0.18 MG FLUOCINOLONE ACETONIDE INSERT FOR THE TREATMENT OF CHRONIC POSTOPERATIVE PSEUDOPHAKIC CYSTOID MACULAR EDEMA

PURPOSE

To report the outcomes of the 0.18 mg fluocinolone acetonide insert (FAi) in the treatment of chronic (>6 months) postoperative cystoid macular edema after cataract surgery.

METHODS

This was a retrospective consecutive case series of eyes with chronic postoperative cystoid macular edema treated with the FAi. Visual acuity, intraocular pressure, optical coherence tomography metrics, and supplemental therapies were extracted from the charts before and at 3, 6, 12, 18, and 21 months after FAi placement, when available.

RESULTS

Nineteen eyes of 13 patients with chronic postoperative cystoid macular edema after cataract surgery underwent FAi placement with an average follow-up of 15.4 months. Ten eyes (52.6%) had a ≥2-line gain in visual acuity. Sixteen eyes (84.2%) had a ≥20% reduction in optical coherence tomography central subfield thickness. Eight eyes (42.1%) had complete resolution of CME. Improvements in central subfield thickness and visual acuity were sustained throughout individual follow-up. Compared with 18 eyes (94.7%) requiring local corticosteroid supplementation before FAi, only six eyes (31.6%) required supplementation after FAi. Similarly, of the 12 eyes (63.2%) that were on corticosteroid drops before FAi, only 3 (15.8%) required drops after FAi.

CONCLUSION

Eyes with chronic postoperative cystoid macular edema after cataract surgery treated with the FAi had improved and sustained visual acuity and optical coherence tomography metrics, along with a reduction in supplemental treatment burden.

MULTIMODAL IMAGING FINDINGS IN ACUTE WEST NILE VIRUS CHORIORETINITIS

PURPOSE

To describe multimodal imaging findings of acute West Nile virus chorioretinitis.

METHODS

Observational case report. Fundus photographs, fluorescein angiography, indocyanine green angiography, and swept-source optical coherence tomography angiography were used to characterize and describe the clinical findings.

RESULTS

A 58-year-old man presented with acute painless vision loss in the right eye. Multimodal imaging demonstrated multifocal pinpoint early-phase hyperfluorescence with late expanding leakage on fluorescein angiography and late hyperfluorescence on indocyanine green angiography. Swept-source optical coherence tomography angiography en face imaging of the ellipsoid zone layer revealed target-like lesions with central hyperreflectivity with surrounding hyporeflectivity. At 4-week follow-up, the chorioretinal lesions now demonstrated greater demarcation of borders with increased pigmentation. At 8-week follow-up, fundus examination revealed multiple target-like lesions with hyperpigmentation centrally surrounded by a hypopigmented rim. Repeat fluorescein angiography demonstrated central hypofluorescence with surrounding hyperfluorescent staining rim prompting workup for West Nile virus, which was later confirmed by laboratory testing. The patient's visual acuity and clinical examination remained stable on subsequent follow-up visits.

CONCLUSION

Our case highlights multimodal imaging findings in the acute phase of West Nile virus chorioretinitis, which may be crucial to early diagnosis and identification.

Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD

BACKGROUND

The development and testing of a deep learning (DL)-based approach for detection and measurement of regions of Ellipsoid Zone (EZ) At-Risk to study progression in nonexudative age-related macular degeneration (AMD).

METHODS

Used in DL model training and testing were 341 subjects with nonexudative AMD with or without geographic atrophy (GA). An independent dataset of 120 subjects were used for testing model performance for prediction of GA progression. Accuracy, specificity, sensitivity, and intraclass correlation coefficient (ICC) for DL-based EZ At-Risk percentage area measurement was calculated. Random forest-based feature ranking of EZ At-Risk was compared to previously validated quantitative OCT-based biomarkers.

RESULTS

The model achieved a detection accuracy of 99% (sensitivity = 99%; specificity = 100%) for EZ At-Risk. Automatic EZ At-Risk measurement achieved an accuracy of 90% (sensitivity = 90%; specificity = 84%) and the ICC compared to ground truth was high (0.83). In the independent dataset, higher baseline mean EZ At-Risk correlated with higher progression to GA at year 5 (p < 0.001). EZ At-Risk was a top ranked feature in the random forest assessment for GA prediction.

CONCLUSIONS

This report describes a novel high performance DL-based model for the detection and measurement of EZ At-Risk. This biomarker showed promising results in predicting progression in nonexudative AMD patients.

