Diabete MellitusNCT06541834
Predicting the Risk of Diabetic Neurodegenerative Disorders by Artificial Intelligence Tools Based on Retinal Imaging
An observational study of Diabete Mellitus and Cognitive Impairment, run by Ospedale San Raffaele at 1 site in Italy.
Trial summary
Diabetic Retinopathy (DR) is the most frequent complication of diabetes, and its presence and severity are related to the appearance of both micro and macrovascular events. Risk profiles have been suggested as a major direction for research in diabetes, based on non- invasive retinal imaging evaluations. Read more about this study
- Who is it for?
- Ages 45 years and older
- Conditions the study is for
- Diabete Mellitus, Cognitive Impairment
- What is being tested?
- Retinal imaging
- Type of treatment
- Medical device
- How many people
- 250 participants
- Where
- 1 siteItaly
- Study dates
- 30 Aug 2024to 30 Aug 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 45 years and older
- All sexes
- Adult, Older adult
Study population: Male or female >45 years old affected by type 2 diabetes.
Who may be able to join
- Male or female > 45 years-old;
- Diagnosis of type 2 DM;
- No previous treatment for diabetic retinopathy;
- Clear ocular media;
- Ability to communicate well with the Investigator and to understand and comply with the requirements of the study;
- Ability to provide written informed consent in accordance with institutional, local and national regulatory guidelines and to attend all study visits
Who cannot join
- Patients affected by other retinal disease than diabetic retinopathy;
- Presence of diabetic macular edema;
- Presence of proliferative diabetic retinopathy;
- Any media opacities, including corneal opacity, cataract formation and hemorrhage in the vitreous body, which may interfere with viewing by the laser surgeon of the target structures in the study eye(s). Subject requiring cataract surgery in the next 12 months must be excluded;
- Aphakic eye(s) with vitreous in the anterior chamber;
- Neovascular glaucoma;
Show all 19Show fewer
- Glaucoma caused by congenital angle anomalies;
- Open angle of less than 90º or extensive peripheral anterior and low synechia, present circumferentially around the corner;
- Glaucoma secondary to active uveitis;
- Any other ocular condition that would progress in the study period and confound visual acuity assessment a part from diabetic retinopathy;
- Presence of idiopathic or autoimmune-associated uveitis;
- Any ocular or systemic medication known to be toxic to the lens, retina or optic nerve;
- Any intra-ocular surgery on a qualifying eye within three months prior to entry in the study;
- Any prior thermal laser in the macula or intravitreal injections or panphotocoagulation;
- History of vitrectomy, filtering surgery, corneal transplant or retinal detachment surgery;
- Previous therapeutic radiation in the ocular region in either eye;
- Participation in an investigational drug, biologic, or device study within 6 months prior to baseline [Note: observational clinical studies solely involving over-the-counter vitamins, supplements, or diets are not exclusionary];
- Has a serious medical illness that will prevent the subject from performing study activities (including cardiac, hepatic, renal, respiratory, endocrinologic, neurologic, or hematologic disease) or, in the judgement of the Investigator, is likely to require surgical intervention or hospitalization at any point during the study;
- In the opinion of the Investigator, is unlikely to comply with the study protocol.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Riccardo Sacconi, MD, PhD contact
Italy1 site, 1 recruiting
- Recruiting
Ospedale San Raffaele
Milan, 20138
Riccardo Sacconi, MD, PhD, FEBO, sacconi.riccardo@hsr.it
About this study
Official title: Predicting the Risk of Diabetic Neurodegenerative Disorders by Artificial Intelligence Tools Based on Retinal Imaging-DINEURET (PNRR-MCNT2-2023-12378367)
Diabetic Retinopathy (DR) is the most frequent complication of diabetes, and its presence and severity are related to the appearance of both micro and macrovascular events.
Risk profiles have been suggested as a major direction for research in diabetes, based on non- invasive retinal imaging evaluations. There has been promising evidence that artificial intelligence (AI) based on fundus photographs can detect clinical metrics and systemic conditions invisible to expert human observers. Notably, deep-learning (DL) convolutional neural networks (CNNs) developed for retinal photographs have been shown superior performance in the detection of DR compared with human assessment.
