Comparison of Short-Wavelength Reduced-Illuminance and Conventional Autofluorescence Imaging in Stargardt Macular Dystrophy

Purpose To compare grading results between short-wavelength reduced-illuminance and conventional autofluorescence imaging in Stargardt macular dystrophy. Design Reliability study. Methods setting: Moorfields Eye Hospital, London (United Kingdom). patients: Eighteen patients (18 eyes) with Stargardt macular dystrophy. observation procedures: A series of 3 fundus autofluorescence images using 3 different acquisition parameters on a custom-patched device were obtained: (1) 25% laser power and total sensitivity 87; (2) 25% laser power and freely adjusted sensitivity; and (3) 100% laser power and freely adjusted total sensitivity (conventional). The total area of 2 hypoautofluorescent lesion types (definitely decreased autofluorescence and poorly demarcated questionably decreased autofluorescence) was measured. main outcome measures: Agreement in grading between the 3 imaging methods was assessed by kappa coefficients (κ) and intraclass correlation coefficients. Results The mean ± standard deviation area for images acquired with 25% laser power and freely adjusted total sensitivity was 2.04 ± 1.87 mm2 for definitely decreased autofluorescence (n = 15) and 1.86 ± 2.14 mm2 for poorly demarcated questionably decreased autofluorescence (n = 12). The intraclass correlation coefficient (95% confidence interval) was 0.964 (0.929, 0.999) for definitely decreased autofluorescence and 0.268 (0.000, 0.730) for poorly demarcated questionably decreased autofluorescence. Conclusions Short-wavelength reduced-illuminance and conventional fundus autofluorescence imaging showed good concordance in assessing areas of definitely decreased autofluorescence. However, there was significantly higher variability between imaging modalities for assessing areas of poorly demarcated questionably decreased autofluorescence

Deep Placental Vessel Segmentation for Fetoscopic Mosaicking

During fetoscopic laser photocoagulation, a treatment for twin-to-twin transfusion syndrome (TTTS), the clinician first identifies abnormal placental vascular connections and laser ablates them to regulate blood flow in both fetuses. The procedure is challenging due to the mobility of the environment, poor visibility in amniotic fluid, occasional bleeding, and limitations in the fetoscopic field-of-view and image quality. Ideally, anastomotic placental vessels would be automatically identified, segmented and registered to create expanded vessel maps to guide laser ablation, however, such methods have yet to be clinically adopted. We propose a solution utilising the U-Net architecture for performing placental vessel segmentation in fetoscopic videos. The obtained vessel probability maps provide sufficient cues for mosaicking alignment by registering consecutive vessel maps using the direct intensity-based technique. Experiments on 6 different in vivo fetoscopic videos demonstrate that the vessel intensity-based registration outperformed image intensity-based registration approaches showing better robustness in qualitative and quantitative comparison. We additionally reduce drift accumulation to negligible even for sequences with up to 400 frames and we incorporate a scheme for quantifying drift error in the absence of the ground-truth. Our paper provides a benchmark for fetoscopy placental vessel segmentation and registration by contributing the first in vivo vessel segmentation and fetoscopic videos dataset.Comment: Accepted at MICCAI 202

Scotopic Microperimetric Assessment of Rod Function in Stargardt Disease (SMART) Study: Design and Baseline Characteristics (Report No. 1)

PURPOSE: To describe the study design and characteristics at first visit of participants in the longitudinal Scotopic Microperimetric Assessment of Rod Function in Stargardt Disease (SMART) study. METHODS: Scotopic microperimetry (sMP) was performed in one designated study eye in a subset of participants with molecularly proven ABCA4-associated Stargardt disease (STGD1) enrolled in a multicenter natural history study (ProgStar). Study visits were every 6 months over a period ranging from 6 to 24 months, and also included fundus autofluorescence (FAF). RESULTS: SMART enrolled 118 participants (118 eyes). At the first visit of SMART, the mean sensitivity in mesopic microperimetry was 11.48 (±5.05; range 0.00-19.88) dB and in sMP 11.25 (±5.26; 0-19.25) dB. For FAF, all eyes had a lesion of decreased autofluorescence (mean lesion size 3.62 [±3.48; 0.10-21.46] mm2), and a total of 76 eyes (65.5%) had a lesion of definitely decreased autofluorescence with a mean lesion size of 3.46 (±3.60; 0.21-21.46) mm2. CONCLUSIONS: Rod function is impaired in STGD1 and can be assessed by sMP. Testing rod function may serve as a potential outcome measure for future clinical treatment trials. This is evaluated in the SMART study

