Comparison of visual performance between diffractive bifocal and diffractive trifocal intraocular lenses.

To evaluate the visual performance of a diffractive bifocal intraocular lens (IOL) with + 4.0 D near addition (ZMB00) and a diffractive trifocal IOL with + 2.17 D and + 3.25 D near addition (AcrySof IQ PanOptix TFNT00), we investigated the 10-week postoperative parameters after cataract surgery in which ZMB00 or TFNT00 lenses were implanted bilaterally from 2011 to 2020 (with a 3-month interval between implantation of the right and left lenses). The study included 1448 eyes of 724 patients. The diffractive bifocal group comprised 1326 eyes of 663 patients (aged 67.0 ± 7.8 years; females/males, 518/145), and the diffractive trifocal group comprised 122 eyes of 61 patients (aged 66.6 ± 7.3 years; females/males, 35/26). A linear mixed-effects model using data for both eyes, with strict adjustments for sex, age, subjective refraction spherical equivalent, subjective refraction cylinder, corneal astigmatism, axial length, corneal higher-order aberrations, and pupil diameter, ensured statistical validity. Uncorrected near visual acuity and higher-order aberrations (ocular/internal, scaled to a pupil size of 4 mm) (Wavefront_4mm_postoperative_Ocular/Internal_Spherical) were significantly better in the bifocal group (p < 0.00068, Wald test). Uncorrected intermediate visual acuity, contrast sensitivity (6.3/4.0/2.5/1.6/1.0/0.7 degrees), and contrast sensitivity with glare (4.0/1.6/1.0/0.7 degrees) were significantly better in the trifocal group (p < 0.00068, Wald test).

Using artificial intelligence to improve human performance: efficient retinal disease detection training with synthetic images.

BACKGROUND: Artificial intelligence (AI) in medical imaging diagnostics has huge potential, but human judgement is still indispensable. We propose an AI-aided teaching method that leverages generative AI to train students on many images while preserving patient privacy. METHODS: A web-based course was designed using 600 synthetic ultra-widefield (UWF) retinal images to teach students to detect disease in these images. The images were generated by stable diffusion, a large generative foundation model, which we fine-tuned with 6285 real UWF images from six categories: five retinal diseases (age-related macular degeneration, glaucoma, diabetic retinopathy, retinal detachment and retinal vein occlusion) and normal. 161 trainee orthoptists took the course. They were evaluated with two tests: one consisting of UWF images and another of standard field (SF) images, which the students had not encountered in the course. Both tests contained 120 real patient images, 20 per category. The students took both tests once before and after training, with a cool-off period in between. RESULTS: On average, students completed the course in 53 min, significantly improving their diagnostic accuracy. For UWF images, student accuracy increased from 43.6% to 74.1% (p<0.0001 by paired t-test), nearly matching the previously published state-of-the-art AI model's accuracy of 73.3%. For SF images, student accuracy rose from 42.7% to 68.7% (p<0.0001), surpassing the state-of-the-art AI model's 40%. CONCLUSION: Synthetic images can be used effectively in medical education. We also found that humans are more robust to novel situations than AI models, thus showcasing human judgement's essential role in medical diagnosis.

Revolutionizing Patient Monitoring in Age-Related Macular Degeneration: A Comparative Study on the Necessity and Efficiency of the AMD VIEWER.

(1) Background: Age-related Macular Degeneration (AMD) is a critical condition leading to blindness, necessitating lifelong clinic visits for management, albeit with existing challenges in monitoring its long-term progression. This study introduced and assessed an innovative tool, the AMD long-term Information Viewer (AMD VIEWER), designed to offer a comprehensive display of crucial medical data-including visual acuity, central retinal thickness, macular volume, vitreous injection treatment history, and Optical Coherent Tomography (OCT) images-across an individual eye's entire treatment course. (2) Methods: By analyzing visit frequencies of patients with a history of invasive AMD treatment, a comparative examination between a Dropout group and an Active group underscored the clinical importance of regular visits, particularly highlighting better treatment outcomes and maintained visual acuity in the Active group. (3) Results: The efficiency of AMD VIEWER was proven by comparing it to manual data input by optometrists, showing significantly faster data display with no errors, unlike the time-consuming and error-prone manual entries. Furthermore, an elicited Net Promoter Score (NPS) of 70 from 10 ophthalmologists strongly endorsed AMD VIEWER's practical utility. (4) Conclusions: This study underscores the importance of regular clinic visits for AMD patients. It suggests the AMD VIEWER as an effective tool for improving treatment data management and display.

