Cognitive DysfunctionAI-MindNCT05159661
Intelligent Digital Tools for Screening of Brain Connectivity and Dementia Risk Estimation in People Affected by Mild Cognitive Impairment
An observational study of Cognitive Dysfunction and Dementia, run by Oslo University Hospital at 5 sites in 4 countries.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 60 to 75 years
- Conditions the study is for
- Cognitive Dysfunction, Dementia, Mild Cognitive Impairment
- How many people
- 1,000 participants
- Where
- 5 sitesin 4 countries
- Study dates
- 1 Mar 2021to 27 Feb 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
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 60 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
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.
Who may be able to join
- Male and female aged between 60 and 75 years
- MCI diagnosis with a MMSE >= 25
- or MCI diagnosis with MoCa >= 17
Who cannot join
- 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
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- 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.
Trial locations and contacts
5 sites in 4 countries.
5 sites in 4 countries
Italy2 sites, 2 recruiting
- Recruiting
Università Cattolica del Sacro Cuore Campus di Roma
Roma, 00168
Cristina Nardulli, info.aimindproject@gmail.com
- Recruiting
Scientific Institute for Research, Hospitalization and Healthcare
Roma, 00179
Frederica Lino, info.aimindproject@gmail.com
Finland1 site, 1 recruiting
- Recruiting
Helsinki University Hospital
Helsinki, 00280
Paivi Olli, aimindsuomi@gmail.com
Norway1 site, 1 recruiting
- Recruiting
Oslo University Hospital
Oslo, 0450
Cathrine Faye, 95833193 ext. 0047, cfaye@a-support.no
Vebjørn Andersson, B.Sc, 41859640 ext. 0047, vebjoran@uio.no
Spain1 site, 1 recruiting
- Recruiting
Universidad Complutense de Madrid
Madrid, 28040
Soraya Alfonsín Romero, proyectoAIMind@gmail.com
About this study
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.
Read the 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.
- Conditions
- Cognitive Dysfunction, Dementia, Mild Cognitive Impairment
- Keywords
- MCI, AI, EEG, Alzheimer, Dementia, Functional brain connectivity, Deep learning, Machine learning
- Medical subject headings
- Cognitive Dysfunction, Dementia
What is being measured
The primary outcome is the main question the study is designed to answer.
AI-Mind Connector with estimated specificity and sensitivity value > 0.9
To validate the AI-Mind Connector as a biomarker for early brain network connectivity disturbance in at-risk patients.
Measured: 2026
AI-Mind Predictor with estimated specificity and sensitivity value > 0.9.
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.
Measured: 2026
Secondary outcomes (2)
Clinical utility of Digital Cognitive Test compared to classical Neuropsychological test
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.
Measured: 2026
M/EEG connectivity measures
To validate the accuracy of different M/EEG (connectivity) data features for predicting the risk of dementia
Measured: 2026
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Dec 2021
- Study start1 Mar 2021
- Primary completion30 Sep 2025 (estimated)
- Study completion27 Feb 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Cognitive DysfunctionStudies of the same condition, open and under way.
- More trials run by Oslo University HospitalThe sponsor's other registered studies.
- 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
- Other
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Oslo University Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Aalto University, Accelopment AG, Alzheimer Europe, BrainSymph AS, Det Norske Veritas, Helsinki University Central Hospital, IRCCS San Raffaele Roma, Lurtis Rules S.L., Neuroconnect Srl, Oslo Metropolitan University, Radboud University Medical Center, Tallinna Ülikool, Universidad Complutense de Madrid, Catholic University of the Sacred Heart
- Responsible party
- Principal investigator, Ira Hebold Haraldsen, Oslo University Hospital
- Investigators
- Ira Haraldsen, PhD, MD, Principal investigator, Oslo University Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05159661
- Sponsor's protocol ID
- 204084
- Acronym
- AI-Mind
- Status last verified
- Apr 2024
- First submitted
- 6 Oct 2021
- Last updated
- 2 Apr 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 2 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Intelligent Digital Tools for Screening of Brain Connectivity and Dementia Risk Estimation in People Affected by Mild Cognitive Impairment
- ClinicalTrials.gov ID
- NCT05159661
- Acronym / sponsor ID
- AI-Mind / 204084
- Conditions
- Cognitive Dysfunction, Dementia, Mild Cognitive Impairment
- Keywords
- MCI, AI, EEG, Alzheimer, Dementia, Functional brain connectivity, Deep learning, Machine learning
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Oslo University HospitalUniversity, hospital or other
- Collaborators
- Aalto University, Accelopment AG, Alzheimer Europe, BrainSymph AS, Det Norske Veritas, Helsinki University Central Hospital, IRCCS San Raffaele Roma, Lurtis Rules S.L., Neuroconnect Srl, Oslo Metropolitan University, Radboud University Medical Center, Tallinna Ülikool, Universidad Complutense de Madrid, Catholic University of the Sacred Heart
- Study start
- 1 Mar 2021 (actual)
- Primary completion
- 30 Sep 2025 (estimated)
- Study completion
- 27 Feb 2026 (estimated)
- First posted
- 16 Dec 2021 (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.
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.
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 design
- Observational model
- Other
- Time perspective
- Prospective
Who may qualify
- Ages
- 60 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (3 listed)
- Male and female aged between 60 and 75 years
- MCI diagnosis with a MMSE >= 25
- or MCI diagnosis with MoCa >= 17
Key exclusion criteria (10 listed)
- 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;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
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.
2 secondary outcomes
Clinical utility of Digital Cognitive Test compared to classical Neuropsychological test
Time frame: 2026
M/EEG connectivity measures
Time frame: 2026
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Apr 2024.
- Offcial project website for the AI-Mind projectLink provided by the sponsor.
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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. This study is not recruiting at the moment.
Ira Haraldsen, PhD, MD principal investigator
Oslo University Hospital
5 sites in 4 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cognitive Dysfunction and Dementia, run by Oslo University Hospital at 5 sites in 4 countries.
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 3 inclusion and 10 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: status not confirmed, as of the sponsor's last update on 2 Apr 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 5 sites in Italy, Finland, Norway, Spain. 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Ira Haraldsen, PhD, MD (92011533 ext. 0047, ira.haraldsen@icloud.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
AI-Mind Connector with estimated specificity and sensitivity value > 0.9 (time frame: 2026). The study lists 2 primary outcomes in all. 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 2 Apr 2024; AzTrials last refreshed its copy on 7 Nov 2026.