Suitability and Early Clinical Outcomes of Corneal Donor Tissue in the 76-80-Year-Old Age Group.

PURPOSE: There is a significant global shortage of corneal donor tissue suitable for keratoplasty. One simple strategy for addressing this shortage is to increase the upper age limit for acceptable tissue over the current customary upper limit of age 75. We describe a pilot study completed at one eye bank procuring, processing, and distributing keratoplasty tissue from donors aged 76 to 80 years. METHODS: This is a retrospective case series of donor tissues aged 76 to 80 years in comparison with donor tissues aged 71 to 75 years. Standard tissue parameters were evaluated for all tissues, including tissue suitability, mean endothelial cell density (ECD), death-to-procurement time, and cause of death. For the older tissues, clinical outcomes through 3 months were obtained from each surgeon, including intraoperative and postoperative complications. RESULTS: Corneal tissues from donors aged 76 to 80 years had a similar suitability rate (57%) when compared with donors aged 71 to 75 years (59%) (P = 0.635). Both groups had comparable ECDs (P = 0.097). Early clinical outcomes of corneal grafts from donors older than 76 years were favorable, with no early graft failure or significant concerns for clinical safety or efficacy. CONCLUSIONS: Our findings suggest that corneal tissues aged 76 to 80 years can be safely and efficiently transplanted in the United States. While additional study is needed, our results strengthen the case that expanding the upper age limit for donor age has the potential to help meet the global shortage for suitable keratoplasty tissue.

Dexamethasone Intracanalicular Insert versus Standard Topical Steroids for the Prophylaxis of Inflammation after Cataract Surgery.

PURPOSE: To compare the efficacy of an intracanalicular dexamethasone intracanalicular insert (DII) to a topical prednisolone acetate 1% taper for preventing breakthrough inflammation (iritis or cystoid macular edema) during the first post-operative month (POM1) after cataract surgery DESIGN: Retrospective, non-randomized comparative interventional study METHODS: Patients received either DII or topical prednisolone acetate 1% eyedrops (control) during POM1. Exclusion criteria included history of iritis, glaucoma, intraoperative posterior capsular rupture or vitreous prolapse, immediate postoperative anterior chamber inflammation requiring treatment, or less than 1 month follow up post-operatively. Outcomes included development of breakthrough inflammation after >3 days postoperatively necessitating additional anti-inflammatory drops, cystoid macular edema, and increased intraocular pressure at POM1. RESULTS: 266 eyes of 174 patients were included in the DII group, and 258 eyes of 167 patients in the control group. Demographics, comorbidities, and baseline IOP were comparable between groups. The breakthrough inflammation rate was significantly higher in the DII group compared to control (9.0% vs 3.1%; p < .01); cystoid macular edema rates were similar between groups (4.9% vs 4.3%; p = .75). There were no cases of increased IOP >10mmHg at POM1 compared to baseline in either group. CONCLUSION: After cataract surgery, DII demonstrated a higher rate of breakthrough inflammation than a standard topical steroid regimen with no significant differences in CME rate or IOP increase; however, overall, the rate of postoperative complications was low. DII can be a safe and effective alternative to topical corticosteroid therapy after cataract surgery.

Nontraditional approaches to sedation for anterior segment surgery: a narrative review.

PURPOSE OF REVIEW: Surgical and anesthetic technological advancement have made both cataract and noncataract anterior segment surgery significantly less invasive and time-intensive, facilitating the transition of some of these procedures from the operating room under monitored anesthesia care (MAC) to the office-based setting without MAC. This transition has been aided by the popularization of nonintravenous approaches to achieving patient sedation for these procedures. In this review, we discuss the literature surrounding traditional and nontraditional methods of achieving patient sedation for anterior segment surgery. RECENT FINDINGS: Our survey of the literature suggests that nonintravenous (IV) approaches to sedation for these procedures may be just as safe, effective, and satisfactory to patients as traditional IV approaches. SUMMARY: As anterior segment surgery becomes less invasive and less time-intensive, providers considering transitioning their cataract and anterior segment surgery out of the operating room and into the office-based setting without MAC anesthesia should consider the non-IV sedation options outlined in this review to achieve adequate patient sedation and comfort.

Comparison of Machine and Human Expert Evaluation of Capsulorrhexis Creation Performance Through Analysis of Surgical Video Recordings.

