Computational Imaging Biomarker Correlation with Intraocular Cytokine Expression in Diabetic Macular Edema: Radiomics Insights from the IMAGINE Study.

Purpose: Various pathways and cytokines are implicated in pathogenesis of diabetic macular edema (DME). Computational imaging biomarkers (CIBs) of vessel tortuosity from ultra-widefield fluorescein angiography (UWFA) and texture patterns from OCT images have been associated with anti-vascular endothelial growth factor (VEGF) therapy treatment response in DME. This analysis was a radiogenomic assessment of the association between underlying cytokines, UWFA, and OCT-based DME CIBs. Design: Biclustering analysis based on UWFA and OCT CIBs to identify a common imaging phenotype across patients with subsequent assessment of underlying cytokine signatures and treatment response attributes. Participants: The IMAGINE DME study was a post hoc study of cytokine expressions that included 24 eyes with sufficient baseline aqueous humor samples and an in-depth assessment of the imaging studies obtained during the phase I/II DmeAntiVEgf study (DAVE) that measured different cytokine expressions. Methods: A total of 151 graph or morphologic features quantifying leakage shape, size, density, interobject distance, and architecture of leakage spots and 5 vessel tortuosity features were extracted from the baseline UWFA scans, and 494 texture-based radiomics features were extracted from each of the fluid and retinal tissue compartments of OCT images. Biclustering enables simultaneous clustering of patients and features and was used to aggregate patients in terms of their commonality of phenotypes (based on similar imaging attributes) and to identify commonality in terms of cytokine expression and treatment response to anti-VEGF therapy. Main Outcome Measures: Identification of eyes with similar imaging phenotypes to evaluate commonalities of patterns and underlying cytokine expression. Results: Strong correlations between VEGF and 7 UWFA leakage morphologic features (Pearson correlation coefficient [PCC], 0.45-0.51; P < 0.05), 1 vascular tortuosity-based UWFA feature (PCC, 0.45; P = 0.00016), and 2 OCT-derived intraretinal fluid texture features (PCC, 0.58-0.63; P < 0.05) were identified. Strong correlation between intraretinal fluid features and other cytokines (PCC, 0.41-0.59; P < 0.05) were also observed. Conclusions: This study identified groups of eyes with similar imaging phenotypes as defined by UWFA and OCT CIBs that demonstrated similar treatment response patterns and cytokine expression, including a strong association between VEGF with UWFA-derived leakage morphologic and vessel tortuosity features.

Deep Learning Segmentation, Visualization, and Automated 3D Assessment of Ciliary Body in 3D Ultrasound Biomicroscopy Images.

Purpose: This study aimed to develop a fully automated deep learning ciliary body segmentation and assessment approach in three-dimensional ultrasound biomicroscopy (3D-UBM) images. Methods: Each 3D-UBM eye volume was aligned to the optic axis via multiplanar reformatting. Ciliary muscle and processes were manually annotated, and Deeplab-v3+ models with different loss functions were trained to segment the ciliary body (ciliary muscle and processes) in both en face and radial images. Results: We trained and tested the models on 4320 radial and 3864 en face images from 12 cadaver eye volumes. Deep learning models trained on radial images with Dice loss achieved the highest mean F1-score (0.89) for ciliary body segmentation. For three-class segmentation (ciliary muscle, processes, and background), radial images with Dice loss achieved the highest mean F1-score (0.75 for the ciliary process and 0.82 for the ciliary muscle). Part of the ciliary muscle (10.9%) was misclassified as the ciliary process and vice versa, which occurred owing to the difficulty in differentiating the ciliary muscle-processes border, even by experts. Deep learning segmentation made further editing by experts at least seven times faster than a fully manual approach. In eight cadaver eyes, the average ciliary muscle, process, and body volumes were 56 ± 9, 43 ± 13, and 99 ± 18 mm3, respectively. The average surface area of the ciliary muscle, process, and body were 346 ± 45, 363 ± 83, and 709 ± 80 mm2, respectively. We performed transscleral cyclophotocoagulation in cadaver eyes to shrink the ciliary processes. Both manual and automated measurements from deep learning segmentation show a decrease in volume, surface area, and 360° cross-sectional area measurements. Conclusions: The proposed deep learning segmentation of the ciliary body and 3D measurements showed transscleral cyclophotocoagulation-related changes in the ciliary body. Translational Relevance: Automated ciliary body assessment using 3D-UBM has the translational potential for ophthalmic treatment planning and monitoring.

