Detecting Progression in Advanced Glaucoma: Are Optical Coherence Tomography Global Metrics Viable Measures?

Hybrid deep learning and optimal graph search method for optical coherence tomography layer segmentation in diseases affecting the optic nerve

Accurate segmentation of retinal layers in optical coherence tomography (OCT) images is critical for assessing diseases that affect the optic nerve, but existing automated algorithms often fail when pathology causes irregular layer topology, such as extreme thinning of the ganglion cell-inner plexiform layer (GCIPL). Deep LOGISMOS, a hybrid approach that combines the strengths of deep learning and 3D graph search to overcome their limitations, was developed to improve the accuracy, robustness and generalizability of retinal layer segmentation. The method was trained on 124 OCT volumes from both eyes of 31 non-arteritic anterior ischemic optic neuropathy (NAION) patients and tested on three cross-sectional datasets with available reference tracings: Test-NAION (40 volumes from both eyes of 20 NAION subjects), Test-G (29 volumes from 29 glaucoma subjects/eyes), and Test-JHU (35 volumes from 21 multiple sclerosis and 14 control subjects/eyes) and one longitudinal dataset without reference tracings: Test-G-L (155 volumes from 15 glaucoma patients/eyes). In the three test datasets with reference tracings (Test-NAION, Test-G, and Test-JHU), Deep LOGISMOS achieved very high Dice similarity coefficients (%) on GCIPL: 89.97±3.59, 90.63±2.56, and 94.06±1.76, respectively. In the same context, Deep LOGISMOS outperformed the Iowa reference algorithms by improving the Dice score by 17.5, 5.4, and 7.5, and also surpassed the deep learning framework nnU-Net with improvements of 4.4, 3.7, and 1.0. For the 15 severe glaucoma eyes with marked GCIPL thinning (Test-G-L), it demonstrated reliable regional GCIPL thickness measurement over five years. The proposed Deep LOGISMOS approach has potential to enhance precise quantification of retinal structures, aiding diagnosis and treatment management of optic nerve diseases.

Progressive Macular Vessel Density Loss and Visual Field Progression in Open-angle Glaucoma Eyes with Central Visual Field Damage

PURPOSE

To investigate the association between the longitudinal changes in both macular vessel density (mVD) and macular ganglion cell-inner plexiform layer thickness (mGCIPLT) and visual field (VF) progression (including central VF progression) in open-angle glaucoma (OAG) patients with central visual field (CVF) damage at different glaucoma stages.

DESIGN

Retrospective longitudinal study.

PARTICIPANTS

This study enrolled 223 OAG eyes with CVF loss at baseline classified as early-to-moderate (133 eyes) or advanced (90 eyes) stage based on the VF mean deviation (MD) (-10 dB).

METHODS

Serial mVDs at parafoveal and perifoveal sectors and mGCIPLT measurements were obtained using OCT angiography and OCT during a mean follow-up of 3.5 years. Visual field progression was determined using both the event- and trend-based analyses during follow-up.

MAIN OUTCOME MEASURES

Linear mixed-effects models were used to compare the rates of change in each parameter between VF progressors and nonprogressors. Logistic regression analyses were performed to determine the risk factors for VF progression.

RESULTS

In early-to-moderate stage, progressors showed significantly faster rates of change in the mGCIPLT (-1.02 vs. -0.47 μm/year), parafoveal (-1.12 vs. -0.40%/year), and perifoveal mVDs (-0.83 vs. -0.44%/year) than nonprogressors (all P < 0.05). In advanced stage cases, only the rates of change in mVDs (parafoveal: -1.47 vs. -0.44%/year; perifoveal: -1.04 vs. -0.27%/year; all P < 0.05) showed significant differences between the groups. By multivariable logistic regression analyses, the faster rate of mVD loss was a predictor of VF progression regardless of glaucoma stage, while the rate of mGCIPLT loss was significantly associated with VF progression only in early-to-moderate stage cases.

CONCLUSIONS

Progressive mVD loss is significantly associated with VF progression (including central VF progression) in the OAG eyes with CVF loss regardless of the glaucoma stage.

FINANCIAL DISCLOSURE(S)

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Progression of Early Glaucomatous Damage: Performance of Summary Statistics From Optical Coherence Tomography and Perimetry

Purpose

Performance comparison of optical coherence tomography (OCT) and visual field (VF) summary metrics for detecting glaucomatous progression.

Methods

Thirty healthy control eyes (mean deviation [MD], -1.25 ± 2.03; pattern standard deviation [PSD] , 1.78 ± 0.77) and 91 patient eyes comprised of 54 glaucoma patients and 37 glaucoma suspects (MD, -1.58 ± 1.96; PSD, 2.82 ± 1.92) with a follow-up of at least 1 year formed a group to evaluate progression with event analyses (P-Event). A subset of eyes with an additional criterion of a minimum of four tests was used for trend analyses (P-Trend) (30 healthy controls and 73 patients). For P-Event analysis, test-retest variability thresholds (lower 5th percentile) were estimated with repeat tests within a 4-month period. A P-Event eye was considered a "progressor" if the difference between follow-up and baseline tests exceeded the variability thresholds. For the P-Trend analysis, rates of change were calculated based on least-squares regression. Negative rates with significant (P < 0.05) values were considered progressing. For a reference standard, 17 patient eyes were classified as definitely progressing based on clear evidence of structural and corresponding functional progression.