Read more
The relationship between retinal vascular abnormalities and neurovascular complications of diabetes has been reported. The retina is a window to the body that allows a non-invasive observation of microvascular and neural tissues. However, in clinical practice there are no reported phenotypic indicators or reliable examinations to identify type 2 diabetic (T2D) patients with neurodegenerative/cognitive impairment. The presence of cognitive Impairment is a very frequent complication in diabetic patients, reported up to 60% of the diabetics when compared to only 11 % in the non-diabetics (OR of 8.78).
Furthermore, AI based on retinal imaging has never been applied before to predict the onset and worsening of neurodegenerative/cognitive impairment of T2D in a real-world setting.
The aim of this project is to develop trustworthy AI tools for predicting the risk of developing and progressing of neurodegenerative/cognitive diabetic impairment based on retinal images, in T2D population. For the development and validation of these tools, T2D patients will be enrolled from 4 well-established Italian centers.
The proposal of this study is addressed to health care systems, in order to improve their consciousness about diabetic neurodegenerative/cognitive complications and reduce the related economic burden. Since the huge majority of these disorders remain undiagnosed, DINEURET will provide new cost-effective screening strategies to identify these patients.
4 centers will be involved:
- 75 patients will be included in the IRCCS Ospedale San Raffaele, Milan;
- 75 patients will be included in the IRCCS MultiMedica, Milan;
- 50 patients will be included in the Ospedale Della Murgia "Fabio Perinei", Altamura;
- 50 patients will be included in the Azienda Ospedaliero-Universitaria (AOUI) of Cagliari, Cagliari.
- Conditions
- Diabete Mellitus, Cognitive Impairment
- Being tested
- Retinal imaging
- Medical subject headings
- Diabetes Mellitus, Cognitive Dysfunction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Retinal imagingDevice
Data of retinal imaging were acquired using Spectralis (Heidelberg, Germany) and California (Optos, UK).
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of AI based model
To evaluate the accuracy (sensibility and specificity) of the AI based model in the prediction of a worsening of neurodegenerative/cognitive impairment (defined as > 2 point decrease at Montreal Cognitive Assessment scale) based on the retinal imaging acquired at the baseline.
Measured: 30 August 2026
Secondary outcomes (2)
Reliability and reproducibility of the AI based model To characterize clinical phenotypes within T2D based on the risk of developing and worsening of cognitive decline.
To assess the reliability and reproducibility of the AI based model on different sub-samples (patients with different degrees of neurocognitive impairment).
Measured: 30 August 2026
Clinical phenotypes of T2D patients
To select clinical phenotypes of T2D patients based on retinal imaging that are characterized by higher risk of developing and worsening of cognitive decline.
Measured: 30 August 2026
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Aug 2024
- Study start30 Aug 2024
- Primary completion1 Apr 2026 (estimated)
- Study completion30 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabete MellitusStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 250 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ospedale San Raffaele
- Sponsor type
- University, hospital or other
- Collaborators
- Riccardo Sacconi, Ilaria Zucchiatti
- Responsible party
- Principal investigator, Querques Giuseppe, Ospedale San Raffaele
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06541834
- Sponsor's protocol ID
- DINEURET
- Status last verified
- Mar 2025
- First submitted
- 26 Jul 2024
- Last updated
- 14 Mar 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 14 Mar 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Predicting the Risk of Diabetic Neurodegenerative Disorders by Artificial Intelligence Tools Based on Retinal Imaging-DINEURET (PNRR-MCNT2-2023-12378367)
- ClinicalTrials.gov ID
- NCT06541834
- Acronym / sponsor ID
- DINEURET
- Conditions
- Diabete Mellitus, Cognitive Impairment
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 250 participants (estimated)
- Lead sponsor
- Ospedale San RaffaeleUniversity, hospital or other
- Collaborators
- Riccardo Sacconi, Ilaria Zucchiatti
- Study start
- 30 Aug 2024 (actual)
- Primary completion
- 1 Apr 2026 (estimated)
- Study completion
- 30 Aug 2026 (estimated)
- First posted
- 7 Aug 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Diabetic Retinopathy (DR) is the most frequent complication of diabetes, and its presence and severity are related to the appearance of both micro and macrovascular events.
