Ophthalmology science最新文献

{"title":"Quantification of Hyperreflective Foci in Age-related Macular Degeneration by Polarization-Sensitive OCT","authors":"Ryo Terao MD, PhD ,&nbsp;Shuichiro Aoki MD, PhD ,&nbsp;Kohdai Kitamoto MD, PhD ,&nbsp;Kota Totani AE ,&nbsp;Masahiro Yamanari PhD ,&nbsp;Satoshi Sugiyama MSc ,&nbsp;Tatsuya Inoue MD, PhD ,&nbsp;Ryo Obata MD, PhD ,&nbsp;Keiko Azuma MD, PhD","doi":"10.1016/j.xops.2025.100792","DOIUrl":"10.1016/j.xops.2025.100792","url":null,"abstract":"<div><h3>Purpose</h3><div>To quantify hyperreflective foci (HRF) using polarization-sensitive OCT (PS-OCT) and evaluate the effect of anti-VEGF therapy on HRF reduction.</div></div><div><h3>Design</h3><div>Retrospective study.</div></div><div><h3>Subjects</h3><div>Twelve eyes from 12 patients with neovascular age-related macular degeneration (nAMD) who underwent PS-OCT imaging before and after 4 intravitreal injections of faricimab, administered every 4 weeks.</div></div><div><h3>Methods</h3><div>Retinal layers between the inner border of the inner nuclear layer and the outer border of the outer segment of photoreceptors were analyzed. Regions with entropy values exceeding the mean + 2 standard deviations from healthy controls (entropy: 0.0896 ± 0.0270) were isolated to quantify hyperentropic foci (HEF), representing HRF.</div></div><div><h3>Main Outcome Measures</h3><div>The sum and area of HEF were calculated as total HEF and area aggregate to compare before and after the treatment.</div></div><div><h3>Results</h3><div>The mean patient age was 77.4 ± 8.6 years, with an equal distribution of males and females (6 each). Total HEF was significantly associated with worse baseline visual acuity (coefficient: 0.0015297, <em>P</em> = 0.0004). Faricimab treatment significantly reduced both total HEF (<em>P</em> = 0.0049) and area aggregate (<em>P</em> = 0.0068). However, conventional OCT did not detect significant improvements in total reflectivity nor area aggregate.</div></div><div><h3>Conclusions</h3><div>Polarization-sensitive OCT is a valuable imaging modality for extracting and quantifying HRF in the neurosensory retina. Faricimab significantly reduces HEF in nAMD eyes, highlighting its potential therapeutic effect beyond conventional OCT-detected changes.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosures may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100792"},"PeriodicalIF":3.2,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Re: Chaurasia et al: Highly Accurate and Precise Automated Cup-to-Disc Ratio Quantification for Glaucoma Screening","authors":"Eunice Jin Hui Goh MMed (Ophth), FRCOphth ,&nbsp;Boon Peng Yap BEng ,&nbsp;Kelvin Zhenghao Li MMed (Ophth), FRCOphth","doi":"10.1016/j.xops.2025.100788","DOIUrl":"10.1016/j.xops.2025.100788","url":null,"abstract":"","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100788"},"PeriodicalIF":3.2,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparative Validation Study of Near Visual Acuity Assessment Using Different Handheld Acuity Charts","authors":"David Ziyou Chen MBBS, FRCOphth ,&nbsp;Yih-Chung Tham PhD ,&nbsp;Liang Shen PhD ,&nbsp;Soon-Phaik Chee MMed (Ophth), FRCOphth","doi":"10.1016/j.xops.2025.100790","DOIUrl":"10.1016/j.xops.2025.100790","url":null,"abstract":"<div><h3>Objective</h3><div>To develop a conversion table and compare the cross-validity of 3 types of widely utilized near vision charts: the ETDRS near chart, the N-notation chart, and the Rosenbaum chart.</div></div><div><h3>Design</h3><div>A prospective, cross-sectional, comparative validation study.</div></div><div><h3>Participants</h3><div>Aged ≥40 years.</div></div><div><h3>Methods</h3><div>A conversion table for the 3 types of near charts was created using objective character sizing based on vertical height captured using a surgical microscope with a 10× magnification. Eligible presbyopic patients had their near vision tested sequentially with 3 near charts in a randomized order.</div></div><div><h3>Main Outcome Measures</h3><div>Pearson correlation coefficient (<em>r</em>) for the relationship among the near visual acuity charts. The consistency between the different charts was evaluated by Bland−Altman diagrams.