[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100547647":3},{"organization":4,"armGroups":7,"interventions":10,"overallOfficials":10,"centralContacts":15,"locations":22,"responsibleParty":47,"collaborators":49,"id":56,"slug":57,"hasResults":58,"nctId":59,"briefTitle":60,"officialTitle":61,"acronym":62,"eligibilityCriteria":63,"healthyVolunteers":58,"sex":64,"minAge":65,"maxAge":10,"enrollmentInfo":66,"targetDuration":10,"studyType":69,"phases":10,"briefSummary":70,"conditions":71,"keywords":10,"overallStatus":24,"whyStopped":10,"lastUpdateSubmitDate":74,"lastUpdatePostDateStruct":75,"startDateStruct":78,"completionDateStruct":80,"leadSponsor":82,"locationsCount":83},{"fullName":5,"class":6},"Centro Cardiologico Monzino","OTHER",[8,12],{"label":9,"type":10,"description":11,"interventionNames":10},"Retrospective Cohort",null,"For the retrospective study, we will enrol 3,000 patients \\>18 years old who underwent CCTA and meet all of the inclusion and exclusion criteria, with at least 4-year follow-up. The primary endpoint and patient characteristics will be those of the CTP-PRO study. Since women are less affected by CAD, at a ratio of 35:65, to correct for this expected imbalance we will weight recruitment to obtain relatively sex-balanced cohorts. In subgroups of patients, available data from invasive coronary angiography, FFR and OCT will be collected to help develop, test and refine the diagnostic performance of the automated AI tools.",{"label":13,"type":10,"description":14,"interventionNames":10},"Prospective Cohort","The cohort will include subjects prospectively enrolled in the CCTA arm of the CTP-PRO study. The subjects will be followed-up for 24 months after CCTA.",[16],{"name":17,"role":18,"phone":19,"phoneExt":20,"email":21},"Gianluca Pontone","CONTACT","0258002574","+39","gianluca.pontone@cardiologicomonzino.it",[23,40],{"facility":5,"status":24,"city":25,"state":25,"zip":26,"country":27,"countryCode":28,"cosmosGeoPoint":29,"geoPoint":34,"contacts":35},"RECRUITING","Milan","20131","Italy","IT",{"type":30,"coordinates":31},"Point",[32,33],9.18951,45.46427,{"lat":33,"lon":32},[36],{"name":37,"role":18,"phone":38,"phoneExt":20,"email":39},"Chiara Centenaro","0258002031","chiara.centenaro@cardiologicomonzino.it",{"facility":5,"status":24,"city":25,"state":41,"zip":26,"country":27,"countryCode":28,"cosmosGeoPoint":42,"geoPoint":44,"contacts":45},"MI",{"type":30,"coordinates":43},[32,33],{"lat":33,"lon":32},[46],{"name":37,"role":18,"phone":10,"phoneExt":10,"email":10},{"type":48,"investigatorFullName":10,"investigatorTitle":10,"investigatorAffiliation":10,"oldNameTitle":10,"oldOrganization":10},"SPONSOR",[50,52,54],{"name":51,"class":6},"Fondazione IRCCS Policlinico San Matteo di Pavia",{"name":53,"class":6},"Politecnico di Milano",{"name":55,"class":6},"Scientific Institute San Raffaele","100547647","trustworthy-integrated-artificial-intelligence-tools-for-predicting-high-risk-coronary-plaques-100547647",false,"NCT06410690","Trustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS","Rustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS","AI-CORPS","Inclusion Criteria:\n\n* patients (age ≥ 18 years) with known or suspected CAD referred for clinically indicated diagnostic evaluation;\n* CCTA performed with state-of-the-art scanner technology, i.e., scanners with more than 64 slices.\n\nExclusion Criteria:\n\n* performance of any non-invasive diagnostic test within 90 days before enrolment;\n* low-to-intermediate pre-test likelihood of CAD according to the updated Diamond-Forrester risk model score;\n* acute coronary syndrome;\n* evidence of clinical instability;\n* contraindication to contrast agent administration and\u002For impaired renal function;\n* inability to sustain a breath hold;\n* pregnancy;\n* cardiac arrhythmias;- presence of a pacemaker or implantable cardioverter defibrillator;\n* contraindications to the administration of sublingual nitrates, β-blockers or adenosine;\n* structural cardiomyopathy","ALL","18 Years",{"count":67,"type":68},4000,"ESTIMATED","OBSERVATIONAL","Coronary artery disease (CAD) is among the leading cause of death and disability. Identification of patients at high risk of cardiovascular events is pivotal. However, current risk stratification based on imaging and known biomarkers is suboptimal. The objective of this proposal is to develop a multicriteria decision model for non-invasive assessment of vulnerable atherosclerotic patients and to evaluate its ability to predict the occurrence of an adverse event in intermediate-to-high risk patients with suspected or known CAD. The planned workflow includes a first step using a retrospective cohort of patients undergoing clinically indicated coronary angiography (CCTA) to develop an integrated application for automatic coronary artery segmentation, quantitative plaque analysis, biomechanics and fluid dynamics, based on machine learning, radiomics and computational analysis approaches and validated against the reference standard for each tool. The second step will apply this new methodology to a larger retrospective cohort of patients with the integration of genomic biomarker assessment to derive the most accurate risk stratification model to properly identify vulnerable patients and vulnerable plaques with respect to outcome. Finally, in the third step, the derived predictive model will be prospectively validated in an independent cohort of patients from an ongoing study (CTP-PRO study) to assess the robustness and accuracy of the proposed solution.",[72,73],"Coronary Artery Disease","Coronary Computed Tomography Angiography","2026-05-26",{"date":76,"type":77},"2026-05-29","ACTUAL",{"date":79,"type":77},"2023-05-22",{"date":81,"type":68},"2026-11-30",{"name":5,"class":6},2]