Translational Vision Science & Technology最新文献

{"title":"Artificial Intelligence for Optical Coherence Tomography in Glaucoma.","authors":"Mak B Djulbegovic, Henry Bair, David J Taylor Gonzalez, Hiroshi Ishikawa, Gadi Wollstein, Joel S Schuman","doi":"10.1167/tvst.14.1.27","DOIUrl":"10.1167/tvst.14.1.27","url":null,"abstract":"<p><strong>Purpose: </strong>The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant opportunities in the diagnosis and management of glaucoma. This article explores the application of various DL models in enhancing OCT capabilities and addresses the challenges associated with their clinical implementation.</p><p><strong>Methods: </strong>A review of articles utilizing DL models was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), autoencoders, and large language models (LLMs). Key developments and practical applications of these models in OCT image analysis were emphasized, particularly in the context of enhancing image quality, glaucoma diagnosis, and monitoring progression.</p><p><strong>Results: </strong>CNNs excel in segmenting retinal layers and detecting glaucomatous damage, whereas RNNs are effective in analyzing sequential OCT scans for disease progression. GANs enhance image quality and data augmentation, and autoencoders facilitate advanced feature extraction. LLMs show promise in integrating textual and visual data for comprehensive diagnostic assessments. Despite these advancements, challenges such as data availability, variability, potential biases, and the need for extensive validation persist.</p><p><strong>Conclusions: </strong>DL models are reshaping glaucoma management by enhancing OCT's diagnostic capabilities. However, the successful translation into clinical practice requires addressing major challenges related to data variability, biases, fairness, and model validation to ensure accurate and reliable patient care.</p><p><strong>Translational relevance: </strong>This review bridges the gap between basic research and clinical care by demonstrating how AI, particularly DL models, can markedly enhance OCT's clinical utility in diagnosis, monitoring, and prediction, moving toward more individualized, personalized, and precise treatment strategies.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"27"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11760759/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143034135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable Deep Learning for Glaucomatous Visual Field Prediction: Artifact Correction Enhances Transformer Models.","authors":"Kornchanok Sriwatana, Chanon Puttanawarut, Yanin Suwan, Titipat Achakulvisut","doi":"10.1167/tvst.14.1.22","DOIUrl":"10.1167/tvst.14.1.22","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this study was to develop a deep learning approach that restores artifact-laden optical coherence tomography (OCT) scans and predicts functional loss on the 24-2 Humphrey Visual Field (HVF) test.</p><p><strong>Methods: </strong>This cross-sectional, retrospective study used 1674 visual field (VF)-OCT pairs from 951 eyes for training and 429 pairs from 345 eyes for testing. Peripapillary retinal nerve fiber layer (RNFL) thickness map artifacts were corrected using a generative diffusion model. Three convolutional neural networks and 2 transformer-based models were trained on original and artifact-corrected datasets to estimate 54 sensitivity thresholds of the 24-2 HVF test.</p><p><strong>Results: </strong>Predictive performances were calculated using root mean square error (RMSE) and mean absolute error (MAE), with explainability evaluated through GradCAM, attention maps, and dimensionality reduction techniques. The Distillation with No Labels (DINO) Vision Transformers (ViT) trained on artifact-corrected datasets achieved the highest accuracy (RMSE, 95% confidence interval [CI] = 4.44, 95% CI = 4.07, 4.82 decibel [dB], MAE = 3.46, 95% CI = 3.14, 3.79 dB), and the greatest interpretability, showing improvements of 0.15 dB in global RMSE and MAE (P < 0.05) compared to the performance on original maps. Feature maps and visualization tools indicate that artifacts compromise DINO-ViT's predictive ability but improve with artifact correction.</p><p><strong>Conclusions: </strong>Combining self-supervised ViTs with generative artifact correction enhances the correlation between glaucomatous structures and functions.</p><p><strong>Translational relevance: </strong>Our approach offers a comprehensive tool for glaucoma management, facilitates the exploration of structure-function correlations in research, and underscores the importance of addressing artifacts in the clinical interpretation of OCT.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"22"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143024836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Noninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.","authors":"Rehana Khan, Vinod Maseedupally, Kaveri A Thakoor, Rajiv Raman, Maitreyee Roy","doi":"10.1167/tvst.14.1.20","DOIUrl":"10.1167/tvst.14.1.20","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.</p><p><strong>Methods: </strong>The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels. Eighty percent of the dataset was used for algorithm development and 20% for validation. A deep-convolutional neural network, utilizing VGG16, ResNet50, and InceptionV3 architectures, was trained to predict anemia and estimate Hb levels. Sensitivity, specificity, and accuracy were calculated, and receiver operating characteristic (ROC) curves were generated for comparison with clinical anemia data. GradCAM saliency maps highlighted regions linked to anemia and image processing techniques to quantify anemia-related features.