Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24', 'removedCountries': ['Australia', 'Japan', 'South Korea']}, 'conditionBrowseModule': {'meshes': [{'id': 'D003324', 'term': 'Coronary Artery Disease'}, {'id': 'D006331', 'term': 'Heart Diseases'}], 'ancestors': [{'id': 'D003327', 'term': 'Coronary Disease'}, {'id': 'D017202', 'term': 'Myocardial Ischemia'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D001161', 'term': 'Arteriosclerosis'}, {'id': 'D001157', 'term': 'Arterial Occlusive Diseases'}, {'id': 'D014652', 'term': 'Vascular Diseases'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 218}, 'targetDuration': '1 Day', 'patientRegistry': True}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2013-05'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2015-03', 'completionDateStruct': {'date': '2015-03', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2015-03-31', 'studyFirstSubmitDate': '2013-05-15', 'studyFirstSubmitQcDate': '2013-05-15', 'lastUpdatePostDateStruct': {'date': '2015-04-03', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2013-05-17', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2015-03', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Diagnostic Accuracy', 'timeFrame': '30 days', 'description': 'To compare the per-patient, per-vessel and per-segment diagnostic accuracy of CCTA with SSF to conventional CCTA, as compared to invasive quantitative coronary angiography.'}, {'measure': 'Diagnostic Interpretability', 'timeFrame': '30 days', 'description': 'To compare the per-patient, per-vessel and per-segment diagnostic interpretability of CCTA with SSF to conventional CCTA, as compared to invasive quantitative coronary angiography.'}, {'measure': 'Image quality', 'timeFrame': '30 day', 'description': 'To compare the per-patient, per-vessel and per-segment quantitative image quality of CCTA with SSF to conventional CCTA, as compared to invasive quantitative coronary angiography.'}], 'secondaryOutcomes': [{'measure': 'Upper threshold of heart rate', 'timeFrame': '1 day', 'description': 'To determine the upper threshold of heart rate below which CCTA with SSF is most effective.'}, {'measure': 'incremental & additive value', 'timeFrame': '1 day', 'description': 'To determine the incremental \\& additive value of SSF to conventional CCTA for diagnostic accuracy / diagnostic interpretability / image quality.'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'keywords': ['Heart Disease', 'Coronary Artery Disease', 'Coronary Arteriosclerosis'], 'conditions': ['Coronary Artery Disease', 'Coronary Arteriosclerosis']}, 'descriptionModule': {'briefSummary': 'To demonstrate the incremental utility of SSF for individuals undergoing CCTA, with expected improvements in image quality and diagnostic accuracy.', 'detailedDescription': 'Hypothesis: Coronary CT angiography (CCTA) employing a novel intracycle motion compensation algorithm (SnapShot Freeze \\[SSF\\]) will be superior to CCTA without an intracycle motion compensation algorithm ("conventional" CCTA) for diagnostic accuracy and image quality.\n\nScientific Basis: Preliminary study (Leipsic, Min, Journal of Cardiovascular Computed Tomography \\[in press\\]) of coronary CT angiograms in individuals undergoing pre-procedural assessment for transcatheter aortic valve replacement (n=36) demonstrate improved image quality of CCTA using SSF compared to CCTA not using SSF. Importantly, individuals in this study did not receive heart rate slowing agents (e.g., beta blockers), and diagnostic image quality was substantially improved. While not statistically powered on a per-patient basis, per-segment diagnostic accuracy of CCTA using SSF was superior to conventional CCTA. These results are complementary to those derived from internal testing at GE Healthcare wherein phantom work has demonstrated improved diagnostic performance using SSF compared to conventional image acquisitions.