Ignite Creation Date:
2025-12-24 @ 6:50 PM
Ignite Modification Date:
2026-01-06 @ 6:06 PM
Study NCT ID:
NCT06826157
Status:
ENROLLING_BY_INVITATION
Last Update Posted:
2025-02-17
First Post:
2024-12-04
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
The Role of Advanced Electroencephalographic Data as Marker of Pathology and Prognosis in Primary Dementias
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000544', 'term': 'Alzheimer Disease'}, {'id': 'D020961', 'term': 'Lewy Body Disease'}, {'id': 'D057180', 'term': 'Frontotemporal Dementia'}, {'id': 'D060825', 'term': 'Cognitive Dysfunction'}, {'id': 'D003704', 'term': 'Dementia'}], 'ancestors': [{'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': 'D020734', 'term': 'Parkinsonian Disorders'}, {'id': 'D001480', 'term': 'Basal Ganglia Diseases'}, {'id': 'D009069', 'term': 'Movement Disorders'}, {'id': 'D000080874', 'term': 'Synucleinopathies'}, {'id': 'D057174', 'term': 'Frontotemporal Lobar Degeneration'}, {'id': 'D057177', 'term': 'TDP-43 Proteinopathies'}, {'id': 'D057165', 'term': 'Proteostasis Deficiencies'}, {'id': 'D008659', 'term': 'Metabolic Diseases'}, {'id': 'D009750', 'term': 'Nutritional and Metabolic Diseases'}, {'id': 'D003072', 'term': 'Cognition Disorders'}]}, 'interventionBrowseModule': {'meshes': [{'id': 'D004569', 'term': 'Electroencephalography'}], 'ancestors': [{'id': 'D003943', 'term': 'Diagnostic Techniques, Neurological'}, {'id': 'D019937', 'term': 'Diagnostic Techniques and Procedures'}, {'id': 'D003933', 'term': 'Diagnosis'}, {'id': 'D004568', 'term': 'Electrodiagnosis'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'SINGLE_GROUP', 'interventionModelDescription': 'Intervention study, monocentric and multiparametric'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 175}}, 'statusModule': {'overallStatus': 'ENROLLING_BY_INVITATION', 'startDateStruct': {'date': '2021-11-05', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-02', 'completionDateStruct': {'date': '2027-01-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-02-13', 'studyFirstSubmitDate': '2024-12-04', 'studyFirstSubmitQcDate': '2025-02-10', 'lastUpdatePostDateStruct': {'date': '2025-02-17', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2025-02-13', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2026-04-15', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Cortical source densities in resting-state EEG for mild cognitive impairment: Markers of differential diagnosis and dementia conversion prediction', 'timeFrame': '36 months', 'description': 'Source densities in resting-state high-definition EEG in patients with mild cognitive impairment, measured as cortical markers for differential diagnosis of dementias and prediction of conversion to full-blown dementia'}], 'secondaryOutcomes': [{'measure': "Accuracy of EEG markers in distinguishing Alzheimer's disease from other dementias measured by sensivity", 'timeFrame': '36 months', 'description': "Diagnostic accuracy of EEG markers in distinguishing Alzheimer's disease (AD) from other dementias (e.g., frontotemporal dementia, Lewy-body dementia), measured as the ability to correctly identify cases that are not Alzheimer's (e.g., frontotemporal dementia, Lewy-body dementia) compared to Alzheimer's cases."}, {'measure': "Accuracy of EEG markers in distinguishing Alzheimer's disease from other dementias measured by specifity", 'timeFrame': '36 months', 'description': "Diagnostic accuracy of EEG markers in distinguishing Alzheimer's disease (AD) from other dementias measured as the ability to correctly identify cases that are not Alzheimer's (e.g., frontotemporal dementia, Lewy-body dementia) compared to Alzheimer's cases"}, {'measure': "Relationship between Alzheimer's disease and other dementias with APOE genetic variants", 'timeFrame': '36 months', 'description': 'Relationship with APOE genetic variants (e.g., presence of APOE ε4 allele), quantified through cortical source densities reconstructed using sLORETA.'