Ignite Creation Date:
2025-12-24 @ 11:41 PM
Ignite Modification Date:
2025-12-31 @ 3:18 AM
Study NCT ID:
NCT05794451
Status:
RECRUITING
Last Update Posted:
2024-07-26
First Post:
2023-03-20
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Developing an Artificial Intelligence System to Detect Cognitive Impairment
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000544', 'term': 'Alzheimer Disease'}, {'id': 'D060825', 'term': 'Cognitive Dysfunction'}], 'ancestors': [{'id': 'D003704', 'term': 'Dementia'}, {'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D024801', 'term': 'Tauopathies'}, {'id': 'D019636', 'term': 'Neurodegenerative Diseases'}, {'id': 'D019965', 'term': 'Neurocognitive Disorders'}, {'id': 'D001523', 'term': 'Mental Disorders'}, {'id': 'D003072', 'term': 'Cognition Disorders'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'CROSS_SECTIONAL', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 4000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2023-03-20', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-07', 'completionDateStruct': {'date': '2025-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-07-25', 'studyFirstSubmitDate': '2023-03-20', 'studyFirstSubmitQcDate': '2023-03-31', 'lastUpdatePostDateStruct': {'date': '2024-07-26', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-04-03', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Cognition', 'timeFrame': 'One day', 'description': 'The Montreal Cognitive Assessment (MoCA) is a 10-minute paper-based test that aims to detect MCI in older patients with symptomatology, suggesting impaired cognition. The MoCA is composed of 12 tasks to detect short-term memory, visuospatial ability, executive functioning, phonemic fluency, abstraction, attention, concentration, working memory, language, and orientation.'}, {'measure': "Cognition for adults diagnosed with Alzheimer's disease", 'timeFrame': 'One day', 'description': 'The Self-reported Cognitive Difficulties (CDS)75 is a 39-item questionnaire that requires participants or their caregivers in case of AD to rate how often they currently experience cognitive difficulties in everyday life using a 5-point scale (0 -"never" to 4 -"very often").'}, {'measure': 'Self-figure drawing -Cognition', 'timeFrame': 'One day', 'description': 'Self-figure drawing. Participants will be asked to draw themselves using a pencil on an A4-sized sheet of paper.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Alzheimer Disease', 'Healthy Aging', 'Mild Cognitive Impairment']}, 'descriptionModule': {'briefSummary': "Alzheimer's disease dementia (AD) is a debilitating and prevalent neurodegenerative disease in older adults globally. Cognitive impairment, a hallmark of AD, is assessed through verbal tests that require high specialization, and while accepted as screening tools for AD, general practitioners seldom use them. AD can be diagnosed with expensive, invasive neuroimaging and blood tests, but these are usually conducted when cognitive functioning is already severely impaired. Thus, finding a novel, non-invasive tool to detect and differentiate mild cognitive impairment (MCI) and AD is a prime public health interest. Self-figure drawings (a projective tool in which individuals are asked to draw a picture of themselves), are easy to administer and have been shown to differentiate between healthy and cognitively impaired individuals, including AD. Convolutional Neural Network (CNN) (a type of deep neural network, applied to analyze visual imagery) has advanced to assess health conditions using art products. Therefore, the proposed study suggests utilizing CNN-based methods to develop and test an application tailored to differentiate between drawings of individuals with MCI, AD, and healthy controls (HC) using 4,000 self-figure drawings. This"}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '60 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Adults aged 60 or above, who live in Israel.', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Adults aged 60 and above with subtle signs of risk of future cognitive decline, residing in the community or in nursing homes with a minimum of 10 years of education.\n\nExclusion Criteria:\n\n* Current or past psychiatric illness, the presence of congenital/organic cognitive condition, severe visual or motor impairment, and terminal illness (to avoid the effect of comorbidities).'}, 'identificationModule': {'nctId': 'NCT05794451', 'briefTitle': 'Developing an Artificial Intelligence System to Detect Cognitive Impairment', 'organization': {'class': 'OTHER', 'fullName': 'University of Haifa'}, 'officialTitle': "Developing an Artificial Intelligence System to Detect Mild Cognitive Impairment and Alzheimer's Disease Dementia Through Self-Figure Drawing: An Innovative Approach", 'orgStudyIdInfo': {'id': 'ALZAI'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Healthy controls', 'description': 'Adults aged 60 and above without cognitive impairment'}, {'label': 'Mild cognitive impairment', 'description': 'Adults 60 and above with mild cognitive impairment'}, {'label': "Alzheimer's disease", 'description': "Adults diagnosed with Alzheimer's disease"}]}, 'contactsLocationsModule': {'locations': [{'city': 'Haifa', 'status': 'RECRUITING', 'country': 'Israel', 'contacts': [{'name': 'Amit Perry, MA', 'role': 'CONTACT', 'email': 'perryamit1@gmail.com'}], 'facility': 'University of Haifa', 'geoPoint': {'lat': 32.81303, 'lon': 34.99928}}], 'centralContacts': [{'name': 'Amit Perry, MA', 'role': 'CONTACT', 'email': 'peryamit1@gmail.com', 'phone': '+9722454258'}], 'overallOfficials': [{'name': 'Johanna Czamanski-Cohen, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'University of Haifa'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'This is an artificial intelligence study, thus there will not be a dataset available for sharing.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Haifa', 'class': 'OTHER'}, 'collaborators': [{'name': 'Technion, Israel Institute of Technology', 'class': 'OTHER'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Senior Lecturer', 'investigatorFullName': 'Johanna Czamanski-Cohen', 'investigatorAffiliation': 'University of Haifa'}}}}