Comparison of visual performance between bifocal and extended-depth-of-focus intraocular lenses.

We compared the visual performance of a bifocal intraocular lens (IOL) (ZMB00) and an extended-depth-of-focus (EDOF) IOL (ZXR00V) by evaluating postoperative parameters at 10 weeks after the last surgery in cataract patients who underwent bilateral ZMB00 or ZXR00V implantation between 2011 and 2020. The right and left lenses were implanted within 3 months of each other. The study enrolled 1536 eyes of 768 patients; the ZMB00 group comprised 1326 eyes of 663 patients (age: 67.0 ± 7.8 years; female/male, 518/145), and the ZXR00V group comprised 210 eyes of 105 patients (age: 67.8 ± 6.9 years; female/male, 39/66). A linear mixed-effects model using data for both eyes, with strict adjustments for sex, age, subjective refraction spherical equivalent, subjective refraction cylinder, corneal astigmatism, axial length, corneal higher-order aberrations and pupil diameter, ensured statistical validity. Uncorrected near visual acuity, corrected near visual acuity, and near spectacle independence were significantly better in the ZMB00 group (p<0.00068, Wald test) than in the ZXR00V group. Contrast sensitivity (visual angle of the test target: 4.0°/2.5°/1.6°/1.0°/0.7°) and contrast sensitivity with glare (4.0°/2.5°/1.6°/1.0°/0.7°) were significantly better in the ZXR00V group (p<0.00068, Wald test) than in the ZMB00 group. Uncorrected intermediate visual acuity, contrast sensitivity with glare (6.3°), and 25-item National Eye Institute Visual Function Questionnaire (VFQ-25) scores for General Vision were slightly but significantly better in the ZXR00V group than in the ZMB00 group (p<0.05, Wald test). At high-performance levels, the two IOL groups had different characteristics regarding various visual performance parameters.

Training data size and predication errors in the use of machine-learning assisted intraocular lens power calculation.

This retrospective study examined the effect of the size of training data on the accuracy of machine learning-assisted SRK/T power calculation. Clinical records of 4800 eyes of 4800 Japanese patients with intraocular lenses (IOLs) were reviewed. A support vector regressor (SVR) was used for refining the SRK/T formula, and dataset sizes for training and evaluation were reduced from full to 1/64. The prediction errors from the postoperative refractions were calculated, and the proportion within ± 0.25 D, ± 0.50 D, and ± 1.00 D of errors were compared with those using full data. The influence of the difference in A-constant was also evaluated. Prediction errors within ± 0.50 D in the use of full data were obtained with the dataset of ≥ 150 eyes (P = 0.016), whereas the datasets of ≥ 300 eyes were required for the error within ± 0.25 D (P < 0.030). The prediction errors did not alter with the A-constant values among IOLs with open-loop haptics, except for IOLs with plated haptics. In conclusion, the accuracy of SVR-assisted SRK/T could be achieved with the training dataset of ≥ 150 eyes for the Japanese population, and the calculation was versatile for any open-looped IOLs.

Comparative visual performance of diffractive bifocal and rotationally asymmetric refractive intraocular lenses.

