Using Cardiac MRI to Predict Outcomes in Patients With STEMI
NCT ID: NCT07072858
Last Updated: 2025-07-18
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
RECRUITING
1000 participants
OBSERVATIONAL
2014-01-01
2025-12-30
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
The 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/conduit/booster strain indices.
Approximately 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.
The 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.
No investigational treatment is involved. All imaging and clinical data are collected as part of routine care and analyzed retrospectively for outcome prediction.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Impact of Persistent Microvascular Obstruction by Cardiac Magnetic Resonance on Prognosis for ST-segment Elevation Myocardial Infarction
NCT06759532
CMR for Prognosis Assessment in NSTEMI
NCT03516578
Development and Validation of a Cardiac Magnetic Resonance-Based Multimodal Deep Learning Model for Long-Term Outcome Prediction in ST-Segment Elevation Myocardial Infarction
NCT07277400
A Prospective Multicenter Clinical Study on the Long-term Prognosis of Patients With ST-segment Elevation Myocardial Infarction Using Cardiac Magnetic Resonance Imaging.
NCT07057492
Predictive Value of Cardiovascular Magnetic Resonance Related Parameters in STEMI Patients After Primary PCI for Adverse Left Ventricular Remodeling and Major Adverse Cardiovascular Events
NCT04789564
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Traditional CMR indicators such as infarct size, left ventricular ejection fraction (LVEF), and microvascular obstruction (MVO) have demonstrated utility in post-MI risk stratification. However, these parameters do not fully exploit the wealth of information embedded within the full CMR dataset, especially data reflecting myocardial and atrial mechanics. In this study, we apply advanced computational methods-including radiomics, machine learning, and survival modeling techniques-to analyze multidimensional features extracted from routine, non-contrast CMR sequences.
CMR image acquisition includes short-axis cine imaging and dedicated functional sequences allowing for the quantification of bi-ventricular and bi-atrial function and deformation. Specifically, the following parameters are collected and analyzed:
* Left Ventricular (LV) Parameters LV End-Diastolic Volume (LVEDV) LV End-Systolic Volume (LVESV) LV Stroke Volume (LVSV) LVEF Global Longitudinal Strain (LVGLS) Global Circumferential Strain (LVGCS) Global Radial Strain (LVGRS)
* Right Ventricular (RV) Parameters RVEDV RVESV RVSV RV Mass RVEF RVGLS, RVGCS, RVGRS
* Left Atrial (LA) Parameters Maximum Volume (LAVmax) Pre-Atrial Contraction Volume (LAVpac) Minimum Volume (LAVmini) Total, Passive, and Booster Emptying Fractions (LAEF) Reservoir, Conduit, and Booster Strain
* Right Atrial (RA) Parameters RAVmax RAVpac RAVmini Total, Passive, and Booster RAEF RA Reservoir, Conduit, and Booster Strain All images are analyzed by trained imaging specialists using semi-automated tools (e.g., CVI42) for myocardial and atrial contouring. The left ventricular myocardium is segmented at the end-diastolic phase, and regions of interest (ROIs) are exported for radiomic analysis using ITK-SNAP and PyRadiomics. Preprocessing includes voxel size resampling, normalization, and gray-level discretization.
To ensure reliability and minimize redundancy, feature selection is performed in several stages. First, features with intra- and inter-observer intraclass correlation coefficients (ICC) ≥ 0.75 are retained. Second, highly collinear features are removed using correlation thresholding. Third, feature importance is assessed via random survival forests (RSF), followed by least absolute shrinkage and selection operator (LASSO) Cox regression to construct an optimized feature set. Selected features are used to calculate a radiomics-based risk score (RAD score), which is incorporated into survival models.
Patients are divided into a training and validation cohort using stratified random sampling based on MACE incidence. The primary outcome is the occurrence of major adverse cardiovascular events (MACE), including cardiovascular death, reinfarction, and heart failure hospitalization. Prognostic models are developed using multivariable Cox regression and evaluated using Harrell's concordance index (C-index), calibration plots, and time-dependent receiver operating characteristic (ROC) curves. Risk stratification analyses are conducted across subgroups defined by conventional imaging markers (e.g., infarct size, LVEF, MVO).
The analysis pipeline is implemented using R software, and internal validation is performed to assess model stability. Multiple imputation is used to address missing data, and sensitivity analyses are conducted to test the robustness of the predictive models under various assumptions. No experimental intervention or investigational drug is administered in this study; data collection is non-interventional and integrated into routine clinical care.
