Ignite Creation Date:
2025-12-25 @ 4:07 AM
Ignite Modification Date:
2025-12-26 @ 3:03 AM
Study NCT ID:
NCT04986020
Status:
UNKNOWN
Last Update Posted:
2021-08-02
First Post:
2021-07-21
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Identifying New Biomarkers of Parkinson's From Routine Brain Imaging
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D010300', 'term': 'Parkinson Disease'}], 'ancestors': [{'id': 'D020734', 'term': 'Parkinsonian Disorders'}, {'id': 'D001480', 'term': 'Basal Ganglia Diseases'}, {'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D009069', 'term': 'Movement Disorders'}, {'id': 'D000080874', 'term': 'Synucleinopathies'}, {'id': 'D019636', 'term': 'Neurodegenerative Diseases'}]}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2021-06-11', 'size': 411969, 'label': 'Study Protocol', 'hasIcf': False, 'hasSap': False, 'filename': 'Prot_000.pdf', 'typeAbbrev': 'Prot', 'uploadDate': '2021-07-21T08:31', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 20000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'NOT_YET_RECRUITING', 'startDateStruct': {'date': '2021-08-01', 'type': 'ESTIMATED'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2021-07', 'completionDateStruct': {'date': '2024-07-01', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2021-07-21', 'studyFirstSubmitDate': '2021-07-21', 'studyFirstSubmitQcDate': '2021-07-21', 'lastUpdatePostDateStruct': {'date': '2021-08-02', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-08-02', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-07-01', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The presence of novel putative biomarkers of future PD development as defined by a deep-learning method', 'timeFrame': '3 years'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Parkinson Disease']}, 'descriptionModule': {'briefSummary': "The study will use routine computer tomography (CT), magnetic resonance spectroscopy (MRI) and nuclear medicine (NM) brain imaging data to produce new diagnostic tests for the onset of Parkinson's disease. This will enable hopefully earlier diagnosis than is currently possible. This will entail the analysis of anonymised CT/MRI/NM brain images collected prior to the point when these subjects were diagnosed with PD.", 'detailedDescription': "We intend to use historical CT/MRI/nuclear medicine brain scans to identify novel imaging biomarkers of prodromal Parkinson's disease. The primary data source for the study will be MRI and CT brain scans, whilst nuclear medicine imaging brain imaging (DAT scans) will be used to validate models produced and provide a functional outcome measure of brain dopamine uptake. We shall utilise a an artificial intelligence approach to compare scans of PD cases with matched controls in order to identify these imaging biomarkers.\n\nA list of participants with a diagnosis will be compiled. This list, together with relevant clinical data, will be linked with historical CT/MRI/nuclear medicine scans carried out over the preceding years. A control group of matched non-PD scans will also be compiled.\n\nThe dataset will be anonymised and a bespoke ML pipeline will be used to identify imaging featureswhich may be indicative of prodromal PD. This initial stage will be carried out at University Hospital Plymouth NHS Trust (UHPNT), the Royal Cornwall Hospital NHS Trust (RCHNT) and Cornwall Partnership NHS Trust (CPNT). If successful, findings will be validated in a larger sample of scans compiled from hospitals regionally and nationally."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Participants drawn from the catchment areas of participating healthcare organisations', 'healthyVolunteers': True, 'eligibilityCriteria': "Inclusion Criteria:\n\n\\- A clinical diagnosis of Parkinson's\n\nExclusion Criteria:\n\n\\- No clinical diagnosis of Parkinson's"}, 'identificationModule': {'nctId': 'NCT04986020', 'briefTitle': "Identifying New Biomarkers of Parkinson's From Routine Brain Imaging", 'organization': {'class': 'OTHER', 'fullName': 'University of Plymouth'}, 'officialTitle': "Identifying New Biomarkers of Parkinson's From Routine Brain Imaging", 'orgStudyIdInfo': {'id': '2557'}, 'secondaryIdInfos': [{'id': 'IRAS 280243', 'type': 'OTHER', 'domain': 'Health Research Authority'}]}, 'armsInterventionsModule': {'armGroups': [{'label': 'Parkinson disease', 'description': "Participants with a clinical diagnosis of Parkinson's disease", 'interventionNames': ['Diagnostic Test: MRI']}, {'label': 'Control', 'description': 'Controls', 'interventionNames': ['Diagnostic Test: MRI']}], 'interventions': [{'name': 'MRI', 'type': 'DIAGNOSTIC_TEST', 'description': 'Identification of novel biomarkers from MRI', 'armGroupLabels': ['Control', 'Parkinson disease']}]}, 'contactsLocationsModule': {'centralContacts': [{'name': 'Stephen Mullin, MRCP. PhD.', 'role': 'CONTACT', 'email': 'stephen.mullin@plymouth.ac.uk', 'phone': '01752764487'}, {'name': 'Megan Courtman, MSc.', 'role': 'CONTACT', 'email': 'megan.courtman@postgrad.plymouth.ac.uk', 'phone': '01752764487'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Plymouth', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Clinical Lecturer in Neurology', 'investigatorFullName': 'Stephen Mullin', 'investigatorAffiliation': 'University of Plymouth'}}}}