Molecular Genetic Mechanisms in Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is among the leading causes of irreversible blindness worldwide. In addition to environmental risk factors, such as tobacco use and diet, genetic background has long been established as a major risk factor for the development of AMD. However, our ability to predict disease risk and personalize treatment remains limited by our nascent understanding of the molecular mechanisms underlying AMD pathogenesis. Research into the molecular genetics of AMD over the past two decades has uncovered 52 independent gene variants and 34 independent loci that are implicated in the development of AMD, accounting for over half of the genetic risk. This research has helped delineate at least five major pathways that may be disrupted in the pathogenesis of AMD: the complement system, extracellular matrix remodeling, lipid metabolism, angiogenesis, and oxidative stress response. This review surveys our current understanding of each of these disease mechanisms, in turn, along with their associated pathogenic gene variants. Continued research into the molecular genetics of AMD holds great promise for the development of precision-targeted, personalized therapies that bring us closer to a cure for this debilitating disease.

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.

Predictive Assessment of Quantitative Ultra-Widefield Angiographic Features for Future Need for Anti-VEGF Therapy in Diabetic Eye Disease.

The objective of this study was to identify biomarkers that predict a future need for anti-VEGF therapy in diabetic retinopathy (DR). Eyes with DR that underwent ultra-widefield angiography (UWFA) and had at least a 1 year follow-up were grouped based on future anti-VEGF treatment requirements: (1) not requiring treatment, (2) immediate treatment (within 3 months of UWFA), and (3) delayed treatment (after 3 months of UWFA). Quantitative UWFA features and clinical factors were evaluated. Random forest models were built to differentiate eyes requiring immediate and delayed treatment from the eyes not requiring treatment. A total of 173 eyes were included. The mean follow-up was 22 (range: 11-43) months. The macular leakage index, panretinal leakage index, presence of DME, and visual acuity were significantly different in eyes requiring immediate (n = 38) and delayed (n = 34) treatment compared to eyes not requiring treatment (n = 101). Random forest model differentiating eyes requiring immediate treatment from eyes not requiring treatment demonstrated an AUC of 0.91 ± 0.07. Quantitative angiographic features have potential as important predictive biomarkers of a future need for anti-VEGF therapy in DR and may serve to guide the frequency of a follow-up.

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.].

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.

Longitudinal assessment of quantitative ultra-widefield ischaemic and vascular parameters in sickle cell retinopathy.

PURPOSE: To evaluate longitudinal quantitative ischaemic and vasculature parameters, including ischaemic index, vessel area, length and geodesic distance in sickle cell retinopathy (SCR) on ultra-widefield fluorescein angiography (UWFA). METHODS: Optimal UWFA images from two longitudinal timepoints of 74 eyes from 45 patients with SCR were aligned and a common region of interest was determined. A deep-learning augmented ischaemia and vascular segmentation platform was used for feature extraction. Geodesic distance maps demonstrating the shortest distance within the vascular masks from the centre of the optic disc were created. Ischaemic index, vessel area, vessel length and geodesic distance were measured. Paired t-test and linear mixed effect model analysis were performed. RESULTS: Overall, 25 (44 eyes) patients with HbSS, 14 (19 eyes) with HbSC, 6 (11 eyes) with HbSthal and other genotypes were included. Mean age was 40.1±11.0 years. Mean time interval between two UWFA studies was 23.0±15.1 months (range: 3-71.3). Mean panretinal ischaemic index increased from 10.0±7.2% to 10.9±7.3% (p<0.005). Mean rate of change in ischaemic index was 0.5±0.7% per year. Mean vessel area (p=0.020) and geodesic distance (p=0.048) decreased significantly. Multivariate analysis demonstrated baseline ischaemic index and Goldberg stage are correlated with progression. CONCLUSION: Longitudinal ischaemic index and retinal vascular parameter measurements demonstrate statistically significant progression in SCR. The clinical significance of these relatively small magnitude changes remains unclear but may provide insights into the progression of retinal ischaemia in SCR.

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.

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.

Real-Time Diabetic Retinopathy Severity Score Level versus Ultra-Widefield Leakage Index-Guided Management of Diabetic Retinopathy: Two-Year Outcomes from the Randomized PRIME Trial.

