OCT and OCT-A Deep Learning in Diabetic Patients Wiht Artificial Pancreas Device

Federico II University

Status: Completed

Conditions: Type 1 Diabetes Mellitus With Artificial Pancreas Device

Treatments: Device: hybrid artificial pancreas systems (CSII)

Study type: Observational

Funder types: Other

Identifiers

NCT05809843

2403/2023

Details and patient eligibility

About

This study evaluates the ability of deep learning to improve the knowledge about structural and vascular retinal changes in diabetic patients undergoing artificial pancreas device, using optical coherence tomography angiography.

Full description

hybrid artificial pancreas systems (CSII) are able to adjust the type 1 diabetic patient's glycemic levels with insulin doses appropriate to the patient's blood glucose.

The optical coherence tomography angiography represents a novel and noninvasive diagnostic technique that allows a detailed and quantitative analysis of retinal and choriocapillary vascular features.

The study evaluates the changes in optical coherence tomography angiography features in diabetic patients undergoing artificial pancreas device, elaborating these data with artificial intelligence.

Enrollment: 11 patients

Sex: All

Ages: 18 to 80 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• • age older than 18 years

  • diagnosis of type 1 diabetes
  • treatment with artificial pancreas device
  • absence of previous ocular surgery and congenital eye diseases.
  • absence of errors of refraction
  • absence of lens opacities
  • absence of low-quality OCT and OCTA images

Exclusion criteria

• age younger than 18 years
• previous ocular surgery and congenital eye diseases
• errors of refraction
• lens opacities
• low-quality OCT and OCTA images

Trial design

11 participants in 2 patient groups

rype 1 diabetc patients with artificial pancreas device

Treatment:

Device: hybrid artificial pancreas systems (CSII)

healthy patients matched age and sex without diabetes and ocular disease