Longitudinal Changes in Scotopic and Mesopic Macular Function as Assessed with Microperimetry in Patients with Stargardt Disease: SMART Study Report No. 2: Short Title: Scotopic and Mesopic Macular Functions in Stargardt Disease

PURPOSE: To estimate and compare cross-sectional scotopic versus mesopic macular sensitivity losses measured by microperimetry, and to report and compare the longitudinal rates of scotopic and mesopic macular sensitivity losses in ABCA4 gene associated Stargardt Disease (STGD1). DESIGN: Multicenter prospective cohort study. METHODS: Participants: 127 molecular confirmed STGD1 patients enrolled from 6 centers in the USA and Europe and followed every 6 months for up to 2 years. OBSERVATION PROCEDURES: The Nidek MP-1S device was used to measure macular sensitivities of the central 20° under mesopic and scotopic conditions. The mean deviations (MD) from normal for mesopic macular sensitivity for the fovea (within 2° eccentricity) and extrafovea (4°-10° eccentricity), and the MD for scotopic sensitivity for the extrafovea were calculated. Linear mixed effects models were used to estimate mesopic and scotopic changes. MAIN OUTCOME MEASURES: Baseline mesopic mean deviation (mMD) and scotopic MD (sMD) and rates of longitudinal changes in the mMDs and sMD. RESULTS: At baseline, all eyes had larger sMD, and the difference between extrafoveal sMD and mMD was 10.7 dB (p<.001). Longitudinally, all eyes showed a statistically significant worsening trend: the rates of foveal mMD and extrafoveal mMD and sMD changes were 0.72 (95%CI: 0.37 to 1.07), 0.86 (95%CI: 0.58 to 1.14) and 1.12 (95%CI: 0.66 to 1.57) dB/year, respectively. CONCLUSIONS: In STGD1, in extrafovea, loss of scotopic macular function preceded and was faster than the loss of mesopic macular function. Scotopic and mesopic macular sensitivities using microperimetry provide alternative visual function outcomes for STGD1 treatment trials

Consensus Nomenclature for Reporting Neovascular Age-Related Macular Degeneration Data: Consensus on Neovascular Age-Related Macular Degeneration Nomenclature Study Group

© 2019 American Academy of Ophthalmology Purpose: To establish a process to evaluate and standardize a state-of-the-art nomenclature for reporting neovascular age-related macular degeneration (AMD) data. Design: Consensus meeting. Participants: An international panel of retina specialists, imaging and image reading center experts, and ocular pathologists. Methods: During several meetings organized under the auspices of the Macula Society, an international study group discussed and codified a set nomenclature framework for classifying the subtypes of neovascular AMD and associated lesion components. Main Outcome Measures: A consensus classification of neovascular AMD. Results: The study group created a standardized working definition of AMD. The components of neovascular AMD were defined and subclassified. Disease consequences of macular neovascularization were delineated. Conclusions: The framework of a consensus nomenclature system, a definition of AMD, and a delineation of the subtypes of neovascular AMD were developed. Establishing a uniform set of definitions will facilitate comparison of diverse patient groups and different studies. The framework presented is modified and updated readily, processes that are anticipated to occur on a periodic basis. The study group suggests that the consensus standards outlined in this article be used in future reported studies of neovascular AMD and clinical practice

Optical Coherence Tomography in the UK Biobank Study – Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies

Purpose: To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness. Methods: In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available “spectral domain” OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion. Results: 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days. Conclusions: We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging

The Effect of Macular Hole Duration on Surgical Outcomes: An Individual Participant Data Study of Randomized Controlled Trials