The prospective PRIME trial applied real-time, objective imaging biomarkers to determine individualized retreatment needs with intravitreal aflibercept injections (IAI) among eyes with diabetic retinopathy (DR). 40 eyes with nonproliferative or proliferative DR without diabetic macular edema received monthly IAI until a DR severity scale (DRSS) level improvement of ≥2 steps was achieved. Eyes were randomized 1:1 to DRSS- or PLI- guided management. At the final 2-year visit, DRSS level was stable or improved compared to baseline in all eyes, and mean PLI decreased by 11% (p = 0.73) and 23.6% (p = 0.25) in the DRSS- and PLI-guided arms. In both arms, the percent of pro re nata (PRN) visits requiring IAI was significantly higher in year 2 versus 1 (p < 0.0001). The percent of PRN visits receiving IAI during year 1 was significantly correlated with the percent of PRN visits with IAI during year 2 (p < 0.0001). Through week 104, 77.4% of instances of DRSS level worsening in the DRSS-guided arm were preceded by or occurred alongside an increase of PLI. Overall, consistent IAI re-treatment interval requirements were observed longitudinally among individual patients. Additionally, PLI increases appeared to precede DRSS level worsening, highlighting PLI as a valuable biomarker in the management of DR.

Multi-Compartment Spatially-Derived Radiomics From Optical Coherence Tomography Predict Anti-VEGF Treatment Durability in Macular Edema Secondary to Retinal Vascular Disease: Preliminary Findings.

OBJECTIVE: Diabetic macular edema (DME) and retinal vein occlusion (RVO) are the leading causes of visual impairments across the world. Vascular endothelial growth factor (VEGF) stimulates breakdown of blood-retinal barrier that causes accumulation of fluid within macula. Anti-VEGF therapy is the first-line treatment for both the diseases; however, the degree of response varies for individual patients. The main objective of this work was to identify the (i) texture-based radiomics features within individual fluid and retinal tissue compartments of baseline spectral-domain optical coherence tomography (SD-OCT) images and (ii) the specific spatial compartments that contribute most pertinent features for predicting therapeutic response. METHODS: A total of 962 texture-based radiomics features were extracted from each of the fluid and retinal tissue compartments of OCT images, obtained from the PERMEATE study. Top-performing features selected from the consensus of different feature selection methods were evaluated in conjunction with four different machine learning classifiers: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Random Forest (RF), and Support Vector Machine (SVM) in a cross-validated approach to distinguish eyes tolerating extended interval dosing (non-rebounders) and those requiring more frequent dosing (rebounders). RESULTS: Combination of fluid and retinal tissue features yielded a cross-validated area under receiver operating characteristic curve (AUC) of 0.78±0.08 in distinguishing rebounders from non-rebounders. CONCLUSIONS: This study revealed that the texture-based radiomics features pertaining to IRF subcompartment were most discriminating between rebounders and non-rebounders to anti-VEGF therapy. Clinical Impact: With further validation, OCT-based imaging biomarkers could be used for treatment management of DME patients.

LONGITUDINAL ELLIPSOID ZONE DYNAMICS AFTER MACULAR HOLE REPAIR IN THE DISCOVER STUDY: Structure-Function Assessment.

PURPOSE: To evaluate association of the baseline macular hole (MH) geometric features and longitudinal ellipsoid zone integrity with the visual acuity outcome after surgical repair. METHODS: This was a post-hoc analysis of eyes in the DISCOVER study undergoing vitrectomy repair for MH. Anatomical and functional data were collected through one year postoperatively. An automated retinal layer segmentation platform was used for the assessment of outer retinal metrics and volumetric reconstruction of MH. Association of longitudinal ellipsoid zone features and baseline MH height, width, and volume with VA outcomes were investigated. RESULTS: Eighty-four eyes with MH were included. The mean baseline VA was 20 of 114 and increased to 20 of 45 (P < 0.001) at postoperative Month 12 (N = 45). Successful MH closure was achieved in 98.8% of cases. Ellipsoid zone integrity metrics significantly improved from baseline (P = 0.002) and postoperative Month 1 (P < 0.001) to post-operative Month 12. Ellipsoid zone metrics independently correlated with VA at all follow-up visits (P < 0.05). Increased baseline MH width and volume negatively correlated with the VA at postoperative Month 12 (P < 0.001). Preoperative VA and EZ integrity on optical coherence tomography were predictors for postoperative VA. CONCLUSION: Baseline MH volumetric parameters and EZ parameters were associated with VA outcomes after repair.