</p><p><strong>Results: </strong>For predicting anemia, the InceptionV3 model demonstrated the best performance, achieving 98% accuracy, 99% sensitivity, 97% specificity, and an area under the curve (AUC) of 0.98 (95% confidence interval [CI] = 0.97-0.99). For estimating Hb levels, the mean absolute error for the InceptionV3 model was 0.58 g/dL (95% CI = 0.57-0.59 g/dL). The model focused on the area around the optic disc and the neighboring retinal vessels, revealing that anemic subjects exhibited significantly increased vessel tortuosity and reduced vessel density (P < 0.001), with variable effects on vessel thickness.</p><p><strong>Conclusions: </strong>The InceptionV3 model accurately predicted anemia and Hb levels, highlighting the potential of deep learning and vessel analysis for noninvasive anemia detection.</p><p><strong>Translational relevance: </strong>The proposed method offers the possibility to quantitatively predict hematological parameters in a noninvasive manner.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"20"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11771037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143024875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In Vitro Analysis of Pressure Resistance in the Paul Glaucoma Implant and Ahmed ClearPath 250 With and Without Polypropylene Thread Inside the Tube.","authors":"Andi Masdipa, Sachiko Kaidzu, Masaki Tanito","doi":"10.1167/tvst.14.1.2","DOIUrl":"10.1167/tvst.14.1.2","url":null,"abstract":"<p><strong>Purpose: </strong>Pressure resistance characteristics of the Paul glaucoma implant (PGI) and Ahmed ClearPath 250 (ACP), with and without the insertion of polypropylene thread in their tubes, were evaluated.</p><p><strong>Methods: </strong>The in vitro flow pressure was evaluated at varying flow rates, both with and without threads (6-0 for PGI and 4-0 or 3-0 for ACP). Cross-sectional areas of the tube lumen and thread were measured to calculate pressure resistance using the Hagen-Poiseuille equation.</p><p><strong>Results: </strong>For the PGI without the thread, the pressure remained relatively low and constant across all flow rates. In contrast, with the insertion of a 6-0 thread, there was a significant increase in pressure resistance, with the pressure increasing from 7.5 mm Hg at 1 µL/min to 43.8 mm Hg at 5 µL/min. For the ACP, the pressure resistance remained relatively constant across all flow rates without a thread and with either 4-0 or 3-0 threads. However, the pressure was higher with 3-0 threads compared with a 4-0 thread. The actual measured pressures agreed well with theoretical values in the no-thread conditions, but were consistently higher than the theoretical values in the threaded conditions.</p><p><strong>Conclusions: </strong>Inserting polypropylene threads into the tubes of nonvalved glaucoma drainage devices significantly affects pressure resistance with various degree.</p><p><strong>Translational relevance: </strong>PGI with a 6-0 polypropylene thread may not require external tube ligation to prevent hypotony, whereas ACP with a 4-0 thread likely requires additional ligation. Using a 3-0 thread in ACP may enhance pressure resistance sufficiently to avoid tube ligation, but this requires careful clinical consideration.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"2"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717134/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142955736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social Determinants of Uncorrected Distance and Near Visual Impairment in an Older Adult Population.","authors":"Po-Jen Lin, Alison G Abraham, Pradeep Ramulu, Aleks Mihailovic, Anna Kucharska-Newton, Xinxing Guo","doi":"10.1167/tvst.14.1.8","DOIUrl":"10.1167/tvst.14.1.8","url":null,"abstract":"<p><strong>Purpose: </strong>Uncorrected visual impairment (VI) significantly impacts life quality and exacerbates age-related health issues. Social determinants of health (SDOH) are associated with uncorrected VI, but quantitative evidence is limited. This study investigated the link between SDOH and uncorrected VI among aging adults to identify disparities and improve vision care.</p><p><strong>Methods: </strong>We used data from the Atherosclerosis Risk in Communities (ARIC) study visits 4 and 6 and the ancillary Eye Determinants of Cognition (EyeDOC) study. We included subjects who were >70 years old and extracted their sex, race, residence, household income, education level, having an eye doctor, health insurance status, and Area Deprivation Index (ADI) and vision outcomes. Uncorrected VI was categorized into uncorrected distance (UDVI) or near visual impairment (UNVI). Associations between SDOH indicators and VI were evaluated using logistic regressions.</p><p><strong>Results: </strong>Among 967 adults (mean ± SD age, 78.6 ± 4.35 years; 37.9% male), UDVI was found in 293 and UNVI in 186. Living in Jackson, MS, was associated with lower odds for UNVI (adjusted odds ratio [aOR] = 0.36; 95% CI, 0.20-0.65). Higher odds for UNVI were associated with male sex (aOR = 2.01; 95% CI, 1.41-2.87), low educational attainment (aOR for not completing high school = 2.32; 95% CI, 1.37-3.92; aOR for high school only = 1.92; 95% CI, 1.26-2.92), no eye doctor (aOR = 1.58; 95% CI, 1.05-2.39), and having government health insurance only (aOR = 1.48; 95% CI, 1.00-2.17). Associations between SDOH factors and UDVI were weaker or non-existent.