We compared the visual performance of a diffractive bifocal intraocular lens (IOL) with + 4.0 D near addition (ZMB00 [Johnson & Johnson Surgical Vision]) and a rotationally asymmetric refractive IOL with + 1.5 D near addition (LS-313 MF15 [Teleon Surgical BV]) 10 weeks after cataract patients' last surgery for bilateral ZMB00 or LS-313 MF15 implantation between 2011 and 2020, with the lenses of each eye implanted within 3 months of each other. The ZMB00 and LS-313 MF15 groups comprised 1326 eyes of 663 patients (age: 67.0 ± 7.8 years; females/males, 518/145) and 448 eyes of 224 patients (73.6 ± 7.0 years; females/males, 125/99), respectively. A linear mixed-effects model using data for both eyes, with strict adjustments for sex, age, subjective refraction spherical equivalent, subjective refraction cylinder, corneal astigmatism, axial length, corneal higher-order aberrations, and pupil diameter, ensured statistical validity. Compared to LS-313 MF15, ZMB00 achieved significantly superior uncorrected near visual acuity, reduced higher-order aberrations (ocular/internal, scaled to a 4-mm pupil; Wavefront_4_post_Ocular_Total Higher-Order Aberration/Third/Fourth/Trefoil/Coma/Tetrafoil/Spherical, Wavefront_4_post_Internal_Astigmatism/Total Higher-Order Aberration/Third/Trefoil/Coma/Tetrafoil/Spherical), and superior distance and near spectacle independence (p < 0.00068, Wald test). Contrast sensitivity, measured without (visual angle of the test target: 6.3°/4.0°/2.5°/1.6°/1.0°/0.7°) or with glare (4.0°/2.5°/1.6°/1.0°/0.7°), was significantly better in the LS-313 MF15 than the ZMB00 group (p < 0.00068, Wald test).

Machine learning adaptation of intraocular lens power calculation for a patient group.

BACKGROUND: To examine the effectiveness of the use of machine learning for adapting an intraocular lens (IOL) power calculation for a patient group. METHODS: In this retrospective study, the clinical records of 1,611 eyes of 1,169 Japanese patients who received a single model of monofocal IOL (SN60WF, Alcon) at Miyata Eye Hospital were reviewed and analyzed. Using biometric metrics and postoperative refractions of 1211 eyes of 769 patients, constants of the SRK/T and Haigis formulas were optimized. The SRK/T formula was adapted using a support vector regressor. Prediction errors in the use of adapted formulas as well as the SRK/T, Haigis, Hill-RBF and Barrett Universal II formulas were evaluated with data from 395 eyes of 395 distinct patients. Mean prediction errors, median absolute errors, and percentages of eyes within ± 0.25 D, ± 0.50 D, and ± 1.00 D, and over + 0.50 D of errors were compared among formulas. RESULTS: The mean prediction errors in the use of the SRT/K and adapted formulas were smaller than the use of other formulas (P < 0.001). In the absolute errors, the Hill-RBF and adapted methods were better than others. The performance of the Barrett Universal II was not better than the others for the patient group. There were the least eyes with hyperopic refractive errors (16.5%) in the use of the adapted formula. CONCLUSIONS: Adapting IOL power calculations using machine learning technology with data from a particular patient group was effective and promising.

Use of a Machine Learning Method in Predicting Refraction after Cataract Surgery.

The present study aims to describe the use of machine learning (ML) in predicting the occurrence of postoperative refraction after cataract surgery and compares the accuracy of this method to conventional intraocular lens (IOL) power calculation formulas. In total, 3331 eyes from 2010 patients were assessed. The objects were divided into training data and test data. The constants for the IOL power calculation formulas and model training for ML were optimized using training data. Then, the occurrence of postoperative refraction was predicted using conventional formulas, or ML models were calculated using the test data. We evaluated the SRK/T formula, Haigis formula, Holladay 1 formula, Hoffer Q formula, and Barrett Universal II formula (BU-II); similar to ML methods, we assessed support vector regression (SVR), random forest regression (RFR), gradient boosting regression (GBR), and neural network (NN). Among the conventional formulas, BU-II had the lowest mean and median absolute error of prediction. Therefore, we compared the accuracy of our method with that of BU-II. The absolute errors of some ML methods were lower than those of BU-II. However, no statistically significant difference was observed. Thus, the accuracy of our method was not inferior to that of BU-II.

Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics.

