Ignite Creation Date:
2025-12-24 @ 2:15 PM
Ignite Modification Date:
2026-01-02 @ 1:11 PM
Study NCT ID:
NCT04580095
Status:
COMPLETED
Last Update Posted:
2022-04-14
First Post:
2020-09-23
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Artificial Intelligence for Improved Echocardiography
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D006331', 'term': 'Heart Diseases'}], 'ancestors': [{'id': 'D002318', 'term': 'Cardiovascular Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'OTHER', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 88}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-09-29', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-04', 'completionDateStruct': {'date': '2021-06-30', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-04-07', 'studyFirstSubmitDate': '2020-09-23', 'studyFirstSubmitQcDate': '2020-10-02', 'lastUpdatePostDateStruct': {'date': '2022-04-14', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-10-08', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-06-30', 'type': 'ACTUAL'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Image quality', 'timeFrame': '0 days', 'description': 'Image quality will be evaluated in a blinded manner by echocardiography experts post hoc. A standardized scoring system for image quality in echocardiography developed locally will be utilized for evaluation with score 1-6, where 1 is minimum and 6 is maximum score. The two study arms will be compared.'}, {'measure': 'Inter-observer variation of left ventricular size', 'timeFrame': '0 days', 'description': 'Throughout this study, the sonographers and expert cardiologist will perform measurements based on their individual echocardiographic images. Differences in measurements will be evaluated to determine inter-observer variation between sonographers and cardiologists.'}, {'measure': 'Inter-observer variation of left ventricular function', 'timeFrame': '0 days', 'description': 'Throughout this study, the sonographers and expert cardiologist will perform measurements based on their individual echocardiographic images. Differences in measurements will be evaluated to determine inter-observer variation between sonographers and cardiologists.'}, {'measure': 'Validation of AI algorithm to detect foreshortening', 'timeFrame': '0 days', 'description': 'Comparison of AI algorithm to detect foreshortening with manual reference'}, {'measure': 'Inter-observer variation of left atrial size', 'timeFrame': '0 days', 'description': 'Throughout this study, the sonographers and expert cardiologist will perform measurements based on their individual echocardiographic images. Differences in measurements will be evaluated to determine inter-observer variation between sonographers and cardiologists.'}, {'measure': 'Inter-observer variation of left atrial function', 'timeFrame': '0 days', 'description': 'Throughout this study, the sonographers and expert cardiologist will perform measurements based on their individual echocardiographic images. Differences in measurements will be evaluated to determine inter-observer variation between sonographers and cardiologists.'}, {'measure': 'Development of AI algorithm for real-time assessment of left atrium', 'timeFrame': '0 days', 'description': 'Cardiac structures as left atrial (LA) lumen, LA wall, LA appendix, mitral valve will be annotated and used as reference.'}, {'measure': 'Variation by methodology', 'timeFrame': '0 days', 'description': 'Variation in measurement by the mode of measurement'}], 'primaryOutcomes': [{'measure': 'Left ventricular apical foreshortening', 'timeFrame': '0 days', 'description': 'Apical foreshortening will be evaluated in a blinded manner by echocardiography experts post hoc. The two study arms will be compared.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Heart Diseases']}, 'referencesModule': {'references': [{'pmid': '41360622', 'type': 'DERIVED', 'citation': 'Pettersen H, Sabo S, Pasdeloup D, Smistad E, Olaisen S, Ostvik A, Stolen S, Grenne BL, Lovstakken L, Dalen H, Holte E. Real-time deep learning-based image guiding and automated left ventricular measurements to reduce test-retest variability. Open Heart. 2025 Dec 7;12(2):e003783. doi: 10.1136/openhrt-2025-003783.'}, {'pmid': '39045079', 'type': 'DERIVED', 'citation': 'Sabo S, Pasdeloup D, Pettersen HN, Smistad E, Ostvik A, Olaisen SH, Stolen SB, Grenne BL, Holte E, Lovstakken L, Dalen H. Real-time guidance by deep learning of experienced operators to improve the standardization of echocardiographic acquisitions. Eur Heart J Imaging Methods Pract. 2023 Nov 27;1(2):qyad040. doi: 10.1093/ehjimp/qyad040. eCollection 2023 Sep.'}, {'pmid': '39044792', 'type': 'DERIVED', 'citation': 'Sabo S, Pettersen HN, Smistad E, Pasdeloup D, Stolen SB, Grenne BL, Lovstakken L, Holte E, Dalen H. Real-time guiding by deep learning during echocardiography to reduce left ventricular foreshortening and measurement variability. Eur Heart J Imaging Methods Pract. 2023 Aug 1;1(1):qyad012. doi: 10.1093/ehjimp/qyad012. eCollection 2023 May.'}]}, 'descriptionModule': {'briefSummary': 'The purpose of this study is to assess the effect of artificial intelligence algorithms on image quality in echocardiography.', 'detailedDescription': 'The study population will be recruited from appointed patients at the Clinic of Cardiology, St. Olavs Hospital. After being informed about the study, all patients giving informed consent and meeting the eligibility requirements will undergo their standard clinical echocardiographic exam performed by a sonographer at the clinic. Two additional examinations will then be performed by a different sonographer and an expert cardiologist, respectively.\n\nIn one of the study arms the sonographer randomized to perform the second exam will use the AI algorithm (intervention).'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Capacity to consent\n\nExclusion Criteria:\n\n* Indication for echocardiographic contrast agents'}, 'identificationModule': {'nctId': 'NCT04580095', 'briefTitle': 'Artificial Intelligence for Improved Echocardiography', 'organization': {'class': 'OTHER', 'fullName': 'Helse Nord-Trøndelag HF'}, 'officialTitle': 'Technology Revisiting Ultrasound Solutions of Tomorrow - Artificial Intelligence for Improved Echocardiography', 'orgStudyIdInfo': {'id': 'TRUST-AI_201'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'With AI algorithm', 'description': 'In the "With AI algorithm" arm, the sonographer will perform the echocardiographic exam using the AI algorithm.', 'interventionNames': ['Other: AI algorithm for apical foreshortening in echocardiography']}, {'type': 'NO_INTERVENTION', 'label': 'Without AI algorithm', 'description': 'In the "Without AI algorithm", the echocardiographic exam will be performed without the use of the AI algorithm.'}], 'interventions': [{'name': 'AI algorithm for apical foreshortening in echocardiography', 'type': 'OTHER', 'description': 'The algorithm is based on artificial intelligence, giving the sonographer performing the echocardiographic exam real-time feedback on left ventricular apical foreshortening.The algorithm is developed using deep learning techniques by technologists at the Department of Circulation and Medical Imaging, NTNU.', 'armGroupLabels': ['With AI algorithm']}]}, 'contactsLocationsModule': {'locations': [{'zip': '7491', 'city': 'Trondheim', 'country': 'Norway', 'facility': 'St. Olav University Hospital', 'geoPoint': {'lat': 63.43049, 'lon': 10.39506}}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Helse Nord-Trøndelag HF', 'class': 'OTHER'}, 'collaborators': [{'name': 'St. Olavs Hospital', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}