Purpose: Achieving competency in cataract surgery is an essential component of ophthalmology residency training. Video-based analysis of surgery can change training through its objective, reliable, and timely assessment of resident performance. Methods: Using the Image Labeler application in MATLAB, the capsulorrhexis step of 208 surgical videos, recorded at the University of Michigan, was annotated for subjective and objective analysis. Two expert surgeons graded the creation of the capsulorrhexis based on the International Council of Ophthalmology's Ophthalmology Surgical Competency Assessment Rubric:Phacoemulsification (ICO-OSCAR:phaco) rating scale and a custom rubric (eccentricity, roundness, size, centration) that focuses on the objective aspects of this step. The annotated rhexis frames were run through an automated analysis to obtain objective scores for these components. The subjective scores were compared using both intra and inter-rater analyses to assess the consistency of a human-graded scale. The subjective and objective scores were compared using intraclass correlation methods to determine relative agreement. Results: All rhexes were graded as 4/5 or 5/5 by both raters for both items 4 and 5 of the ICO-OSCAR:phaco rating scale. Only roundness scores were statistically different between the subjective graders (mean difference = -0.149, p-value = 0.0023). Subjective scores were highly correlated for all components (>0.6). Correlations between objective and subjective scores were low (0.09 to 0.39). Conclusion: Video-based analysis of cataract surgery presents significant opportunities, including the ability to asynchronously evaluate performance and provide longitudinal assessment. Subjective scoring between two raters was moderately correlated for each component.

Evaluation of Methods for Detection and Semantic Segmentation of the Anterior Capsulotomy in Cataract Surgery Video.

Background: The capsulorhexis is one of the most important and challenging maneuvers in cataract surgery. Automated analysis of the anterior capsulotomy could aid surgical training through the provision of objective feedback and guidance to trainees. Purpose: To develop and evaluate a deep learning-based system for the automated identification and semantic segmentation of the anterior capsulotomy in cataract surgery video. Methods: In this study, we established a BigCat-Capsulotomy dataset comprising 1556 video frames extracted from 190 recorded cataract surgery videos for developing and validating the capsulotomy recognition system. The proposed system involves three primary stages: video preprocessing, capsulotomy video frame classification, and capsulotomy segmentation. To thoroughly evaluate its efficacy, we examined the performance of a total of eight deep learning-based classification models and eleven segmentation models, assessing both accuracy and time consumption. Furthermore, we delved into the factors influencing system performance by deploying it across various surgical phases. Results: The ResNet-152 model employed in the classification step of the proposed capsulotomy recognition system attained strong performance with an overall Dice coefficient of 92.21%. Similarly, the UNet model with the DenseNet-169 backbone emerged as the most effective segmentation model among those investigated, achieving an overall Dice coefficient of 92.12%. Moreover, the time consumption of the system was low at 103.37 milliseconds per frame, facilitating its application in real-time scenarios. Phase-wise analysis indicated that the Phacoemulsification phase (nuclear disassembly) was the most challenging to segment (Dice coefficient of 86.02%). Conclusion: The experimental results showed that the proposed system is highly effective in intraoperative capsulotomy recognition during cataract surgery and demonstrates both high accuracy and real-time capabilities. This system holds significant potential for applications in surgical performance analysis, education, and intraoperative guidance systems.

Baseline Participant Characteristics at Enrollment in the Zoster Eye Disease Study.

PURPOSE: The Zoster Eye Disease Study (ZEDS) is the first randomized clinical trial to study the efficacy of long-term (1 year) suppressive valacyclovir treatment on herpes zoster ophthalmicus (HZO) outcomes. This article details the baseline characteristics of participants. SETTING: The study was set at 95 participating clinical centers in 33 states, Canada, and New Zealand. STUDY POPULATION: Immunocompetent adults with a history of a characteristic HZO unilateral rash and documentation of an episode of active dendriform epithelial keratitis, stromal keratitis, endothelial keratitis, or iritis within the preceding year, enrolled in ZEDS from November 2017 to January 2023. INTERVENTION: Participants were randomized to double-masked oral valacyclovir 1 gm daily versus placebo for 1 year of treatment and followed for 18 months. RESULTS: Five hundred twenty-seven participants were enrolled across 4 strata according to age at HZO onset (younger or older than 60 years) and duration of HZO at enrollment (less or greater than 6 months), with an even distribution of men and women and a median age of 60 years. More participants with recent (57%, 300/527) than chronic HZO and younger than 60 years at HZO onset (54%, 286/527) were enrolled. Most participants were treated acutely with a recommended antiviral regimen (91%, 480/527) and had not been vaccinated against zoster (79%, 418/527). CONCLUSIONS: The broad ZEDS study population enhances the likelihood that ZEDS will provide generalizable high-quality evidence regarding the efficacy and safety of suppressive valacyclovir for HZO immunocompetent adults and whether it should become standard of care. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03134196.

Factors Associated With Laboratory Test Negativity Following a Transition in Specimen Collection in Microbial Keratitis Cases.

