There is a growing body of evidence that early glaucomatous damage involves the macula. The anatomical basis of this damage can be studied using frequency domain optical coherence tomography (fdOCT), by which the local thickness of the retinal nerve fiber layer (RNFL) and local retinal ganglion cell plus inner plexiform (RGC+) layer can be measured. Based upon averaged fdOCT results from healthy controls and patients, we show that: 1. For healthy controls, the average RGC+ layer thickness closely matches human histological data; 2. For glaucoma patients and suspects, the average RGC+ layer shows greater glaucomatous thinning in the inferior retina (superior visual field (VF)); and 3. The central test points of the 6° VF grid (24-2 test pattern) miss the region of greatest RGC+ thinning. Based upon fdOCT results from individual patients, we have learned that: 1. Local RGC+ loss is associated with local VF sensitivity loss as long as the displacement of RGCs from the foveal center is taken into consideration; and 2. Macular damage is typically arcuate in nature and often associated with local RNFL thinning in a narrow region of the disc, which we call the macular vulnerability zone (MVZ). According to our schematic model of macular damage, most of the inferior region of the macula projects to the MVZ, which is located largely in the inferior quadrant of the disc, a region that is particularly susceptible to glaucomatous damage. A small (cecocentral) region of the inferior macula, and all of the superior macula (inferior VF), project to the temporal quadrant, a region that is less susceptible to damage. The overall message is clear; clinicians need to be aware that glaucomatous damage to the macula is common, can occur early in the disease, and can be missed and/or underestimated with standard VF tests that use a 6° grid, such as the 24-2 VF test.

PURPOSE. To better understand the relative contributions of rod, cone, and melanopsin to the human pupillary light reflex (PLR) and to determine the optimal conditions for assessing the health of the rod, cone, and melanopsin pathways with a relatively brief clinical protocol. METHODS. PLR was measured with an eye tracker, and stimuli were controlled with a Ganzfeld system. In experiment 1, 2.5 log cd/m(2) red (640 ± 10 nm) and blue (467 ± 17 nm) stimuli of various durations were presented after dark adaptation. In experiments 2 and 3, 1-second red and blue stimuli were presented at different intensity levels in the dark (experiment 2) or on a 0.78 log cd/m(2) blue background (experiment 3). Based on the results of experiments 1 to 3, a clinical protocol was designed and tested on healthy control subjects and patients with retinitis pigmentosa and Leber's congenital amaurosis. RESULTS. The duration for producing the optimal melanopsin-driven sustained pupil response after termination of an intense blue stimulus was 1 second. PLR rod- and melanopsin-driven components are best studied with low- and high-intensity flashes, respectively, presented in the dark (experiment 2). A blue background suppressed rod and melanopsin responses, making it easy to assess the cone contribution with a red flash (experiment 3). With the clinical protocol, robust melanopsin responses could be seen in patients with few or no contributions from the rods and cones. CONCLUSIONS. It is possible to assess the rod, cone, and melanopsin contributions to the PLR with blue flashes at two or three intensity levels in the dark and one red flash on a blue background.

No abstract

Glaucomatous arcuate defects of the macula's RNFL meet the disc temporal to the peak of the main arcuate bundles and produce a range of macular VF defects from clear arcuate scotomas to a papillofoveal horizontal step ("pistol barrel scotoma"). If RGC displacement is taken into consideration, the RNFL and VF defects can be compared directly.

A novel automated boundary segmentation algorithm is proposed for fast and reliable quantification of nine intra-retinal boundaries in optical coherence tomography (OCT) images. The algorithm employs a two-step segmentation schema based on gradient information in dual scales, utilizing local and complementary global gradient information simultaneously. A shortest path search is applied to optimize the edge selection. The segmentation algorithm was validated with independent manual segmentation and a reproducibility study. It demonstrates high accuracy and reproducibility in segmenting normal 3D OCT volumes. The execution time is about 16 seconds per volume (480×512×128 voxels). The algorithm shows potential for quantifying images from diseased retinas as well.

Purpose To better understand the nature of glaucomatous damage, especially to the macula, the inner retinal thickness maps obtained with frequency domain optical coherence tomography (fdOCT) were averaged. Methods Frequency domain optical coherence tomography macular and optic disc cube scans were obtained from 54 healthy eyes and 156 eyes with glaucomatous optic neuropathy. A manually corrected algorithm was used for layer segmentation. Patients’ eyes were grouped both by mean deviation (MD) and hemifield classification using standard categories and 24-2 (6° grid) visual fields (VFs). To obtain average difference maps, the thickness of retinal nerve fiber (RNF) and retinal ganglion cell plus inner plexiform (RGC+) layers were averaged and subtracted from the average control values. Results On the average difference maps, RGC+ and RNF layer thinning was seen in the patient groups with VFs classified as normal. The pattern of the thinning was the same, but the degree of thinning increased with decreased MD and with classification category (from normal to arcuate). This RGC+ thinning was largely within the central four points of the 24-2 (6° grid) field, after correcting for RGC displacement. Conclusion 1. VF categories represent different degrees of the same pattern of RGC+ and RNFL layer thinning. 2. RGC+ damage occurs in the central macula even in patients with VFs classified as normal. 3. The 6° grid (24-2) pattern is not optimally designed to detect macular damage. 4. A schematic model of RGC projections is proposed to explain the pattern of macular loss, including the greater vulnerability of the inferior retinal region. Translational relevance The 24-2 is not an optimal test pattern for detecting or following glaucomatous damage. Further, we suggest clinical fdOCT reports include RGC+ and RNFL probability plots combined with VF information.

There appeared to be as many abnormal 10-2 hemifields (53%) as abnormal 24-2 hemifields (59%). Of the eyes with normal 24-2 hemifields, 16% were classified as abnormal when the 10-2 test was used. Of the abnormal 10-2 hemifields, 68%, 8%, and 25% were arcuatelike, widespread, and other, respectively. The average total deviation values and number of abnormal points plots revealed superior VF defects that were deeper and closer to fixation than those in the inferior VF. CONCLUSIONS AND RELEVANCEThe 10-2 VF was abnormal in nearly as many hemifields as was the 24-2 VF, including some with normal 24-2 VF, suggesting that the 24-2 test is not optimal for detecting early damage of the macula. The pattern of the defects was in agreement with a recent model of macular damage.

Purpose Retinal nerve fiber (RNFL) thickness and visual field loss data from patients with glaucoma were analyzed in the context of a model, to better understand individual variation in structure versus function. Methods Optical coherence tomography (OCT) RNFL thickness and standard automated perimetry (SAP) visual field loss were measured in the arcuate regions of one eye of 140 patients with glaucoma and 82 normal control subjects. An estimate of within-individual (measurement) error was obtained by repeat measures made on different days within a short period in 34 patients and 22 control subjects. A linear model, previously shown to describe the general characteristics of the structure–function data, was extended to predict the variability in the data. Results For normal control subjects, between-individual error (individual differences) accounted for 87% and 71% of the total variance in OCT and SAP measures, respectively. SAP within-individual error increased and then decreased with increased SAP loss, whereas OCT error remained constant. The linear model with variability (LMV) described much of the variability in the data. However, 12.5% of the patients’ points fell outside the 95% boundary. An examination of these points revealed factors that can contribute to the overall variability in the data. These factors include epiretinal membranes, edema, individual variation in field-to-disc mapping, and the location of blood vessels and degree to which they are included by the RNFL algorithm. Conclusions The model and the partitioning of within- versus between-individual variability helped elucidate the factors contributing to the considerable variability in the structure-versus-function data.