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Purpose: Assessment of glaucomatous damage in animal models is facilitated by rapid and accurate quantification of retinal ganglion cell (RGC) axonal loss and morphologic change. However, manual assessment is extremely time- and labor-intensive. Here, we developed AxoNet 2.0, an automated deep learning (DL) tool that (i) counts normal-appearing RGC axons and (ii) quantifies their morphometry from light micrographs., Methods: A DL algorithm was trained to segment the axoplasm and myelin sheath of normal-appearing axons using manually-annotated rat optic nerve (ON) cross-sectional micrographs. Performance was quantified by various metrics (e.g., soft-Dice coefficient between predicted and ground-truth segmentations). We also quantified axon counts, axon density, and axon size distributions between hypertensive and control eyes and compared to literature reports., Results: AxoNet 2.0 performed very well when compared to manual annotations of rat ON (R2 = 0.92 for automated vs. manual counts, soft-Dice coefficient = 0.81 ± 0.02, mean absolute percentage error in axonal morphometric outcomes < 15%). AxoNet 2.0 also showed promise for generalization, performing well on other animal models (R2 = 0.97 between automated versus manual counts for mice and 0.98 for non-human primates). As expected, the algorithm detected decreased in axon density in hypertensive rat eyes (P ≪ 0.001) with preferential loss of large axons (P < 0.001)., Conclusions: AxoNet 2.0 provides a fast and nonsubjective tool to quantify both RGC axon counts and morphological features, thus assisting with assessing axonal damage in animal models of glaucomatous optic neuropathy., Translational Relevance: This deep learning approach will increase rigor of basic science studies designed to investigate RGC axon protection and regeneration.

Purpose: To characterize optic nerve head (ONH) blood flow (BF) changes in nonhuman primate experimental glaucoma (EG) using laser speckle flowgraphy (LSFG) and the microsphere method and to evaluate the correlation between the two methods., Methods: EG was induced in one eye each of 9 rhesus macaques by laser treatment to the trabecular meshwork. Prior to lasering and following onset of intraocular pressure (IOP) elevation, retinal never fiber layer thickness (RNFLT) and ONH BF were measured biweekly by spectral-domain optical coherence tomography and LSFG, respectively, until RNFLT loss was approximately 40% in the EG eye. Final BF was measured by LSFG and by the microsphere method in the anterior ONH (MS-BF(ANT)), posterior ONH (MS-BF(POST)), and peripapillary retina (MS-BF(PP))., Results: Baseline RNFLT and LSFG-BF showed no difference between the two eyes (P = 0.69 and P = 0.43, respectively, paired t-test). Mean (± SD) IOP was 30 ± 6 mm Hg in EG eyes and 13 ± 2 mm Hg in control eyes (P < 0.001). EG eye RNFLT and LSFG-BF were reduced by 42 ± 16% (P < 0.0001) and 22 ± 13% (P = 0.003), respectively, at the final time point. EG eye MS-BF(ANT), MS-BF(POST), and MS-BF(PP) were reduced by 41 ± 17% (P < 0.001), 22 ± 34% (P = 0.06), and 30 ± 12% (P = 0.001), respectively, compared with the control eyes. Interocular ONH LSFG-BF differences significantly correlated to that measured by the microsphere method (R(2) = 0.87, P < 0.001)., Conclusions: Chronic IOP elevation causes significant ONH BF decreases in the EG model. The high correlation between the BF reduction measured by LSFG and the microsphere method provides evidence that the LSFG is capable of assaying BF for a critical deep ONH region.

Purpose: We determined the relationship between total optic nerve axon counts and peripapillary retinal nerve fiber layer thickness (RNFLT) measured in vivo by spectral domain optical coherence tomography (SDOCT)., Methods: A total of 22 rhesus macaques had three or more baseline measurements in both eyes of peripapillary RNFLT made by SDOCT. Laser photocoagulation then was applied to the trabecular meshwork of one eye to induce chronic unilateral IOP elevation. SDOCT measurements of RNFLT continued approximately every two weeks until the predefined study endpoint was reached in each animal. At endpoint, animals were sacrificed and the optic nerve was sampled approximately 2 mm behind the globe to obtain thin sections for histologic processing and automated axon counting across 100% of the optic nerve cross-sectional area., Results: At the final imaging session, the average loss of RNFLT was 20 ± 21%, ranging from essentially no loss to nearly 65% loss. Total optic nerve axon count in control eyes ranged from 812,478 to 1,280,474. The absolute number of optic nerve axons was related linearly to RNFLT (axon count = 12,336 × RNFLT((μm)) - 257,050, R(2) = 0.65, P < 0.0001), with a Pearson correlation coefficient of 0.81. There also was a strong linear relationship between relative optic nerve axon loss (glaucomatous-to-control eye) and relative RNFLT at the final imaging session, with a slope close to unity but a significantly negative intercept (relative axon loss((%)) = 1.05 × relative RNFLT loss((%)) - 14.4%, R(2) = 0.75, P < 0.0001). The negative intercept was robust to variations of fitted model because relative axon loss was -14% on average for all experimental glaucoma (EG) eyes within 6% (measurement noise) of zero relative loss., Conclusions: There is a strong linear relationship between total optic nerve axon count and RNFLT measured in vivo by SDOCT. However, substantial loss of optic nerve axons (∼10%-15%) exists before any loss of RNFLT manifests and this discrepancy persists systematically throughout a wide range of damage.

Purpose: To compare peripapillary retinal nerve fiber layer thickness (RNFLT), RNFL retardance, and retinal function at the onset of optic nerve head (ONH) surface topography change in experimental glaucoma (EG)., Methods: Thirty-three rhesus macaques had three or more weekly baseline measurements in both eyes of ONH surface topography, peripapillary RNFLT, RNFL retardance, and multifocal electroretinography (mfERG). Laser photocoagulation was then applied to the trabecular meshwork of one eye to induce chronic elevation of IOP and weekly recordings continued alternating between ONH surface topography and RNFLT during one week and RNFL retardance and mfERG the next week. Data were pooled for the group at the onset of ONH surface topography change in each EG eye, which was defined as the first date when either the mean position of the disc (MPD) fell below the 95% confidence limit of each eye's individual baseline range and/or when the topographic change analysis (TCA) map was subjectively judged as having demonstrated change, whichever came first. Analysis of variance with post hoc tests corrected for multiple comparisons were used to assess parameter changes., Results: At onset of ONH surface topography change, there was no significant difference for RNFLT versus baseline or fellow control eyes. RNFL retardance and mfERG were significantly reduced in the recordings just prior (median of 9 days) to ONH onset (P < 0.01) and had progressed significantly (P < 0.001) an average of 17 days later (median of 7 days after ONH onset). RNFLT did not exhibit significant thinning until 15 days after onset of ONH surface topography change (P < 0.001)., Conclusions: These results support the hypothesis that during the course of glaucomatous neurodegeneration, axonal cytoskeletal and retinal ganglion cell functional abnormalities exist before thinning of peripapillary RNFL axon bundles begins.