Search Results (574)

Non-ST-segment-elevation acute coronary syndrome (NSTE-ACS) often coexists with multivessel coronary artery disease (MVD), complicating treatment decisions. Current guidelines suggest complete revascularization (CR), yet robust evidence in hemodynamically stable patients remains insufficient. However, the comparative benefit of CR over incomplete revascularization (IR) in reducing ischemic events and improving cardiac function in this population is not well established. The aim of this study was to evaluate the impact of CR on all-cause mortality, cardiac death, and ischemic readmissions at 6 and 12 months, as the composite primary outcome, and to assess left ventricular ejection fraction (LVEF) improvement at discharge and hospital length of stay, as secondary outcomes. A total of 282 hemodynamically stable NSTE-ACS patients with MVD were included, of whom 218 (77.3%) underwent CR and 64 (22.7%) IR. The primary composite outcome occurred in 40.6% of IR patients versus 11.0% in the CR group at 6 months (p < 0.001), and 68.8% vs. 22.0% at 12 months (p < 0.001). CR was associated with significantly lower rates of all-cause and cardiac death, myocardial infarction, and unstable angina. Stroke incidence was similar. Event-free survival favored CR. Multivariable analysis identified CR and baseline LVEF as independent predictors of 12-month outcomes (HR for CR: 7.797; 95% CI: 3.961–15.348; p < 0.001; HR for LVEF: 0.959; CI: 0.926–0.994; p = 0.021). These findings strongly support CR as the preferred therapeutic strategy. Future prospective randomized studies are warranted to confirm the results. Full article

Background: The widespread use of cardiac magnetic resonance imaging (MRI) in clinical practice has enabled the identification of numerous patients with evident damage from previous myocarditis, whether known or unknown. For years, myocardial fibrosis has been a topic of interest due to its established correlation with arrhythmic events in various clinical settings, including ischemic heart disease, dilated cardiomyopathy, and hypertrophic cardiomyopathy. MIBG scintigraphy is a method widely used in patients who are candidates for defibrillator implantation or have experienced heart failure. This examination evaluates the sympathetic innervation of the myocardium. Objective: To assess the real arrhythmogenic risk of non-ischemic scars identified in symptomatic or asymptomatic patients through the use of MIBG. Methods: Patients were retrospectively selected based on the presence of non-ischemic myocardial fibrosis detected by cardiac MRI, consistent with a myocarditis outcome (even in the absence of a clear history of myocarditis). These patients underwent myocardial scintigraphy with MIBG using a tomographic technique. Results: A total of 50 patients (41 males, mean age 51 ± 16 years) who underwent MRI from 2019 to June 2024 were selected. The primary indication for MRI was ventricular ectopic extrasystoles detected on Holter ECG (n = 12, 54%), while five patients underwent MRI following a known acute infectious event (23%, including three cases of COVID-19 infection). All symptomatic patients presented with chest pain in the acute phase, accompanied by elevated hsTNI levels (mean value: 437 pg/mL). The MRI findings showed normal ventricular volumes (LV: 80 mL/m², RV: 81 mL/m²) and normal ejection fractions (56% and 53%, respectively). The mean native T1 mapping value was 1013 ms (normal range: 950–1050). T2 mapping values were altered in the 5 patients who underwent MRI during the acute phase (mean value: 57 ms), without segmentation. Additionally, three patients had non-tamponade pericardial effusion. All patients exhibited LGE (nine subepicardial, seven midwall, six patchy). All patients underwent myocardial scintigraphy with MIBG at least 6 months after the acute event, with only one case yielding a positive result. This patient, a 57-year-old male, had the most severe clinical presentation, including more than 65,000 premature ventricular beats (PVBs) and multiple episodes of paroxysmal supraventricular tachycardia (PSVT) recorded on Holter ECG. MRI findings showed severe left ventricular dysfunction, a slightly dilated LV, and midwall LGE at the septum, coinciding with hypokinetic areas. Conclusions: MIBG scintigraphy could be a useful tool in assessing arrhythmic risk in patients with previous myocarditis. It could help reduce the clinical burden of incidental findings of non-ischemic LGE, which does not appear to be independently associated with an increased risk profile. Full article

