Search Results (158)

Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep or heterogeneous arrhythmogenic substrates. Cardiac imaging, especially when multimodal and integrated with mapping systems, has emerged as a critical adjunct to enhance procedural efficacy, safety, and individualized strategy. This comprehensive review explores the evolving role of various imaging modalities, including echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), and intracardiac echocardiography (ICE), in the preprocedural and intraprocedural phases of VT ablation. We highlight their respective strengths in substrate identification, anatomical delineation, and real-time guidance. While limitations persist, including costs, availability, artifacts in device carriers, and lack of standardization, future advances are likely to redefine procedural workflows. 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: 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

Heart failure (HF) is a complex clinical syndrome that results from any structural or functional impairment of ventricular filling or ejection of blood. The etiology of heart failure is multifactorial, encompassing ischemic heart disease, hypertension, valvular disorders, cardiomyopathies, and metabolic and infiltrative diseases. Despite advances in pharmacologic and device-based therapies, heart failure continues to carry a substantial burden of morbidity, mortality, and healthcare utilization. With the advancement and increased accessibility of cardiac imaging modalities, the diagnostic accuracy for identifying the underlying etiologies of nonischemic cardiomyopathy has significantly improved, allowing for more precise classification and tailored management strategies. This review aims to provide a comprehensive analysis of the current understanding of heart failure, encompassing epidemiology, etiological factors, with a specific focus on diagnostic imaging modalities including the role of echocardiography and strain imaging, cardiac magnetic resonance imaging (CMR), cardiac computed tomography (CT), and nuclear positron emission tomography (PET) imaging and recent advances in the diagnosis and management of heart failure. Full article

Various cardiac pathologies such as ischemic/non-ischemic heart disease, valvular heart disease and genetic heart disease may impair cardiac function and lead to heart failure (HF). Each individual condition but also the common endpoint of HF may involve the brain and the immune system next to the heart. The interaction of these systems plays an important role, particularly in the pathogenesis and prognosis of HF, and stress plays a pivotal role in this interaction. The stress system (SS) of the body can be activated by any stress factor exceeding a predefined threshold and all body structures including brain, heart and immune system can be affected. The SS is also responsible for body homeostasis. Both acute and chronic stress may lead to the development of acute and chronic heart disease. Magnetic Resonance Imaging (MRI) is the ideal noninvasive tool without radiation that can provide valuable information about the effect of the SS in various systems/organs using targeted protocols. A holistic approach provided by MRI has the potential to improve our knowledge regarding stress mechanisms on the axis of heart–brain–immune system in HF that may impact effective, individualized treatment. In this review paper, we describe how MRI can be used as a noninvasive tool to assess the effect of stress on the brain–immune system-heart-axis, discussing current possibilities, limitations and future directions. Full article

Tricuspid regurgitation (TR) represents a significant, often silently progressing, valvular heart disease with historically suboptimal management due to perceived high surgical risks. Transcatheter tricuspid valve interventions (TTVI) offer a promising, less invasive therapeutic avenue. Central to the success of TTVI is Right Ventricular Reverse Remodelling (RVRR), defined as an improvement in RV structure and function, which strongly correlates with enhanced patient survival. The right ventricle (RV) undergoes complex multi-scale biomechanical maladaptations, progressing from adaptive concentric to maladaptive eccentric hypertrophy, coupled with increased stiffness and fibrosis. Molecular drivers of this pathology include early failure of antioxidant defenses, metabolic shifts towards glycolysis, and dysregulation of microRNAs. Accurate RV function assessment necessitates advanced imaging modalities like 3D echocardiography, Cardiac Magnetic Resonance Imaging (CMR), and Computed Tomography (CT), along with strain analysis. Following TTVI, RVRR typically manifests as a biphasic reduction in RV volume overload, improved myocardial strain, and enhanced RV-pulmonary arterial coupling. Emerging molecular biomarkers alongside advanced imaging-derived biomechanical markers like CT-based 3D-TAPSE and RV longitudinal strain, are proving valuable. Artificial intelligence (AI) and machine learning (ML) are transforming prognostication by integrating diverse clinical, laboratory, and multi-modal imaging data, enabling unprecedented precision in risk stratification and optimizing TTVI strategies. Full article