</div></div><div><h3>Results</h3><div>A total of 204 participants (129 women, 63.2%) were recruited for the study (mean age, 58.9 ± 7.1 years). For correlation, <em>r</em> ranged from 0.596 to 0.836 (all <em>P</em> &lt; 0.001). The Rosenbaum chart had the smallest range of difference against the ETDRS chart (standard deviation [SD] = 0.12), followed by the N-notation chart (SD = 0.15). Most of the converted logarithm of the minimum angle of resolution (logMAR) values from the N-notation and Rosenbaum charts were between 0.0 and 0.1 higher than the ETDRS logMAR equivalent (range: 0.07–0.11), with a tendency for both the N-notation and Rosenbaum charts to overestimate logMAR at more positive values.</div></div><div><h3>Conclusions</h3><div>We have developed a conversion table for 3 types of commonly used near vision charts. When compared with the ETDRS near chart, the Rosenbaum chart had a smaller range of difference than the N-notation chart. Both the Rosenbaum and N-notation charts tended to underestimate near vision at worse vision.</div></div><div><h3>Financial Disclosure(s)</h3><div>The author(s) have no proprietary or commercial interest in any materials discussed in this article.</div></div>","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100790"},"PeriodicalIF":3.2,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning−Driven Exophthalmometry through Facial Photographs in Thyroid Eye Disease","authors":"Joonhyeon Park PhD ,&nbsp;Jin Sook Yoon MD, PhD ,&nbsp;Namju Kim MD, PhD ,&nbsp;Kyubo Shin PhD ,&nbsp;Hyun Young Park MD, PhD ,&nbsp;Jongchan Kim MS ,&nbsp;Jaemin Park MS ,&nbsp;Jae Hoon Moon MD, PhD ,&nbsp;JaeSang Ko MD, PhD","doi":"10.1016/j.xops.2025.100791","DOIUrl":"10.1016/j.xops.2025.100791","url":null,"abstract":"<div><h3>Objective</h3><div>To develop and evaluate a deep learning (DL)-assisted system for proptosis measurement using facial photographs in thyroid eye disease (TED).</div></div><div><h3>Design</h3><div>A retrospective cohort study.</div></div><div><h3>Participants</h3><div>This study included 1108 patients with TED from Severance Hospital (SH) and 171 from Seoul National University Bundang Hospital (SNUBH).</div></div><div><h3>Methods</h3><div>The DL-assisted system was trained using 1610 facial images paired with Hertel exophthalmometry measurements from SH and externally validated using 511 SNUBH images. The system employs a dual-stream ResNet-18 neural network, utilizing both red-green-blue images and depth maps generated by the ZoeDepth algorithm.</div></div><div><h3>Main Outcome Measures</h3><div>Accuracy was assessed using mean absolute error (MAE), Pearson correlation coefficient, intraclass correlation coefficient (ICC), and area under the curve of the receiver operating characteristic curve.</div></div><div><h3>Results</h3><div>The DL-assisted system achieved an MAE of 1.27 mm for the SH dataset and 1.24 mm for the SNUBH dataset. Pearson correlation coefficients were 0.82 and 0.77, respectively, with ICCs indicating strong reliability (0.80 for SH and 0.73 for SNUBH). The receiver operating characteristic curve analysis showed area under the curves of 0.91 for SH and 0.88 for SNUBH in detecting proptosis. The system detected significant proptosis changes (≥ 2 mm) with 74.6% accuracy.</div></div><div><h3>Conclusions</h3><div>The DL-assisted system offers an accurate, accessible method for exophthalmometry in patients with TED using facial photographs. This tool presents a promising alternative to traditional exophthalmometry, potentially improving access to reliable proptosis measurement in both clinical and nonspecialist settings.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100791"},"PeriodicalIF":3.2,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal Comparison of Geographic Atrophy Enlargement Using Manual, Semiautomated, and Deep Learning Approaches","authors":"Jacob Bogost ,&nbsp;Rachel E. Linderman PhD ,&nbsp;Robert Slater PhD ,&nbsp;Thomas F. Saunders OD ,&nbsp;Caleb Pacheco ,&nbsp;Jeong Pak PhD ,&nbsp;Rick Voland PhD ,&nbsp;Barbara Blodi MD ,&nbsp;Amitha Domalpally MD, PhD","doi":"10.1016/j.xops.2025.100787","DOIUrl":"10.1016/j.xops.2025.100787","url":null,"abstract":"<div><h3>Objective</h3><div>To compare a fully automated artificial intelligence (AI) model, a semiautomated method, and manual planimetry in the longitudinal assessment of geographic atrophy (GA) using fundus autofluorescence images.