Deep learning has shown remarkable success in medical image analysis over the last decade; however, many contributions focused on supervised methods which learn exclusively from labeled training samples. Acquiring expert-level annotations in large quantities is time-consuming and costly, even more so in medical image segmentation, where annotations are required on a pixel level and often in 3D. As a result, available labeled training data and consequently performance is often limited. Frequently, however, additional unlabeled data are available and can be readily integrated into model training, paving the way for semi- or self-supervised learning (SSL). In this work, we investigate popular SSL strategies in more detail, namely Transformation Consistency, Student–Teacher and Pseudo-Labeling, as well as exhaustive combinations thereof. We comprehensively evaluate these methods on two 2D and 3D cardiac Magnetic Resonance datasets (ACDC, MMWHS) for which several different multi-compartment segmentation labels are available. To assess performance in limited dataset scenarios, different setups with a decreasing amount of patients in the labeled dataset are investigated. We identify cascaded Self-Supervision as the best methodology, where we propose to employ Pseudo-Labeling and a self-supervised cascaded Student–Teacher model simultaneously. Our evaluation shows that in all scenarios, all investigated SSL methods outperform the respective low-data supervised baseline as well as state-of-the-art self-supervised approaches. This is most prominent in the very-low-labeled data regime, where for our proposed method we demonstrate $10.17\%$ and $6.72\%$ improvement in Dice Similarity Coefficient (DSC) for ACDC and MMWHS, respectively, compared with the low-data supervised approach, as well as $2.47\%$ and $7.64\%$ DSC improvement, respectively, when compared with related work. Moreover, in most experiments, our proposed method is able to greatly decrease the performance gap when compared to the fully supervised scenario, where all available labeled samples are used. We conclude that it is always beneficial to incorporate unlabeled data in cardiac MRI segmentation whenever it is present. Full article

Background/Objectives: Cardiac involvement in systemic sclerosis (SSc) ranges from subclinical to severe. While pulmonary artery hypertension (PAH) is well-documented, the mechanism of left ventricular (LV) ischemia remains unclear. Oxygen-sensitive cardiovascular magnetic resonance (OS-CMR) imaging offers a novel approach to assessing myocardial oxygenation and ischemia. This study evaluated the changes in myocardial deoxygenation in response to stress using LV OS-CMR in SSc patients without known cardiac disease. Methods: We prospectively recruited SSc patients without prior cardiac disease or risk factors, and age- and sex-matched healthy volunteers (HVs). All participants underwent transthoracic echocardiography (TTE) and 3T CMR, including native T1 mapping, rest/stress OS-CMR, stress perfusion, and late gadolinium enhancement (LGE). The primary outcome was a change in the LV OS-CMR signal intensity (SI) after adenosine stress. Results: Thirty-three participants (23 SSc, 10 HV) were enrolled. SSc patients had significantly lower global LV OS-CMR SI compared to HV (13.4 ± 6.5 vs. 19.5 ± 3.6, p = 0.011). OS-CMR SI change ≤ 10% was observed in at least one segment in 20 (87%) SSc patients and globally in 12 (52%). LGE was present in 5 (22%) patients, and 18 (78%) had ≥1 abnormal T1 mapping segment. LV global longitudinal strain (GLS) was reduced in SSc patients compared to the HVs (−19.04 ± 3.86 vs. −21.92 ± 3.72, p = 0.045). All HVs had normal CMR and TTE findings. Conclusions: SSc patients without known cardiovascular disease or PAH demonstrated subclinical LV ischemia with an impaired myocardial oxygenation response to stress. They further demonstrated LV myocardial deformation abnormalities and LV diffuse fibrosis when compared to an age-matched control group. Our findings support the presence of early coronary microvascular dysfunction and LV myocardial fibrosis in this population, which may explain the adverse cardiovascular risk seen in this population, independent of the presence of PAH. Full article

