Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

OBJECTIVE: To assess the morphology of perifoveal capillary network with quantitative parameters in young patients with diabetes mellitus type I (DM I) using an algorithm. METHODS: Fifty-three images (33 eyes of 33 DM I patients and 20 eyes of 20 non-DM controls) were chosen retrospectively from the University Hospital of Heraklion digital fluorescein angiography database. An additional group consisting of patients with advanced DR abnormalities was included in our analysis to investigate whether our method detects alterations when they are present. The developed algorithm allows the user to manually trace the perifoveal capillary network by selecting with the cursor in a 5° × 5° subimage field of the original image, including the foveal avascular zone (FAZ), and provides measurements of the capillary density, the branch point density, and the FAZ surface in this subarea. RESULTS: The age in the patient group was 19 ± 5 years; age was 21 ± 8 years for the control group. Patients had a history of DM I for 11 ± 5 years. The mapping revealed a perifoveal capillary density of 2.494 ± 0.559 deg-1 in the DM I group versus 2.974 ± 0.442 deg-1 in the control group (p = 0.005). The branch point density was 3.041 ± 0.919 branch points/deg2 and 3.613 ± 1.338 branch points/deg2 in each group, respectively (p = 0.128). The FAZ area was 0.216 ± 0.061 deg2 in the diabetic group and 0.208 ± 0.060 deg2 in the control group (p = 0.672). CONCLUSIONS: The selected quantitative parameters tend to increase or decrease in diabetic patients, in agreement with previous studies. Among the parameters, capillary density may represent the most sensitive metric for the detection of very early diabetic changes. Further improvement of the method could contribute to the development of an automated processing tool for capillary network quantitative assessment.

Original publication

DOI

10.1016/j.jcjo.2017.09.029

Type

Journal article

Journal

Can j ophthalmol

Publication Date

06/2018

Volume

53

Pages

199 - 206