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Diabetic Retinopathy clinical trials

View clinical trials related to Diabetic Retinopathy.

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NCT ID: NCT05147701 Recruiting - Glaucoma Clinical Trials

Safety of Cultured Allogeneic Adult Umbilical Cord Derived Mesenchymal Stem Cells for Eye Diseases

Start date: February 1, 2022
Phase: Phase 1
Study type: Interventional

This trial will study the safety and efficacy of intravenous and sub-tenon delivery of cultured allogeneic adult umbilical cord derived mesenchymal stem cells for the treatment of Eye diseases

NCT ID: NCT05140304 Not yet recruiting - Clinical trials for Diabetic Retinopathy

Analysis of FAZ in Diabetic Retinopathy Using OCT Angiography

Start date: November 30, 2021
Phase: N/A
Study type: Interventional

Study and assessment of characteristic changes in foveal avascular zone during different stages of diabetic retinopathy using OCTA.

NCT ID: NCT05138029 Recruiting - Clinical trials for Diabetic Retinopathy

Study on Precision Treatment of Diabetic Retinopathy Macular Edema Guided by Real-time OCT During Operation

Start date: November 15, 2021
Phase: Phase 3
Study type: Interventional

Select Proliferative Proliferative diabetic retinopathy(PDR) patients who are planning to undergo vitrectomy for informed notification. After obtaining informed consent, vitrectomy will be performed. After hemorrhage is removed, the macular shape can be obtained through intraoperative optical coherence tomography (iOCT) real-time scanning. If the central Macular Thickness (CMT) of the patient is ≥250μm, random Enter the Anti-vascular endothelial growth factor (anti-VEGF) treatment group, the internal limiting membrane stripping group and the glucocorticoid treatment group for treatment, and compare the patients' visual acuity (1 day, 7 days, 1 month, 3 months, 6 months) and The thickness of the center of the macula, compare and observe its treatment effect.

NCT ID: NCT05135195 Completed - Glaucoma Clinical Trials

A Virtual Reality Platform Simulating Visual Impairment for Testing of Electronic Travel Aids and Performing Orientation and Mobility Training

Start date: October 24, 2021
Phase: N/A
Study type: Interventional

In this study, the study team utilize virtual reality (VR) to simulate visual impairments of different types and severity in healthy subjects. The platform implements three of the most widespread forms of visual impairment in the United States (US): age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma, each with three levels of severity, (mild, moderate, and severe). At present, glaucoma is further developed toward a multidimensional visual impairment simulation. The platform is utilized: i) to provide a safe, controllable, and repeatable set of environments for development and preliminary testing of electronic travel aids (ETAs) in a variety of conditions (i.e., using the ETA to navigate in the immersed environment); and ii) to equip blind and low vision (BVI) professionals, inclusive of orientation and mobility (O&M) instructors, with a controlled, tunable training platform for skill/capacity building, assessment, and refinement of O&M techniques, as well as visually impaired trainees with a safe and immersive environment to improve their O&M skills and learn novel techniques. Two sets of hypothesis-driven experiments are proposed to assess the feasibility of the platform with respect to these two objectives.

NCT ID: NCT05132660 Enrolling by invitation - Clinical trials for Diabetic Retinopathy

Treating Early Stage Diabetic Retinopathy

TESDR
Start date: July 1, 2022
Phase: Early Phase 1
Study type: Interventional

To determine if levodopa will slow the appearance of blood vessel changes in the eyes of patients with diabetes. Treatment will be started in patients with diabetes show delays in the electrical activity of the retina when measured non-invasively with a electroretinogram.

NCT ID: NCT05131451 Completed - Type 2 Diabetes Clinical Trials

ACCESS: AI for pediatriC diabetiC Eye examS Study

ACCESS
Start date: November 24, 2021
Phase: N/A
Study type: Interventional

The purpose of this study is to determine if providing in clinic point-of-care autonomous AI diabetic retinopathy exams improves screening rates compared to standard of care referral to an eye care provider, in a randomized control trial in a racially and ethnically diverse cohort of youth.

NCT ID: NCT05130385 Recruiting - Glaucoma Clinical Trials

High Resolution Optical Coherence Tomography

Start date: November 30, 2021
Phase:
Study type: Observational

Comparison of high-resolution optical coherence tomography (High-Res-OCT) to conventional imaging modalities for the diagnosis of eye diseases

NCT ID: NCT05112445 Active, not recruiting - Clinical trials for Diabetic Retinopathy

Retinal Ischemia Characterization in Diabetes - "RICHARD"

RICHARD
Start date: May 3, 2022
Phase:
Study type: Observational [Patient Registry]

Retinal ischemia characterization in diabetes - RICHARD

NCT ID: NCT05105620 Completed - Clinical trials for Diabetic Retinopathy

Deep Learning for Fluorescein Angiography and Optical Coherence Tomography Macular Thickness Map Image Translation

Start date: August 1, 2018
Phase:
Study type: Observational

Diabetic macular edema (DME) is one of the leading causes of visual impairment in patients with diabetes. Fluorescein angiography (FA) plays an important role in diabetic retinopathy (DR) staging and evaluation of retinal vasculature. However, FA is an invasive technique and does not permit the precise visualization of the retinal vasculature. Optical coherence tomography (OCT) is a non-invasive technique that has become popular in diagnosing and monitoring DR and its laser, medical, and surgical treatment. It provides a quantitative assessment of retinal thickness and location of edema in the macula. Automated OCT retinal thickness maps are routinely used in monitoring DME and its response to treatment. However, standard OCT provides only structural information and therefore does not delineate blood flow within the retinal vasculature. By combining the physiological information in FA with the structural information in the OCT, zones of leakage can be correlated to structural changes in the retina for better evaluation and monitoring of the response of DME to different treatment modalities. The occasional unavailability of either imaging modality may impair decision-making during the follow-up of patients with DME. The problem of medical data generation particularly images has been of great interest, and as such, it has been deeply studied in recent years especially with the advent of deep convolutional neural networks(DCNN), which are progressively becoming the standard approach in most machine learning tasks such as pattern recognition and image classification. Generative adversarial networks (GANs) are neural network models in which a generation and a discrimination networks are trained simultaneously. Integrated network performance effectively generates new plausible image samples. The aim of this work is to assess the efficacy of a GAN implementing pix2pix image translation for original FA to synthetic OCT color-coded macular thickness map image translation and the reverse (from original OCT color-coded macular thickness map to synthetic FA image translation).

NCT ID: NCT05079399 Recruiting - Clinical trials for Diabetic Retinopathy

Biomarker of Diabetic Retinopathy

Start date: January 1, 2022
Phase:
Study type: Observational

Diabetic retinopathy (DR) is a complication of diabetes in which blood vessels supplying blood to the back of the eye (retina) are dysfunctional. This can lead to an improper supply of oxygen and nutrients to the retinal tissue, or it may trigger the formation of new blood vessels in response to the oxygen/nutrient deficiency. Ultimately affecting the normal vision. There is no known marker that will provide information on the health status of retinal blood vessels. Using highly specialized cells in the blood, this study will try to discover a marker of DR.