Auto-aligned OCT for Eye Disorders

Overseen By Michelle N McCall, MCAPM, BA

Age: Any Age

Sex: Any

Trial Phase: Academic

Sponsor: Duke University

Disqualifiers: Pregnancy, Corneal opacity, Cataract, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 4

50 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

The goal of the current study is to conduct a pilot study to test a new version of the handheld OCT device capable of auto-alignment to image the retina in adult volunteers, and adult and pediatric patients in clinic.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It is best to discuss this with the study team or your healthcare provider.

Is Auto-aligned OCT safe for use in humans?

A study on the second-generation frequency-domain optical coherence tomography (FD-OCT) system assessed its safety, indicating that this type of OCT technology is generally safe for use in humans. ^{1 2 3 4 5}

How does the Auto-aligned OCT treatment differ from other treatments for eye disorders?

Auto-aligned OCT is unique because it uses advanced imaging techniques to automatically align and register images from different devices, providing more accurate and comprehensive information about the eye's structure. This approach enhances the precision of diagnosis and monitoring compared to traditional OCT methods, which may not integrate data from multiple sources as effectively. ^{6 7 8 9 10}

What data supports the effectiveness of the treatment Auto-aligned OCT for eye disorders?

Research shows that aligning and averaging multiple OCT scans can improve the quality of retinal images, making it easier to diagnose and monitor eye conditions. This suggests that Auto-aligned OCT, which likely uses similar techniques, could be effective in providing clearer images for better eye disorder management. ^{2 8 11 12 13}

Who Is on the Research Team?

Xi Chen, MD, PhD

Principal Investigator

Duke University

Are You a Good Fit for This Trial?

This trial is for both adults and children with various eye conditions such as Purtscher Retinopathy, optic nerve issues, neuro-ophthalmological disorders, glaucoma, and other retinal diseases. It aims to include volunteers who can undergo imaging with a new handheld device in a clinical setting.

Exclusion Criteria

Group 1: Healthy adult volunteers must not be students or employees under direct supervision of the investigators, must not have prior problems with pupil dilation, and pregnant women receiving dilating drops are excluded

I don't have any health issues that prevent eye exams or imaging.

My child can undergo an eye exam and does not have conditions like corneal opacity or cataract.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Imaging Sessions

Participants undergo handheld OCT imaging to assess retinal microanatomy and thickness

2 years

Up to 4 single imaging sessions at clinical visits

Follow-up

Participants are monitored for any changes in retinal microanatomy and thickness

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Auto-aligned OCT

Trial Overview The study is testing an advanced version of a handheld OCT (Optical Coherence Tomography) device that automatically aligns itself to capture images of the retina. This pilot study will assess its effectiveness in real-world clinic settings on adult and pediatric patients.

How Is the Trial Designed?

Group I: Group 3: Pediatric patients in ophthalmology clinics Experimental Treatment 1 Intervention

Minor participants recruited from the patient population of Duke Eye Center undergoing clinical examination (n=10)

Group II: Group 2: Adult patients in ophthalmology clinics Experimental Treatment 1 Intervention

Adult participants recruited from the patient population of Duke Eye Center undergoing clinical examination (n=20)

Group III: Group 1: Healthy adult volunteers Experimental Treatment 1 Intervention

Healthy adult volunteers recruited from the patient population, students or employees of Duke University or Duke Eye Center (n=20)

Who Is Running the Clinical Trial?

Duke University

Lead Sponsor

Trials

2,495

Recruited

5,912,000+

National Institutes of Health (NIH)

Collaborator

Trials

2,896

Recruited

8,053,000+

National Eye Institute (NEI)

Collaborator

Trials

572

Recruited

1,320,000+

Citations

1. England pubmed.ncbi.nlm.nih.gov

Enhanced optical coherence tomography imaging by multiple scan averaging. [2022]

2. China pubmed.ncbi.nlm.nih.gov

Helvacioglu reproducibility index: a new algorithm to evaluate the effects of misalignments on the measurements of retinal nerve fiber layer by spectral-domain OCT. [2022]

3. United States pubmed.ncbi.nlm.nih.gov

Enhancing the signal-to-noise ratio in ophthalmic optical coherence tomography by image registration--method and clinical examples. [2022]

4. United States pubmed.ncbi.nlm.nih.gov

Segmentation error in Stratus optical coherence tomography for neovascular age-related macular degeneration. [2009]

5. Germany pubmed.ncbi.nlm.nih.gov

Self-examination low-cost full-field OCT (SELFF-OCT) for patients with various macular diseases. [2023]

6. Brazil pubmed.ncbi.nlm.nih.gov

Repeatability and reproducibility of automatic segmentation of retinal layers in healthy subjects using Spectralis optical coherence tomography. [2018]

7. United States pubmed.ncbi.nlm.nih.gov

Feasibility and safety of the second-generation, frequency domain optical coherence tomography (FD-OCT): a multicenter study. [2016]

8. Germany pubmed.ncbi.nlm.nih.gov

Motion artefact correction in retinal optical coherence tomography using local symmetry. [2019]

9. Germany pubmed.ncbi.nlm.nih.gov

Prevalences of segmentation errors and motion artifacts in OCT-angiography differ among retinal diseases. [2022]

10. United States pubmed.ncbi.nlm.nih.gov

Training Deep Learning Models to Work on Multiple Devices by Cross-Domain Learning with No Additional Annotations. [2023]

11. United States pubmed.ncbi.nlm.nih.gov

Automated inter-device 3D OCT image registration using deep learning and retinal layer segmentation. [2023]

12. Switzerland pubmed.ncbi.nlm.nih.gov

Agreement between time-domain and spectral-domain optical coherence tomography in the assessment of macular thickness in patients with idiopathic macular telangiectasia type 2. [2014]

13. United States pubmed.ncbi.nlm.nih.gov

Integrated adaptive optics optical coherence tomography and adaptive optics scanning laser ophthalmoscope system for simultaneous cellular resolution in vivo retinal imaging. [2021]