Ignite Creation Date:
2025-12-25 @ 2:19 AM
Ignite Modification Date:
2025-12-27 @ 11:06 PM
Study NCT ID:
NCT05146934
Status:
COMPLETED
Last Update Posted:
2021-12-07
First Post:
2021-06-30
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
The Relationship Between Hormone Sensitivity and Imaging of Idiopathic Interstitial Pneumonia by Artificial Intelligence
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D054988', 'term': 'Idiopathic Interstitial Pneumonias'}], 'ancestors': [{'id': 'D054990', 'term': 'Idiopathic Pulmonary Fibrosis'}, {'id': 'D011658', 'term': 'Pulmonary Fibrosis'}, {'id': 'D017563', 'term': 'Lung Diseases, Interstitial'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'RETROSPECTIVE', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 150}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2019-12-30', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2021-06', 'completionDateStruct': {'date': '2021-06-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2021-11-23', 'studyFirstSubmitDate': '2021-06-30', 'studyFirstSubmitQcDate': '2021-11-23', 'lastUpdatePostDateStruct': {'date': '2021-12-07', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2021-12-07', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-06-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'development of artificial intelligence algorithm model', 'timeFrame': '3-6 months after medication', 'description': 'The U-net method of deep learning convolutional neural network (CNN) was used to create the recognition model of different imaging features. Imaging features include ground-glass opacity, reticulation, honeycomb and consolidation. With the area ratio of imaging features of the two groups as the input and hormone efficacy as the output, the correlation model between imaging features and hormone sensitivity was established by using artificial intelligence k nearest neighbor (KNN) algorithm and support vector machine (SVM) algorithm.'}], 'primaryOutcomes': [{'measure': 'clinical data and imaging feature ratios in both groups', 'timeFrame': '3-6 months after medication', 'description': 'clinical data including ages，gender，symptoms,signs,smoking history,complications,laboratory examination，lung function. Imaging feature including ground-glass opacity, reticulation, honeycomb and consolidation.'}], 'secondaryOutcomes': [{'measure': 'the relationship between imaging feature ratios and hormone sensibility', 'timeFrame': '3-6 months after medication', 'description': 'Logistic regression analyzing the relationship between imaging feature ratios and hormone sensibility.'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Hormone sensitivity', 'imaging features', 'artificial intelligence'], 'conditions': ['Idiopathic Interstitial Pneumonia']}, 'descriptionModule': {'briefSummary': 'Application of artificial intelligence deep learning algorithm to analyze the relationship between hormone sensitivity of idiopathic interstitial pneumonia and imaging features of high resolution CT.', 'detailedDescription': 'Methods: the medical records and chest high-resolution CT images of patients with idiopathic interstitial pneumonia admitted to the respiratory department of the Third Hospital of Peking University from June 1, 2012 to December 31, 2020 were retrospectively analyzed.Application of artificial intelligence deep learning neural convolution network method to create recognition technology of different imaging features.Including ground glass, mesh, honeycomb, nodule or consolidation, the model was established. IIP patients were divided into hormone sensitive group and hormone insensitive group according to whether the use of hormone was effective or not.Logistic regression analysis was used to analyze the correlation between statistically significant parameters and hormone sensitivity.Artificial intelligence was used to establish the correlation model between imaging features and clinical data and hormone sensitivity.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '90 Years', 'minimumAge': '18 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'From June 1, 2012 to December 31, 2020, all inpatients with IIP were admitted to the respiratory and critical care department of the Third Hospital of Peking University. Total patients are 150, 45 patients using hormone, average age 62 years old, 21 male.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\nClinical-pathological-radiology diagnosis of idiopathic interstitial pneumonia Hormone therapy was used; The follow-up data were complete, and the effect of hormone use could be judged.\n\nExclusion Criteria:\n\nLung infection disease; Heart failure; Connective tissue disease; IIP Without hormone therapy ; IIP but the follow-up data were incomplete, and the effect of hormone use could not be judged.'}, 'identificationModule': {'nctId': 'NCT05146934', 'acronym': 'IIP', 'briefTitle': 'The Relationship Between Hormone Sensitivity and Imaging of Idiopathic Interstitial Pneumonia by Artificial Intelligence', 'organization': {'class': 'OTHER', 'fullName': 'Peking University Third Hospital'}, 'officialTitle': 'The Relationship Between Hormone Sensitivity and Imaging of Idiopathic Interstitial Pneumonia by Artificial Intelligence', 'orgStudyIdInfo': {'id': 'LM2019173'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Hormone sensitive group', 'description': 'Prednisone, 0.5mg/kgqd, 3-6months', 'interventionNames': ['Radiation: high resolution CT']}, {'label': 'Hormone insensitivity group', 'description': 'Prednisone, 0.5mg/kgqd, 3-6months', 'interventionNames': ['Radiation: high resolution CT']}], 'interventions': [{'name': 'high resolution CT', 'type': 'RADIATION', 'description': 'Ground glass，honeycomb，reticulation, consolidation', 'armGroupLabels': ['Hormone insensitivity group', 'Hormone sensitive group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '100191', 'city': 'Beijing', 'state': 'Beijing Municipality', 'country': 'China', 'facility': 'Peking University Third Hospital', 'geoPoint': {'lat': 39.9075, 'lon': 116.39723}}], 'overallOfficials': [{'name': 'Bei He', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Peking University Third Hospital Respiratory and critical care department'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Peking University Third Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}