PURPOSE: Negative laboratory results make targeting microbial keratitis treatment difficult. We investigated factors associated with laboratory negativity in patients with microbial keratitis in the context of a transition to a new specimen collection method. METHODS: Microbial keratitis patients with associated laboratory tests were identified in the electronic health record of a tertiary care facility from August 2012 to April 2022. Patient demographics and laboratory results were obtained. Random sampling of 50% of charts was performed to assess the impact of the ocular history and pretreatment measures. The relationship between probability of negative laboratory results with demographics, ocular history, pretreatment measures, and utilization of a new specimen collection method (i.e. ESwab) was evaluated by multivariable logistic regression. RESULTS: Of 3395 microbial keratitis patients identified, 31% (n = 1051) had laboratory tests. Laboratory testing increased over time (slope = 2.5% per year, p < 0.001; 19.6% in 2013 to 42.2% in 2021). Laboratory negative rate increased over time (slope = 2.2% per year, p = 0.022; 48.5% in 2013 to 62.3% in 2021). Almost one-third of patients (31.2%, n = 164) were pretreated with steroids. Over two-thirds of patients were pretreated with antibiotics (69.5%, n = 367). 56.5% (n = 297) of patients were outside referrals. In multivariable regression, patients with corticosteroid pretreatment had lower odds of negative laboratory results (odds ratio [OR] = 0.49, p = 0.001). There were higher odds of negative laboratory results for every additional antibiotic prescribed to a patient prior to presentation (OR = 1.30, p = 0.006) and for specimens collected using ESwabs (OR = 1.69, p = 0.005). Age, prior eye trauma, outside referrals, and contact lens wear were not significantly associated with negative laboratory results. CONCLUSION: More microbial keratitis associated laboratory tests are being taken over time. Over 60% of tests were negative by 2022. Factors associated with negative laboratory test results included pretreatment with antibiotics and specimens collected with the new collection method.

Adaptive Tensor-Based Feature Extraction for Pupil Segmentation in Cataract Surgery.

Cataract surgery remains the only definitive treatment for visually significant cataracts, which are a major cause of preventable blindness worldwide. Successful performance of cataract surgery relies on stable dilation of the pupil. Automated pupil segmentation from surgical videos can assist surgeons in detecting risk factors for pupillary instability prior to the development of surgical complications. However, surgical illumination variations, surgical instrument obstruction, and lens material hydration during cataract surgery can limit pupil segmentation accuracy. To address these problems, we propose a novel method named adaptive wavelet tensor feature extraction (AWTFE). AWTFE is designed to enhance the accuracy of deep learning-powered pupil recognition systems. First, we represent the correlations among spatial information, color channels, and wavelet subbands by constructing a third-order tensor. We then utilize higher-order singular value decomposition to eliminate redundant information adaptively and estimate pupil feature information. We evaluated the proposed method by conducting experiments with state-of-the-art deep learning segmentation models on our BigCat dataset consisting of 5,700 annotated intraoperative images from 190 cataract surgeries and a public CaDIS dataset. The experimental results reveal that the AWTFE method effectively identifies features relevant to the pupil region and improved the overall performance of segmentation models by up to 2.26% (BigCat) and 3.31% (CaDIS). Incorporation of the AWTFE method led to statistically significant improvements in segmentation performance (P < 1.29 × 10-10 for each model) and yielded the highest-performing model overall (Dice coefficients of 94.74% and 96.71% for the BigCat and CaDIS datasets, respectively). In performance comparisons, the AWTFE consistently outperformed other feature extraction methods in enhancing model performance. In addition, the proposed AWTFE method significantly improved pupil recognition performance by up to 2.87% in particularly challenging phases of cataract surgery.

CatStep: Automated Cataract Surgical Phase Classification and Boundary Segmentation Leveraging Inflated 3D-Convolutional Neural Network Architectures and BigCat.

Objective: Accurate identification of surgical phases during cataract surgery is essential for improving surgical feedback and performance analysis. Time spent in each surgical phase is an indicator of performance, and segmenting out specific phases for further analysis can simplify providing both qualitative and quantitative feedback on surgical maneuvers. Study Design: Retrospective surgical video analysis. Subjects: One hundred ninety cataract surgical videos from the BigCat dataset (comprising nearly 4 million frames, each labeled with 1 of 11 nonoverlapping surgical phases). Methods: Four machine learning architectures were developed for segmentation of surgical phases. Models were trained using cataract surgical videos from the BigCat dataset. Main Outcome Measures: Models were evaluated using metrics applied to frame-by-frame output and, uniquely in this work, metrics applied to phase output. Results: The final model, CatStep, a combination of a temporally sensitive model (Inflated 3D Densenet) and a spatially sensitive model (Densenet169), achieved an F1-score of 0.91 and area under the receiver operating characteristic curve of 0.95. Phase-level metrics showed considerable boundary segmentation performance with a median absolute error of phase start and end time of just 0.3 seconds and 0.1 seconds, respectively, a segmental F1-score @70 of 0.94, an oversegmentation score of 0.89, and a segmental edit score of 0.92. Conclusion: This study demonstrates the feasibility of high-performance automated surgical phase identification for cataract surgery and highlights the potential for improved surgical feedback and performance analysis. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.