Using Advanced CT Scans and Blood Markers to Better Understand Heart Damage and Recovery After a Heart Attack

Acute Myocardial Infarction (AMI)

magnetic resonance, miRNA, myocardial infarction, adverse ventricular remodeling, spectral computed tomography

Acute myocardial infarction with ST-segment elevation (STEMI) remains a leading cause of morbidity and mortality worldwide. Although advances in reperfusion therapy have reduced early mortality, many patients later develop adverse ventricular remodeling (AVR), which increases the risk of heart failure and cardiovascular death. Current imaging methods, such as echocardiography and cardiac magnetic resonance (CMR), provide valuable prognostic information but have limitations in availability, cost, and their ability to predict AVR early and individually. Spectral computed tomography (CT) is an emerging imaging technique that can characterize myocardial tissue, quantify infarct size, assess microvascular obstruction, and detect complications, with lower contrast and radiation requirements compared to conventional CT. In parallel, circulating microRNAs (miRNAs) have been identified as stable and non-invasive biomarkers that reflect key biological processes in post-infarction remodeling. Several miRNAs are linked to fibrosis, apoptosis, and ventricular remodeling, suggesting their potential to complement imaging findings in risk prediction. This study proposes a multicenter, prospective cohort of patients with STEMI and reduced left ventricular function to evaluate whether combining spectral CT tissue characterization with serum miRNA profiling can improve early prediction of AVR. The main objective is to generate and validate a multiparametric prognostic model integrating imaging and molecular biomarkers to identify high-risk patients who may benefit from closer monitoring and tailored therapeutic strategies.

Background and Rationale Acute myocardial infarction with ST-segment elevation (STEMI) continues to represent a major public health challenge, being one of the leading causes of morbidity and mortality worldwide. Advances in reperfusion therapy, particularly primary percutaneous coronary intervention (PCI), have substantially reduced short-term mortality rates. Nevertheless, a large proportion of patients experience adverse ventricular remodeling (AVR) during follow-up. AVR is characterized by pathological changes in left ventricular (LV) geometry, wall thinning, chamber dilation, and progressive decline in contractile function. These changes are strongly associated with the development of heart failure and increased long-term mortality. Traditional imaging modalities, such as echocardiography and cardiac magnetic resonance (CMR), have been used to characterize post-infarction myocardial damage and to monitor remodeling. Echocardiography is widely available and provides important functional information, but it lacks the ability to characterize myocardial tissue in depth. CMR is currently the gold standard for infarct size quantification, detection of microvascular obstruction, and assessment of myocardial viability; however, it is costly, time-consuming, and not universally accessible. There remains an unmet need for more accessible, rapid, and accurate tools to predict AVR early after STEMI. Spectral computed tomography (CT) has recently emerged as an innovative imaging technique that goes beyond conventional CT by providing spectral information and material decomposition. This technology enables enhanced tissue characterization, accurate quantification of myocardial perfusion defects, and identification of complications such as myocardial rupture or thrombus, all while using reduced contrast volume and lower radiation doses compared with older-generation scanners. Preliminary data suggest that spectral CT can approximate some of the information traditionally obtained through CMR, potentially offering a more accessible tool for post-infarction risk stratification. In parallel, circulating microRNAs (miRNAs) have been identified as highly stable, non-invasive biomarkers involved in key biological processes relevant to cardiac remodeling, including fibrosis, apoptosis, angiogenesis, and inflammatory signaling. Several miRNAs have been associated with infarct size, LV dysfunction, and clinical outcomes in patients with acute myocardial infarction. Integrating molecular biomarkers with imaging could provide a powerful multiparametric model for early prediction of AVR, guiding patient-tailored therapeutic strategies. The SPECTRAMI-CARE study (SPEctral CT and miRna In Acute Myocardial Infarction for Comprehensive Adverse Remodeling Evaluation) is designed as a prospective, multicenter observational cohort. The protocol aims to evaluate the complementary role of spectral CT and circulating miRNAs in predicting adverse remodeling after STEMI with impaired LV function. Imaging Procedures Spectral CT: Performed within the first week after STEMI. Parameters include assessment of infarct size, perfusion defects, myocardial edema, and complications (e.g., thrombus, aneurysm). Quantitative indices will be derived from material decomposition images, iodine density maps, and virtual monoenergetic reconstructions. Cardiac MRI (sub-cohort): Used as a reference standard for infarct size, microvascular obstruction, and myocardial viability. Data will be compared with spectral CT findings for concordance and accuracy. Echocardiography: Performed at baseline and follow-up for routine functional assessment (LV volumes, LVEF, diastolic function, right ventricular parameters). Molecular Biomarker Assessment Peripheral blood samples will be collected at baseline (≤72h after PCI), at 1 month, and at 3 months. miRNA profiling will be performed using next-generation sequencing and validated with quantitative RT-PCR. Candidate miRNAs previously implicated in fibrosis, apoptosis, angiogenesis, and remodeling will be specifically analyzed. Expression levels will be correlated with imaging findings and clinical outcomes. Statistical Analysis Sample size will be based on expected incidence of AVR (\ 30% in high-risk STEMI populations). Multivariable logistic regression and Cox proportional hazards models will be used to identify predictors of AVR and clinical outcomes. Model performance will be evaluated using C-statistics, calibration plots, and net reclassification improvement (NRI). Internal validation will be performed with bootstrapping; external validation will be explored in an independent cohort. Ethics and Dissemination The study will comply with the Declaration of Helsinki and local ethics regulations. Informed consent will be obtained from all participants. Data will be anonymized and stored securely. Results will be disseminated through peer-reviewed publications and presentations at scientific conferences, with the aim of contributing to precision medicine in post-infarction care. Significance SPECTRAMI-CARE is expected to provide novel insights into the early identification of patients at risk for adverse remodeling after STEMI. By integrating cutting-edge imaging and molecular biomarkers, this study seeks to advance risk stratification and facilitate personalized strategies to improve outcomes. Spectral CT, if validated against CMR, may offer a more accessible alternative for myocardial tissue characterization, while circulating miRNAs may add a non-invasive layer of biological information. The multiparametric model proposed has the potential to change clinical practice by identifying high-risk patients earlier and enabling targeted therapeutic interventions.

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