</div></div><div><h3>Design</h3><div>A retrospective analysis of 3 GA assessment methods: AI, Heidelberg Eye Explorer semiautomated software (RegionFinder), and manual planimetry.</div></div><div><h3>Subjects and Controls</h3><div>One hundred eight patients (185 eyes) with GA from a phase IIb clinical trial by GlaxoSmithKline, which evaluated an experimental drug that did not reduce GA enlargement compared with the placebo.</div></div><div><h3>Methods</h3><div>Fundus autofluorescence images of 185 eyes were annotated using manual planimetry, semiautomated RegionFinder, and a fully automated AI model trained and validated on manual planimetry annotations at screening, year 1, and year 2. Artificial intelligence masks were compared with human-guided methods, and regression errors were assessed by stacking masks from consecutive visits. Agreement between methods was assessed using Bland−Altman plots, Dice similarity coefficient (DSC), and comparisons of GA growth rates. Artificial intelligence performance was evaluated based on its need for human edits and frequency of regression errors.</div></div><div><h3>Main Outcome Measures</h3><div>Agreement between methods was evaluated using Bland−Altman plots, DSC, and intraclass correlation coefficients (ICCs). The mean GA growth rate (mm²/year) and square root transformation of GA size were compared across methods. Artificial intelligence performance was assessed by the percentage of acceptable masks and the frequency of longitudinal regression errors.</div></div><div><h3>Results</h3><div>At screening, the mean GA area was 7.22 mm² with RegionFinder, 8.37 mm² with AI, and 8.66 mm² with manual planimetry. RegionFinder measured smaller GA areas than both AI and manual, with a mean difference of −1.45 mm² (95% confidence interval [CI]: −1.56, −1.35) versus AI (ICC = 0.945) and −1.87 mm² (95% CI: −1.99, −1.75) versus manual (ICC = 0.920). Growth rates were comparable between RegionFinder (1.54 mm²/year), AI (1.68 mm²/year), and manual (1.80 mm²/year) (<em>P</em> = 0.25). Artificial intelligence masks were deemed acceptable in 84.8% of visits, and 81.4% of cases showed no regression over time.</div></div><div><h3>Conclusions</h3><div>Artificial intelligence accurately measures GA in approximately 85% of cases, requiring human intervention in only 15%, indicating potential to streamline GA measurement in clinical trials while maintaining human oversight.</div></div><div><h3>Financial Disclosure(s)</h3><div>The author(s) have no proprietary or commercial interest in any materials discussed in this article.</div></div>","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100787"},"PeriodicalIF":3.2,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased Prevalence of Myopia in the United States between 1971 and 1972 and 1999 and 2004—A Reappraisal","authors":"Mark A. Bullimore FCOptom, PhD,&nbsp;Xu Cheng MD, PhD,&nbsp;Noel A. Brennan MScOptom, PhD","doi":"10.1016/j.xops.2025.100786","DOIUrl":"10.1016/j.xops.2025.100786","url":null,"abstract":"","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100786"},"PeriodicalIF":3.2,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Repeatability of Fractal Analysis in OCT Angiography of the Macula and Optic Nerve Head","authors":"Gustavo Rosa Gameiro MD, PhD,&nbsp;Alessandro A. Jammal MD, PhD,&nbsp;Verônica Vilasboas-Campos MD,&nbsp;Jianhua Wang MD, PhD,&nbsp;Felipe A. Medeiros MD, PhD","doi":"10.1016/j.xops.2025.100784","DOIUrl":"10.1016/j.xops.2025.100784","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the repeatability of OCT angiography (OCTA) vessel density measurements using fractal analysis in the macula and optic nerve head (ONH) regions.</div></div><div><h3>Design</h3><div>A prospective longitudinal observational cohort study.</div></div><div><h3>Participants</h3><div>One hundred sixteen eyes from 71 primary open-angle glaucoma patients with valid macula OCTA scans and 91 eyes from 59 primary open-angle glaucoma patients with valid ONH OCTA scans, with 53 patients contributing scans for both regions.