Ignite Creation Date:
2025-12-24 @ 11:28 PM
Ignite Modification Date:
2025-12-25 @ 9:15 PM
Study NCT ID:
NCT05282056
Status:
COMPLETED
Last Update Posted:
2022-05-04
First Post:
2022-03-14
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
COVID-19 Volumetric Quantification on Computer Tomography Using Computer Aided Diagnostics
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D000086382', 'term': 'COVID-19'}], 'ancestors': [{'id': 'D011024', 'term': 'Pneumonia, Viral'}, {'id': 'D011014', 'term': 'Pneumonia'}, {'id': 'D012141', 'term': 'Respiratory Tract Infections'}, {'id': 'D007239', 'term': 'Infections'}, {'id': 'D014777', 'term': 'Virus Diseases'}, {'id': 'D018352', 'term': 'Coronavirus Infections'}, {'id': 'D003333', 'term': 'Coronaviridae Infections'}, {'id': 'D030341', 'term': 'Nidovirales Infections'}, {'id': 'D012327', 'term': 'RNA Virus Infections'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['PARTICIPANT'], 'maskingDescription': 'The random assignment is done automatically by the CAD system and is not visible to the patient. The radiologist obviously sees which cases have CAD analysis and which not.'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'CAD outputs are turned off for randomly chosen 50% of patients, which represent the control group. The other 50% are analysed using CAD'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 200}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2022-02-24', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-05', 'completionDateStruct': {'date': '2022-03-15', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-05-03', 'studyFirstSubmitDate': '2022-03-14', 'studyFirstSubmitQcDate': '2022-03-14', 'lastUpdatePostDateStruct': {'date': '2022-05-04', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2022-03-16', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2022-03-15', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Mean difference of lung affection quantification percentage', 'timeFrame': 'At CT acquisition time, up to 2 weeks', 'description': 'The objective measurement of lung affection percentage is measured against pixel level labels. A lower difference mean better outcome.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['CAD', 'AI', 'Artificial Intelligence'], 'conditions': ['COVID-19']}, 'referencesModule': {'references': [{'pmid': '36966179', 'type': 'DERIVED', 'citation': 'Bercean BA, Birhala A, Ardelean PG, Barbulescu I, Benta MM, Rasadean CD, Costachescu D, Avramescu C, Tenescu A, Iarca S, Buburuzan AS, Marcu M, Birsasteanu F. Evidence of a cognitive bias in the quantification of COVID-19 with CT: an artificial intelligence randomised clinical trial. Sci Rep. 2023 Mar 25;13(1):4887. doi: 10.1038/s41598-023-31910-3.'}]}, 'descriptionModule': {'briefSummary': 'The aim of the study is to asses the influence of computer aided diagnostic to the process of lung affection quantification on computer tomography in COVID-19 confirmed patients.', 'detailedDescription': "The lung involvement of COVID-19 patients has been showed to be correlated to clinical outcomes and became part of the clinical practice. Even though various scores can be used, the affection estimation is usually done on computer tomography, using radiologists's estimation skills which is a highly subjective process.\n\nArtificial intelligence is a known objective constant and therefore a potential radiologist complement. This trial aims at studying the effect of using a computer aided diagnostic software integrated in the normal clinical practice of radiologists from Timisoara County Emergency Hospital. It uses the AI-PROBE analysis setup, which turns off the CAD outputs for randomly chosen 50% the cases (control) and then compares the radiological reports for differences between the two arms."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD', 'ADULT', 'OLDER_ADULT'], 'minimumAge': '16 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* RT-PCR confirmed patients of COVID-19\n\nExclusion Criteria:\n\n* 15 or lower'}, 'identificationModule': {'nctId': 'NCT05282056', 'briefTitle': 'COVID-19 Volumetric Quantification on Computer Tomography Using Computer Aided Diagnostics', 'organization': {'class': 'INDUSTRY', 'fullName': 'XVision'}, 'officialTitle': 'COVID-19 Volumetric Quantification on Computer Tomography Using Computer Aided Diagnostics', 'orgStudyIdInfo': {'id': '282/01.02.2022'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'CAD analysis', 'description': 'The XVision COVID-19 computer aided diagnostic software is used by radiologist at CT analysis time', 'interventionNames': ['Diagnostic Test: CAD analysis']}, {'type': 'NO_INTERVENTION', 'label': 'No CAD analysis', 'description': 'No CAD analysis is shown to radiologist.'}], 'interventions': [{'name': 'CAD analysis', 'type': 'DIAGNOSTIC_TEST', 'description': 'CAD shows the radiologist automatically delineated areas of potential COVID-19 affection, together with an overall lung affection percentage.', 'armGroupLabels': ['CAD analysis']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Timișoara', 'state': 'Timiș County', 'country': 'Romania', 'facility': 'Pius Brinzeu Timisoara County Emergency Hospital', 'geoPoint': {'lat': 45.75372, 'lon': 21.22571}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED', 'description': 'The statistical analysis, data points and possibly deidentified images.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Bogdan Bercean', 'class': 'INDUSTRY'}, 'collaborators': [{'name': 'Pius Brinzeu Timisoara County Emergency Hospital', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR_INVESTIGATOR', 'investigatorTitle': 'Head of Artificial Intelligence', 'investigatorFullName': 'Bogdan Bercean', 'investigatorAffiliation': 'XVision'}}}}