Screening, Monitoring, and Treating Children With Juvenile Idiopathic Arthritis-associated Uveitis: Visualizing Better Outcomes

Noninfectious ocular inflammatory disease, or uveitis, is a common and devastating complication of juvenile idiopathic arthritis (JIA). As many as 20% of children with JIA develop JIA-associated uveitis (JIA-U), and 50% experience ocular complications that can lead to damage.1,2

Over Expression of Cancer Stem Cell Marker CD44 and Its Clinical Significance in Patients with Oral Squamous Cell Carcinoma

Cancer stem cell marker CD44 is a cell-surface glycoprotein which is involved in various cellular functions such as cell-cell interactions, cell adhesion, haematopoiesis and tumour metastasis. The CD44 gene transcription is partly activated by beta-catenin and Wnt signalling pathway, the later pathway being linked to tumour development. However, the role of CD44 in oral squamous cell carcinoma (OSCC) is not well understood. We investigated the expression of CD44 in peripheral circulation, tumour tissues of oral cancer patients and oral squamous cell carcinoma cell lines by ELISA and quantitative (q)-RTPCR. Relative CD44s mRNA expression was significantly higher in peripheral circulation (p = 0.04), tumour tissues (p = 0.049) and in oral cancer cell lines (SCC4, SCC25 p = 0.02, SCC9 p = 0.03). Circulating CD44total protein levels were also significantly (p < 0.001) higher in OSCC patients that positively correlated with increasing tumour load and loco-regional spread of the tumour. The circulating tumour stem cell marker CD44 appears to be a potent indicator of tumour progression and may be useful for developing suitable therapeutics strategies for patients with oral squamous cell carcinoma.

Longitudinal Quantitative Ultrawide-field Fluorescein Angiography Dynamics in the RUBY Diabetic Macular Edema Study

OBJECTIVE

The purpose of this study was to evaluate the longitudinal change in quantitative ultrawide-field angiographic (UWFA) parameters and correlate them with functional outcomes and spectral domain-OCT metrics.

DESIGN

This study is a post hoc analysis of the phase II RUBY study: a prospective, randomized trial of patients with diabetic macular edema (DME) treated with either intravitreal aflibercept injection (IAI) or combined IAI/nesvacumab (antiangiopoietin 2 mAb).

SUBJECTS

Subjects with DME that underwent UWFA across all treatment groups (n = 44).

METHODS

A machine learning-enabled feature extraction system generated panretinal quantitative UWFA metrics, including leakage, ischemia, and microaneurysm (MA) burden. Zonal assessments were performed corresponding to the macula, midperiphery, and far periphery.

MAIN OUTCOME MEASURES

Changes in ischemic area and index (proportion of nonperfusion in analyzable retina), leakage area and index (proportion of leakage in analyzable retina), and MA count at baseline, week 12, week 24, and week 36 were analyzed. Spectral-domain-OCT quantitative metrics, such as central subfield thickness, ellipsoid zone (EZ) integrity parameters, intraretinal fluid (IRF) volume, and subretinal fluid (SRF) volume were extracted via a machine learning-enhanced OCT feature extraction platform and analyzed. Additionally, the effect of these changes on best-corrected visual acuity (BCVA) was evaluated.

RESULTS

Mean panretinal leakage index, zonal leakage area, and panretinal MA count improved significantly between baseline and week 36. Panretinal ischemic index decreased between baseline and week 36, with some aspects showing significant improvement. Mean BCVA significantly improved from baseline to week 36. There was a significant inverse correlation between change in BCVA and change in macular leakage area. A direct correlation was observed between both baseline macular leakage area and panretinal leakage index with IRF volume, SRF volume, and EZ disruption on OCT.

CONCLUSIONS

Assessment of UWFA parameters demonstrates a significant improvement in panretinal leakage index, leakage area, and MA burden in eyes treated with IAI with or without nesvacumab. A numeric reduction in panretinal ischemic index and area was noted. The analysis also shows the critical association of leakage with visual and OCT features. This highlights the potential role of UWFA in disease burden assessment, with leakage parameters serving as a primary end point.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found after the references.

Machine Learning-Based Automated Detection of Hydroxychloroquine Toxicity and Prediction of Future Toxicity Using Higher-Order OCT Biomarkers

OBJECTIVE

Despite guidelines for hydroxychloroquine (HCQ) toxicity screening, there are clear challenges to accurate detection and interpretation. In the current report, the feasibility of automated machine learning (ML)-based detection of HCQ retinopathy and prediction of progression to toxicity in eyes without preexisting toxicity has been described.

DESIGN

Retrospective, longitudinal cohort study.

SUBJECTS

Subjects on HCQ therapy.

METHODS

This was an institutional review board-approved, retrospective, longitudinal image analysis of 388 subjects on HCQ. Multilayer, compartmental, retinal segmentation with ellipsoid zone (EZ) mapping was used to harvest quantitative spectral-domain (SD)-OCT biomarkers. Using a combination of clinical features (i.e., cumulative HCQ dose and the duration of therapy) and quantitative imaging biomarkers (e.g., volumetric EZ integrity and compartmental measurements), ML models were created to detect toxicity and predict progression based on ground-truth OCT-based toxicity readings by 2 masked retina specialists. Furthermore, 10-fold cross-validation was performed.

MAIN OUTCOME MEASURES

The model performance was visualized using receiver operator curves and calculating the area under the curve (AUC). The corresponding sensitivity and specificity values were evaluated for the feasibility of HCQ toxicity screening and prediction.

RESULTS

The prevalence of HCQ toxicity in this cohort of 388 patients was 9.8% (n = 38). Twenty-one eyes progressed to toxicity during follow-up. OCT-based features (i.e., partial EZ attenuation, EZ volume, outer nuclear layer volume, and compartmental thicknesses) and clinical features (i.e., HCQ daily dose, HCQ cumulative dose, and duration of therapy) showed significant differences between the toxic and nontoxic groups. Percentage area with partial EZ attenuation (i.e., percentage of the macula with an EZ-retinal pigment epithelium thickness of ≤ 20 μm) was the most discriminating single feature (toxic, 35.7 ± 46.5%; nontoxic, 1.8 ± 4.4%; P < 0.0001). Using a random forest model, high-performance, automated toxicity detection was achieved, with a mean AUC of 0.97, sensitivity of 95%, and specificity of 91%. Furthermore, the toxicity progression prediction model had a mean AUC of 0.89, with a sensitivity and specificity of 90% and 80%, respectively.

CONCLUSIONS

This report described the feasibility of high-performance automated classification models that used a combination of clinical and quantitative SD-OCT biomarkers to detect HCQ retinal toxicity and predict progression to toxicity in cases without toxicity. Future work is needed to validate these findings in an independent dataset.

Effect of endogenous hormones, antisperm antibody and oxidative stress on semen quality of crossbred bulls

The present study was designed to evaluate the effect of factors like hormones, antisperm antibody (ASA), and oxidative stress and its relation with semen quality in crossbred bulls. Ejaculates from two bulls were categorized into good (n = 12) and poor (n = 12) based on initial progressive motility, that is, ≥70% and ≤50%, respectively. The level of hormones like Testosterone (p < 0.05) and PGE₂ (p < 0.01) was significantly higher in good-quality ejaculates compared to poor-quality ejaculates; however, estradiol (p < 0.05), progesterone, oxidative stress, and ASAs were significantly higher (p < 0.01) in poor-quality ejaculates compared to good-quality ejaculates. Therefore, it could be concluded that oxidative stress and hormonal imbalance might have resulted in high number of dead and defective spermatozoa which was ultimately responsible for poor quality semen ejaculates.

OCT-Derived Radiomic Features Predict Anti-VEGF Response and Durability in Neovascular Age-Related Macular Degeneration

PURPOSE

No established biomarkers currently exist for therapeutic efficacy and durability of anti-VEGF therapy in neovascular age-related macular degeneration (nAMD). This study evaluated radiomic-based quantitative OCT biomarkers that may be predictive of anti-VEGF treatment response and durability.

DESIGN

Assessment of baseline biomarkers using machine learning (ML) classifiers to predict tolerance to anti-VEGF therapy.

PARTICIPANTS

Eighty-one participants with treatment-naïve nAMD from the OSPREY study, including 15 super responders (patients who achieved and maintained retinal fluid resolution) and 66 non-super responders (patients who did not achieve or maintain retinal fluid resolution).

METHODS

A total of 962 texture-based radiomic features were extracted from fluid, subretinal hyperreflective material (SHRM), and different retinal tissue compartments of OCT scans. The top 8 features, chosen by the minimum redundancy maximum relevance feature selection method, were evaluated using 4 ML classifiers in a cross-validated approach to distinguish between the 2 patient groups. Longitudinal assessment of changes in different texture-based radiomic descriptors (delta-texture features) between baseline and month 3 also was performed to evaluate their association with treatment response. Additionally, 8 baseline clinical parameters and a combination of baseline OCT, delta-texture features, and the clinical parameters were evaluated in a cross-validated approach in terms of association with therapeutic response.

MAIN OUTCOME MEASURES

The cross-validated area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to validate the classifier performance.

RESULTS

The cross-validated AUC by the quadratic discriminant analysis classifier was 0.75 ± 0.09 using texture-based baseline OCT features. The delta-texture features within different OCT compartments between baseline and month 3 yielded an AUC of 0.78 ± 0.08. The baseline clinical parameters sub-retinal pigment epithelium volume and intraretinal fluid volume yielded an AUC of 0.62 ± 0.07. When all the baseline, delta, and clinical features were combined, a statistically significant improvement in the classifier performance (AUC, 0.81 ± 0.07) was obtained.

CONCLUSIONS

Radiomic-based quantitative assessment of OCT images was shown to distinguish between super responders and non-super responders to anti-VEGF therapy in nAMD. The baseline fluid and SHRM delta-texture features were found to be most discriminating across groups.

Bacillary Detachment in Neovascular Age-Related Macular Degeneration: Incidence, Clinical Features, and Response to Anti-VEGF Therapy

OBJECTIVE

To evaluate the incidence of bacillary layer detachment among patients with neovascular age-related macular degeneration (nAMD) and their response to anti-VEGF therapy.