Risk profiles have been suggested as a major direction for research in diabetes, based on non- invasive retinal imaging evaluations. There has been promising evidence that artificial intelligence (AI) based on fundus photographs can detect clinical metrics and systemic conditions invisible to expert human observers. Notably, deep-learning (DL) convolutional neural networks (CNNs) developed for retinal photographs have been shown superior performance in the detection of DR compared with human assessment.
The relationship between retinal vascular abnormalities and neurovascular complications of diabetes has been reported. The retina is a window to the body that allows a non-invasive observation of microvascular and neural tissues. However, in clinical practice there are no reported phenotypic indicators or reliable examinations to identify type 2 diabetic (T2D) patients with neurodegenerative/cognitive impairment. The presence of cognitive Impairment is a very frequent complication in diabetic patients, reported up to 60% of the diabetics when compared to only 11 % in the non-diabetics (OR of 8.78).
Furthermore, AI based on retinal imaging has never been applied before to predict the onset and worsening of neurodegenerative/cognitive impairment of T2D in a real-world setting.
The aim of this project is to develop trustworthy AI tools for predicting the risk of developing and progressing of neurodegenerative/cognitive diabetic impairment based on retinal images, in T2D population. For the development and validation of these tools, T2D patients will be enrolled from 4 well-established Italian centers.
The proposal of this study is addressed to health care systems, in order to improve their consciousness about diabetic neurodegenerative/cognitive complications and reduce the related economic burden. Since the huge majority of these disorders remain undiagnosed, DINEURET will provide new cost-effective screening strategies to identify these patients.
4 centers will be involved:
- 75 patients will be included in the IRCCS Ospedale San Raffaele, Milan;
- 75 patients will be included in the IRCCS MultiMedica, Milan;
- 50 patients will be included in the Ospedale Della Murgia "Fabio Perinei", Altamura;
- 50 patients will be included in the Azienda Ospedaliero-Universitaria (AOUI) of Cagliari, Cagliari.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 45 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Male or female >45 years old affected by type 2 diabetes.
Key inclusion criteria (6 listed)
- Male or female > 45 years-old;
- Diagnosis of type 2 DM;
- No previous treatment for diabetic retinopathy;
- Clear ocular media;
- Ability to communicate well with the Investigator and to understand and comply with the requirements of the study;
Key exclusion criteria (19 listed)
- Patients affected by other retinal disease than diabetic retinopathy;
- Presence of diabetic macular edema;
- Presence of proliferative diabetic retinopathy;
- Any media opacities, including corneal opacity, cataract formation and hemorrhage in the vitreous body, which may interfere with viewing by the laser surgeon of the target structures in the study eye(s). Subject requiring cataract surgery in the next 12 months must be excluded;
- Aphakic eye(s) with vitreous in the anterior chamber;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Retinal imagingData of retinal imaging were acquired using Spectralis (Heidelberg, Germany) and California (Optos, UK). | Device | – |
Primary outcome
Accuracy of AI based model
Time frame: 30 August 2026
To evaluate the accuracy (sensibility and specificity) of the AI based model in the prediction of a worsening of neurodegenerative/cognitive impairment (defined as > 2 point decrease at Montreal Cognitive Assessment scale) based on the retinal imaging acquired at the baseline.
2 secondary outcomes
Reliability and reproducibility of the AI based model To characterize clinical phenotypes within T2D based on the risk of developing and worsening of cognitive decline.
Time frame: 30 August 2026
Clinical phenotypes of T2D patients
Time frame: 30 August 2026
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 Mar 2025.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Riccardo Sacconi, MD, PhD contact
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Diabete Mellitus and Cognitive Impairment, run by Ospedale San Raffaele at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 19 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 14 Mar 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Giuseppe Querques, MD, PhD (00390226432648, giuseppe.querques@hotmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of AI based model (time frame: 30 August 2026). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 14 Mar 2025.