</div></div><div><h3>Methods</h3><div>Participants underwent 5 OCTA imaging sessions at weekly intervals using the Spectralis spectral-domain OCT (Heidelberg Engineering). OCT angiography images were processed for fractal analysis focusing on small vessels (&lt;25 μm in diameter) within <em>en face</em> slabs of the superficial vascular complex (SVC), deep vascular complex (DVC), full retina, and nerve fiber layer vascular plexus (NFLVP). Vessel density repeatability was assessed using the coefficient of variation (CoV) with bootstrapped 95% confidence intervals. Associations between fractal analysis parameters and peripapillary retinal nerve fiber layer (RNFL) thickness were analyzed.</div></div><div><h3>Main Outcome Measures</h3><div>Repeatability of OCTA vessel density quantified by fractal analysis and correlation with RNFL thickness.</div></div><div><h3>Results</h3><div>One thousand three hundred twenty-eight macula OCTA scans from 269 visits and 801 ONH scans from 164 visits were included. Fractal analysis demonstrated high repeatability for vessel density measurements, with CoVs ranging from 0.4% to 0.9% in the macula and 0.7% to 1.8% in the ONH region. Full retina slabs exhibited the best repeatability in both regions, while DVC measurements in the ONH showed the highest variability (CoV = 1.8%). Moderate correlations between fractal parameters and RNFL thickness were observed in the ONH (SVC: rho = 0.65; NFLVP: rho = 0.67; <em>P</em> &lt; 0.001) and macula (SVC: rho = 0.33, <em>P</em> &lt; 0.001).</div></div><div><h3>Conclusions</h3><div>High repeatability of OCTA vessel density measurements using fractal analysis was observed in the macula and ONH regions, supporting its potential utility in monitoring vascular changes in glaucoma. Future studies should investigate its diagnostic accuracy and ability to detect disease progression.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100784"},"PeriodicalIF":3.2,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Imminent Conversion to Exudative Age-Related Macular Degeneration Using Multimodal Data and Ensemble Machine Learning","authors":"T.Y.Alvin Liu MD ,&nbsp;Yuxuan Liu MS ,&nbsp;Madeleine S. Gastonguay BS ,&nbsp;Dan Midgett PhD ,&nbsp;Nathanael Kuo PhD ,&nbsp;Yujie Zhao ,&nbsp;Kareef Ullah ,&nbsp;Gwyneth Alexander ,&nbsp;Todd Hartman ,&nbsp;Neslihan D. Koseoglu MD ,&nbsp;Craig Jones PhD","doi":"10.1016/j.xops.2025.100785","DOIUrl":"10.1016/j.xops.2025.100785","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Objective&lt;/h3&gt;&lt;div&gt;Exudative age-related macular degeneration (eAMD) is a major cause of central vision loss. Identifying patients at high risk of imminent eAMD could enable timely treatment and improve outcomes. Our goal was to develop and compare classical machine learning (ML) and deep learning (DL) models to predict imminent eAMD conversion within 6 months and integrate OCT with clinical data into a single predictive model.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Design&lt;/h3&gt;&lt;div&gt;Retrospective cohort study.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Participants&lt;/h3&gt;&lt;div&gt;Patients seen at the Wilmer Eye Institute between 2013 and 2021 with eAMD in ≥1 eye.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;Spectral domain OCT volumes prior to conversion and the corresponding clinical data (age, best-corrected visual acuity, sex, and fellow-eye status) were collected and used for model training or testing. ResNet-50 and classical ML (Random Forest and XGBoost) models were trained to predict imminent conversion to eAMD within 6 months on an eye level. For the multilayer perceptron (MLP) framework, the trained ResNet-50 model was used as the feature encoder, and a downsampled feature vector concatenated with corresponding clinical tabular data was passed through the MLP (prediction head). Data were partitioned at the patient level (75% training, 15% validation, and 10% testing). Model performance was evaluated using the area under the operating characteristic curve (AUC) and 95% confidence interval (CI) for the model AUC was calculated using the percentile method after bootstrapping the test set 10 000 times. Model comparisons were made using modified paired &lt;em&gt;t&lt;/em&gt; test. &lt;em&gt;P&lt;/em&gt; &lt; 0.05 was considered statistically significant.