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['high-definition electroencephalogram', 'Brain Magnetic Resonance Imaging', 'Biomarker profile', 'Positron Emission Tomography', 'Apolipoprotein E', 'Mild Cognitive Impairment', 'Frontotemporal dementia', 'Lewy-body dementia', 'Dementia'], 'conditions': ['Alzheimer Disease', 'Lewy Body Dementia (LBD)', 'Mild Alzheimer Disease', 'Frontotemporal Dementia (FTD)', 'Mild Cognitive Impairment (MCI)', 'Healthy Subjects']}, 'referencesModule': {'references': [{'type': 'BACKGROUND', 'citation': 'Pascual-Marqui RD. Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization. 2007.'}, {'pmid': '26199870', 'type': 'BACKGROUND', 'citation': "Teipel SJ, Kurth J, Krause B, Grothe MJ; Alzheimer's Disease Neuroimaging Initiative. The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment - Beyond classical regression. Neuroimage Clin. 2015 May 21;8:583-93. doi: 10.1016/j.nicl.2015.05.006. eCollection 2015."}, {'type': 'BACKGROUND', 'citation': "International AsD. World Alzheimer Report 2019: Attitudes to dementia. London: Alzheimer's Disease International, 2019"}, {'pmid': '34098525', 'type': 'BACKGROUND', 'citation': "Cecchetti G, Agosta F, Basaia S, Cividini C, Cursi M, Santangelo R, Caso F, Minicucci F, Magnani G, Filippi M. Resting-state electroencephalographic biomarkers of Alzheimer's disease. Neuroimage Clin. 2021;31:102711. doi: 10.1016/j.nicl.2021.102711. Epub 2021 May 29."}, {'pmid': '28592453', 'type': 'BACKGROUND', 'citation': "McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor JP, Weintraub D, Aarsland D, Galvin J, Attems J, Ballard CG, Bayston A, Beach TG, Blanc F, Bohnen N, Bonanni L, Bras J, Brundin P, Burn D, Chen-Plotkin A, Duda JE, El-Agnaf O, Feldman H, Ferman TJ, Ffytche D, Fujishiro H, Galasko D, Goldman JG, Gomperts SN, Graff-Radford NR, Honig LS, Iranzo A, Kantarci K, Kaufer D, Kukull W, Lee VMY, Leverenz JB, Lewis S, Lippa C, Lunde A, Masellis M, Masliah E, McLean P, Mollenhauer B, Montine TJ, Moreno E, Mori E, Murray M, O'Brien JT, Orimo S, Postuma RB, Ramaswamy S, Ross OA, Salmon DP, Singleton A, Taylor A, Thomas A, Tiraboschi P, Toledo JB, Trojanowski JQ, Tsuang D, Walker Z, Yamada M, Kosaka K. Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology. 2017 Jul 4;89(1):88-100. doi: 10.1212/WNL.0000000000004058. Epub 2017 Jun 7."}, {'pmid': '21810890', 'type': 'BACKGROUND', 'citation': 'Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, van Swieten JC, Seelaar H, Dopper EG, Onyike CU, Hillis AE, Josephs KA, Boeve BF, Kertesz A, Seeley WW, Rankin KP, Johnson JK, Gorno-Tempini ML, Rosen H, Prioleau-Latham CE, Lee A, Kipps CM, Lillo P, Piguet O, Rohrer JD, Rossor MN, Warren JD, Fox NC, Galasko D, Salmon DP, Black SE, Mesulam M, Weintraub S, Dickerson BC, Diehl-Schmid J, Pasquier F, Deramecourt V, Lebert F, Pijnenburg Y, Chow TW, Manes F, Grafman J, Cappa SF, Freedman M, Grossman M, Miller BL. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011 Sep;134(Pt 9):2456-77. doi: 10.1093/brain/awr179. Epub 2011 Aug 2.'}, {'pmid': '21514250', 'type': 'BACKGROUND', 'citation': "McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):263-9. doi: 10.1016/j.jalz.2011.03.005. Epub 2011 Apr 21."}, {'pmid': '21514249', 'type': 'BACKGROUND', 'citation': "Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):270-9. doi: 10.1016/j.jalz.2011.03.008. Epub 2011 Apr 21."}, {'pmid': '29653606', 'type': 'BACKGROUND', 'citation': "Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, Holtzman DM, Jagust W, Jessen F, Karlawish J, Liu E, Molinuevo JL, Montine T, Phelps C, Rankin KP, Rowe CC, Scheltens P, Siemers E, Snyder HM, Sperling R; Contributors. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018 Apr;14(4):535-562. doi: 10.1016/j.jalz.2018.02.018."