Association Between Fluid Volume in Inner Nuclear Layer and Visual Acuity in Diabetic Macular Edema

Deep learning assisted fluid volume calculation for assessing anti-vascular endothelial growth factor effect in diabetic macular edema

Objective

To develop an algorithm using deep learning methods to calculate the volume of intraretinal and subretinal fluid in optical coherence tomography (OCT) images for assessing diabetic macular edema (DME) patients' condition changes.

Design

Cross-sectional study.

Participants

Treatment-naive patients diagnosed with DME recruited from April 2020 to November 2021.

Methods

The deep learning network, which was built for autonomous segmentation utilizing an encoder-decoder network based on the U-Net architecture, was used to calculate the volume of intraretinal fluid (IRF) and subretinal fluid (SRF). The alterations of retinal vessel density and thickness, and the correlation between best-corrected visual acuity (BCVA) and OCT parameters were analyzed.

Results

2,955 OCT images of fourteen eyes from DME patients with IRF and SRF who received anti-vascular endothelial growth factor (VEGF) agents were obtained. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the algorithm was 0.993 for IRF and 0.998 for SRF. The volumes of IRF and SRF were significantly decreased from 1.93 ± 0.58 /1.14 ± 0.25 mm3 (baseline) to 0.26 ± 0.13 /0.26 ± 0.18 mm3 (post-injection), respectively (p = 0.0170 for IRF, and p = 0.0004 for SRF). The Spearman correlation demonstrated that the reduction of IRF volume was negatively correlated with age (coefficient = -0.698, p = 0.006).

Conclusion

We developed a deep learning assisted fluid volume calculation algorithm with high sensitivity and specificity for assessing the volume of IRF and SRF in DME patients. Key words: deep learning; diabetic macular edema; optical coherence tomography.

Early Sign of Retinal Neovascularization Evolution in Diabetic Retinopathy: A Longitudinal OCT Angiography Study

Purpose

To assess whether the combination of en face OCT and OCT angiography (OCTA) can capture observable, but subtle, structural changes that precede clinically evident retinal neovascularization (RNV) in eyes with diabetic retinopathy (DR).

Design

Retrospective, longitudinal study.

Participants

Patients with DR that had at least 2 visits.

Methods

We obtained wide-field OCTA scans of 1 eye from each participant and generated en face OCT, en face OCTA, and cross-sectional OCTA. We identified eyes with RNV sprouts, defined as epiretinal hyperreflective materials on en face OCT with flow signals breaching the internal limiting membrane on the cross-sectional OCTA without recognizable RNV on en face OCTA and RNV fronds, defined as recognizable abnormal vascular structures on the en face OCTA. We examined the corresponding location from follow-up or previous visits for the presence or progression of the RNV.

Main Outcome Measures

The characteristics and longitudinal observation of early signs of RNV.

Results

From 71 eyes, we identified RNV in 20 eyes with the combination of OCT and OCTA, of which 13 (65%) were photographically graded as proliferative DR, 6 (30%) severe nonproliferative DR, and 1 (5%) moderate nonproliferative diabetic retinopathy. From these eyes, we identified 38 RNV sprouts and 26 RNV fronds at the baseline. Thirty-four RNVs (53%) originated from veins, 24 (38%) were from intraretinal microabnormalities, and 6 (9%) were from a nondilated capillary bed. At the final visit, 53 RNV sprouts and 30 RNV fronds were detected. Ten eyes (50%) showed progression, defined as having a new RNV lesion or the development of an RNV frond from an RNV sprout. Four (11%) RNV sprouts developed into RNV fronds with a mean interval of 7.0 months. Nineteen new RNV sprouts developed during the follow-up, whereas no new RNV frond was observed outside an identified RNV sprout. The eyes with progression were of younger age (P = 0.014) and tended to be treatment naive (P = 0.07) compared with eyes without progression.

Conclusions

Longitudinal observation demonstrated that a combination of en face OCT and cross-sectional OCTA can identify an earlier form of RNV before it can be recognized on en face OCTA.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Artificial Intelligence-Based Quantification of Central Macular Fluid Volume and VA Prediction for Diabetic Macular Edema Using OCT Images

INTRODUCTION

We studied the correlation of central macular fluid volume (CMFV) and central subfield thickness (CST) with best-corrected visual acuity (BCVA) in treatment-naïve eyes with diabetic macular edema (DME) 1 month after anti-vascular endothelial growth factor (VEGF) therapy.

METHODS

This retrospective cohort study investigated eyes that received anti-VEGF therapy. All participants underwent comprehensive examinations and optical coherence tomography (OCT) volume scans at baseline (M0) and 1 month after the first treatment (M1). Two deep learning models were separately developed to automatically measure the CMFV and the CST. Correlations were analyzed between the CMFV and the logMAR BCVA at M0 and logMAR BCVA at M1. The area under the receiver operating characteristic curve (AUROC) of CMFV and CST for predicting eyes with BCVA [Formula: see text] 20/40 at M1 was analyzed.

