Intelligent Digital Tools for Screening of Brain Connectivity and Dementia Risk Estimation in People Affected by Mild Cognitive Impairment (AI-Mind)

April 1, 2024 updated by: Ira Hebold Haraldsen, Oslo University Hospital
Every three seconds someone in the world develops dementia. There are over 50 million people worldwide living with dementia and by 2030 this figure is expected to reach 82 million. Besides time-consuming patient investigations with low discriminative power for dementia risk, current treatment options focus on late symptom management. By screening brain connectivity and dementia risk estimation in people affected by mild cognitive impairment, the European Union (EU) funded AI-Mind project will open the door to extending the 'dementia-free' period by offering proper diagnosis and early intervention. AI-Mind will develop two artificial intelligence-based digital tools that will identify dysfunctional brain networks and assess dementia risk. Personalised patient reports will be generated, potentially opening new windows for intervention possibilities.

Study Overview

Status

Recruiting

Conditions

Detailed Description

The aim of this study is to validate an AI based risk assessment tool for new clinical neurological data management in five clinical centres (Oslo OUS, Helsinki HUH, Madrid UCM, Rome IRCCS and Rome UCSC)). Today, around 50% of patients with mild cognitive impairment (MCI) are at risk to develop dementia, and that early risk signs include brain network disturbances as an expression of beginning synaptic dysfunction in the course of dementia development. This synaptic dysfunction can be registered by electrophysiological brain signals. The AI-Mind Connector will identify such disturbed brain network based on EEG technology. Brain networks patterns are identified among other mathematical possibilities by Graph theory. Classical machine learning and deep learning approaches of artificial intelligence will be used in automating these brain network identification processes in existing M/EEG data.

The secondly developed tool, the AI-Mind Predictor, will serve as an enriched Connector, a multimodal prediction method for risk estimation of dementia in MCI patients. In addition to Connector data, cognitive test results, genetic apolipoprotein E (APOE) allele and P-Tau-protein level information are integrated in the AI-Mind Predictor. The AI-Mind Predictor will discriminate between people at risk for further dementia development and non-at-risk. The anticipated high specific and sensitive AI-Mind Predictor results will be compared to state-of-the-art (SOA) approaches.

The cutting-edge AI-Mind model development and testing will be done by available anonymised and prospective pseudo-anonymised data collected at the 5 included clinical centres. Final adaptation, validation, and prototype development will be conducted by the hereby described collection of prospective data of a total 1000 MCI subjects, based on standardized clinical inclusion/exclusion criteria listed below. All patients will sign an informed consent before entering the study.

The patients will follow the AI-Mind protocol for a 2-year period in parallel with the SOA follow-up procedures at each hospital and country. The protocol includes repetitive M/EEG measurements, digitalised cognitive testing, and at the first visit a blood sample for APOE allele and p-Tau 181 analyses. At two of our clinical centres (HUH and UCM) clinical MEG is additionally offered for specific feature extraction for modelling by new EEG based AI-Mind Connector technology.

Importantly, AI-Mind's new data handling procedure will only use existing well-established, globally accessible and low-cost SOA technologies. With AI-Mind's new data processing approach the goal is to increase today's low predictive value (<0.5) of SOA clinical dementia prediction, and proactively select, with higher accuracy than before, MCI patients at risk to be able to receive earlier clinical intervention. Thereby, AI-Mind wishes to contribute to delaying dementia development by detecting the risk already at the first visit when symptoms occur.

Study Type

Observational

Enrollment (Estimated)

1000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

  • Name: Lina Plataniti, M.Sc.
  • Phone Number: 0047 45008425
  • Email: linpla@ous-hf.no

Study Locations

  • Finland
      • Helsinki, Finland, 00280
  • Italy
      • Roma, Italy, 00168
      • Roma, Italy, 00179
  • Norway
      • Oslo, Norway, 0450
        • Recruiting
        • Oslo University Hospital
        • Contact:
        • Contact:
          • Vebjørn Andersson, B.Sc
          • Phone Number: 0047 41859640
          • Email: vebjoran@uio.no
  • Spain
      • Madrid, Spain, 28040

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

60 years to 75 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Approximately 1000 MCI participants will be screened and consecutively enrolled at AI-MINDs by the clinical criteria and assessments. All patients will be enrolled by SOA procedures being referred to neurological and memory clinics due to their mild cognitive impaired symptoms.

