD between 1996 and 2017. Outcomes including glaucoma reoperation, corneal graft procedure, and VT-complications after GDD were measured. Kaplan-Meier analysis was used to compare cumulative rate of reaching outcomes over time after GDD placement among the 3 glaucoma groups. Results: When comparing the OAG, PXE, and NVG groups, there were no significant differences in post-GDD cumulative rates of reoperation (P=0.33), corneal graft (P=0.26), or VT-complications (P=0.65) over time. For all eyes, the overall cumulative rates for each outcome measure increased beyond 5 years, and specific Kaplan-Meier rates (5-y, 10-y) included: reoperation (16%, 25%), corneal graft (6%, 12%), VT-complications (9%, 14%). When comparing specific GDDs, the Ahmed FP7 had a higher cumulative reoperation rate over time compared with the Baerveldt 350 (P=0.019). Conclusion: Glaucoma type did not significantly affect post-GDD cumulative rates of reoperation, corneal graft, and VT-complication among the OAG, PXE, and NVG groups. For all eyes, cumulative rates of reoperation, corneal graft, and VT-complications increased beyond 5 years. The Ahmed FP7 had a significantly higher cumulative reoperation rate compared with the Baerveldt 350 over time.

Précis: Kaplan-Meier analysis was used to compare the rate of corneal grafting after glaucoma drainage device (GDD) placement in pediatric and adult patients. Adults were at an increased risk of receiving a corneal graft after device placement. Purpose: The goal of this study was to compare the rate of corneal graft implantation after GDD placement in pediatric and adult patients. Patients: Patients receiving a GDD between January 1, 1985 and December 31, 2017 were selected from the medical records. Patients receiving their first device while <18 years of age were considered children for the extent of the study. Methods: We compared the rate of receiving a corneal graft after GDD implantation using Kaplan-Meier analysis. Baseline patient characteristics and surgical characteristics were compared using a generalized estimating equation. Results: Corneal grafting occurred in 8.6% of adults and 4.7% of children from the original cohort. The rate of receiving a corneal graft at 5, 10, and 15 years was 9.4%, 16.8%, 39.4% and 1.6%, 1.6%, 12.5% for adults and children, respectively. However, certain characteristics were different between the 2 groups. Conclusion: Adult patients were more likely to receive a corneal graft after GDD placement. However, pediatric and adult patients differed in the prevalence of preexisting corneal disease, glaucoma type, GDD type used, and types of previous surgeries. Elucidation of the impact of these factors on corneal graft rate requires a larger cohort size.