}]}, 'descriptionModule': {'briefSummary': "The study aims to use advanced brainwave recordings of electroencephalogram (EEG) to understand early signs of Alzheimer's disease (AD) in people with mild memory problems, known as amnestic Mild Cognitive Impairment (MCI). The goals of the study are to:\n\n1. Find early markers of Alzheimer by analyzing EEG recordings, the researchers hope to identify patterns that indicate the presence of Alzheimer's disease. They will compare these patterns with other brain scans, like Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans, and look at different biological markers in the participants' spinal fluid and genetic data.\n2. Predict the risk of Alzheimer's disease. The study will try to find EEG patterns that can predict whether someone with MCI will develop full-blown Alzheimer's disease. The aim is to create a system that combines EEG data with other brain scans and genetic information to better understand the risk of disease progression.\n3. Track changes over time: The research will also monitor changes in brain activity and structure over time to understand how Alzheimer's disease progresses.\n\nIn addition to studying people with MCI, the researchers will also look at EEG patterns in people with mild Alzheimer's disease (MILD AD), frontotemporal dementia (FTD), and Lewy-body dementia (LBD) to see how these patterns differ across various brain conditions. This could help improve the accuracy of diagnosing these diseases and understanding their link to genetic factors.", 'detailedDescription': "The main aim of the project is to examine resting-state high definition EEG cortical sources of participants diagnosed with amnestic MCI with the goal of:\n\n\\- exploring EEG-markers of Alzheimer's disease pathology and their relationships with both conventional and non-conventional brain MRI data. Researchers will explore these relationships after grouping participants according to their cerebrospinal fluid (CSF) biomarkers profile.\n\nResearchers will explain further relationships through brain Positron Tomography Emission with fluorodeoxyglucose (PET-FDG) data performed during clinical diagnostic work-up and with Apolipoprotein E (APOE) gene profile.\n\n* prospectively identifying EEG-markers predictive of clinical conversion to full-blown AD dementia and defining an algorithm for risk stratification by combining them with brain MRI, brain FDG-PET and genetic data;\n* assessing the longitudinal changes of electrophysiological and MRI signals throughout the AD neuropathology progression;\n\nThe secondary aim of the project is to assess the accuracy of the Alzheimer-related EEG signal patterns identified in the MCI group. This will be done by comparing the EEG data with the APOE genetic information in a group of patients diagnosed with mild dementia due to Alzheimer's disease, frontotemporal dementia and Lewy-Body dementia"}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '85 Years', 'minimumAge': '50 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion criteria for all study subjects:\n\n* right-handed participants;\n* monolingual native Italian speakers;\n* age between 50-85 years old;\n* normal or corrected-to-normal visual acuity;\n* oral and written informed consent to study participation.\n* if assuming psychotropic drugs (i.e., benzodiazepines, antipsychotics, antidepressants), they should be at stable dosage for more than 4 weeks.\n\nInclusion criteria for MCI patients:\n\n* diagnosis of amnestic MCI;\n* mini Mental State Examination (MMSE) score ≥ 24;\n* if assuming anticholinesterase inhibitors (i.e., galantamine, rivastigmine, donepezil) or memantine, they should be at stable dosage for more than 4 weeks;\n* available CSF AD biomarkers.\n\nInclusion criteria for patients with mild dementia:\n\n* diagnosis of AD dementia, FTD or LBD.\n* MMSE score ≥ 15;\n* if assuming anticholinesterase inhibitors (i.e., galantamine, rivastigmine, donepezil) or memantine, they should be at stable dosage for more than 4 weeks.