\n\nLong-term Goal/Purpose: To demonstrate the incremental utility of SSF for individuals undergoing CCTA, with expected improvements in image quality and diagnostic accuracy. If the aims of this study are achieved, the use of SSF for effective temporal resolution improvement may obviate (or reduce) the need for CT hardware for improved temporal resolution.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'Consenting adult patients ≥18 years of age, Suspected but without known prior history of CAD, Not actively taking heart rate lowering agents at least 48 hours prior to study (e.g., AV nodal blockers such as beta blockers, calcium channel blockers or digoxin)', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Consenting adult patients ≥18 years of age;\n2. Suspected but without known prior history of CAD\n3. Not actively taking heart rate lowering agents at least 48 hours prior to study (e.g., AV nodal blockers such as beta blockers, calcium channel blockers or digoxin)\n4. Glomerular filtration rate \\>60 ml/min\n5. CCTA and ICA within 1 week of each other with no interscan event (e.g., myocardial infarction or coronary revascularization)\n\nExclusion Criteria:\n\n1. Incomplete ICA or CCTA;\n2. Known CAD (prior myocardial infarction, PCI, CABG)\n3. Atrial Fibrillation\n4. Abnormal Renal Function (GFR \\<60 ml/min)\n5. Unwilling or unable to give consent\n6. Non-cardiac illness with life expectancy \\<1 year\n7. Concomitant participation in another clinical trial in which subject is subject to investigational drug or device\n8. Pregnant women\n9. Allergy to iodinated contrast agent\n10. Contraindications to nitroglycerin\n11. Systolic blood pressure ≤90 mm Hg\n12. Contraindications to β blockers or nitroglycerin'}, 'identificationModule': {'nctId': 'NCT01856504', 'acronym': 'VICTORY', 'briefTitle': 'Validation of an Intracycle CT Motion CORrection Algorithm for Diagnostic AccuracY', 'organization': {'class': 'INDUSTRY', 'fullName': 'MDDX LLC'}, 'officialTitle': 'Validation of an Intracycle CT Motion CORrection Algorithm for Diagnostic AccuracY: A Prospective Multicenter Study', 'orgStudyIdInfo': {'id': 'VICTORY'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'CCTA Patient', 'description': '1. Consenting adult patients ≥18 years of age;\n2. Suspected but without known prior history of CAD\n3. Not actively taking heart rate lowering agents at least 48 hours prior to study (e.g., AV nodal blockers such as beta blockers, calcium channel blockers or digoxin)\n4. Glomerular filtration rate \\>60 ml/min\n5. CCTA and ICA within 1 week of each other with no interscan event (e.g., myocardial infarction or coronary revascularization)'}]}, 'contactsLocationsModule': {'locations': [{'zip': '94104', 'city': 'San Francisco', 'state': 'California', 'country': 'United States', 'facility': 'MDDX', 'geoPoint': {'lat': 37.77493, 'lon': -122.41942}}, {'city': 'Bethesda', 'state': 'Maryland', 'country': 'United States', 'facility': 'Walter Reed Medical Center', 'geoPoint': {'lat': 38.98067, 'lon': -77.10026}}, {'city': 'Independence', 'state': 'Missouri', 'country': 'United States', 'facility': 'Midwest Cardiology Associates', 'geoPoint': {'lat': 39.09112, 'lon': -94.41551}}, {'city': 'San Isidro', 'country': 'Argentina', 'facility': 'Diagnostico Maipu', 'geoPoint': {'lat': -34.46971, 'lon': -58.52111}}, {'zip': 'V6T 1Z4', 'city': 'Vancouver', 'state': 'British Columbia', 'country': 'Canada', 'facility': 'University of British Columbia', 'geoPoint': {'lat': 49.24966, 'lon': -123.11934}}, {'city': 'Hyderabad', 'country': 'India', 'facility': 'FACTS', 'geoPoint': {'lat': 17.38405, 'lon': 78.45636}}, {'city': 'Monzino', 'country': 'Italy', 'facility': 'Centro Cardiologico Monzino'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'MDDX LLC', 'class': 'INDUSTRY'}, 'collaborators': [{'name': 'GE Healthcare', 'class': 'INDUSTRY'}], 'responsibleParty': {'type': 'SPONSOR'}}}}