RESULTS

This study included 156 DME eyes from 89 patients. The median CMFV decreased from 0.272 (0.061-0.568) at M0 to 0.096 (0.018-0.307) mm3 at M1. The CST decreased from 414 (293-575) to 322 (252-430) μm. The logMAR BCVA decreased from 0.523 (0.301-0.817) to 0.398 (0.222-0.699). Multivariate analysis demonstrated that the CMFV was the only significant factor for logMAR BCVA at both M0 (β = 0.199, p = 0.047) and M1 (β = 0.279, p = 0.004). The AUROC of CMFV for predicting eyes with BCVA [Formula: see text] 20/40 at M1 was 0.72, and the AUROC of CST was 0.69.

CONCLUSIONS

Anti-VEGF therapy is an effective treatment for DME. Automated measured CMFV is a more accurate prognostic factor than CST for the initial anti-VEGF treatment outcome of DME.

Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina

This study sought to identify demographic variations in retinal thickness measurements from optical coherence tomography (OCT), to enable the calculation of cell density parameters across the neural layers of the healthy human macula. From macular OCTs (n = 247), ganglion cell (GCL), inner nuclear (INL), and inner segment-outer segment (ISOS) layer measurements were extracted using a customized high-density grid. Variations with age, sex, ethnicity, and refractive error were assessed with multiple linear regression analyses, with age-related distributions further assessed using hierarchical cluster analysis and regression models. Models were tested on a naïve healthy cohort (n = 40) with Mann-Whitney tests to determine generalizability. Quantitative cell density data were calculated from histological data from previous human studies. Eccentricity-dependent variations in OCT retinal thickness closely resemble topographic cell density maps from human histological studies. Age was consistently identified as significantly impacting retinal thickness (p = .0006, .0007, and .003 for GCL, INL and ISOS), with gender affecting ISOS only (p < .0001). Regression models demonstrated that age-related changes in the GCL and INL begin in the 30th decade and were linear for the ISOS. Model testing revealed significant differences in INL and ISOS thickness (p = .0008 and .0001; however, differences fell within the OCT's axial resolution. Qualitative comparisons show close alignment between OCT and histological cell densities when using unique, high-resolution OCT data, and correction for demographics-related variability. Overall, this study describes a process to calculate in vivo cell density from OCT for all neural layers of the human retina, providing a framework for basic science and clinical investigations.

Utility of En Face OCT for the Detection of Clinically Unsuspected Retinal Neovascularization in Patients with Diabetic Retinopathy

PURPOSE

To assess the value of en face OCT for detecting clinically unsuspected retinal neovascularization (RNV) in patients with nonproliferative diabetic retinopathy (NPDR).

DESIGN

A retrospective, cross-sectional study.

PARTICIPANTS

Treatment-naïve patients clinically graded as NPDR in an ongoing prospective observational OCT angiography (OCTA) study at a tertiary care center.

METHODS

Each patient underwent imaging of 1 eye with a spectral-domain OCTA, generating a 17 × 17-mm widefield image by montaging four 9 × 9-mm scans. Two independent graders examined a combination of en face OCT, en face OCTA with a custom vitreoretinal interface slab, and cross-sectional OCTA to determine the presence of RNV. We measured the area of RNV flow within RNV lesions on en face OCTA.

MAIN OUTCOME MEASURES

Detection rate of clinically occult RNV with OCT and OCTA.

RESULTS

Of 63 enrolled eyes, 27 (43%) were clinically graded as severe NPDR, 16 (25%) as moderate NPDR, and 20 (32%) as mild NPDR. Using the combination of en face OCT, en face OCTA, and cross-sectional OCTA, the graders detected 42 RNV lesions in 12 (19%) eyes, of which 8 (67%) were graded as severe NPDR, 2 (17%) as moderate NPDR, and 2 (17%) as mild NPDR. The sensitivity of en face OCT alone for detecting eyes with RNV was similar to that of en face OCTA alone (100% vs. 92%; P = 0.32), whereas the specificity of en face OCT alone was significantly lower than that of en face OCTA alone (32% vs. 73%; P < 0.001). For detecting individual RNV lesions, the en face OCT was 100% sensitive, compared with 67% sensitivity for the en face OCTA (P < 0.001). The area of RNV lesions that manual grading with en face OCTA alone missed was significantly smaller than that of manually detectable RNV (Mean [standard deviation] RNV flow area, 0.015 [0.020] mm2 vs. 0.16 [0.36] mm2; P < 0.001).

CONCLUSION

The combination of en face OCT and OCTA can detect clinically occult RNV with high sensitivity. For screening these small lesions, en face OCT may be a useful imaging modality.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Automated Macular Fluid Volume As a Treatment Indicator for Diabetic Macular Edema

Introduction: To assess the diagnostic accuracy of automatically quantified macular fluid volume (MFV) for treatment-required diabetic macular edema (DME). Methods: This retrospective cross-sectional study included eyes with DME. The commercial software on optical coherence tomography (OCT) produced the central subfield thickness (CST), and a custom deep-learning algorithm automatically segmented the fluid cysts and quantified the MFV from the volumetric scans of an OCT angiography system. Retina specialists treated patients per standard of care based on clinical and OCT findings without access to the MFV. The main outcome measures were the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity of the CST, MFV, and visual acuity (VA) for treatment indication. Results: Of 139 eyes, 39 (28%) were treated for DME during the study period and 101 (72%) were previously treated. The algorithm detected fluid in all eyes; however, only 54 eyes (39%) met the DRCR.net criteria for center-involved ME. The AUROC of MFV predicting a treatment decision of 0.81 was greater than that of CST (0.67) (P = .0048). Untreated eyes that met the optimal threshold for treatment-required DME based on MFV (>0.031 mm3) had better VA than treated eyes (P = .0053). A multivariate logistic regression model showed that MFV (P = .0008) and VA (P = .0061) were significantly associated with a treatment decision, but CST was not. Conclusions: MFV had a higher correlation with the need for treatment for DME than CST and may be especially useful for ongoing management of DME.

Short-term outcomes in patients with center-involving diabetic macular edema after a single dose of intravitreal bevacizumab

Background

A significant portion of diabetic macular edema (DME) is refractory to anti-vascular endothelial growth factor (anti-VEGF) agents. This study investigates morphological and functional outcomes to a single intravitreal bevacizumab (IVB) injection in patients with center-involving DME (ciDME) at 4–6 weeks and compares treatment responders and non-responders based on spectral domain optical coherence tomography (SD-OCT) features.

Methods

IRB approved observational, retrospective chart review of patients with ciDME, identified by ICD-10 code, who received IVB and underwent baseline and 4–6 weeks follow-up SD-OCT imaging between January 1, 2016 and January 19, 2021. Patients who had received previous treatment with anti-VEGF or intraocular steroids within 1 year were excluded. Variables included best-corrected visual acuity (BCVA), central subfield thickness (CST) and total macular volume (TMV). Eyes were classified as responders if CST reduction was greater than 10%. OCT scans were graded qualitatively by two masked graders using Imagivault software. Paired Student’s t-tests, Wilcoxon signed rank tests and Chi-Square tests were used for analysis.

Results

A total of 334 prospective subjects were identified, and after applying exclusion criteria 52 eyes from 46 patients (mean age 64.22 ± 8.12 years, 58.7% male) were included. Mean BCVA did not significantly change with treatment, 63.9 ETDRS letters (~ 20/50) at baseline and 65.9 ETDRS letters (~ 20/50) post-treatment (p = 0.07). Mean CST decreased from 466 ± 123 μm at baseline to 402 ± 86 μm post-treatment (p < 0.001). 22 (42.3%) of eyes were categorized as responders and 30 (57.7%) as non-responders. Average change in CST from baseline in responders was -164 μm (p < 0.001) and + 9 μm in non-responders (p = 0.47). Vitreomacular adhesion (VMA) was more prevalent in non-responders (28.7% vs. 4.8%, p = 0.03). In addition, cyst location in the inner nuclear layer (INL) was present more frequently in responders (95.5% vs. 73.3%, p = 0.037) as was subretinal fluid (45.5% vs. 13.3%, p = 0.01).

Conclusion

The short-term response to a single IVB was sub-optimal with structural but no functional improvements. Greater baseline CST, presence of INL cysts and subretinal fluid may represent factors indicative of a better treatment response.

OCT-Based Biomarkers are Associated with Systemic Inflammation in Patients with Treatment-Naïve Diabetic Macular Edema

INTRODUCTION

Diabetic macular edema (DME) is one of the major sight-threatening complications of diabetic retinopathy, which is associated with retinal inflammation. However, it is still unknown whether DME is associated with systemic inflammation. The study aimed to investigate the association between systemic inflammatory and optical coherence tomography (OCT) biomarkers in patients with treatment-naïve center-involving diabetic macular edema (DME) and to further explore the role of systemic inflammation in DME.

METHODS

Medical records including clinical characteristics and ophthalmic examinations were collected from patients with treatment-naïve center-involving DME. Systemic inflammation markers including systemic immune-inflammatory index (SII), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) were calculated. OCT biomarkers, including intraretinal cyst (IRC) size, disorganization of retinal inner layers (DRIL), external limiting membrane (ELM)/ellipsoid zone (EZ) integrity, retinal hyperreflective foci (HRF), subretinal fluid (SRF) and vitreomacular (VM) status were evaluated manually. Correlation analysis and multivariable linear regression models were used to investigate the relationship between systemic inflammatory markers and OCT biomarkers.

RESULTS

A total of 82 patients with treatment-naïve center-involving DME were included. The number of HRF on OCT was correlated with SII, NLR, and PLR and positively associated with SII (p < 0.001) in both univariate and multivariate linear regression analyses. The differences remained largely the same during subgroup analysis controlling DM duration, SRF, and ELM/EZ integrity. No significant association was observed between other OCT biomarkers and blood inflammatory markers.

CONCLUSION

Retinal HRF in diabetic macular edema is associated with blood inflammatory markers, which supports the theory of HRF's inflammatory nature and emphasizes the important role of inflammation in DME. SII may be a potential marker for DME treatment decisions.