Topic: To define the effect of symptom duration on outcomes in people undergoing surgery for idiopathic full-thickness macular holes (iFTMHs) by means of an individual participant data (IPD) study of randomized controlled trials (RCTs). The outcomes assessed were primary iFTMH closure and postoperative best-corrected visual acuity (BCVA). Clinical Relevance: Idiopathic full-thickness macular holes are visually disabling with a prevalence of up to 0.5%. Untreated BCVA is typically reduced to 20/200. Surgery can close holes and improve vision. Symptom duration is thought to affect outcomes with surgery, but the effect is unclear. Methods: A systematic review identified eligible RCTs that included adults with iFTMH undergoing vitrectomy with gas tamponade in which symptom duration, primary iFTMH closure, and postoperative BCVA were recorded. Bibliographic databases were searched for articles published between 2000 and 2020. Individual participant data were requested from eligible studies. Results: Twenty eligible RCTs were identified. Data were requested from all studies and obtained from 12, representing 940 eyes in total. Median symptom duration was 6 months (interquartile range, 3–10). Primary closure was achieved in 81.5% of eyes. There was a linear relationship between predicted probability of closure and symptom duration. Multilevel logistic regression showed each additional month of duration was associated with 0.965 times lower odds of closure (95% confidence interval [CI], 0.935–0.996, P = 0.026). Internal limiting membrane (ILM) peeling, ILM flap use, better preoperative BCVA, face-down positioning, and smaller iFTMH size were associated with increased odds of primary closure. Median postoperative BCVA in eyes achieving primary closure was 0.48 logarithm of the minimum angle of resolution (logMAR) (20/60). Multilevel logistic regression showed for eyes achieving primary iFTMH closure, each additional month of symptom duration was associated with worsening BCVA by 0.008 logMAR units (95% CI, 0.005–0.011, P < 0.001) (i.e., ∼1 Early Treatment Diabetic Retinopathy Study letter loss per 2 months). ILM flaps, intraocular tamponade using long-acting gas, better preoperative BCVA, smaller iFTMH size, and phakic status were also associated with improved postoperative BCVA. Conclusions: Symptom duration was independently associated with both anatomic and visual outcomes in persons undergoing surgery for iFTMH. Time to surgery should be minimized and care pathways designed to enable this

International Classification System for Ocular Complications of Anti-VEGF Agents in Clinical Trials

\ua9 2024 American Academy of OphthalmologyPurpose: Complications associated with intravitreal anti-VEGF therapies are reported inconsistently in the literature, thus limiting an accurate evaluation and comparison of safety between studies. This study aimed to develop a standardized classification system for anti-VEGF ocular complications using the Delphi consensus process. Design: Systematic review and Delphi consensus process. Participants: Twenty-five international retinal specialists participated in the Delphi consensus survey. Methods: A systematic literature search was conducted to identify complications of intravitreal anti-VEGF agent administration based on randomized controlled trials (RCTs) of anti-VEGF therapy. A comprehensive list of complications was derived from these studies, and this list was subjected to iterative Delphi consensus surveys involving international retinal specialists who voted on inclusion, exclusion, rephrasing, and addition of complications. Furthermore, surveys determined specifiers for the selected complications. This iterative process helped to refine the final classification system. Main Outcome Measures: The proportion of retinal specialists who choose to include or exclude complications associated with anti-VEGF administration. Results: After screening 18 229 articles, 130 complications were categorized from 145 included RCTs. Participant consensus via the Delphi method resulted in the inclusion of 91 complications (70%) after 3 rounds. After incorporating further modifications made based on participant suggestions, such as rewording certain phrases and combining similar terms, 24 redundant complications were removed, leaving a total of 67 complications (52%) in the final list. A total of 14 complications (11%) met exclusion thresholds and were eliminated by participants across both rounds. All other remaining complications not meeting inclusion or exclusion thresholds also were excluded from the final classification system after the Delphi process terminated. In addition, 47 of 75 proposed complication specifiers (63%) were included based on participant agreement. Conclusions: Using the Delphi consensus process, a comprehensive, standardized classification system consisting of 67 ocular complications and 47 unique specifiers was established for intravitreal anti-VEGF agents in clinical trials. The adoption of this system in future trials could improve consistency and quality of adverse event reporting, potentially facilitating more accurate risk-benefit analyses. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article

Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10–12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63–0.83. Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology