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Novel Neuroradiological Workflow for the Assisted DIAgnosis and Management of DEMentia with Artificial Intelligence

Novel Neuroradiological Workflow for the Assisted DIAgnosis and Management of DEMentia with Artificial Intelligence

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06877182
Acronym
DIADEMA
Enrollment
80000
Registered
2025-03-14
Start date
2024-08-30
Completion date
2027-08-31
Last updated
2025-03-19

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Alzheimer Disease, Dementia

Keywords

Neuroimaging, Artificial Intelligence (AI), Dementia, Assisted Diagnosis, Magnetic Resonance Imaging (MRI)

Brief summary

Identifying, screening and monitoring individuals at risk of Alzheimer's disease (AD) and dementia is a formidable challenge. Neuroimaging, and in particular magnetic resonance imaging (MRI), is crucial to detect structural neurodegeneration. However, current quantification tools are mainly limited to research contexts and produce non-standardised results. DIADEMA will build a systematic and standardised workflow to support neuro(radio)logical diagnosis. By combining artificial intelligence (AI) and machine learning (ML) the investigators will significantly enhance the clinical diagnosis of AD in neuroradiology. The investigator's main hypothesis is that an efficient workflow and associated higher diagnostic accuracy will substantially reduce healthcare costs, support clinical decision-making, provide second-opinion tools and improve patient care. This dual advance will have a profound impact on the healthcare system, marking an important step in the fight against Alzheimer's disease and dementia.

Interventions

To evaluate the possibility to improve the neuroradiologic workflow with AI models

Sponsors

UNINA
CollaboratorUNKNOWN
UNITO
CollaboratorUNKNOWN
Ospedale Fate bene Fratelli di Brescia
CollaboratorUNKNOWN
IRCCS SYNLAB SDN
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

* patients who perform brain magnetic resonance during the last 20 years

Exclusion criteria

\-

Design outcomes

Primary

MeasureTime frameDescription
Improvement of the neuroradiological workflow performance1-36 monthROC curves

Countries

Italy

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026