Optical Coherence Tomography Angiography (OCT-A) Quantitative Assessment of Choriocapillaris Blood Flow in Central Serous Chorioretinopathy (CSC)
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Central Serous Chorioretinopathy
- Sponsor
- Hospices Civils de Lyon
- Enrollment
- 120
- Primary Endpoint
- Total number average individual area of flow signal voids
- Status
- Completed
- Last Updated
- 6 years ago
Overview
Brief Summary
Optical Coherence Tomography Angiography (OCT-A) is a noninvasive imaging technique that allows one to see blood vessels in the retina. The investigating team used this approach in patients with acute, recurrent and persistent subtypes of Central Serous Chorioretinopathy (CSC) to check for possible Choriocapillaris hypoperfusion. The presence or absence of these microvascular changes was explored in both eyes of the patients and compared to a control group of healthy volunteers. The possibility of a correlation between Choriocapillaris flow deficits, age and spontaneous resolution of serous retinal detachment was also evaluated. This study was conducted in an effort to improve one's understanding of this disease and other pachychoroid disorders.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Patients with acute, recurrent or persistent forms of central serous chorioretinopathy
Exclusion Criteria
- •Patients with chronic central serous chorioretinopathy were not eligible for inclusion
Outcomes
Primary Outcomes
Total number average individual area of flow signal voids
Time Frame: 2 months
3x3 Optical Coherence Tomography Angiography (OCT-A) images on choriocapillaris slab were exported from the Angioplex software and then imported into the open-source Fiji software. Each image was binarized in black and white pixels. Thresholded areas greater than or equal to 1 white pixel were considered as flow signal voids
Total area of flow signal voids
Time Frame: 2 months
3x3 Optical Coherence Tomography Angiography (OCT-A) images on choriocapillaris slab were exported from the Angioplex software and then imported into the open-source Fiji software. Each image was binarized in black and white pixels. Thresholded areas greater than or equal to 1 white pixel were considered as flow signal voids