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Main Outcome Measures&lt;/h3&gt;&lt;div&gt;Area under the operating characteristic curve.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results&lt;/h3&gt;&lt;div&gt;Thirty-three thousand one hundred eighty-nine OCT volumes from 2084 patients (63% female; 89.1% White, 4.8% Black, and 2.3% Asian) were included. The mean age at the time of first-eye conversion was 78.9 (± 9.3) years. Our best-performing models, “MLP multimodal” (trained with both OCT and clinical data; AUC: 0.76, 95% CI: 0.71–0.80) and “CNN OCT” (trained with only OCT data; AUC: 0.75, 95% CI: 0.70–0.79), had a DL (ResNet-50) architecture; “MLP multimodal” outperformed “CNN OCT” in predicting both all-eye (&lt;em&gt;P&lt;/em&gt; &lt; 0.05) and first-eye conversion (&lt;em&gt;P&lt;/em&gt; &lt; 0.001).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusions&lt;/h3&gt;&lt;div&gt;The 3-dimensional DL models, trained with OCT volumes, are capable of predicting both first-eye and fellow-eye imminent conversion to eAMD. The addition of clinical data further improved the model performance. These models, if validated prospectively, could serve as screening tools and allow retinal specialists to prioritize patients with more acute retinal issues.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Financial Disclosure(s)&lt;/h3&gt;&lt;div&gt;Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100785"},"PeriodicalIF":3.2,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144124774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Features and Natural Progression of Unilateral High Myopia in Adults: A Comparison Study","authors":"Dong Geun Kim MD ,&nbsp;Seok Hyun Bae MD ,&nbsp;Dong Ju Kim MD ,&nbsp;Jong Suk Lee MD ,&nbsp;Kwangsic Joo MD, PhD ,&nbsp;Sang Jun Park MD, PhD ,&nbsp;Se Joon Woo MD, PhD ,&nbsp;Kyu Hyung Park MD, PhD","doi":"10.1016/j.xops.2025.100780","DOIUrl":"10.1016/j.xops.2025.100780","url":null,"abstract":"<div><h3>Purpose</h3><div>To investigate and compare the clinical characteristics of patients with unilateral high myopia (UHM) and bilateral high myopia (BHM) based on axial length (AL).</div></div><div><h3>Design</h3><div>A retrospective cohort study.</div></div><div><h3>Participants</h3><div>Adult patients diagnosed with UHM or BHM between March 2011 and August 2021.</div></div><div><h3>Methods</h3><div>Unilateral high myopia was defined as ≥26 mm AL in 1 eye and &lt;26 mm in the other, with ≥2 mm difference. Bilateral high myopia was defined as ≥26 mm AL in both eyes, with ≤3 mm difference. In each patient, the eye with the longer AL was designated the “longer eye” and the other the “shorter eye.” We analyzed differences in clinical features, including ophthalmic history, best-corrected visual acuity, ocular biometry, and myopic maculopathy grade. Myopic maculopathy was graded based on atrophy, traction, and neovascularization using a known method. Long-term features included treatments for myopic neovascular maculopathy and myopic tractional maculopathy and AL change over time.</div></div><div><h3>Main Outcome Measures</h3><div>Comparison of clinical characteristics between UHM and BHM groups.</div></div><div><h3>Results</h3><div>We analyzed 369 patients (79 with UHM and 290 with BHM) with a median follow-up period of 4.5 years. The UHM group had a higher proportion of women than the BHM group (88.8% vs. 76.2%, <em>P</em> = 0.025). Compared with longer eyes in the BHM group, those in the UHM group had worse best-corrected visual acuity (0.8 ± 0.6 vs. 0.6 ± 0.6 in logarithm of the minimum angle of resolution, <em>P</em> &lt; 0.001) despite having shorter AL (29.1 ± 1.6 mm vs. 30.6 ± 1.9 mm, <em>P</em> &lt; 0.001). In the analysis of AL changes, shorter eyes in the UHM group showed no elongation over time (0.014 mm/year, <em>P</em> = 0.12), unlike the longer eyes in UHM and both eyes in BHM (0.049–0.071 mm/year, <em>P</em> &lt; 0.01).</div></div><div><h3>Conclusions</h3><div>Adult UHM patients mostly lacked associated environmental factors. The poorer visual acuity in the longer eyes of UHM patients, which cannot be explained by structural abnormalities, suggests that the interocular difference may have originated in early childhood. During the follow-up period, AL elongation and myopic complications occurred at similar rates in the longer eye of UHM and both eyes of BHM. Meanwhile, such changes were not observed in the shorter eye in UHM. Further investigation of the underlying mechanisms, such as the genetic factors contributing to this extreme asymmetry, is warranted.