Skip to main content
OpenTrials
Enrolling by Invitation

NCT Number: NCT07378891

Artificial-Intelligence-based Early Detection of Diabetic Retinopathy (FUNDUS AI)

Examination of individuals with prediabetes and established diabetes for early signs of diabetic retinopathy.

Enrolling by Invitation

Interested in participating?

Request Info

Key information

Conditions

Diabetes (DM) Cardiovascular Diseases Diabetes Complications Diabetes Mellitus Diabetic Angiopathies Diabetic Retinopathy Endocrine System Diseases Eye Diseases Glucose Metabolism Disorders Metabolic Diseases Nutritional and Metabolic Diseases PreDiabetes Prediabetic State Retinal Diseases Vascular Diseases

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Observational

Primary location

University Hospital Tuebingen, Dep. Diabetology

Tübingen, 72076, Germany

About this study

Fundus images are acquired and analyzed using an AI algorithm. The fundus images are captured using two devices: a stationary fundus camera (CenterVue DRSplus) and the Optomed Aurora IQ handheld fundus camera. Retinal images are examined using AI-based image analysis.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Voluntary adults
  • Aged between 18 and 80 years
  • Understanding of the study explanations and instructions
  • Prediabetes (defined by elevated fasting glucose 100-125 mg/dL and/or 2-hour glucose in the oral glucose tolerance test of 140-199 mg/dL and/or HbA1c of 5.7-6.4%)
  • manifest diabetes (all types of diabetes according to Ahlqvist)

Exclusion criteria

  • participants unable to give consent
  • Those who do not agree to be informed about incidentally detected pathological findings
  • Uncontrolled arterial hypertension (Stage III) despite multiple antihypertensive medications
  • Eye diseases that impair the interpretability of the fundus examination

Treatment and study plan

Primary outcomes

  1. Assessment of retinal changes

    Time frame: Day 1

    Assessment of retinal changes in individuals with prediabetes and diabetes, quantified using an AI algorithm.

Secondary outcomes

  1. Image quality and comparison of the fundus cameras

    Time frame: Day 1

    The automatically assessed image quality and the comparison of stationary and mobile fundus cameras

  2. Influence of clinical parameters on retinal vascular changes

    Time frame: Day 1

    Influence of clinical parameters such as anthropometric measurements (WHR, blood pressure, BMI) and laboratory parameters of glucose and lipid metabolism on retinal vascular changes

  3. Association of medications with the ocular fundus

    Time frame: Day 1

    Association of antidiabetic and lipid-lowering medications with the ocular fundus

Sponsors and collaborators

Lead sponsor

University Hospital Tuebingen

Other

Registry information

Official study title

Künstliche Intelligenz (KI)-gestützte Früherkennung Der Diabetischen Retinopathie (FUNDUS-KI)

Acronym: FUNDUS AI

Important dates

Study start
2025
Primary completion
2028
Study completion
2028
First posted
Jan 30, 2026
Registry last updated
Feb 10, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.