Search Results (10)

Background/Objectives: Discrepancies in diabetic retinopathy (DR) grading are well-documented, with retinal non-perfusion (RNP) quantification posing greater challenges. This study assessed intergrader agreement in DR evaluation, focusing on qualitative severity grading and quantitative RNP measurement. We aimed to improve agreement through structured consensus meetings. Methods: A retrospective analysis of 100 comparisons from 50 eyes (36 patients) was conducted. Two paired medical retina fellows graded ultra-widefield color fundus photographs (CFP) and fundus fluorescein angiography (FFA) images. CFP assessments included DR severity using the International Clinical Diabetic Retinopathy (ICDR) grading system, DR Severity Scale (DRSS), and predominantly peripheral lesions (PPL). FFA-based RNP was defined as capillary loss with grayscale matching the foveal avascular zone. Weekly adjudication by a senior specialist resolved discrepancies. Intergrader agreement was evaluated using Cohen’s kappa (qualitative DRSS) and intraclass correlation coefficients (ICC) (quantitative RNP). Bland–Altman analysis assessed bias and variability. Results: After eight consensus meetings, CFP grading agreement improved to excellent: kappa = 91% (ICDR DR severity), 89% (DRSS), and 89% (PPL). FFA-based PPL agreement reached 100%. For RNP, the non-perfusion index (NPI) showed moderate overall ICC (0.49), with regional ICCs ranging from 0.40 to 0.57 (highest in the nasal region, ICC = 0.57). Bland–Altman analysis revealed a mean NPI difference of 0.12 (limits: −0.11 to 0.35), indicating acceptable variability despite outliers. Conclusions: Structured consensus training achieved excellent intergrader agreement for DR severity and PPL grading, supporting the clinical reliability of ultra-widefield imaging. However, RNP measurement variability underscores the need for standardized protocols and automated tools to enhance reproducibility. This process is critical for developing robust AI-based screening systems. Full article

Geographic atrophy (GA) is a progressive retinal disease associated with late-stage age-related macular degeneration (AMD), a significant cause of visual impairment in senior adults. GA lesion segmentation is important for disease monitoring in clinical trials and routine ophthalmic practice; however, its manual delineation is time-consuming, laborious, and subject to inter-grader variability. The use of artificial intelligence (AI) is rapidly expanding within the medical field and could potentially improve accuracy while reducing the workload by facilitating this task. This systematic review evaluates the performance of AI algorithms for GA segmentation and highlights their key limitations from the literature. Five databases and two registries were searched from inception until 23 March 2024, following the PRISMA methodology. Twenty-four studies met the prespecified eligibility criteria, and fifteen were included in this meta-analysis. The pooled Dice similarity coefficient (DSC) was 0.91 (95% CI 0.88–0.95), signifying a high agreement between the reference standards and model predictions. The risk of bias and reporting quality were assessed using QUADAS-2 and CLAIM tools. This review provides a comprehensive evaluation of AI applications for GA segmentation and identifies areas for improvement. The findings support the potential of AI to enhance clinical workflows and highlight pathways for improved future models that could bridge the gap between research settings and real-world clinical practice. Full article

Objectives: This study investigated the visual search behaviour of optometrists and fellowship-trained ophthalmologists when screening for diabetic retinopathy in retinal photographs. Methods: Participants assessed and graded retinal photographs on a computer screen while a Gazepoint GP3 HD eye tracker recorded their eye movements. Areas of interest were derived from the raw data using Hidden Markov modelling. Fixation strings were extracted by matching raw fixation data to areas of interest and resolving ambiguities with graph search algorithms. Fixation strings were clustered using Affinity Propagation to determine search behaviours characteristic of the correct and incorrect response groups. Results: A total of 23 participants (15 optometrists and 8 ophthalmologists) completed the grading task, with each assessing 20 images. Visual search behaviour differed between correct and incorrect responses, with data suggesting correct responses followed a visual search strategy incorporating the optic disc, macula, superior arcade, and inferior arcade as areas of interest. Data from incorrect responses suggest search behaviour driven by saliency or a search pattern unrelated to anatomical landmarks. Referable diabetic retinopathy was correctly identified in 86% of cases. Grader accuracy was 64.8% with good inter-grader agreement (α = 0.818). Conclusions: Our study suggests that a structured visual search strategy is correlated with higher accuracy when assessing retinal photographs for diabetic retinopathy. Referable diabetic retinopathy is detected at high rates; however, there is disagreement between clinicians when determining a precise severity grade. Full article