DESIGN

Post hoc analysis of the OSPREY clinical trial, a prospective, double-masked, phase II study comparing 6-mg brolucizumab with 2-mg aflibercept over 56 weeks.

PARTICIPANTS

Participants with treatment-naive nAMD at the initiation of the trial were included in the analysis (n = 81).

METHODS

Spectral-domain OCT (SD-OCT) scans were obtained at 4-week intervals throughout the OSPREY study and were segmented automatically using a proprietary, machine learning-enabled higher-order feature-extraction platform.

MAIN OUTCOME MEASURES

The presence of bacillary detachment, and in these eyes the effect of anti-VEGF therapy on change from baseline in visual acuity (VA), central subfield thickness (CST), retinal fluid volumes, subretinal hyper-reflective material (SHRM) volume, subretinal pigment epithelium (sub-RPE) fluid volume, and ellipsoid zone (EZ) integrity at week 56.

RESULTS

Bacillary detachment was identified in 7.4% (6 of 81) eyes, which had higher fluid volumes, increased CST, EZ attenuation, and increased sub-RPE volume at baseline compared with eyes without bacillary detachment. Anti-VEGF treatment resulted in the resolution of bacillary detachment in 100% of the eyes. In eyes with bacillary detachment at baseline, the anti-VEGF treatment decreased CST, fluid burden, and SHRM volumes throughout the treatment course; however, there was no significant change from baseline in VA, sub-RPE volume, or EZ integrity throughout the 56-week course of anti-VEGF treatment.

CONCLUSIONS

Bacillary detachment is an OCT signature that is identifiable in a notable proportion of nAMD eyes. Anti-VEGF therapy resulted in 100% resolution of bacillary detachment and significant decreases in CST and SHRM volume; however, improvements in VA may have been limited by persistent EZ attenuation.

Impact of Baseline Quantitative OCT Features on Response to Risuteganib for the Treatment of Dry Age-Related Macular Degeneration: The Importance of Outer Retinal Integrity

OBJECTIVE

The purpose of the study was to perform a post hoc analysis to explore the effect of baseline anatomic characteristics identified on OCT on best-corrected visual acuity (BCVA) responses to risuteganib from the completed phase II study in subjects with dry age-related macular degeneration (AMD).

DESIGN

Post hoc analysis of a randomized, double-masked, placebo-controlled, phase II study.

SUBJECTS

Eyes with intermediate dry AMD with BCVA between 20/40 and 20/200. Patients with concurrent vision-influencing or macula-obscuring ocular pathologies were excluded.

METHODS

Patients were randomized to receive a 1-mg intravitreal risuteganib injection or a sham injection at baseline. A second 1-mg intravitreal injection of risuteganib was given at week 16 to those in the treatment arm. Two independent, masked reading centers evaluated the baseline anatomic characteristics on OCT to explore features associated with positive responses to risuteganib.

MAIN OUTCOME MEASURES

Treatment response was defined as a gain of ≥ 8 letters in BCVA from baseline to week 28 in the treatment arm, compared with baseline to week 12 in the sham group. Anatomic parameters, measured by retinal segmentation platforms, including measures of retinal thickness were compared between the responders and nonresponders to risuteganib.

RESULTS

Thirty-nine patients completed the study and underwent analysis. In the treatment arm, 48% of eyes demonstrated treatment responses, compared with 7% in the sham group. In the quantitative anatomic assessment, enhanced ellipsoid integrity, greater outer retinal thickness, and decreased geographic atrophy were associated with increased BCVA gains to risuteganib.

CONCLUSIONS

This post hoc analysis demonstrated that baseline OCT features may help determine the likelihood of a functional response to risuteganib. The characterization of higher-order OCT features may provide important information regarding biomarkers for treatment response and could facilitate optimized clinical trial enrollment and enrichment.

Exploring the angiographic-biologic phenotype in the IMAGINE study: quantitative UWFA and cytokine expression

BACKGROUND

This study investigates the association of intraocular cytokine expression and ultrawide-field fluorescein angiography (UWFA) quantitative imaging biomarkers and their association with angiographical feature response after antivascular endothelial growth factor (VEGF) therapy in diabetic macular oedema (DME).

METHODS

The IMAGINE DME study is a post hoc imaging biomarker and intraocular cytokine assessment from the DAVE study, a prospective DME clinical trial that included aqueous humour sampling and UWFA imaging. Fifty-four cytokines associated with inflammation and angiogenesis were evaluated through multiplex arrays. UWFA parameters were assessed using an automated feature analysis platform to determine ischaemic and leakage indices and microaneurysm (MA) count. Eyes were classified into UWFA responder or non-responder groups based on longitudinal quantitative UWFA parameter improvement. Cytokine expression was correlated with UWFA metrics and evaluated in the context of therapeutic response.