Results

Isolated OCT and VF summary metrics were either inadequately sensitive or not too specific. Combinations of OCT-OCT and OCT-VF metrics markedly improved specificity to nearly 100%. A novel combination of OCT metrics (circumpapillary retinal nerve fiber layer and ganglion cell layer) showed high precision, with 13 of the 15 statistical progressors confirmed as true positives.

Conclusions

Although relying solely on metrics is not recommended for clinical purposes, in situations requiring very high specificity and precision, combinations of OCT-OCT metrics can be used.

Translational Relevance

All available OCT and VF metrics can miss eyes with progressive glaucomatous damage and/or can falsely identify progression in stable eyes.

The 24-2 Visual Field Guided Progression Analysis Can Miss the Progression of Glaucomatous Damage of the Macula Seen Using OCT

PURPOSE

To better understand the efficacy of the 24-2 guided progression analysis (GPA) in the detection of progression in eyes with early glaucoma (i.e., 24-2 mean deviation [MD] better than -6 dB) by comparing 24-2 GPA with a reference standard (RS) based on a combination of OCT and 24-2 and 10-2 visual field (VF) information.

DESIGN

Cross-sectional study.

PARTICIPANTS

Ninety-nine eyes from 99 individuals, including 70 suspected or early glaucomatous eyes (24-2 MD better than -6 dB) and 29 healthy controls (HCs).

METHODS

All the eyes had at least 4 OCT and VF test dates over a period that ranged from 12 to 59 months. The 24-2 VF tests included 2 baseline tests and at least 2 follow-up tests. The 2 baseline tests were performed within an average of 5.6 days (median, 7 days), and the last follow-up test was performed at least 1 year after the first baseline visit.

MAIN OUTCOME MEASURES

A commercial 24-2 GPA software, with default settings, characterized the eyes as having "likely progression" (LP) or "possible progression" (PP); both were considered "progressing" for this analysis. For RS, 3 authors graded progression using strict criteria and a combination of a custom OCT progression report and commercial 24-2 and 10-2 GPA reports for the same test dates as GPA.

RESULTS

The reference standard identified 10 (14%) of the 70 patient eyes and none of the HC eyes as having progression. The 24-2 guided progression analysis identified 13 of the 70 patient eyes as having progression (PP or LP). However, it correctly classified only 4 (40%) of the 10 RS progressors. All 6 of the RS progressors missed by the 24-2 GPA showed progression in the macula. In addition, the 24-2 GPA identified 2 of the 29 HC eyes as progressors and 9 patient eyes without progression based on the RS.

CONCLUSIONS

In eyes with early glaucoma (i.e., 24-2 MD, > -6 dB) in this study, the 24-2 GPA missed progression seen using OCT and exhibited a relatively high rate of false positives. Furthermore, the region progressing typically included the macula. The results suggest that including OCT and/or 10-2 VFs should improve the detection of progression.

Central Macular Topographic and Volumetric Measures: New Biomarkers for Detection of Glaucoma

Purpose

To test the hypothesis that newly developed shape measures using optical coherence tomography (OCT) macular volume scans can discriminate patients with perimetric glaucoma from healthy subjects.

Methods

OCT structural measures defining macular topography and volume were recently developed based on cubic Bézier curves. We exported macular volume scans from 135 eyes with glaucoma (133 patients) and 155 healthy eyes (85 subjects) and estimated global and quadrant-based measures. The best subset of measures to predict glaucoma was explored with a gradient boost model (GBM) with subsequent logistic regression. Accuracy and area under receiver operating curves (AUC) were the primary metrics. In addition, we separately investigated model performance in 66 eyes with mild glaucoma (mean deviation ≥ -6 dB).

Results

Average (±SD) 24-2 mean deviation was -8.2 (±6.1) dB in eyes with glaucoma. The main predictive measures for glaucoma were temporal inferior rim height, nasal inferior pit volume, and temporal inferior pit depth. Lower values for these measures predicted higher risk of glaucoma. Sensitivity, specificity, and AUC for discriminating between healthy and glaucoma eyes were 81.5% (95% CI = 76.6-91.9%), 89.7% (95% CI = 78.7-94.2%), and 0.915 (95% CI = 0.882-0.948), respectively. Corresponding metrics for mild glaucoma were 84.8% (95% CI = 72.1%-95.5%), 85.8% (95% CI = 87.1%-97.4%), and 0.913 (95% CI = 0.867-0.958), respectively.

Conclusions

Novel macular shape biomarkers detect early glaucoma with clinically relevant performance. Such biomarkers do not depend on intraretinal segmentation accuracy and may be helpful in eyes with suboptimal macular segmentation.

Translational Relevance

Macular shape biomarkers provide valuable information for detection of early glaucoma and may provide additional information beyond thickness measurements.