</div></div><div><h3>Financial Disclosure(s)</h3><div>The author(s) have no proprietary or commercial interest in any materials discussed in this article.</div></div>","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100780"},"PeriodicalIF":3.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143907489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal Analysis of Mesopic Microperimetry in a Phase II Trial Evaluating Minocycline for Geographic Atrophy","authors":"Thilaka Arunachalam BS ,&nbsp;Maria Abraham ScM ,&nbsp;Christine Orndahl PhD ,&nbsp;Supriya Menezes MS ,&nbsp;Souvick Mukherjee PhD ,&nbsp;Cameron Duic BS ,&nbsp;Minali Prasad BA ,&nbsp;Fares Siddig BS ,&nbsp;Sunil Bellur MD ,&nbsp;Alisa T. Thavikulwat MD ,&nbsp;Clare Bailey MD ,&nbsp;SriniVas R. Sadda MD ,&nbsp;Wai T. Wong MD, PhD ,&nbsp;Emily Y. Chew MD ,&nbsp;Brett G. Jeffrey PhD ,&nbsp;Tiarnán D.L. Keenan BM BCh, PhD","doi":"10.1016/j.xops.2025.100783","DOIUrl":"10.1016/j.xops.2025.100783","url":null,"abstract":"<div><h3>Purpose</h3><div>To analyze mesopic microperimetry data from a recent phase II trial of minocycline for geographic atrophy (GA) for possible efficacy on the change in visual function and, in the absence of efficacy, to perform longitudinal analyses as a natural history study.</div></div><div><h3>Design</h3><div>Phase II, prospective, single-arm, nonrandomized trial. After a 9-month run-in phase, participants began oral minocycline 100 mg twice daily for 3 years.</div></div><div><h3>Participants</h3><div>Individuals with GA in ≥1 eye.</div></div><div><h3>Methods</h3><div>Participants underwent mesopic microperimetry at baseline, month 3, and every 6 months thereafter, using a custom T-shaped test pattern. Rates of change in microperimetry parameters were compared between the 24-month treatment phase and 9-month run-in phase by linear spline regression.</div></div><div><h3>Main Outcome Measures</h3><div>The mean macular and responding sensitivity; the mean perilesional and extralesional sensitivity; number of absolute and relative scotomatous loci.</div></div><div><h3>Results</h3><div>Thirty study eyes from 30 participants (mean age 74.1 years) underwent microperimetry (mean follow-up 27.4 months). For 5 of the 6 microperimetry parameters, no significant difference in the rate of change between the treatment and run-in phases was observed. The difference between the 2 phases was −0.74 decibels (dB)/year (standard error [SE] 0.85; <em>P</em> = 0.39) for mean macular sensitivity, −0.30 dB/year (SE 0.85; <em>P</em> = 0.72) for mean responding sensitivity, 1.23 dB/year (SE 1.01; <em>P</em> = 0.22) for mean perilesional sensitivity, and −0.02 (SE 0.01; <em>P</em> = 0.31) for transformed mean extralesional sensitivity. The difference in incidence rate ratios between the 2 phases was 1.17 (SE 0.11; <em>P</em> = 0.14) for absolute scotomatous loci and 0.73 (SE 0.11; <em>P</em> = 0.004) for relative scotomatous loci.</div></div><div><h3>Conclusions</h3><div>The results do not appear consistent with a clinically meaningful effect of minocycline on the rate of visual function decline from GA progression. This is consistent with previous analyses of the corresponding structural data. The findings demonstrate the advantages and disadvantages of different microperimetry parameters. The optimal testing patterns and parameters represent a trade-off between greater sensitivity vs. greater risk of floor/ceiling effects, with regional averages providing a useful compromise. The results may provide insights to guide the development of microperimetry end points for clinical trials.</div></div><div><h3>Financial Disclosure(s)</h3><div>Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.</div></div>","PeriodicalId":74363,"journal":{"name":"Ophthalmology science","volume":"5 5","pages":"Article 100783"},"PeriodicalIF":3.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143895827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}