Transseptal puncture (TSP) is an essential step for left heart procedures that allows access to the left atrium (LA) through the fossa ovalis (FO) of the interatrial septum (IS). Initially developed for diagnostic purposes, today, it is performed for procedures that require large-bore device delivery systems and complex three-dimensional navigation in the left atrium. TSP supports various interventions, including atrial fibrillation ablation, left atrial appendage closure, and transcatheter mitral valve repair and replacement. While traditionally performed with Brockenbrough needles under fluoroscopic guidance, the integration of transesophageal and intracardiac echocardiography (TEE/ICE) has significantly improved its safety and precision. Despite its generally high success rate, TSP poses challenges in complex anatomies or for less experienced operators, with complications such as cardiac tamponade, aortic root puncture, and embolic events. Anatomical variations, such as thickened or floppy septa, further complicate the procedure. Technological advancements, including radiofrequency-based systems and specialized guidewires, have enhanced safety in difficult cases. Effective training, including echocardiography and complication management, is vital for operator proficiency. This review outlines the procedural steps for safe TSP, emphasizing proper equipment selection, anatomical considerations, and vascular access techniques. Common complications are discussed alongside management strategies. Advanced tools and techniques for addressing challenging scenarios are highlighted. Full article

Background: Artificial intelligence (AI) and deep learning are increasingly applied in cardiovascular imaging. However, the “black box” nature of these models raises challenges for clinical trust and integration. Explainable Artificial Intelligence (XAI) seeks to address these concerns by providing insights into model decision-making. This systematic review synthesizes current research on the use of XAI methods in radiological cardiovascular imaging. Methods: A systematic literature search was conducted in PubMed, Scopus, and Web of Science to identify peer-reviewed original research articles published between January 2015 and March 2025. Studies were included if they applied XAI techniques—such as Gradient-Weighted Class Activation Mapping (Grad-CAM), Shapley Additive Explanations (SHAPs), Local Interpretable Model-Agnostic Explanations (LIMEs), or saliency maps—to cardiovascular imaging modalities, including cardiac computed tomography (CT), magnetic resonance imaging (MRI), echocardiography and other ultrasound examinations, and chest X-ray (CXR). Studies focusing on nuclear medicine, structured/tabular data without imaging, or lacking concrete explainability features were excluded. Screening and data extraction followed PRISMA guidelines. Results: A total of 28 studies met the inclusion criteria. Ultrasound examinations (n = 9) and CT (n = 9) were the most common imaging modalities, followed by MRI (n = 6) and chest X-rays (n = 4). Clinical applications included disease classification (e.g., coronary artery disease and valvular heart disease) and the detection of myocardial or congenital abnormalities. Grad-CAM was the most frequently employed XAI method, followed by SHAP. Most studies used saliency-based techniques to generate visual explanations of model predictions. Conclusions: XAI holds considerable promise for improving the transparency and clinical acceptance of deep learning models in cardiovascular imaging. However, the evaluation of XAI methods remains largely qualitative, and standardization is lacking. Future research should focus on the robust, quantitative assessment of explainability, prospective clinical validation, and the development of more advanced XAI techniques beyond saliency-based methods. Strengthening the interpretability of AI models will be crucial to ensuring their safe, ethical, and effective integration into cardiovascular care. Full article