Anomalies of coronary artery origins are rare but significant conditions that can range from benign to life-threatening. Early detection through imaging is crucial in preventing adverse outcomes. The treatment strategy varies depending on the type and severity of the anomaly, ranging from pharmacological treatment to surgery. A 22-year-old male patient, after syncope, after excluding other causes, had an exercise drill test, which was clinically negative and ECG-positive. Angio-CT revealed an undeveloped left main coronary artery (LMCA), and the circulation was supplied through the right coronary artery (RCA). The RCA provides the left anterior descending artery (LAD), and the LAD retrogradely supplies the left circumflex artery (LCX). The myocardial perfusion scintigraphy showed a slight lack of perfusion in the anterior wall (6% of total perfusion). The patient was qualified for further observation. A 77-year-old female underwent cardiac CT due to stenocardia. CT showed a lack of LMCA. The initial segment of the RCA gave rise to the left coronary artery (LCA), which encircled the aortic bulb posteriorly and bifurcated into branches resembling the LCX and LAD. After the Heart Team consultation, the patient was deemed eligible for conservative treatment. Angio-CT is a valuable tool for detecting coronary artery anomalies. Full article

Background: Breast and hematological cancer treatments, especially with anthracyclines, have been shown to be associated with an increased risk of cardiotoxicity (CTX). An accurate prediction of cardiotoxicity risk and early detection of myocardial injury may allow for effective cardioprotection to be instituted and tailored to reverse cardiac dysfunction and prevent the discontinuation of essential cancer treatments. Objectives: The PRoactive Evaluation of Function to Evade Cardio Toxicity (PREFECT) study sought to evaluate the ability of fast-strain-encoded (F-SENC) cardiac magnetic resonance imaging (CMR) and 2D echocardiography (2D Echo) to stratify patients at risk of CTX prior to initiating cancer treatment, detect early signs of cardiac dysfunction, including subclinical CTX (sub-CTX) and CTX, and monitor for recovery (REC) during cardioprotective therapy. Methods: Fifty-nine patients with breast cancer or lymphoma were prospectively monitored for CTX with F-SENC CMR and 2D Echo over at least 1 year for evidence of cardiac dysfunction during anthracycline based chemotherapy. F-SENC CMR also monitored myocardial deformation in 37 left ventricular (LV) segments to obtain a MyoHealth risk score based on both longitudinal and circumferential strain. Sub-CTX and CTX were classified based on pre-specified cardiotoxicity definitions. Results: CTX was observed in 9/59 (15%) and sub-CTX in 24/59 (41%) patients undergoing chemotherapy. F-SENC CMR parameters at baseline predicted CTX with a lower LVEF (57 ± 5% vs. 61 ± 5% for all, p = 0.05), as well as a lower MyoHealth (70 ± 9 vs. 79 ± 11 for all, p = 0.004) and a worse global circumferential strain (GCS) (−18 ± 1 vs. −20 ± 1 for all, p < 0.001). Pre-chemotherapy MyoHealth had a higher accuracy in predicting the development of CTX compared to CMR LVEF and 2D Echo LVEF (AUC = 0.85, 0.69, and 0.57, respectively). The 2D Echo parameters on baseline imaging did not stratify CTX risk. F-SENC CMR obtained good or excellent images in 320/322 (99.4%) scans. During cancer treatment, MyoHealth had a high accuracy of detecting sub-CTX or CTX (AUC = 0.950), and the highest log likelihood ratio (indicating a higher probability of detecting CTX) followed by F-SENC GLS and F-SENC GCS. CMR LVEF and CMR LV stroke volume index (LVSVI) also significantly worsened in patients developing CTX during cancer treatment. Conclusions: F-SENC CMR provided a reliable and accurate assessment of myocardial function during anthracycline-based chemotherapy, and demonstrated accurate early detection of CTX. In addition, MyoHealth allows for the robust identification of patients at risk for CTX prior to treatment with higher accuracy than LVEF. Full article