Real-Time Photographic- and Fluorescein Angiographic-Guided Management of Diabetic Retinopathy: Randomized PRIME Trial Outcomes.

PURPOSE: To assess the safety and efficacy of as-needed (PRN) intravitreal aflibercept injections (IAI) in managing diabetic retinopathy (DR) guided by the real-time DR severity scale (DRSS) level or panretinal leakage index (PLI) assessment among eyes without diabetic macular edema (DME). DESIGN: Prospective, randomized phase 2 trial (PRIME). METHODS: A total of 40 eyes with nonproliferative (NPDR) or proliferative DR (PDR) received monthly IAIs until a DRSS improvement of ≥2 steps was achieved and eyes were randomized (1:1) to DRSS-guided or PLI-guided management strategies graded by a central reading center. Main outcome measurements included safety and changes in DRSS and PLI. RESULTS: Through week 52, 95% of eyes achieved a DRSS improvement of ≥2 steps. Following DRSS improvement, 97% of eyes required at least 1 PRN IAI. In eyes requiring PRN IAI and completing week 52, 100% and 59% experienced DRSS worsening (P = .01) in the DRSS- and PLI-guided arms, respectively. Through week 52, mean PLI decreased 18.2% (P = .49) and 54.6% (P <.0001), respectively, in the DRSS- and PLI-guided arms. NPDR versus PDR eyes at baseline achieved a DRSS improvement of ≥2 steps after a mean 4.9 and 3.6 IAIs (P = .03). Two eyes developed a PDR event at week 52 following 5 months of quiescence. CONCLUSIONS: The randomized PRIME study analyzed 2 imaging-based biomarkers to guide PRN management with IAI of DR without DME: DRSS level and PLI. Within the context of this study with limitations, most patients required IAI re-treatment every 3-4 months, and deterioration of PLI appeared to precede DRSS level worsening. Finally, these findings reaffirm the fact that close clinical follow-up is important even among eyes that achieve substantial DRSS improvements with apparently quiescent disease.

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.

Comparison of Modified Posterior Sub-Tenon's vs. Trans-Septal Triamcinolone Injection for Non-infectious Uveitis.

Purpose: To compare the safety and efficacy of trans-septal vs. modified posterior sub-Tenon's (PST) corticosteroid injections for noninfectious uveitis.Methods: Retrospective comparison of periocular triamcinolone injection by modified PST (n = 36) vs. traditional trans-septal (n = 79) techniques. Safety and efficacy outcomes were analyzed with regression models.Results: There was no significant difference in visual acuity improvement between the groups at 6 months. There were higher rates of vitritis resolution in the modified PST group but this was not statistically significant (85.7% vs 62.9%, p = .07). Intraocular pressure (IOP) elevation rate trended higher with the modified PST injection (21.9% vs 9.0%, p = .06), with no instances of glaucoma surgery in either group. Two modified PST injection patients with refractory IOP rises had IOP normalization after corticosteroid depot removal. One year cataract surgery rates were similar.Conclusion: Modified PST injection offers clinical efficacy but with possibly higher IOP response rate which could be managed with corticosteroid removal.

iOCT-assisted macular hole surgery: outcomes and utility from the DISCOVER study.

BACKGROUND/AIMS: This study aimed to characterise the clinical outcomes and utility of intraoperative optical coherence tomography (iOCT)-assisted macular hole (MH) repair. METHODS: This was a post hoc analysis of eyes in the D etermination of feasibility of I ntraoperative S pectral domain microscope C ombined/integrated O CT V isualization during E n face R etinal and ophthalmic surgery (DISCOVER) study undergoing surgical MH repair with use of iOCT. Functional and surgical outcome data were collected through 12 months postoperatively. MH closure rate, postoperative visual acuity (VA), percentage of cases in which iOCT provided valuable feedback and altered surgical decision making were measured. RESULTS: Eighty-four eyes were included in this study. The mean preoperative VA measured 20/114. The mean postoperative VA improved to 20/68 (p<0.001) at month 1, 20/48 (p<0.001) at month 3 and 20/45 (p<0.001) at month 12 or later. In 43 cases (51%), surgeons reported that iOCT provided valuable information (eg, confirming release of vitreomacular traction and identification of occult residual membranes). In 10 cases (12%), iOCT data specifically altered surgical decision making. Postoperative day 1 transtamponade OCT confirmed tissue apposition and apparent hole closure in 74% of eyes (21/26). All five open holes on postoperative day 1 closed following positioning. Single-surgery MH closure was achieved in 97.6% of cases. One persistent MH was successfully closed with a subsequent surgical repair for a final overall closure rate of 98.8%. Due to chronicity and MH size, additional repair was not recommended for the single remaining persistent MH. CONCLUSION: This study suggests that iOCT may have important utility in MH surgery, including impacting surgical decision making. iOCT-assisted MH surgery resulted in significant improvement in VA and high single-surgery success rate.