Subjects that fulfil the AI-Mind criteria for MCI based on the acknowledged criteria by the National Institute on Aging-Alzheimer's Association (NIA-AA), and meet the projects inclusion criteria listed below, will be offered to participate in the AI-Mind clinical study. The clinical identification of MCI is defined using specific assessment tools known to accurately identify cognitive status and progression of cognitive decline. The assessment tools include the use of Mini Mental State Examination (MMSE), Clinical Dementia Rating (CDR), Instrumental activities of daily living IADL and Petersen/Winblad criteria with 1.5 SD in 1 or more cognitive domains.

Description

Inclusion Criteria:

  • Male and female aged between 60 and 75 years
  • MCI diagnosis with a MMSE >= 25
  • or MCI diagnosis with MoCa >= 17

Exclusion Criteria:

  • Confirmed dementia
  • History of cerebrovascular disease (i.e. stroke episodes)
  • Alcohol Use Disorder Identification Test (AUDIT) score positive
  • Severe medical disorders associated with cognitive impairment (organ insufficiencies, chronic infections, endocrinological disorders)
  • Severe head trauma with structural brain lesion and/or previous brain surgery;
  • Severe mental disorders; Schizophrenia, known Major depression or bipolar disorder
  • Neuroimaging evidence of other potential causes of cognitive decline (e.g. subdural haematoma, malignancy)
  • History of malignancy < 5 years;
  • Recent use of psychotropic drugs including AChEI and Memantine (< 3 months);
  • Participation in trials with experimental drugs.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
AI-Mind Connector with estimated specificity and sensitivity value > 0.9
Time Frame: 2026
To validate the AI-Mind Connector as a biomarker for early brain network connectivity disturbance in at-risk patients.
2026
AI-Mind Predictor with estimated specificity and sensitivity value > 0.9.
Time Frame: 2026
To validate the AI-Mind Predictor as a diagnostic support tool for dementia risk evaluation. AI-Mind Predictor with higher prediction value for early dementia risk than current clinical practice.
2026

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Clinical utility of Digital Cognitive Test compared to classical Neuropsychological test
Time Frame: 2026
Report on the clinical utility of digital cognitive assessment tool for evaluation of cognitive function in people suspected of MCI and compare it to paper pencil classical neuropsychological test (NPT). The specific test (and domains) to be applied are Motor Screening Task (Attention and psychomotor speed), Delayed Matching to Sample (Memory), One Touch Stockings of Cambridge (Executive function), Paired Associates Learning (Memory), Pattern Recognition Memory (Memory), Reaction Time (Attention and psychomotor speed), Rapid Visual Information Processing (Attention and psychomotor speed), Spatial Working Memory (Executive function) and Match to Sample Visual Search (Attention and psychomotor speed). The score of the test domains of the digital cognitive test will be compared to equal domains measured through classical NPT.
2026
M/EEG connectivity measures
Time Frame: 2026
To validate the accuracy of different M/EEG (connectivity) data features for predicting the risk of dementia
2026

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Oslo University Hospital

Collaborators

Radboud University Medical Center
Helsinki University Central Hospital
Catholic University of the Sacred Heart
Universidad Complutense de Madrid
Aalto University
Oslo Metropolitan University
IRCCS San Raffaele Roma
Alzheimer Europe
Accelopment AG
BrainSymph AS
Det Norske Veritas
Lurtis Rules S.L.
Neuroconnect Srl
Tallinna Ülikool

Investigators

  • Principal Investigator: Ira Haraldsen, PhD, MD, Oslo University Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Helpful Links

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

March 1, 2021

Primary Completion (Estimated)

September 30, 2025

Study Completion (Estimated)

February 27, 2026

Study Registration Dates

First Submitted

October 6, 2021

First Submitted That Met QC Criteria

December 10, 2021

First Posted (Actual)

December 16, 2021

Study Record Updates

Last Update Posted (Actual)

April 2, 2024

Last Update Submitted That Met QC Criteria

April 1, 2024

Last Verified

April 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 204084

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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