Accurate segmentation of cardiac MR images using deep neural networks is crucial for cardiac disease diagnosis and treatment planning, as it provides quantitative insights into heart anatomy and function. However, achieving high segmentation accuracy relies heavily on extensive, precisely annotated datasets, which are costly and time-consuming to obtain. This study addresses this challenge by proposing a novel data augmentation framework based on a condition-guided diffusion generative model, controlled by multiple cardiac labels. The framework aims to expand annotated cardiac MR datasets and significantly improve the performance of downstream cardiac segmentation tasks. The proposed generative data augmentation framework operates in two stages. First, a Label Diffusion Module is trained to unconditionally generate realistic multi-category spatial masks (encompassing regions such as the left ventricle, interventricular septum, and right ventricle) conforming to anatomical prior probabilities derived from noise. Second, cardiac MR images are generated conditioned on these semantic masks, ensuring a precise one-to-one mapping between synthetic labels and images through the integration of a spatially-adaptive normalization (SPADE) module for structural constraint during conditional model training. The effectiveness of this augmentation strategy is demonstrated using the U-Net model for segmentation on the enhanced 2D cardiac image dataset derived from the M&M Challenge. Results indicate that the proposed method effectively increases dataset sample numbers and significantly improves cardiac segmentation accuracy, achieving a 5% to 10% higher Dice Similarity Coefficient (DSC) compared to traditional data augmentation methods. Experiments further reveal a strong correlation between image generation quality and augmentation effectiveness. This framework offers a robust solution for data scarcity in cardiac image analysis, directly benefiting clinical applications. Full article

Background/Objectives: The development of normal fetal cardiac function, a dynamic process that has not yet been precisely documented throughout the literature, is difficult to quantify by classic echocardiography. Our aim was to analyze the function of the fetal myocardium through speckle tracking and establish reference values for global and segmental longitudinal strain for both ventricles in fetuses with a gestational age (GA) between 22 and 39 weeks. Methods: We conducted a prospective study in which 170 fetuses underwent echocardiographic evaluation and those 150 that were eligible for the study underwent offline speckle tracking analysis. Results: A mixed-design ANOVA model with Greenhouse–Geisser correction showed no significant differences in regional strain measurements among GA groups (F [2, 147] = 1.25, p = 0.289) but showed significant differences in regional strain measurements among the right ventricle (RV), left ventricle (LV), and interventricular free wall (Greenhouse–Geisser F [1.3, 195.2] = 45.70, p < 0.001, GG ε = 0.66, original df = 2, 294). The wall-by-segment interaction term of the model was statistically significant for regional strain (Greenhouse–Geisser F [2.7, 394.2] = 27.00, p < 0.001, GG ε = 0.67, original df = 4, 588), while the segment-by-gestational age group term had a tendency toward statistical significance (Greenhouse–Geisser F [3.0, 221.4] = 2.21, p = 0.088, GG ε = 0.75, original df = 4, 294). The results of Welch’s ANOVA model showed no significant difference in right-ventricle peak global longitudinal strain (pGLS) between GA groups (F [2.0, 92.2] = 0.52, p = 0.5972) and global longitudinal strain measurements (F [2.0, 89.6] = 27.00, p = 0.3733). Conclusions: The reference values for longitudinal strain, represented by the pGLS for LV, ranged from −20.79 to −8.05 for fetuses with a GA between 22 and 27 weeks, from −20.14 to −8.99 for fetuses with a GA between 28 and 33 weeks, and from −20.19 to −8.88 for fetuses with a GA between 34 and 39 weeks. For RV pGLS, the reference values were between −18.99 and −6.35, also depending on GA. Reference ranges for the large gestational groups studied can help us to recognize subtle changes in fetal cardiac function. Full article

Background: Sex-related differences in left ventricular (LV) reverse remodeling following ST-segment elevation myocardial infarction (STEMI) remain underexplored. We aimed to investigate predictors of reverse remodeling and its association with clinical outcomes, with a focus on sex-specific differences. Methods: We enrolled 253 STEMI patients (91 women, 28%) and assessed echocardiographic parameters at baseline and six months. LV reverse remodeling was defined as a ≥15% reduction in LV end-diastolic volume (LVEDV). Multivariate logistic regression identified independent predictors of remodeling. Clinical outcomes were evaluated over a median follow-up of 17 months (IQR 14–22 months), including major adverse cardiac events (MACEs). Kaplan–Meier and Cox regression analyses were performed. Results: Reverse remodeling occurred in 43% of patients and was more frequent in men than women (47% vs. 37%, p = 0.04). Male sex (OR 0.30; 95% CI: 0.14–0.65; p < 0.0001) and baseline global work efficiency (GWE) (OR 1.64; 95% CI: 1.45–1.85; p < 0.0001) were independent predictors. Men exhibited greater reductions in LVEDV, greater improvements in LV ejection fraction, and superior myocardial work indices. Over the follow-up, patients with reverse remodeling had significantly lower MACE rates compared to those without (10% vs. 24%, p < 0.01). Cox regression demonstrated that reverse remodeling was associated with a reduced risk of MACEs (HR 0.318; 95% CI: 0.181–0.557; p < 0.0001). Conclusions: LV reverse remodeling after STEMI is associated with improved clinical outcomes and is influenced by sex-specific differences. Baseline myocardial work indices, particularly GWE, are strong predictors of reverse remodeling. Men demonstrated a more favorable remodeling profile and myocardial recovery compared to women. Full article