The anticipated contribution of this study is to establish a multimodal, AI-enhanced imaging framework that enables individualized post-STEMI risk assessment using routinely available CMR data. By going beyond visually assessed or conventional parameters, this study may uncover novel patterns of myocardial and atrial dysfunction predictive of long-term outcomes. Furthermore, the use of non-contrast imaging sequences enhances the generalizability and safety of the proposed risk evaluation method.
The protocol is approved by the institutional ethics committee. Quality control includes standardized image acquisition and analysis procedures across centers. Data processing follows pre-specified standard operating procedures (SOPs) for image segmentation, radiomic feature extraction, and modeling. Manual and automated data checks are implemented to ensure consistency and accuracy. The imaging core lab and analytic team remain blinded to outcome data during feature extraction and model construction phases.
By combining cutting-edge image analysis with real-world clinical data, this study aims to inform future CMR-based guidelines for post-infarction care and to facilitate clinical translation of advanced imaging biomarkers into personalized cardiology.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
COHORT
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
STEMI Patients Undergoing CMR After PCI
Cardiac Magnetic Resonance Imaging (CMR)
Cine CMR imaging was performed with steady-state free precession covering short axis continuously from the mitral annulus to the apical level in the 2-, 3- and 4- chamber views using the following parameters: repetition time (TR) = 3.73 ms, echo time (TE) = 1.87 ms, flip angle = 60°, slice thickness 8.0 mm. Cine images of all included patients were acquired prior to contrast administrations. Late gadolinium enhancement images (LGE) images were obtained 10-15 minutes after intravenous injection of gadolinium (0.1 mmol/kg at 3ml/s) at end-diastolic phase on the short axis (TR=6.09 ms; TE= 3.0 ms; flip angle 60°; thickness 8.0 mm) with breath-hold phase-sensitive segmented inversion recovery (PSIR) fast field echo sequence. T2-weighted sequence was performed using turbo spin-echo (TSE)-sequence (TR=1714-2000 ms; TE=8.04 ms; slice thickness 8.0 mm) to estimate myocardial edema. Images were analyzed on freely available validated cardiovascular image analysis software CVI42 (Circle Cardiovas
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
Cardiac Magnetic Resonance Imaging (CMR)
Cine CMR imaging was performed with steady-state free precession covering short axis continuously from the mitral annulus to the apical level in the 2-, 3- and 4- chamber views using the following parameters: repetition time (TR) = 3.73 ms, echo time (TE) = 1.87 ms, flip angle = 60°, slice thickness 8.0 mm. Cine images of all included patients were acquired prior to contrast administrations. Late gadolinium enhancement images (LGE) images were obtained 10-15 minutes after intravenous injection of gadolinium (0.1 mmol/kg at 3ml/s) at end-diastolic phase on the short axis (TR=6.09 ms; TE= 3.0 ms; flip angle 60°; thickness 8.0 mm) with breath-hold phase-sensitive segmented inversion recovery (PSIR) fast field echo sequence. T2-weighted sequence was performed using turbo spin-echo (TSE)-sequence (TR=1714-2000 ms; TE=8.04 ms; slice thickness 8.0 mm) to estimate myocardial edema. Images were analyzed on freely available validated cardiovascular image analysis software CVI42 (Circle Cardiovas
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
Diagnosed with ST-segment elevation myocardial infarction (STEMI), defined as chest pain with ST-segment elevation on ECG and elevated cardiac troponin levels
Underwent primary percutaneous coronary intervention (PCI)
Able to undergo cardiac magnetic resonance (CMR) imaging within 7 days post-PCI
Provided written informed consent
Exclusion Criteria
History of revascularization therapy (PCI or CABG) within the previous 6 months
Severe valvular heart disease or known cardiomyopathy
Presence of bundle branch block or fascicular block that interferes with image interpretation
Known allergy to gadolinium-based contrast agents (for those undergoing contrast-enhanced sequences)
Estimated glomerular filtration rate (eGFR) \<30 mL/min/1.73m² (if contrast use is anticipated)
Pregnant or breastfeeding women
18 Years
80 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Chinese PLA General Hospital
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
XIN A
Dr
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Beijing, , China
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
Yundai Chen
Role: backup
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
S2025-061-01
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.