PURPOSE: To compare the achieved vault using the conventional manufacturer's nomogram and the predicted vault using machine learning, in a large cohort of eyes undergoing posterior chamber phakic intraocular lens (EVO implantable collamer lens [ICL]; STAAR Surgical) implantation. DESIGN: Reliability and validity assessment and comparison. METHODS: Our study comprised a total of 1,745 eyes of 1,745 consecutive patients (mean age ± standard deviation, 26.2 ± 6.8 years) undergoing ICL implantation. At 1 month postoperatively, we quantitatively measured the actual vault, and compared it with the predicted vault using machine leaning of anterior segment optical coherence tomography metrics. RESULTS: All machine learning methods, such as support vector regressor (SVR), gradient boost regressor (GBR), random forest regressor (RFR), and linear regressor (LR), showed significantly less mean absolute error and higher percentages of eyes within 50-200 µm of the targeted ICL vault than the conventional nomogram (P < .001). The RFR provided the lowest mean absolute errors and the highest percentages of eyes within 50 to 200 µm, followed by the GBR, the LR, and the SVR (P < .01). CONCLUSIONS: Machine learning of the preoperative anterior segment optical coherence tomography metrics, especially the RFR, provided significantly higher predictability of the ICL vault than the conventional manufacturer's nomogram, suggesting that it will become an aid for predicting the ICL vault and subsequently selecting the proper ICL size in daily practice.

Author Correction: Comparison of visual performance between monofocal and multifocal intraocular lenses of the same material and basic design.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comparison of visual performance between monofocal and multifocal intraocular lenses of the same material and basic design.

To compare the visual performance of a monofocal intraocular lens (IOL) (ZCB00) and a multifocal IOL (ZMB00) of the same material and basic design, we evaluated postoperative parameters at 10 weeks after the last surgery in cataract patients who underwent bilateral ZCB00 or ZMB00 implantation from December 13, 2010, to July 29, 2019, with the right and left lenses implanted within 3 months of each other. The study enrolled 2,230 eyes of 1,115 patients. The monofocal group comprised 904 eyes of 452 patients (72.3 ± 6.8 years; females/males, 268/184), and the multifocal group comprised 1,326 eyes of 663 patients (67.0 ± 7.8 years; females/males, 518/145). Contrast sensitivity (4.0/2.5/1.6/1.0/0.7 degrees), contrast sensitivity with glare (1.6/1.0/0.7 degrees), and the VFQ-25 score for driving at night were significantly better in the monofocal group (p < 0.00068, Wald test). Uncorrected intermediate/near visual acuity and near spectacle independence were significantly better in the multifocal group (p < 0.00068, Wald test). The two IOL groups had different characteristics in terms of contrast sensitivity, night-time driving, uncorrected intermediate/near visual acuity and near spectacle independence.

Real-Time Extraction of Important Surgical Phases in Cataract Surgery Videos.

The present study aimed to conduct a real-time automatic analysis of two important surgical phases, which are continuous curvilinear capsulorrhexis (CCC), nuclear extraction, and three other surgical phases of cataract surgery using artificial intelligence technology. A total of 303 cases of cataract surgery registered in the clinical database of the Ophthalmology Department of Tsukazaki Hospital were used as a dataset. Surgical videos were downsampled to a resolution of 299 × 168 at 1 FPS to image each frame. Next, based on the start and end times of each surgical phase recorded by an ophthalmologist, the obtained images were labeled correctly. Using the data, a neural network model, known as InceptionV3, was developed to identify the given surgical phase for each image. Then, the obtained images were processed in chronological order using the neural network model, where the moving average of the output result of five consecutive images was derived. The class with the maximum output value was defined as the surgical phase. For each surgical phase, the time at which a phase was first identified was defined as the start time, and the time at which a phase was last identified was defined as the end time. The performance was evaluated by finding the mean absolute error between the start and end times of each important phase recorded by the ophthalmologist as well as the start and end times determined by the model. The correct response rate of the cataract surgical phase classification was 90.7% for CCC, 94.5% for nuclear extraction, and 97.9% for other phases, with a mean correct response rate of 96.5%. The errors between each phase's start and end times recorded by the ophthalmologist and those determined by the neural network model were as follows: CCC's start and end times, 3.34 seconds and 4.43 seconds, respectively and nuclear extraction's start and end times, 7.21 seconds and 6.04 seconds, respectively, with a mean of 5.25 seconds. The neural network model used in this study was able to perform the classification of the surgical phase by only referring to the last 5 seconds of video images. Therefore, our method has performed like a real-time classification.

Comparison of visual performance of toric vs non-toric intraocular lenses with same material.