RESULTS

Twenty-one eyes were included with a mean age of 55±10 years. Increased panretinal leakage index correlated with VEGF (r=0.70, p=0.0005), angiopoietin-like 4 (r=0.77, p=4.6E-5) and interleukin (IL)-6 (r=0.64, p=0.002). Panretinal ischaemic index was associated with tissue inhibitor of metalloproteinases 1 (TIMP-1, r=0.49, p=0.03) and peripheral ischaemia correlated with VEGF (r=0.45, p=0.05). MA count correlated with increased monocyte chemotactic protein-4 (MCP-4, r=0.60, p=0.004) and platelet and endothelial cell adhesion molecule 1 (PECAM-1, r=0.58, p=0.005). Longitudinal MA reduction was associated with decreased baseline VEGF and urokinase receptor (uPAR) (p<0.05). High baseline VEGF and IL-6 were associated with dramatic reduction in macular leakage (p<0.05).

CONCLUSIONS

Baseline and longitudinal quantitative UWFA imaging parameters correlated with multiple aqueous humour cytokine concentrations, including VEGF and IL-6. Further research is needed to assess the possible implications of using these findings for evaluating treatment response.

Deep learning-enabled ultra-widefield retinal vessel segmentation with an automated quality-optimized angiographic phase selection tool

OBJECTIVES

To demonstrate the feasibility of a deep learning-based vascular segmentation tool for UWFA and evaluate its ability to automatically identify quality-optimized phase-specific images.

METHODS

Cumulative retinal vessel areas (RVA) were extracted from all available UWFA frames. Cubic splines were fitted for serial vascular assessment throughout the angiographic phases of eyes with diabetic retinopathy (DR), sickle cell retinopathy (SCR), or normal retinal vasculature. The image with maximum RVA was selected as the optimum early phase. A late phase frame was selected at a minimum of 4 min that most closely mirrored the RVA from the selected early image. Trained image analysts evaluated the selected pairs.

RESULTS

A total of 13,980 UWFA sequences from 462 sessions were used to evaluate the performance and 1578 UWFA sequences from 66 sessions were used to create cubic splines. Maximum RVA was detected at a mean of 41 ± 15, 47 ± 27, 38 ± 8 s for DR, SCR, and normals respectively. In 85.2% of the sessions, appropriate images for both phases were successfully identified. The individual success rate was 90.7% for early and 94.6% for late frames.

CONCLUSIONS

Retinal vascular characteristics are highly phased and field-of-view sensitive. Vascular parameters extracted by deep learning algorithms can be used for quality assessment of angiographic images and quality optimized phase selection. Clinical applications of a deep learning-based vascular segmentation and phase selection system might significantly improve the speed, consistency, and objectivity of UWFA evaluation.

The Association of Fluid Volatility With Subretinal Hyperreflective Material and Ellipsoid Zone Integrity in Neovascular AMD

Purpose

To evaluate the association of fluid volatility with ellipsoid zone (EZ) integrity and subretinal hyperreflective material (SHRM) volume during anti–vascular endothelial growth factor (VEGF) therapy in neovascular age-related macular degeneration (nAMD).

Methods

This study was a post hoc analysis of the OSPREY study. Retinal volatility was quantified as the standard deviation across weeks 12 to 56 for six optical coherence tomography (OCT) metrics: central subfield thickness (CST), total fluid (TF) volume, subretinal fluid (SRF) volume, intraretinal fluid (IRF) volume, macular total retinal fluid index (TRFI), and central macular TRFI. Eyes with volatility ≤ 25th or ≥ 75th percentile values were compared.

Results

Eyes with low volatility in several exudative metrics showed greater change from baseline in SHRM volume at week 12 than eyes with high volatility. During the maintenance phase (weeks 12–56), eyes exhibiting high SRF volatility demonstrated increased SHRM volume compared to eyes with low SRF volatility (P = 0.027). Eyes exhibiting high volatility in CST, TF, and SRF demonstrated less improvement in EZ total attenuation (P < 0.001, P = 0.033, and P = 0.043, respectively) than eyes with low volatility. Early exudative instability (i.e., between weeks 4–8 or weeks 8–12) in multiple parameters (i.e., CST, TF, IRF, macular TRFI, or central macular TRFI) was associated with greater volatility during the maintenance phase (P < 0.05).

Conclusions

Greater volatility in exudative OCT metrics, particularly SRF volatility, was associated with a greater increase in SHRM and less improvement in EZ integrity, suggesting that volatility is detrimental to multiple anatomic features in nAMD. Early exudative instability during the loading phase of treatment was associated with longer-term volatility in exudation.

Computational Imaging Biomarker Correlation with Intraocular Cytokine Expression in Diabetic Macular Edema

Purpose

Design

Participants

Methods

Main Outcome Measures

Results

Conclusions

Characterization of Ultra-Widefield Angiographic Vascular Features in Diabetic Retinopathy with Automated Severity Classification

Purpose

To determine the association between diabetic retinopathy (DR) severity and quantitative retinal vascular features.

Design

Retrospective image analysis study.

Participants

Eyes with DR and eyes with no posterior segment disease (normal eyes) that had undergone ultra-widefield fluorescein angiography (UWFA) with associated color fundus photography. Exclusion criteria were any previous laser photocoagulation, low image quality, intravitreal or periocular pharmacotherapy within 6 months of imaging, and any other significant retinal disease including posterior uveitis, retinal vein occlusion, and choroidal neovascularization.

Methods

The centered early mid-phase UWFA frame that captured the maximum vessel area was selected using automated custom software for each eye. Panretinal and zonal vascular features were extracted using a machine learning algorithm. Eyes with DR were graded for DR severity as mild nonproliferative DR (NPDR), moderate NPDR, severe NPDR, and proliferative DR (PDR). Parameters of normal eyes were compared with age- and gender-matched patients with DR using the t test. Differences between severity groups were evaluated by the analysis of variance and Kruskal-Wallis tests, generalized linear mixed-effects models, and random forest regression models.

Main Outcome Measures

Diabetic retinopathy severity and vascular features (panretinal and zonal vessel area, length and geodesic distance, panretinal area index, tortuosity measures, vascular density measures, and zero vessel density rate).

Results

Ninety-seven eyes from 60 patients with DR and 12 normal eyes from 12 patients that underwent UWFA for evaluation of fellow eye pathology had images of sufficient quality to be included in this analysis. The mean age was 60 ± 10 years in DR eyes and 46 ± 17 years in normal eyes. Panretinal vessel area, mean geodesic distance, skewness, and kurtosis of local vessel density was significantly higher in normal eyes compared with the age- and gender-matched eyes with DR (P < 0.05). Zero vessel density rate, skewness of vessel density, and mean mid-peripheral geodesic distance were among the most important features for distinguishing mild NPDR from advanced forms of DR and PDR versus eyes without PDR.

Conclusions

Automated analysis of retinal vasculature demonstrated associations with DR severity and visual and subvisual vascular biomarkers. Further studies are needed to evaluate the clinical significance of these parameters for DR prognosis and therapeutic response.

Local magnetic behaviour of highly disordered undoped and Co-doped Bi2Se3 nanoplates: a muon spin relaxation study

Magnetism induced by defects in nominally non-magnetic solids has attracted intense scientific interest in recent years. The local magnetism in highly disordered undoped and Co-doped topological insulator (TI) Bi₂Se₃nanoplates has been investigated by muon spin relaxation (μSR). UsingμSR spectroscopy, together with other macroscopic characterizations, we find that these nanoplates are composed of a core with both static fields and dynamically fluctuating moments, and a shell with purely dynamically fluctuating moments. The fluctuations in the core die out at low temperatures, while those in the shell continue till 2 K. When Bi₂Se₃is doped with Co, the static magnetic component increases, whilst keeping the dual (static-plus-dynamic) nature intact. The findings indicate that highly disordered TI's could constitute a new class of promising magnetic materials that can be engineered by magnetic impurity doping.

LONGITUDINAL ELLIPSOID ZONE AND OUTER RETINAL INTEGRITY DYNAMICS AFTER EPIRETINAL MEMBRANE SURGERY

PURPOSE

To quantify ellipsoid zone (EZ) changes in integrity after epiretinal membrane (ERM) surgery, correlate findings to visual acuity, and determine predictors for prognosis.

METHODS

A post hoc analysis of eyes undergoing ERM surgery pooled from the prospective DISCOVER intraoperative optical coherence tomography study and eyes undergoing conventional ERM surgery without intraoperative optical coherence tomography. Quantitative EZ features were extracted using a multilayer machine learning enabled automated segmentation platform after image analyst review/correction for segmentation accuracy. Visual acuity and EZ integrity were quantitatively assessed and correlated before and after ERM surgery. Multiple linear regression was performed to assess preoperative visual acuity and EZ features as predictors for improvement in visual acuity or EZ integrity.

RESULTS

There were 177 eyes from 177 subjects that underwent ERM surgery from the DISCOVER and conventional arms. Improvement in visual acuity and multiple EZ integrity features was noted after ERM surgery, including EZ partial attenuation and EZ-retinal pigment epithelium (RPE) volume (P < 0.05). A reduction in EZ partial attenuation and increase in EZ-RPE central subfield thickness (EZ-RPE CST) was significantly correlated with improved visual acuity after ERM surgery (P < 0.05). More robust EZ-RPE CST at baseline predicted visual acuity improvement after ERM peel in regression modeling (β = 0.005, P < 0.05).

CONCLUSIONS

Longitudinal assessment of EZ features demonstrates significant postoperative improvement in multiple EZ integrity metrics after ERM surgery. Improving EZ integrity was correlated to improving the visual acuity. Ellipsoid zone integrity and visual acuity were significant predictors in regression modeling and may have value in clinical prognostication.

Corneal epithelial defects following vitreoretinal surgery: incidence and outcomes from the DISCOVER study

AIM

To investigate the incidence, risk factors, clinical course, and outcomes of corneal epithelial defects (CED) following vitreoretinal surgery in a prospective study setting.

METHODS

This was a post-hoc analysis of all participants in DISCOVER intraoperative optical coherence tomography study. Subjects with CED 1d after surgery without intraoperative corneal debridement was defined as the postoperative CED group. Subjects who underwent intraoperative debridement were defined as intraoperative debridement group. Eyes were matched 2:1 with controls (eyes without postoperative CED) for comparative assessment. The primary outcomes were the incidence of CED on postoperative day one and the incidence of required intraoperative debridement. Secondary outcomes included time to defect closure, delayed healing (>2wk), visual acuity (VA) and presence of scarring at one year and cornea consult.

RESULTS

This study included 856 eyes that underwent vitreoretinal surgery. Intraoperative corneal debridement was performed to 61 (7.1%) subjects and postoperative CED developed spontaneously in 94 (11.0%) subjects. Significant factors associated with postoperative CED included prolonged surgical duration (P=0.003), diabetes mellitus (P=0.04), postoperative ocular hypotension (P<0.001). Prolonged surgical duration was associated with intraoperative debridement. Delayed defect closure time (>2wk) was associated with corneal scar formation at the end of the 1y in all epithelial defect subjects (P<0.001). The overall rate of corneal scarring for all eyes undergoing vitrectomy was 1.8%.

CONCLUSION

Prolonged duration of surgery is the strongest factor associated with both intraoperative debridement and spontaneous postoperative CED. Delayed defect closure is associated with a greater risk of corneal scarring at one year. The overall rate of corneal scarring following vitrectomy is low at <2%.

Evaluating the utility of deep learning for predicting therapeutic response in diabetic eye disease

Purpose

Deep learning (DL) is a technique explored within ophthalmology that requires large datasets to distinguish feature representations with high diagnostic performance. There is a need for developing DL approaches to predict therapeutic response, but completed clinical trial datasets are limited in size. Predicting treatment response is more complex than disease diagnosis, where hallmarks of treatment response are subtle. This study seeks to understand the utility of DL for clinical problems in ophthalmology such as predicting treatment response and where large sample sizes for model training are not available.

Materials and Methods

Four DL architectures were trained using cross-validated transfer learning to classify ultra-widefield angiograms (UWFA) and fluid-compartmentalized optical coherence tomography (OCT) images from a completed clinical trial (PERMEATE) dataset (n=29) as tolerating or requiring extended interval Anti-VEGF dosing. UWFA images (n=217) from the Anti-VEGF study were divided into five increasingly larger subsets to evaluate the influence of dataset size on performance. Class activation maps (CAMs) were generated to identify regions of model attention.

Results

The best performing DL model had a mean AUC of 0.507 ± 0.042 on UWFA images, and highest observed AUC of 0.503 for fluid-compartmentalized OCT images. DL had a best performing AUC of 0.634 when dataset size was incrementally increased. Resulting CAMs show inconsistent regions of interest.

Conclusions

This study demonstrated the limitations of DL for predicting therapeutic response when large datasets were not available for model training. Our findings suggest the need for hand-crafted approaches for complex and data scarce prediction problems in ophthalmology.

Risk Classification for Progression to Subfoveal Geographic Atrophy in Dry Age-Related Macular Degeneration Using Machine Learning-Enabled Outer Retinal Feature Extraction

BACKGROUND AND OBJECTIVE

To evaluate the utility of spectral-domain optical coherence tomography biomarkers to predict the development of subfoveal geographic atrophy (sfGA).

PATIENTS AND METHODS

This was a retrospective cohort analysis including 137 individuals with dry age-related macular degeneration without sfGA with 5 years of follow-up. Multiple spectral-domain optical coherence tomography quantitative metrics were generated, including ellipsoid zone (EZ) integrity and subretinal pigment epithelium (sub-RPE) compartment features.

RESULTS

Reduced mean EZ-RPE central subfield thickness and increased sub-RPE compartment thickness were significantly different between sfGA convertors and nonconvertors at baseline in both 2-year and 5-year sfGA risk assessment. Longitudinal change assessment showed a significantly higher degradation of EZ integrity in sfGA convertors. The predictive performance of a machine learning classification model based on 5-year and 2-year risk conversion to sfGA demonstrated an area under the receiver operating characteristic curve of 0.92 ± 0.06 and 0.96 ± 0.04, respectively.

CONCLUSIONS

Quantitative outer retinal and sub-RPE feature assessment using a machine learning-enabled retinal segmentation platform provides multiple parameters that are associated with progression to sfGA. [Ophthalmic Surg Lasers Imaging. 2022;53:31-39.].

Retinal Vasculitis Associated With Dermatomyositis Treated With Intravenous Steroids

Purpose:

This work aims to present treatment and long-term follow-up of a 31-year-old woman with dermatomyositis who presented with hemorrhagic retinal vasculitis and macular edema.

Methods:

A retrospective case report is presented.