In clinical practice, left ventricle hypertrophy (LVH) continues to pose a considerable challenge, highlighting the need for more reliable diagnostic approaches. This study aims to propose an automated framework for the quantification of LVH extent and the classification of myocardial segments according to hypertrophy severity using a deep learning-based algorithm. The proposed method was validated on 133 subjects, including both healthy individuals and patients with LVH. The process starts with automatic LV segmentation using U-Net and the segmentation of the left ventricle cavity based on the American Heart Association (AHA) standards, followed by the division of each segment into three equal sub-segments. Then, an automated quantification of regional wall thickness (RWT) was performed. Finally, a convolutional neural network (CNN) was developed to classify each myocardial sub-segment according to hypertrophy severity. The proposed approach demonstrates strong performance in contour segmentation, achieving a Dice Similarity Coefficient (DSC) of 98.47% and a Hausdorff Distance (HD) of 6.345 ± 3.5 mm. For thickness quantification, it reaches a minimal mean absolute error (MAE) of 1.01 ± 1.16. Regarding segment classification, it achieves competitive performance metrics compared to state-of-the-art methods with an accuracy of 98.19%, a precision of 98.27%, a recall of 99.13%, and an F1-score of 98.7%. The obtained results confirm the high performance of the proposed method and highlight its clinical utility in accurately assessing and classifying cardiac hypertrophy. This approach provides valuable insights that can guide clinical decision-making and improve patient management strategies. Full article

Coronary plaque vulnerability, more than luminal stenosis, drives acute coronary syndromes. Optical coherence tomography (OCT), intravascular ultrasound (IVUS), and coronary computed tomography angiography (CCTA) visualize plaque morphology in vivo, but manual interpretation is time-consuming and operator-dependent. We performed a narrative literature survey of artificial intelligence (AI) applications—focusing on machine learning (ML) architectures—for automated coronary plaque segmentation and risk characterization across OCT, IVUS, and CCTA. Recent ML models achieve expert-level lumen and plaque segmentation, reliably detecting features linked to vulnerability such as a lipid-rich necrotic core, calcification, positive remodelling, and a napkin-ring sign. Integrative radiomic and multimodal frameworks further improve prognostic stratification for major adverse cardiac events. Nonetheless, progress is constrained by small, single-centre datasets, heterogeneous validation metrics, and limited model interpretability. AI-enhanced plaque assessment offers rapid, reproducible, and comprehensive coronary imaging analysis. Future work should prioritize large multicentre repositories, explainable architectures, and prospective outcome-oriented validation to enable routine clinical adoption. Full article

Background: Cardiovascular diseases are the leading cause of global mortality, with 80% of coronary heart disease in patients over 65. Understanding aging cardiovascular structures is crucial. Photon-counting computed tomography (PCCT) offers improved spatial and temporal resolution and better signal-to-noise ratio, enabling texture analysis in clinical routines. Detecting structural changes in aging left-ventricular myocardium may help predict cardiovascular risk. Methods: In this retrospective, single-center, IRB-approved study, 90 patients underwent ECG-gated contrast-enhanced cardiac CT using dual-source PCCT (NAEOTOM Alpha, Siemens). Patients were divided into two age groups (50–60 years and 70–80 years). The left ventricular myocardium was segmented semi-automatically, and radiomics features were extracted using pyradiomics to compare myocardial texture features. Epicardial adipose tissue (EAT) density, thickness, and other clinical parameters were recorded. Statistical analysis was conducted with R and a Python-based random forest classifier. Results: The study assessed 90 patients (50–60 years, n = 54, and 70–80 years, n = 36) with a mean age of 63.6 years. No significant differences were found in mean Agatston score, gender distribution, or conditions like hypertension, diabetes, hypercholesterolemia, or nicotine abuse. EAT measurements showed no significant differences. The Random Forest Classifier achieved a training accuracy of 0.95 and a test accuracy of 0.74 for age group differentiation. Wavelet-HLH_glszm_GrayLevelNonUniformity was a key differentiator. Conclusions: Radiomics texture features of the left ventricular myocardium outperformed conventional parameters like EAT density and thickness in differentiating age groups, offering a potential imaging biomarker for myocardial aging. Radiomics analysis of left ventricular myocardium offers a unique opportunity to visualize changes in myocardial texture during aging and could serve as a cardiac risk predictor. Full article