\n\nExclusion criteria for patients:\n\n* secondary forms of cognitive impairment on the basis of historical data, neurologic examination, and cerebral neuroimaging findings;\n* very rapid cognitive decline that occurs over weeks or months, typically indicative of prion disease, neoplasm or metabolic disorders;\n* history of other systemic (including systemic neoplasms in the last 3 years and abnormal hepatorenal functions), neurologic (including epilepsy), psychiatric diseases, head injury, cardiovascular events, and cerebrovascular alterations;\n* alcohol and/or psychotropic drugs abuse;\n* enrolment in clinical trials testing disease-modifying drugs for AD during study;\n* contraindications to MRI study:\n\n 1. Cardiac pacemakers or other types of cardiac catheters;\n 2. metal splinters or fragments;\n 3. metal prostheses not compatible with the magnetic field generated during MRI;\n 4. claustrophobia.\n* Women who are pregnant or intending to become pregnant during the study; breastfeeding women.\n\nExclusion criteria for healthy controls\n\n* History of other systemic (including systemic neoplasms in the last 3 years and abnormal hepatorenal functions), neurologic (including epilepsy), psychiatric diseases, head injury, cardiovascular events, and cerebrovascular alterations;\n* alcohol and/or psychotropic drugs abuse;\n* contraindications to MRI study (see above);\n* women who are pregnant or intending to become pregnant during the study; breastfeeding women.'}, 'identificationModule': {'nctId': 'NCT06826157', 'briefTitle': 'The Role of Advanced Electroencephalographic Data as Marker of Pathology and Prognosis in Primary Dementias', 'organization': {'class': 'OTHER', 'fullName': 'IRCCS San Raffaele'}, 'officialTitle': 'Assessing the Role of Advanced Electroencephalographic Data as Marker of Pathology and Prognosis in Primary Dementias', 'orgStudyIdInfo': {'id': 'DEMEEG'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Clinical, EEG, brain MRI and genetic evaluations', 'description': 'Participants will be screened to evaluate their eligibility. They will undergo clinical and cognitive assessments in addition to 32-channel EEG and 3 Tesla MRI at baseline (T0) and every year for 3 years. Furthermore, at baseline, a known genetic risk factors for AD will be explored (e., APOE gene profile).', 'interventionNames': ['Diagnostic Test: Electroencephalogram', 'Diagnostic Test: 3 Tesla MRI', 'Genetic: Apolipoprotein E genetic test']}], 'interventions': [{'name': 'Electroencephalogram', 'type': 'DIAGNOSTIC_TEST', 'description': 'EEGs will be acquired to explore progressive alteration of EEG patterns throughout the neuropathology progression.', 'armGroupLabels': ['Clinical, EEG, brain MRI and genetic evaluations']}, {'name': '3 Tesla MRI', 'type': 'DIAGNOSTIC_TEST', 'description': 'MRI evaluations will be performed to investigate structural alterations and resting state functional MRI (RS-fMRI) connectivity in participants. Longitudinal measures of cortical/subcortical atrophy and RS-fMRI connectivity will be assessed and their relationship with EEG parameters will be explored.', 'armGroupLabels': ['Clinical, EEG, brain MRI and genetic evaluations']}, {'name': 'Apolipoprotein E genetic test', 'type': 'GENETIC', 'description': 'At baseline, a sample of blood will be collected to perform genetic analysis (APOE alleles) for all participants', 'armGroupLabels': ['Clinical, EEG, brain MRI and genetic evaluations']}]}, 'contactsLocationsModule': {'locations': [{'zip': '20132', 'city': 'Milan', 'state': 'Italy', 'country': 'Italy', 'facility': 'IRCCSS San Raffaele', 'geoPoint': {'lat': 42.78235, 'lon': 12.59836}}], 'overallOfficials': [{'name': 'Massimo MF Filippi, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'IRCCS Ospedale San Raffaele'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'IRCCS San Raffaele', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'MD, Professor', 'investigatorFullName': 'Prof. Massimo Filippi', 'investigatorAffiliation': 'IRCCS San Raffaele'}}}}