Ignite Creation Date:
2025-12-25 @ 1:01 AM
Ignite Modification Date:
2025-12-26 @ 1:35 PM
Study NCT ID:
NCT05614193
Status:
RECRUITING
Last Update Posted:
2023-02-08
First Post:
2022-11-05
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Deep Enhanced Imaging in Stroke and Vascular Neurology
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D020521', 'term': 'Stroke'}, {'id': 'D014652', 'term': 'Vascular Diseases'}, {'id': 'D002561', 'term': 'Cerebrovascular Disorders'}], 'ancestors': [{'id': 'D001927', 'term': 'Brain Diseases'}, {'id': 'D002493', 'term': 'Central Nervous System Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_ONLY'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 1000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2022-12-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-02', 'completionDateStruct': {'date': '2027-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-02-07', 'studyFirstSubmitDate': '2022-11-05', 'studyFirstSubmitQcDate': '2022-11-05', 'lastUpdatePostDateStruct': {'date': '2023-02-08', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-11-14', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2027-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The performance of deep enhanced imaging in lesion detection and diagnosis', 'timeFrame': '1 year', 'description': 'The performance of deep enhanced imaging in lesion detection and diagnosis, including imaging quality, accuracy, sensitivity and specificity in lesion detection and imaging diagnosis.'}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Deep learning', 'Medical imaging', 'Cerebral stroke', 'Cerebrovascular disease', 'Vascular imaging'], 'conditions': ['Radiology', 'Cerebral Stroke', 'Vascular Diseases']}, 'descriptionModule': {'briefSummary': "To investigate the performance of enhanced computed tomography (CT) or magnetic resonance (MR) imaging by deep learning relative to conventional CT or MR imaging in brain stroke and vascular neurology. We expect that the deep enhanced imaging method can shorten the time stay in the imaging session of stroke patients, optimize the overall imaging quality and improve the patients' care in imaging session.", 'detailedDescription': "Early diagnosis of cerebral infarction, detection of ischemic penumbra, evaluation of collateral circulation and identification of vascular lesions by imaging are critical for treatment decision and outcome improvement in cerebral stroke. Multimodal computed tomography (CT) and magnetic resonance (MR) imaging are most prevalent and accessible approaches in clinical scenarios. These two approaches are downgraded either by radiation exposure or long scanning time which may hinder the rapid treatment for patients. Deep learning has shown substantial achievements in medical imaging enhancement. The added value of deep learning method in stroke and vascular neurology has not been thoroughly validated. In this study, we aimed to investigate the performance of enhanced computed tomography (CT) or magnetic resonance (MR) imaging by deep learning relative to conventional CT or MR imaging in brain stroke and vascular neurology. We expect that the deep enhanced imaging method can shorten the time stay in the imaging session of stroke patients, optimize the overall imaging quality and improve the patients' care in imaging session."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '100 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients have experienced stroke or cerebral ischemia and undergone brain imaging and vascular imaging.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* suspecting to have experienced stroke or cerebral ischemia and needed to undergo brain imaging and vascular imaging including CT or MRI\n* no history of kidney failure\n* a minimum age of 18 years\n* obtained written informed consent\n\nExclusion Criteria:\n\n* severe movement artifacts\n* incidental finding of tumor lesion or craniocerebral surgery history\n* poor imaging failed to perform deep learning method\n* women who pregnancy'}, 'identificationModule': {'nctId': 'NCT05614193', 'briefTitle': 'Deep Enhanced Imaging in Stroke and Vascular Neurology', 'organization': {'class': 'OTHER', 'fullName': 'Chinese PLA General Hospital'}, 'officialTitle': 'Deep Enhanced Imaging in Stroke and Vascular Neurology', 'orgStudyIdInfo': {'id': 'AI-301'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Imaging group', 'description': 'Participants with suspecting brain stroke or vascular lesion conducted conventional CT or MR imaging and deep enhanced imaging.', 'interventionNames': ['Diagnostic Test: Deep learning imaging enhancement']}], 'interventions': [{'name': 'Deep learning imaging enhancement', 'type': 'DIAGNOSTIC_TEST', 'description': 'Conventional imaging or down-sampling imaging from CT or MR are enhanced by approved deep learning method.', 'armGroupLabels': ['Imaging group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '100853', 'city': 'Beijing', 'state': 'Beijing Municipality', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Jinhao Lyu, MD', 'role': 'CONTACT', 'email': '330322990@qq.com'}], 'facility': 'Chinese PLA General Hospital', 'geoPoint': {'lat': 39.9075, 'lon': 116.39723}}], 'centralContacts': [{'name': 'Jinhao Lyu', 'role': 'CONTACT', 'email': '330322990@qq.com', 'phone': '+8615903562929'}], 'overallOfficials': [{'name': 'Lou Xin', 'role': 'STUDY_CHAIR', 'affiliation': 'Chinese PLA General Hospital'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Chinese PLA General Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Chairman', 'investigatorFullName': 'Xin Lou', 'investigatorAffiliation': 'Chinese PLA General Hospital'}}}}