Brugada syndrome is a rare inherited heart disease characterized by ventricular arrhythmias and characteristic ST segment elevation, which increases the risk of sudden death. Studies have shown that the pathogenesis of this disease involves a variety of gene mutations, including abnormal functions of sodium, calcium, and potassium ion channels, resulting in cardiac electrophysiological disorders. These variants affect excitability and conduction of cardiomyocytes, thereby increasing the susceptibility to ventricular arrhythmias and sudden death. However, many genetic variants remain of uncertain significance or are insufficiently characterized, necessitating further investigation. This review summarizes the genetic variants associated with Brugada syndrome and discusses their potential implications for improving diagnosis and therapeutic approaches. Full article

Background: Leigh’s Disease is a rare mitochondrial disorder primarily affecting the central nervous system, with frequent secondary cardiac manifestations such as hypertrophic and dilated cardiomyopathies. Early detection of cardiac complications is crucial for patient management, but manual interpretation of cardiac MRI is labour-intensive and subject to inter-observer variability. Methodology: We propose an integrated deep learning framework using cardiac MRI to automate the detection of cardiac abnormalities associated with Leigh’s Disease. Four CNN architectures—Inceptionv3, a custom 3-layer CNN, DenseNet169, and EfficientNetB2—were trained on preprocessed MRI data (224 × 224 pixels), including left ventricular segmentation, contrast enhancement, and gamma correction. Morphological features (area, aspect ratio, and extent) were also extracted to aid interpretability. Results: EfficientNetB2 achieved the highest test accuracy (99.2%) and generalization performance, followed by DenseNet169 (98.4%), 3-layer CNN (95.6%), and InceptionV3 (94.2%). Statistical morphological analysis revealed significant differences in cardiac structure between Leigh’s and non-Leigh’s cases, particularly in area (212,097 vs. 2247 pixels) and extent (0.995 vs. 0.183). The framework was validated using ROC (AUC = 1.00), Brier Score (0.000), and cross-validation (mean sensitivity = 1.000, std = 0.000). Feature embedding visualisation using PCA, t-SNE, and UMAP confirmed class separability. Grad-CAM heatmaps localised relevant myocardial regions, supporting model interpretability. Conclusions: Our deep learning-based framework demonstrated high diagnostic accuracy and interpretability in detecting Leigh’s disease-related cardiac complications. Integrating morphological analysis and explainable AI provides a robust and scalable tool for early-stage detection and clinical decision support in rare diseases. Full article

Coronary no-reflow (CNR) is the failure of blood to reperfuse ischemic myocardial tissue after restoration of the vasculature. CNR poses a significant clinical challenge in the treatment of patients with ST-segment elevation myocardial infarction (STEMI), as it increases mortality and the risk of major adverse cardiac events (MACEs). Myocardial ischemia with subsequent reperfusion results in severe damage to the cardiac microcirculation. The pathophysiological causes of CNR include cardiomyocyte vulnerability, capillary and endothelial damage, leukocyte activation, reactive oxygen species (ROS) production, and changes in microRNA profiles and related gene expression. The impact of percutaneous coronary intervention (PCI) on the occurrence of CNR cannot be overlooked, as it can provoke distal atherothrombotic embolization. Current standards of pharmacological therapy for CNR are confined to intracoronary vasodilators and antiplatelet agents. As our understanding of the pathogenesis of the CNR phenomenon improves, opportunities emerge for developing novel therapeutic strategies. The following literature review provides an overview of the pathophysiology of the no-reflow phenomenon (based on animal and preclinical studies), contemporary treatment trends, and current therapeutic approaches. Full article