AIM: We compared the visual performance of toric intraocular lenses (IOLs) and non-toric IOLs made of the same material. PATIENTS AND MATERIALS: The subjects included patients implanted with either Acrysof IQ® toric IOLs (SN6AT3-9) or Acrysof IQ® IOLs (SN60WF) bilaterally. The toric group included 103 patients who were implanted with Acrysof IQ toric IOLs bilaterally. The non-toric group was a corneal astigmatism-matched control group and included 103 patients who were implanted with Acrysof IQ IOLs bilaterally. RESULTS: The uncorrected distance visual acuity was significantly better in the toric group, whereas the uncorrected 50 cm visual acuity was better in the non-toric group. There was no significant difference in contrast sensitivity (with and without glare) between both the groups. The rate of spectacle dependency for distance vision was significantly lower in the toric group. There were no significant differences between the two groups in all items of the postoperative quality-of-vision questionnaire (25-item Visual Function Questionnaire). CONCLUSION: The toric IOLs used in this study reduced spectacle dependency more than the non-toric IOLs and did not compromise the subjective visual function, but the uncorrected 50 cm vision was worse in toric IOL implanted eyes.

Repeatability of visual acuity testing using a psychometric function.

PURPOSE: To evaluate the repeatability of a new method of measurement of visual acuity by use of a psychometric function. METHODS: The visual acuity of 15 healthy adults was measured by use of a psychometric function (PFVA) and by use of a conventional method using a decimal visual acuity chart (DeVA). We performed two tests. To evaluate intra-rater reliability, a tester measured the visual acuity three times for each subject, and the intraclass correlation coefficients, ICC (1,1), were calculated for PFVA and DeVA. Next, to evaluate inter-rater reliability, three testers measured the visual acuity for one subject, and the ICC (2,1) were calculated for PFVA and DeVA. The PFVA and DeVA of five subjects with ocular diseases were also measured. RESULTS: In the evaluation of intra-rater reliability, the ICC (1,1) of the DeVA was 0.83 and the ICC (1,1) of the PFVA was 0.95. In the evaluation of inter-rater reliability, the ICC (2,1) of the DeVA was 0.88 and the ICC (2,1) of the PFVA was 0.93. In both tests the standard deviations of the PFVA were significantly lower than those of the DeVA. For four of the five subjects with ocular diseases, the PFVA was significantly improved by treatment. CONCLUSION: The repeatability of our method is better than that of the conventional method using a decimal visual acuity chart.

Morphologic characteristics of macular complications of a dome-shaped macula determined by swept-source optical coherence tomography.

PURPOSE: To investigate the morphologic characteristics of macular complications of dome-shaped maculas using swept-source optical coherence tomography (OCT). DESIGN: Retrospective observational case series. METHODS: Axial length measurements and swept-source OCT were performed in 49 highly myopic eyes (in 5 male and 30 female subjects) with dome-shaped maculas. We classified the dome patterns and measured the central retinal thickness, central choroidal thickness, central scleral thickness, and the macular bulge height, and assessed the associations of these parameters with macular complications. RESULTS: The central scleral thickness was significantly negatively correlated with age and the axial length. We classified the eyes into 3 groups: 6 with choroidal neovascularization (CNV group), 8 with retinal pigment epithelial detachment (PED group; 5 with serous retinal detachment), and 35 with no complications (no complications group). Nine eyes had a round dome and 40 had horizontally oriented oval-shaped domes. There were no significant differences in the frequency of macular complications between these patterns. The CNV group was significantly older and had a longer axial length than the other groups. The PED group had significantly larger values for both the central scleral thickness and bulge height than the other groups. The central choroidal thickness was significantly thinner in the CNV group than in the no complications group. CONCLUSION: A dome-shaped macula results from relative thickening of the macular sclera, and this may lead to PED. Thinning of the sclera owing to long-term changes and elongation of the axis may develop CNV and cause visual impairment.

Comparison of visual performance of multifocal intraocular lenses with same material monofocal intraocular lenses.