</p><p><strong>Conclusions: </strong>This study links SDOH factors to uncorrected VI among older adults.</p><p><strong>Translational relevance: </strong>SDOH should be considered when designing interventions to reduce VI in vulnerable communities.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"8"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11731176/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142955525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pulsed Ultrasound-Mediated Drug Delivery Enhancement Through Human Sclera.","authors":"Shuqi You, Suqian Wu, Shicheng Yang, Zhenyang Zhao, Wei Chen, Xiangwu Chen, Huan Wang, Qing Xia, Jiawei Xiong, Hongsheng Zhou, Xiaofen Mo","doi":"10.1167/tvst.14.1.7","DOIUrl":"10.1167/tvst.14.1.7","url":null,"abstract":"<p><strong>Purpose: </strong>The purpose of this study was to characterize whether pulsed ultrasound (PUS) affects transscleral drug delivery.</p><p><strong>Methods: </strong>Fluorescein sodium (NaF, 376 Da) and fluorescein isothiocyanate-conjugated dextran 40 (FD-40, 40 kDa) were used as model drugs. Human sclera grafts were placed in modified Franz diffusion cells and were treated by PUS (1 megahertz [MHz], 0.71 W/cm2, duty cycle 30%, application time 5 minutes) once or repeatedly under various conditions to assess permeation enhancement and reservoir effect. The safety of PUS application was assessed on human sclera grafts ex vivo and rabbit eyes in vivo by histology and temperature measurements.</p><p><strong>Results: </strong>Single PUS application yielded a significant increase in FD-40 permeation (P <  0.05). Repeated PUS applications led to a further enhancement in FD-40 permeation and also significantly promoted NaF permeation (more than 8.51-fold, P <  0.05). The human scleral permeability was temporarily modified by PUS, as evidenced by the increased scleral permeability during PUS application and the unchanged permeability coefficients at steady state. The reservoir effect of human sclera was also enhanced by PUS application. Cavitation was detected under PUS. A minor increase in graft temperature rise (<1°C) and no ocular damage was caused by PUS.</p><p><strong>Conclusions: </strong>PUS is an efficient and safe method to enhance model drugs to transport across human sclera by increasing the scleral permeability transiently and improving the reservoir effect. The enhancement was correlated with the molecule size and further promoted by the repeated PUS application.</p><p><strong>Translational relevance: </strong>Our study provides proof of concept for using PUS to enhance drug delivery to the posterior eye segment.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"7"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11734544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142955738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterization of the Disorganization of the Inner Retinal Layers in Diabetics Using Increased Axial Resolution Optical Coherence Tomography.","authors":"Katharina Wall, Lilith P Arend, Leon von der Emde, Marlene Saßmannshausen, Frank G Holz, Thomas Ach","doi":"10.1167/tvst.14.1.12","DOIUrl":"10.1167/tvst.14.1.12","url":null,"abstract":"<p><strong>Purpose: </strong>To compare a novel high-resolution optical coherence tomography (OCT) with improved axial resolution (High-Res OCT) with conventional spectral-domain OCT (SD-OCT) with regard to their capacity to characterize the disorganization of the retinal inner layers (DRIL) in diabetic maculopathy.</p><p><strong>Methods: </strong>Diabetic patients underwent multimodal retinal imaging (SD-OCT, High-Res OCT, and color fundus photography). Best-corrected visual acuity and diabetes characteristics were recorded. DR was graded using the international clinical diabetic retinopathy severity scale (DRSS). In each OCT B-scan, retinal layers were segmented and the loss of discernibility was annotated. DRIL areas were analyzed in en face projection using FIJI plugins. The Wilcoxon test and regression models were used for statistical analysis.</p><p><strong>Results: </strong>In 93 eyes of 93 patients (mean age, 61.8 ± 12.9 years) DRIL was identified in 48 eyes. DRIL was most frequent in the central subfield (27%). In DRIL eyes, DRSS was significantly higher (4.43 ± 1.01 vs. 2.12 ± 1.66; P < 0.001), BCVA was significantly worse (0.34 ± 0.38 vs. 0.13 ± 0.22; P < 0.001), and the loss of discernibility of the individual inner retinal layers was significantly smaller in High-Res OCT compared with SD-OCT (0.21 ± 0.29 vs. 1.21 ± 1.21 mm2; P < 0.001). The discernibility loss was greatest in the retinal nerve fiber layer and ganglion cell layer.</p><p><strong>Conclusions: </strong>DRIL occurs in eyes with advanced diabetic retinopathy, with a characteristic spread: from the inner toward the outer retina. High-Res OCT shows significantly smaller DRIL areas compared with SD-OCT, because of a more precise delineation of the inner retinal layers.</p><p><strong>Translational relevance: </strong>Using OCT with increased axial resolution could enhance our understanding of DRIL development and progression, providing deeper insights into pathophysiological aspects, including malperfusion in the inner capillary plexus.