[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"heart-ventricles\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:heart-ventricles":30},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,1,0,[8],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":11,"sex":17,"minAge":18,"maxAge":19,"enrollmentInfo":20,"targetDuration":23,"studyType":24,"phases":4,"briefSummary":25,"conditions":26,"keywords":34,"overallStatus":42,"whyStopped":4,"lastUpdateSubmitDate":43,"lastUpdatePostDateStruct":44,"startDateStruct":47,"completionDateStruct":49,"leadSponsor":51,"locationsCount":5},"100598543","using-cardiac-mri-to-predict-outcomes-in-patients-with-stemi-100598543",false,"NCT07072858","Using Cardiac MRI to Predict Outcomes in Patients With STEMI","Prognostic Value of Cardiac Magnetic Resonance Parameters in Patients With ST-Segment Elevation Myocardial Infarction","CMR-RISK-STEMI","Inclusion Criteria:\n\n* Age between 18 and 80 years\n\nDiagnosed with ST-segment elevation myocardial infarction (STEMI), defined as chest pain with ST-segment elevation on ECG and elevated cardiac troponin levels\n\nUnderwent primary percutaneous coronary intervention (PCI)\n\nAble to undergo cardiac magnetic resonance (CMR) imaging within 7 days post-PCI\n\nProvided written informed consent\n\nExclusion Criteria:\n\n* Contraindications to CMR (e.g., severe claustrophobia, implanted cardiac defibrillators or non-compatible pacemakers)\n\nHistory of revascularization therapy (PCI or CABG) within the previous 6 months\n\nSevere valvular heart disease or known cardiomyopathy\n\nPresence of bundle branch block or fascicular block that interferes with image interpretation\n\nKnown allergy to gadolinium-based contrast agents (for those undergoing contrast-enhanced sequences)\n\nEstimated glomerular filtration rate (eGFR) \\\u003C30 mL\u002Fmin\u002F1.73m² (if contrast use is anticipated)\n\nPregnant or breastfeeding women","ALL","18 Years","80 Years",{"count":21,"type":22},1000,"ESTIMATED","5 Years","OBSERVATIONAL","This prospective, multicenter observational study aims to evaluate the prognostic value of a comprehensive set of cardiac magnetic resonance (CMR) imaging parameters in patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI). The study integrates advanced artificial intelligence (AI) techniques to extract and analyze high-dimensional imaging features from multiple CMR sequences-including cine, strain mapping, and functional sequences-going beyond traditional measures such as infarct size or microvascular obstruction.\n\nThe primary objective is to identify novel prognostic markers from routinely acquired CMR images that reflect myocardial structure, function, and mechanical deformation (strain), and to assess their association with long-term clinical outcomes. In addition to standard parameters, the study includes a detailed evaluation of left and right ventricular systolic and diastolic volumes, ejection fractions, and biventricular strain components (including longitudinal, circumferential, and radial strain), as well as left and right atrial volumes, emptying fractions, and reservoir\u002Fconduit\u002Fbooster strain indices.\n\nApproximately 1000 STEMI patients will undergo CMR scanning within one week after PCI. The imaging data will be subjected to AI-based feature extraction and dimensionality reduction algorithms to uncover latent patterns associated with adverse outcomes. Patients will be followed for up to three years for the occurrence of major adverse cardiovascular events (MACE), including cardiovascular death, recurrent myocardial infarction, and heart failure hospitalization.\n\nThe central hypothesis is that comprehensive CMR functional and strain-derived parameters, when analyzed using AI-driven models, offer independent and incremental prognostic value beyond conventional clinical risk factors. This study seeks to establish a data-driven, multimodal imaging framework for personalized risk stratification in STEMI patients, potentially enabling more precise post-infarction management strategies.\n\nNo investigational treatment is involved. All imaging and clinical data are collected as part of routine care and analyzed retrospectively for outcome prediction.",[27,28,29,30,31,32,33],"Myocardial Infarction (MI)","ST Segment Elevation Myocardial Infarction (STEMI)","Magnetic Resonance Imaging (MRI)","Heart Ventricles","Artificial Intelligence (AI)","Prognosis","Ventricular Dysfunction",[35,36,37,38,39,40,41],"ST Segment Elevation Myocardial Infarction","Cardiac Magnetic Resonance Imaging","Cardiac Strain Imaging","Machine Learning","Image Analysis","Survival Analysis","Multimodal Imaging","RECRUITING","2025-07-09",{"date":45,"type":46},"2025-07-18","ACTUAL",{"date":48,"type":46},"2014-01-01",{"date":50,"type":22},"2025-12-30",{"name":52,"class":53},"Chinese PLA General Hospital","OTHER"]