PURPOSE: To compare the visual performance of multifocal intraocular lenses (IOLs) and monofocal IOLs made of the same material. METHODS: The subjects included patients implanted with either Tecnis® monofocal IOLs (ZA9003 or ZCB00) or Tecnis® multifocal IOLs (ZMA00 or ZMB00) bilaterally. We conducted a retrospective study comparing the two types of IOLs. The multifocal group included 46 patients who were implanted with Tecnis® multifocal IOLs bilaterally. The monofocal group was an age- and sex-matched control group, and included 85 patients who were implanted with Tecnis® monofocal IOLs bilaterally. Lens opacity grading, the radius of corneal curvature, corneal astigmatism, axial length and the refractive status were measured preoperatively. Pupil size, ocular aberrometry, distance, intermediate and near visual acuity, contrast sensitivity with and without glare and the responses to a quality-of-vision questionnaire were evaluated pre- and postoperatively. RESULTS: The uncorrected near visual acuity was significantly better in the multifocal group, whereas both the corrected intermediate and near visual acuity were better in the monofocal group. Contrast sensitivity (with and without glare) was significantly better in the monofocal group. The rate of spectacle dependency was significantly lower in the multifocal group. There were no significant differences between the two groups regarding most items of the postoperative quality-of-vision questionnaire (VFQ-25), with the exception that the patients in the monofocal group reported fewer problems with nighttime driving. CONCLUSIONS: The multifocal IOLs used in this study reduced spectacle dependency more so than monofocal IOLs and did not compromise the subjective visual function, with the exception of nighttime driving.

Inhibition of glutamate-induced nitric oxide synthase activation by dopamine in cultured rat retinal neurons.

Previously, we showed that dopamine protects cultured retinal neurons from N-methyl-D-aspartate (NMDA) receptor mediated-glutamate excitotoxicity via dopamine D1 receptor. This study has demonstrated for the first time that nitric oxide synthase (NOS) plays a crucial role in dopamine-induced neuroprotection. Our patch clamp study has shown that dopamine does not affect the NMDA-induced whole cell current. Dopamine or SKF38393 (D1 receptor agonist) inhibited ionomycin (calcium ionophore)-induced toxicity, while dopamine did not affect S-nitrosocysteine (NO donor)-induced toxicity. Biochemical analysis on enzymatic activities has shown that dopamine or cAMP (which is generated through D1 receptor stimulation) inhibits glutamate induced-NOS activation. These results suggest that dopamine inhibits glutamate induced-NOS activation via D1 receptor, resulting in the protection of retinal neurons.

Mitochondrial ATP-sensitive potassium channel: a novel site for neuroprotection.

PURPOSE: It has been shown that bradykinin (BK) protects retinal neurons against glutamate excitotoxicity, but it was not clear how BK inhibits glutamate excitotoxicity. The purpose of this study was to investigate the effect of opening the mitochondrial adenosine triphosphate (ATP)-sensitive potassium (Mit K (ATP)) channel on glutamate excitotoxicity and the protective effect of BK using cultured retinal neurons. METHODS: Primary cultures were obtained from the retina of fetal rats (gestation days 17-19). Glutamate neurotoxicity was assessed by 10-minute exposure to 1 mM glutamate followed by 1-hour incubation in glutamate-free medium, using the trypan blue exclusion method. BK, diazoxide (the opener of the Mit K (ATP) channel), 5HD, and glibenclamide (blockers of the Mit K (ATP) channel) were applied simultaneously with glutamate. Mitochondrial membrane potential was measured as the ratio of 590:527 nm fluorescence of JC-1. RESULTS: Cell viability was markedly reduced by 10-minute exposure to 1 mM glutamate followed by 1-hour incubation in glutamate-free medium, and glutamate induced mitochondrial depolarization of retinal neurons. BK and diazoxide protected retinal neurons against glutamate excitotoxicity and inhibited glutamate-induced mitochondrial depolarization. These actions of BK and diazoxide were inhibited by the coapplication of 5HD and glibenclamide. Furthermore, diazoxide inhibited the sodium nitroprusside (SNP, NO donor) toxicity, but did not inhibit the 3-morpholinosydnonimine (SIN-1, NO, and superoxide donor) toxicity. CONCLUSIONS: These results suggest that BK and diazoxide protect retinal neurons against glutamate excitotoxicity by opening the Mit K (ATP) channel. It is suggested that opening of the Mit K (ATP) channel inhibited glutamate-induced generation of superoxide.