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"12"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11737467/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum in: Focused Ultrasound as a Novel Non-Invasive Method for the Delivery of Gold Nanoparticles to Retinal Ganglion Cells.","authors":"","doi":"10.1167/tvst.14.1.13","DOIUrl":"10.1167/tvst.14.1.13","url":null,"abstract":"","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"13"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11737458/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142972305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Unaided and Aided Visual Acuity in Adults With Down Syndrome.","authors":"Lauren V Schneider, Jason D Marsack, Ruth E Manny, Heather A Anderson","doi":"10.1167/tvst.14.1.30","DOIUrl":"10.1167/tvst.14.1.30","url":null,"abstract":"<p><strong>Purpose: </strong>Individuals with Down syndrome (DS) have reduced visual acuity (VA), even when wearing refractive correction. The relationship between refractive error and VA in adults with DS is explored.</p><p><strong>Methods: </strong>Thirty adults with DS (age = 29 ± 10 years) were enrolled in a trial comparing clinical and objectively determined refractions. Monocular VA was recorded unaided and aided with best refraction. Vectors M, J0, and J45 were calculated from unaided wavefront aberration measures at the habitual pupil size. The square root of the sum of the squared vectors was calculated providing a single positive vector length representing unaided refractive error. Residual refractive error was determined after applying the best performing refraction. Linear regression determined correlation between refractive error and VAs.</p><p><strong>Results: </strong>Unaided and aided VAs ranged from 0.22 to 1.42 logMAR and 0.06 to 0.82 logMAR, respectively. Unaided and residual refractive error represented as vector length ranged from 0.68 diopters (D) to 13.76 D and 0.05 D to 1.87 D, respectively. Unaided refractive error and VA were significantly positively correlated (r2 = 0.776, P < 0.001), but not residual refractive error and VA (r2 = 0.005, P = 0.721).</p><p><strong>Conclusions: </strong>There was a positive correlation between unaided VA and refractive error magnitude in adults with DS; however, unaided VA was better than expected given the high levels of refractive error. Aided VA and residual refractive error were not correlated, despite overall low levels of remaining residual refractive error, suggesting that factors in addition to optical quality may be limiting VA in this population.</p><p><strong>Translational relevance: </strong>Understanding the relationship between refractive error and VA in individuals with DS may provide clinicians clearer expectations for the acuity end points before and after correction for this patient population.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"30"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11781328/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143067204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conjunctival Bulbar Redness Extraction Pipeline for High-Resolution Ocular Surface Photography.","authors":"Philipp Ostheimer, Arno Lins, Lars Albert Helle, Vito Romano, Bernhard Steger, Marco Augustin, Daniel Baumgarten","doi":"10.1167/tvst.14.1.6","DOIUrl":"10.1167/tvst.14.1.6","url":null,"abstract":"<p><strong>Purpose: </strong>To extract conjunctival bulbar redness from standardized high-resolution ocular surface photographs of a novel imaging system by implementing an image analysis pipeline.</p><p><strong>Methods: </strong>Data from two trials (healthy; outgoing ophthalmic clinic) were collected, processed, and used to train a machine learning model for ocular surface segmentation. Various regions of interest were defined to globally and locally extract a redness biomarker based on color intensity. The image-based redness scores were correlated to clinical gradings (Efron) for validation.</p><p><strong>Results: </strong>The model to determine the regions of interest was verified for a segmentation performance, yielding mean intersections over union of 0.9639 (iris) and 0.9731 (ocular surface). All trial data were analyzed and a digital grading scale for the novel imaging system was established. Photographs and redness scores from visits weeks apart showed good feasibility and reproducibility. For scores within the same session, a mean coefficient of variation of 4.09% was observed. A moderate positive Spearman correlation (0.599) was found with clinical grading.</p><p><strong>Conclusions: </strong>The proposed conjunctival bulbar redness extraction pipeline demonstrates that by using standardized imaging, a segmentation model and image-based redness scores' external eye photography can be classified and evaluated. Therefore, it shows the potential to provide eye care professionals with an objective tool to grade ocular redness and facilitate clinical decision-making in a high-throughput manner.</p><p><strong>Translational relevance: </strong>To empower clinicians and researchers with a high-throughput workflow by standardized imaging combined with an analysis tool based on artificial intelligence to objectively determine an image-based redness score.</p>","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"14 1","pages":"6"},"PeriodicalIF":2.6,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11734545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142955734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}