Aortic valve stenosis (AS) is a valvular heart disease that imposes a high afterload on the left ventricle (LV) due to restricted opening of the aortic valve, resulting in LV hypertrophy. Severe AS can lead to syncope, angina pectoris, and heart failure. The number of patients with AS has been increasing due to aging populations, the growing prevalence of lifestyle-related diseases, and advances in diagnostic technologies. Therefore, accurate diagnosis and appropriate treatment of AS are essential. In recent years, transcatheter aortic valve implantation (TAVI) has become feasible, and the number of procedures has rapidly increased, particularly among elderly patients. As treatment options for AS expand and diversify, detailed pre-procedural evaluation has become increasingly important. In particular, diagnostic imaging modalities such as computed tomography (CT) have advanced significantly, with notable improvements in image quality. With recent advancements in CT technology—such as increased detector rows, faster gantry rotation speeds, new image reconstruction methods, and the introduction of dual-energy imaging—the scope of cardiac assessment has expanded beyond the coronary arteries to include valves, myocardium, and the entire heart. This includes evaluating restricted AV opening and cardiac function using four-dimensional imaging, assessing AV annulus diameter and AS severity via calcium scoring with a novel motion correction algorithm, and detecting myocardial damage through late-phase contrast imaging using new reconstruction techniques. In cases of pre-TAVI evaluation or congenital bicuspid valves, CT is also valuable for assessing extracardiac structures, such as access routes and associated congenital heart anomalies. In addition, recent advancements in CT technology have made it possible to significantly reduce radiation exposure during cardiac imaging. CT has become an extremely useful tool for comprehensive cardiac evaluation in patients with aortic stenosis, especially those being considered for surgical treatment. Full article

Background: Obesity has been defined as a true worldwide “pandemic” by the World Health Organization and represents one of the major public health problems. It is associated with a reduction in life expectancy of about 7–8 years due to related cardiovascular diseases such as arterial hypertension, metabolic syndrome, insulin resistance, type 2 diabetes mellitus, and dyslipidemia. Adipose tissue is not merely a fat storage site but a true endocrine and immunologically active organ that secretes hormones and mediators (adipokines), influencing cardiovascular risk and host physiology. Objective: This review summarizes the current understanding of the role of epicardial adipose tissue (EAT) in cardiovascular disease pathophysiology and discusses its clinical diagnostic and therapeutic implications. Methods: A narrative non-systematic review was conducted focusing on recent literature concerning the biological and clinical aspects of cardiac adipose tissue, with particular emphasis on epicardial adipose tissue. The review examined its gene expression profile, secretory function, and interaction with cardiovascular structures and diseases. Findings: There are different types of adipose tissue, including cardiac adipose tissue, which comprises epicardial and pericardial (or paracardiac) fractions. Epicardial adipose tissue is unique due to its proximity to the heart and a distinct gene expression profile compared to other adipose depots such as visceral and subcutaneous fat. EAT plays a crucial role in the development and progression of cardiovascular diseases with high morbidity and mortality, acting both as a metabolic and inflammatory mediator. Conclusion: Cardiac adipose tissue, particularly EAT, is a key player in cardiometabolic disease. Understanding its pathophysiological role and incorporating imaging tools to evaluate EAT may enhance cardiovascular risk stratification and disease management. Full article

Background and Objectives: Nonischemic cardiomyopathies comprise a wide spectrum of heart muscle disorders characterized by different morphological, functional, and tissue abnormalities. Cardiovascular magnetic resonance (CMR) represents the gold standard imaging modality for assessing cardiac morphology, systolic function, and tissue characterization, thereby aiding in early diagnosis, precise phenotyping, and tailored treatment. The aim of this review is to provide an up-to-date overview of CMR techniques for studying myocardial perfusion and their applications to nonischemic cardiomyopathy, not only to rule out an underlying ischemic aetiology but also to investigate the pathophysiological characteristics of microcirculatory dysfunction in these patients. Materials and Methods: We performed a structured review of the literature focusing on first-pass gadolinium perfusion sequences, stress protocols, and emerging pixel-wise perfusion mapping approaches. Studies were selected to illustrate the methods for image acquisition, post-processing, and quantification of myocardial blood flow (MBF) and myocardial perfusion reserve (MPR), as well as to highlight associations with clinical endpoints. Results: First-pass CMR perfusion imaging reliably detects diffuse and regional microvascular dysfunction across cardiomyopathies. Semi-quantitative parameters (e.g., upslope, MPRI) and quantitative MBF mapping (mL/g/min) have demonstrated that impaired perfusion correlates with disease severity, extent of fibrosis, and adverse outcomes, including heart failure hospitalization, arrhythmias, and mortality. Novel automated pixel-wise mapping enhances reproducibility and diagnostic accuracy, distinguishing coronary microvascular dysfunction from balanced three-vessel disease. Microvascular dysfunction—present in approximately 50–60% of dilated cardiomyopathy (DCM), 40–80% of hypertrophic cardiomyopathy (HCM), and >95% of cardiac amyloidosis (CA) patients—has emerged as a key driver of adverse outcomes. Perfusion defects appear early, often preceding overt hypertrophy or fibrosis, and provide incremental prognostic value beyond conventional CMR metrics. Conclusions: CMR represents a powerful tool for detecting myocardial perfusion abnormalities in nonischemic cardiomyopathies, improving phenotyping, risk stratification, and personalized management. Further standardization of quantitative perfusion techniques will facilitate broader clinical adoption. Full article