Background/Objectives: The diagnosis and prognosis of arrested foveal development or foveal hypoplasia (FH) can be made using the Leicester grading system for FH and optical coherence tomography (OCT). In clinical practice, ophthalmologists and ophthalmic health professionals with varying experience consult patients with FH; however, to date, the FH grading system has only been validated amongst experts. We compare the inter-grader and intra-grade agreement of healthcare professionals against expert consensus across all grades of FH. Methods: Handheld and table-mounted OCT images (n = 341) were graded independently at a single centre by experts (n = 3) with over six years of experience and “novice” medical and allied health professionals (n = 5) with less than three years of experience. Sensitivity, specificity, and Cohen’s kappa scores were calculated for each grader, and expert vs. novice performance was compared. Results: All graders showed high sensitivity (median 97% (IQR: 94–99)) and specificity (median 94% (IQR: 90–95)) in identifying the presence or absence of FH. No significant difference was seen in specificity between expert and novice graders, but experts had significantly greater diagnostic sensitivity (median difference = 5.3%, H = 5.00, p = 0.025). Expert graders had the highest agreement with the ground truth and novice graders showed great variability in grading uncommon grades, such as atypical FH. The proposed causes of misclassification included macular decentring in handheld OCT scans in children. Conclusions: Ophthalmologists of varying experience and allied health professionals can accurately identify FH using handheld and table-mounted OCT images. FH identification and paediatric OCT interpretation can be improved in wider ophthalmic clinical settings through the education of ophthalmic staff. Full article

Purpose: To examine the real-world performance of a support vector machine learning software (RetinaLyze) in order to identify the possible presence of diabetic retinopathy (DR) in patients with diabetes via software implementation in clinical practice. Methods: 1001 eyes from 1001 patients—one eye per patient—participating in the Danish National Screening Programme were included. Three independent ophthalmologists graded all eyes according to the International Clinical Diabetic Retinopathy Disease Severity Scale with the exact level of disease being determined by majority decision. The software detected DR and no DR and was compared to the ophthalmologists’ gradings. Results: At a clinical chosen threshold, the software showed a sensitivity, specificity, positive predictive value and negative predictive value of 84.9% (95% CI: 81.8–87.9), 89.9% (95% CI: 86.8–92.7), 92.1% (95% CI: 89.7–94.4), and 81.0% (95% CI: 77.2–84.7), respectively, when compared to human grading. The results from the routine screening were 87.0% (95% CI: 84.2–89.7), 85.3% (95% CI: 81.8–88.6), 89.2% (95% CI: 86.3–91.7), and 82.5% (95% CI: 78.5–86.0), respectively. AUC was 93.4%. The reference graders Conger’s Exact Kappa was 0.827. Conclusion: The software performed similarly to routine grading with overlapping confidence intervals, indicating comparable performance between the two groups. The intergrader agreement was satisfactory. However, evaluating the updated software alongside updated clinical procedures is crucial. It is therefore recommended that further clinical testing before implementation of the software as a decision support tool is conducted. Full article

Background: To investigate the repeatability in vessel caliber measurements by optical coherence tomography angiography (OCTA). Methods: In this prospective study, 28 patients (47 eyes) underwent sequential OCTA imaging of the optic nerve head and macula. Two independent masked graders measured vessel caliber for sequential images of the optic nerve head and macula. The average vessel width was determined and variability between graders and images. Results: A total of 8400 measurements of 420 vessels from 84 OCTA images were included in the analysis. Overall, inter-grader agreement was excellent (ICC 0.90). The coefficient of variation (CoV) for all repeated OCTA images was 0.10. Greater glaucoma severity, older age, macular location, and diagnosis of diabetes were associated with thinner vessels (p < 0.05). CoV was higher in the peripapillary region (0.07) as compared to the macula (0.15). ICC was high for all subgroups except for the macula (ICC = 0.72). Conclusions: Overall, the repeatability of vessel caliber measurements by OCTA was high and variability low. There was greater variability in the measurement of macular vessels, possibly due to technical limitations in acquiring accurate vessel widths for smaller macular vessels. Full article

Hydroxychloroquine (HCQ) ocular toxicity is rare but severe, and progression can occur even after termination of therapy. Case reports have suggested that a bull’s eye maculopathy detected by near-infrared reflectance (NIR) may indicate early HCQ toxicity. This retrospective cross-sectional study evaluated patients treated with HCQ who underwent routine screening with optical coherence tomography (OCT), fundus autofluorescence (FAF) and 10-2 perimetry. NIR images captured alongside OCT were subsequently graded independently by 2 masked graders for the presence of bull’s eye maculopathy, and the result was compared to the outcome of the screening. A total of 123 participants (246 eyes) were included, and 101 (90%) were female. The patients’ mean age was 55.2 ± 13.8 years. The mean time of HCQ usage was 84.0 ± 72.3 months, and the mean weekly dose was 2327 ± 650 mg. Two eyes showed toxicity in all 3 routine screening exams, with one patient suspending HCQ. The prevalence of bull´s eye lesions in NIR was 13% (33 eyes) with substantial intergrader agreement, a 71.3% specificity and 88.0% negative predictive value for HCQ toxicity. We suggest that NIR changes may be a sign of early HCQ toxicity. The detection of NIR bull´s eye lesions may warrant an increased screening frequency. Full article

