The intended purpose of the investigational device in the study is the correction of myopia and myopia with astigmatism in the CE (Conformité Européene) approved range and optimized for presbyopic patients using the treatment option HiSMILE, installed on the VisuMax femtosecond laser.

开始日期2023-10-13

申办/合作机构

London Vision Clinic Ltd.

NCT03473847 / SuspendedN/A

Repeatability and Reproducibility of Carl Zeiss Meditec Cirrus HD OCT 5000, Optovue RTVue OCT, CSO MS-39 OCT and ArcScan Insight 100 Very High-frequency Digital Ultrasound and Comparison Between Devices

The purpose of this study is to evaluate the repeatability and reproducibility of corneal, epithelial, and LASIK flap thickness using the Carl Zeiss Meditec Cirrus HD OCT 5000, Optovue RTVue OCT, CSO MS-39 OCT, and ArcScan Insight 100 very high-frequency digital ultrasound arc-scanner.

开始日期2022-09-01

申办/合作机构

London Vision Clinic Ltd.

[+1]

NCT03841253 / Unknown statusN/A

Treatment of Vision Disturbances Due to Corneal Irregularities by Trans-epithelial Optical Phototherapeutic Keratectomy (TE-oPTK)

This study sets out to evaluate the EpiMaster application software for use in predicting the refractive change induced by a trans-epithelial phototherapeutic keratectomy (TE-PTK) procedure in eyes with irregularly irregular astigmatism. If validation criteria are met during the observational phase, the software refractive prediction will be used to plan the refractive correction in TE-PTK treatments.

开始日期2019-08-01

申办/合作机构

London Vision Clinic Ltd.

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2024-10-01·British Journal of Ophthalmology

Creating realistic anterior segment optical coherence tomography images using generative adversarial networks

Article

作者: Abou Mrad, Anthony ; Haykal, Michèle ; Archer, Timothy J ; Amescua, Guillermo ; Reinstein, Dan Z ; Assaf, Jad F ; Zakka, Cyril ; Lamah, Elsa ; Yammine, Jeffrey ; Awwad, Shady T

AimsTo develop a generative adversarial network (GAN) capable of generating realistic high-resolution anterior segment optical coherence tomography (AS-OCT) images.MethodsThis study included 142 628 AS-OCT B-scans from the American University of Beirut Medical Center. The Style and WAvelet based GAN architecture was trained to generate realistic AS-OCT images and was evaluated through the Fréchet Inception Distance (FID) Score and a blinded assessment by three refractive surgeons who were asked to distinguish between real and generated images. To assess the suitability of the generated images for machine learning tasks, a convolutional neural network (CNN) was trained using a dataset of real and generated images over a classification task. The generated AS-OCT images were then upsampled using an enhanced super-resolution GAN (ESRGAN) to achieve high resolution.ResultsThe generated images exhibited visual and quantitative similarity to real AS-OCT images. Quantitative similarity assessed using FID scored an average of 6.32. Surgeons scored 51.7% in identifying real versus generated images which was not significantly better than chance (p value >0.3). The CNN accuracy improved from 78% to 100% when synthetic images were added to the dataset. The ESRGAN upsampled images were objectively more realistic and accurate compared with traditional upsampling techniques by scoring a lower Learned Perceptual Image Patch Similarity of 0.0905 compared with 0.4244 of bicubic interpolation.ConclusionsThis study successfully developed and leveraged GANs capable of generating high-definition synthetic AS-OCT images that are realistic and suitable for machine learning and image analysis tasks.

2024-03-01·Current Opinion in Ophthalmology

A review of posterior chamber phakic intraocular lenses

Review

作者: Archer, Timothy J. ; Gupta, Ruchi ; Reinstein, Dan Z. ; Potter, Joseph G. ; MacGregor, Cheryl

Purpose of reviewPosterior chamber phakic intraocular lenses (pIOLs) are increasing in popularity as a viable alternative to laser refractive surgery. The purpose of this review is to evaluate the recent updates to pIOLs and to assess the advancements and safety of the procedure.Recent findingsAccurate lens sizing is the key determinant to suitable vault prediction, advancements to sizing formulae including the use of very high frequency (VHF) digital ultrasound and the application of artificial intelligence and machine learning has led to improved vault prediction and safety. The introduction of the central aquaport has been shown to reduce the formation of cataract and is now adopted in most myopic pIOLs. Recently published studies have demonstrated that pIOLs have an excellent safety profile with no increased risk of retinal detachment or endothelial cell loss. Advancements have led to the introduction of extended depth of focus pIOLs for the correction of presbyopia, further research is required to evaluate the efficacy of new lens designs.SummarypIOL surgery is experiencing traction with improved lens design and increased lenses choices such as larger optical zone and presbyopic options. Accuracy of implantable collamer lens sizing is paramount to the safety and clinical outcomes, greater predictability is likely to encourage more posterior chamber pIOL users due to fewer sizing related complications.

2023-09-01·American journal of ophthalmology

Deep Learning-Based Estimation of Implantable Collamer Lens Vault Using Optical Coherence Tomography.

Article

作者: Awwad, Shady T ; Reinstein, Dan Z ; Arbelaez, Juan G ; Ibrahim, Perla ; Choufani, Mathieu ; Boufadel, Peter ; Archer, Timothy ; Assaf, Jad F ; Zakka, Cyril

PURPOSETo develop and validate a deep learning neural network for automated measurement of implantable collamer lens (ICL) vault using anterior segment optical coherence tomography (AS-OCT).DESIGNCross-sectional retrospective study.METHODSA total of 2647 AS-OCT scans were used from 139 eyes of 82 subjects who underwent ICL surgery in 3 different centers. Using transfer learning, a deep learning network was trained and validated for estimating the ICL vault on OCT. A trained operator separately reviewed all OCT scans and measured the central vault using a built-in caliper tool. The model was then separately tested on 191 scans. A Bland-Altman plot was constructed and the mean absolute percentage error (MAPE), mean absolute error (MAE), root mean squared error (RMSE), Pearson correlation coefficient (r), and determination coefficient (R²) were calculated to evaluate the strength and validity of the model.RESULTSOn the test set, the model achieved a MAPE of 3.42%, an MAE of 15.82 µm, a RMSE of 18.85 µm, a Pearson correlation coefficient r of +0.98 (P < .00001), and a coefficient of determination R² of +0.96. There was no significant difference between the vaults of the test set labeled by the technician vs those estimated by the model: 478 ± 95 µm vs 475 ± 97 µm, respectively, P = .064).CONCLUSIONSUsing transfer learning, our deep learning neural network was able to accurately compute the ICL vault from AS-OCT scans, overcoming the limitations of an imbalanced data set and limited training data. Such an algorithm can assist the postoperative assessment in ICL surgery.

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