Characterizing imaging performance requires a multidisciplinary approach that evaluates various interconnected parameters, including dosage optimization and dynamic accuracy. Radiation dose and dynamic accuracy are challenged by patient motion that results in poor image quality. These challenges are more prevalent in the brain/cardiac pediatric patient imaging, as they relate to excess radiation dose that may be associated with various complications. Scanning vulnerable pediatric patients ought to eliminate anesthesia due to critical risks associated in some cases with intracranial hemorrhages, brain strokes, and congenital heart disease. Some pediatric imaging, however, requires prolonged scanning under anesthesia. It can often be a laborious, suboptimal process, with limited field of view and considerable dose. High dynamic accuracy is also necessary to diagnose tissue’s dynamic behavior beyond its static structural morphology. This study presents several performance characterization experiments from a new robotic multimodal imaging system using specially designed calibration methods at different system configurations. Additional musculoskeletal imaging and imaging from a pediatric brain stroke patient without anesthesia are presented for comparisons. The findings suggest that the system’s large dynamically controlled gantry enables scanning at full patient movement and with important improvements in scan times, accuracy, radiation dose, and the ability to image brain structures without anesthesia. This could position the system as a potential transformative tool in the pediatric interventional imaging landscape. Full article

Secondary dilated cardiomyopathy (DCM) refers to left ventricular dilation and impaired systolic function arising from identifiable extrinsic causes, such as ischemia, hypertension, toxins, infections, systemic diseases, or metabolic disorders. Unlike primary DCM, which is predominantly genetic, secondary DCM represents a diverse spectrum of pathophysiological mechanisms linked to external insults on myocardial structure and function. The increasing prevalence of conditions such as alcohol use disorder, chemotherapy-induced cardiotoxicity, and viral myocarditis underscores the need for heightened awareness and early recognition of secondary DCM. A comprehensive analysis of clinical trial data and observational studies involving secondary dilative cardiomyopathy was conducted, with a focus on mortality, symptom relief, and major adverse events. A systematic literature review was performed using databases, including PubMed, Embase, and ClinicalTrials.gov, following PRISMA guidelines for study selection. Data were extracted on patient demographics, etiology of dilation, trial design, outcomes, and follow-up duration. Advances in diagnostic modalities have refined the ability to identify underlying causes of secondary DCM. For example, high-sensitivity troponin and cardiac magnetic resonance imaging are pivotal in diagnosing myocarditis and differentiating it from ischemic cardiomyopathy. Novel insights into toxin-induced cardiomyopathies, such as those related to anthracyclines and immune checkpoint inhibitors, have highlighted pathways of mitochondrial dysfunction and oxidative stress. Treatment strategies emphasize the management of the causing condition alongside standard heart failure therapies, including RAAS inhibitors and beta-blockers. Emerging therapies, such as myocardial recovery protocols in peripartum cardiomyopathy and immune-modulating treatments in myocarditis, are promising in reversing myocardial dysfunction. Secondary DCM encompasses a heterogeneous group of disorders that require a precise etiological diagnosis for effective management. Timely identification and treatment of the underlying cause, combined with optimized heart failure therapies, can significantly improve outcomes. Future research focuses on developing targeted therapies and exploring the role of biomarkers and precision medicine in tailoring treatment strategies for secondary DCM. Full article