Understanding the degree of disc migration is essential in order to diagnose, treat, and assess the prognosis of migrated lumbar disc herniation (LDH). Based on anatomical configuration, we developed a simple six-level grading system for migrated lumbar disc herniation. We aimed to evaluate whether the new grading system was reliable and could replace the previous grading system. We selected 101 cases from our database. Two independent raters evaluated the magnetic resonance images using each grading system. Interobserver, intraobserver, and inter-grading system agreements were assessed using kappa statistics. The most common migration pattern was low-grade inferior migration. Interobserver agreements between the two readers showed substantial agreement in the first and second assessments (k = 0.753 and 0.756, respectively). The intraobserver agreement of reader 1 revealed substantial agreement (k = 0.733), while that of reader 2 revealed almost perfect agreement (k = 0.829). The strengths of the agreements of the new grading system were higher than those of the Lee-Kim grading system. The two grading systems agreed almost perfectly for most measurements. The new grading system was reliable and feasible to determine migrated LDH grade. It allowed for a more intuitive, objective measurement and helped select surgical options. Full article

Reliable outcome measures are required for clinical trials investigating novel agents for preventing progression of capillary non-perfusion (CNP) in retinal vascular diseases. Currently, accurate quantification of topographical distribution of CNP on ultrawide field fluorescein angiography (UWF-FA) by retinal experts is subjective and lack standardisation. A U-net style network was trained to extract a dense segmentation of CNP from a newly created dataset of 75 UWF-FA images. A subset of 20 images was also segmented by a second expert grader for inter-grader reliability evaluation. Further, a circular grid centred on the FAZ was used to provide standardised CNP distribution analysis. The model for dense segmentation was five-fold cross-validated achieving area under the receiving operating characteristic of 0.82 (0.03) and area under precision-recall curve 0.73 (0.05). Inter-grader assessment on the 20 image subset achieves: precision 59.34 (10.92), recall 76.99 (12.5), and dice similarity coefficient (DSC) 65.51 (4.91), and the centred operating point of the automated model reached: precision 64.41 (13.66), recall 70.02 (16.2), and DSC 66.09 (13.32). Agreement of CNP grid assessment reached: Kappa 0.55 (0.03), perfused intraclass correlation (ICC) 0.89 (0.77, 0.93), non-perfused ICC 0.86 (0.73, 0.92), inter-grader agreement of CNP grid assessment values are Kappa 0.43 (0.03), perfused ICC 0.70 (0.48, 0.83), non-perfused ICC 0.71 (0.48, 0.83). Automated dense segmentation of CNP in UWF-FA images achieves performance levels comparable to inter-grader agreement values. A grid placed on the deep learning-based automatic segmentation of CNP generates a reliable and quantifiable method of measurement of CNP, to overcome the subjectivity of human graders. Full article

Purpose: To evaluate the sensitivity and specificity of ultrawide-field fundus photography (UWF-FP) for the detection and classification of sickle cell retinopathy (SCR) by ophthalmologists with varying degrees of expertise in retinal disease. Methods: Patients presenting with sickle cell disease (SCD) in the Créteil University Eye Clinic, having undergone UWF-FP and ultrawide-field fluorescein angiography (UWF-FA) on the same day, were retrospectively included. Eyes with previous retinal photocoagulation were excluded. SCR was graded independently by UWF-FP and UWF-FA using Goldberg classification by two ophthalmologists with varying expertise levels. Results: Sixty-six eyes of 33 patients were included in the study. The sensitivity of UWF-FP for the detection of proliferative SCR was 100%, (95% confidence interval [CI95%] 76.8–100) for the retinal specialist and 100% (CI95% 71.5–100) for the ophthalmology resident. The specificity of UWF-FP for the detection of proliferative SCR was 100% (CI95% 92.7–100) for the retinal specialist and 98.1% (CI95% 89.7–100) for the ophthalmology resident. Conclusions: UWF-FP is a valuable exam for proliferative SCR screening, with excellent sensitivity and specificity and a good inter-grader agreement for ophthalmologists with various degree of skills, and is easy to use in a real-life setting. Full article