Results:

A 31-year-old woman with dermatomyositis treated with systemic immunosuppression was evaluated for acute, reduced vision. Best-corrected visual acuity was hand motion in the right eye and 20/200 in the left eye. Fundus examination revealed diffuse intraretinal hemorrhages, cotton-wool spots, and vascular sheathing with a frosted branch angiitis–like appearance. Optical coherence tomography revealed significant macular edema and subretinal fluid that quickly resolved after admission and treatment with intravenous steroids. Multimodal imaging at 7-year follow-up disclosed long-term sequelae including peripheral nonperfusion and retinal neovascularization.

Conclusions:

When vasculitis associated with dermatomyositis is treated aggressively with intravenous steroids at initial presentation, good visual acuity outcomes can be achieved, but long-term consequences of retinal nonperfusion and neovascularization persist.

Quantitative Imaging Biomarkers in Age-Related Macular Degeneration and Diabetic Eye Disease: A Step Closer to Precision Medicine

The management of retinal diseases relies heavily on digital imaging data, including optical coherence tomography (OCT) and fluorescein angiography (FA). Targeted feature extraction and the objective quantification of features provide important opportunities in biomarker discovery, disease burden assessment, and predicting treatment response. Additional important advantages include increased objectivity in interpretation, longitudinal tracking, and ability to incorporate computational models to create automated diagnostic and clinical decision support systems. Advances in computational technology, including deep learning and radiomics, open new doors for developing an imaging phenotype that may provide in-depth personalized disease characterization and enhance opportunities in precision medicine. In this review, we summarize current quantitative and radiomic imaging biomarkers described in the literature for age-related macular degeneration and diabetic eye disease using imaging modalities such as OCT, FA, and OCT angiography (OCTA). Various approaches used to identify and extract these biomarkers that utilize artificial intelligence and deep learning are also summarized in this review. These quantifiable biomarkers and automated approaches have unleashed new frontiers of personalized medicine where treatments are tailored, based on patient-specific longitudinally trackable biomarkers, and response monitoring can be achieved with a high degree of accuracy.

Synthesis of high luminescent Eu3+ doped nanoparticle and its application as highly sensitive and selective detection of Fe3+ in real water and human blood serum

The present work reports a highly efficient Ca doped Eu: Y₂O₃ i.e Ca_0.05Eu_0.01Y_1.94O₃ (CEY.) nanophosphor material synthesized through a facile combustion method, as a simple and selective turn-off fluorescence probe for the quantitative analysis of iron ions (Fe³⁺). The proposed sensor allows the quantification of iron in the range of 10 µM-90 µM with a limit of detection (LOD) ∼ 63.2 nM under the natural pH range. Moreover, CEY nanophosphor shows an excellent fluorescence phenomenon with a gradual increase in the Fe³⁺ ion concentration. It has been observed that the corresponding PL intensity gets completely quenched with 500 µM Fe³⁺ ion concentration. Furthermore, the applicability of the sensor as an efficient probe has been investigated with real water samples, iron tablets, and human blood serum (HBS). The selectivity of the probe has also been analyzed with various metal ions and biomolecules. Thus, in turn, the as-obtained sensing probe illustrates an excellent accuracy, sensitivity, and selectivity, and offers potential application in clinical diagnosis, biological and real water sample studies, with the detection of Fe³⁺ ion. Furthermore, it does not require any acidic medium for a level-free, and non-enzymic detection of a real sample with almost not affecting the sample quality and henceforth provides more reliable results.

The 2-Year Leakage Index and Quantitative Microaneurysm Results of the RECOVERY Study: Quantitative Ultra-Widefield Findings in Proliferative Diabetic Retinopathy Treated with Intravitreal Aflibercept

Eyes with proliferative diabetic retinopathy (PDR) have been shown to improve in the leakage index and microaneurysm (MA) count after intravitreal aflibercept (IAI) treatment. The authors investigated these changes via automatic segmentation on ultra-widefield fluorescein angiography (UWFA). Forty subjects with PDR were randomized to receive either 2 mg IAI every 4 weeks (Arm 1) or every 12 weeks (Arm 2) through Year 1. After Year 1, Arm 1 switched to quarterly IAI and Arm 2 to monthly IAI through Year 2. By Year 2, the Arm 1 leakage index decreased by 43% from Baseline (p = 0.03) but increased by 59% from Year 1 (p = 0.04). Arm 2 decreased by 61% from Baseline (p = 0.008) and by 31% from Year 1 (p = 0.12). Both cohorts exhibited a significant decline in MAs from Baseline to Year 2 (871 to 410; p < 0.001; 776 to 207; p < 0.001, respectively). Subjects with an improved leakage and MA count showed a more significant improvement in the Diabetic Retinopathy Severity Scale (DRSS) score. Moreover, central subfield thickness (CST) was positively associated with changes in the leakage index. In conclusion, the leakage index and MA counts significantly improved from Baseline following IAI treatment, and monthly injections provided a more rapid and sustained reduction in these parameters compared with quarterly injections.