Objectives: The purpose of this study was to analyze image quality and radiation exposure of thoracic computed tomography angiography (CTA) in children with congenital heart diseases (CHDs) using either manual contrast medium (CM) injection or automated power injectors with bolus tracking. Methods: A total of 137 thoracic CTAs of 120 consecutive pediatric patients were included in this retrospective study. We analyzed the method of CM administration (power injection with bolus tracking (PI) or manual injection (MI)), injection routes, volumes and flow rates of CM. For the evaluation of objective image quality, attenuation values in the heart chambers and great thoracic vessels were determined by region-of-interest (ROI) analysis and signal-to-noise (SNR) and contrast-to-noise (CNR) ratios calculated thereof. Visual image quality was assessed by two blinded readers (four-point Likert-scale) analyzing the presence of artifacts and the depiction of relevant anatomical structures. Effective radiation doses were calculated with dose length products and specific conversion factors. Results: CM administration was performed using PI in 119/137 CTAs, whereas MI was conducted in 18/137. The smallest size of peripheral venous cannulas was 24 gauge in 36/137 (26.3%) cases. Overall mean CM volume was 17 mL ± 16 mL (mean ± SD). In PI, the mean flow rate of CM was 1.52 ± 0.90 mL/s with a range between 0.5 and 5.0 mL/s. When comparing the overall PI population and an age-, size- and weight-matched PI subpopulation (18 cases) with the MI population, attenuation values in Hounsfield units (HU) and CNR values were significantly higher in the PI groups than in the MI group for each relevant cardiac structure (left ventricle, right ventricle, ascending aorta and pulmonary trunk, p = 0.02–0.001). Overall image quality and depiction of cardiac structures were rated significantly better in CTAs with PI (interquartile ranges: “good” to “excellent” (Likert 3–4)) in PI compared with CTAs acquired with MI (interquartile ranges: “fair” to “good” (2–3)) in MI by both readers (p < 0.001). The inter-observer reliability was strong, with a Kendall’s Tau-b correlation coefficient of τ = 0.802 (p < 0.001). The mean effective radiation dose (E) did not differ significantly when comparing the stratified samples (i.e., the matched PI subgroup and the MI group; 0.5 (±0.3) mSv in both, p = 0.76). There were no complications associated with the CM injections for both application approaches. Conclusions: Automated contrast agent applications with power injectors and bolus tracking ensure better image quality in pediatric CTA, even when low volumes and flow rates need to be applied. There is a slight increase in radiation associated with bolus tracking. This approach represents a suitable imaging technique for the work-up of congenital heart disease. Full article

Atrial fibrillation (Afib) recurrence after catheter ablation (CA) remains a significant clinical challenge, driven by a complex and dynamic interplay of structural, electrical, and autonomic mechanisms. While pulmonary vein isolation (PVI) is the cornerstone of CA, recurrence rates remain substantial, highlighting the need to understand the evolving pathophysiology beyond PV reconnection. Post-ablation changes, including inflammation, edema, oxidative stress, and ischemia, create a transient proarrhythmic state that may contribute to early recurrence. Over time, atrial remodeling, fibrosis, and residual autonomic activity further sustain arrhythmogenicity. Additionally, epicardial adipose tissue promotes atrial myopathy, accelerating disease progression, particularly in patients with risk factors such as older age, female sex, obesity, hypertension, obstructive sleep apnea, and heart failure. The multifactorial nature of Afib recurrence underscores the limitations of a “one-size-fits-all” ablation strategy. Instead, a patient-specific approach integrating advanced mapping techniques, multimodal imaging, and computational modeling is essential. Artificial intelligence (AI) and digital twin models hold promise for predicting recurrence by simulating individualized disease progression and optimizing ablation strategies. However, challenges remain regarding the standardization and validation of these novel approaches. A deeper understanding of the dynamic interconnections between the mechanisms driving recurrence is crucial for improving long-term CA outcomes. This review explores the evolving nature of Afib recurrence, emphasizing the need for a precision medicine approach that accounts for the continuous interaction of pathophysiological processes in order to refine patient selection, ablation strategies, and post-procedural management. Full article