Retinal Fluid Volatility Associated With Interval Tolerance and Visual Outcomes in Diabetic Macular Edema in the VISTA Phase III Trial.

PURPOSE: To describe longitudinal retinal fluid dynamics on spectral domain OCT and to identify imaging biomarkers that predict the worsening of DME with interval extension during anti-vascular endothelial growth factor (VEGF) therapy. DESIGN: A post hoc sub-analysis of phase III, VISTA-DME study. METHODS: Eyes received either intravitreal aflibercept injection 2 mg every 4 weeks (2q4) or every 8 weeks after 5 initial monthly injections (2q8), and eyes imaged with the Cirrus HD-OCT system were included. The macular cube was analyzed for 10 time-points from baseline through week 100. Retinal OCT images were evaluated using a novel software platform to extract retinal fluid features for calculation of volumetric fluid parameters, including the retinal fluid index (RFI): the percentage of retinal volume that was occupied by intraretinal fluid. RESULTS: Fifty-five eyes were included in the 2q4 group, and 58 eyes were included in the 2q8 group. Early RFI volatility with a central macular RFI increase by ≥5 points from week 4 to 8 (P = .004, odds ratio [OR] 31.3, 95% confidence interval [CI] 3.0 to 329) and cumulative RFI volatility with an aggregate increase in macular RFI by ≥10 points from those timepoints with increased RFI between baseline to week 20, P = .005, OR 10.2, 95% CI 2.1 to 51.3) were both significant predictors for the worsening of DME and visual acuity when the treatment interval was extended to 8 weeks in the 2q8 group. CONCLUSIONS: Early fluid dynamics as measured by (1) early RFI volatility and (2) cumulative RFI instability with aggregate increased RFI were associated with intolerance of interval extension.

Radiomics-based assessment of ultra-widefield leakage patterns and vessel network architecture in the PERMEATE study: insights into treatment durability.

AIM: To evaluate the potential of radiomics-based ultra-widefield fluorescein angiography (UWFA)-derived imaging biomarkers in retinal vascular disease for predicting therapeutic durability of intravitreal aflibercept injection (IAI). METHODS: The Peripheral and Macular Retinal Vascular Perfusion and Leakage Dynamics in Diabetic Macular Edema and Retinal Venous Occlusions During Intravitreal Aflibercept Injection (IAI) Treatment for Retinal Edema (PERMEATE) study prospectively evaluated quantitative UWFA dynamics in diabetic macular oedema or macular oedema secondary to retinal vascular occlusion. 27 treatment-naïve eyes were treated with 2 mg IAI q4 weeks for the first 6 months, and then administered q8 weeks. Morphological and graph-based attributes were used to model the spatial distribution of leakage areas, while tortuosity measures were used to model the vessel network disorder. Eyes were grouped based on functional tolerance of the first 8-week treatment interval challenge. 'Non-rebounders' (N=15) maintained/improved best-corrected visual acuity (BCVA) following the 8-week challenge. 'Rebounders' (N=12) exhibited worsened BVCA. The image biomarkers were used with a machine learning classifier to preliminarily evaluate their ability to predict BCVA stability. RESULTS: Two new UWFA image-derived biomarkers were identified and extracted. The cross-validated area under the receiver operating characteristic curve (AUC) was 0.77±0.14 using baseline leakage distribution features and 0.73±0.10 for the UWFA baseline tortuosity measures. Additionally, the change in vascular tortuosity between month 4 and baseline yielded an AUC of 0.73±0.08. Three baseline clinical features of letter score, macular volume and central subfield thickness yielded a corresponding AUC of 0.42±0.09. CONCLUSIONS: Two computer-extracted UWFA radiomics-based descriptors were identified as potential biomarkers for predicting treatment durability and tolerance of longer treatment intervals. Conventional treatment parameters were not significantly different between these same groups.