Search Results (446)

Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and initiating interventions like thrombolysis, thrombectomy, or surgical management. In parallel, recent advancements in wearable technology, particularly smart clothing, offer new opportunities for stroke prevention, real-time monitoring, and rehabilitation. These garments integrate various sensors, including electrocardiogram (ECG) electrodes, electroencephalography (EEG) caps, electromyography (EMG) sensors, and motion or pressure sensors, to continuously track physiological and functional parameters. For example, ECG shirts monitor cardiac rhythm to detect atrial fibrillation, smart socks assess gait asymmetry for early mobility decline, and EEG caps provide data on neurocognitive recovery during rehabilitation. These technologies support personalized care across the stroke continuum, from early risk detection and acute event monitoring to long-term recovery. Integration with AI-driven analytics further enhances diagnostic accuracy and therapy optimization. This narrative review explores the application of smart clothing in conjunction with traditional imaging to improve stroke management and patient outcomes through a more proactive, connected, and patient-centered approach. 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

Background/Objectives: Interstitial lung disease (ILD) is frequently complicated by pulmonary hypertension (PH), which is associated with reduced exercise capacity and poor prognosis. Early and accurate non-invasive detection of PH remains a clinical challenge. This study evaluated whether combining quantitative CT analysis of lung fibrosis with cardiac MRI-derived measures of right ventricular (RV) function improves the diagnostic accuracy of PH in patients with ILD. Methods: We retrospectively analyzed 72 ILD patients who underwent chest CT, cardiac MRI, and right heart catheterization (RHC). Lung fibrosis was quantified using a Gaussian Histogram Normalized Correlation (GHNC) software that computed the proportions of diseased lung, ground-glass opacity (GGO), honeycombing, reticulation, consolidation, and emphysema. MRI was used to assess RV end-systolic volume (RVESV), ejection fraction, and RV longitudinal strain. PH was defined as a mean pulmonary arterial pressure (mPAP) ≥ 20 mmHg and pulmonary vascular resistance ≥ 3 Wood units on RHC. Results: Compared to patients without PH, those with PH (n = 21) showed significantly reduced RV strain (−13.4 ± 5.1% vs. −16.4 ± 5.2%, p = 0.026) and elevated RVESV (74.2 ± 18.3 mL vs. 59.5 ± 14.2 mL, p = 0.003). CT-derived indices also differed significantly: diseased lung area (56.4 ± 17.2% vs. 38.4 ± 12.5%, p < 0.001), GGO (11.8 ± 3.6% vs. 8.65 ± 4.3%, p = 0.005), and honeycombing (17.7 ± 4.9% vs. 12.8 ± 6.4%, p = 0.0027) were all more prominent in the PH group. In receiver operating characteristic curve analysis, diseased lung area demonstrated an area under the curve of 0.778 for detecting PH. This increased to 0.847 with the addition of RVESV, and further to 0.854 when RV strain was included. Combined models showed significant improvement in risk reclassification: net reclassification improvement was 0.700 (p = 0.002) with RVESV and 0.684 (p = 0.004) with RV strain; corresponding IDI values were 0.0887 (p = 0.03) and 0.1222 (p = 0.01), respectively. Conclusions: Combining CT-based fibrosis quantification with cardiac MRI-derived RV functional assessment enhances the non-invasive diagnosis of PH in ILD patients. This integrated imaging approach significantly improves diagnostic precision and may facilitate earlier, more targeted interventions in the management of ILD-associated PH. 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: Elevated troponin levels are widely recognized as key biomarkers of myocardial injury and are frequently used in clinical decision making. However, not all instances of troponin elevation indicate true cardiac damage. In some cases, biochemical or immunological interferences may lead to false-positive results. These situations may lead to unnecessary diagnostic interventions and clinical uncertainty, ultimately impacting patient management negatively. This study aims to investigate the underlying mechanisms of false-positive troponin elevation in pediatric patients, focusing on factors such as macrotroponin formation, autoantibodies, and heterophile antibody interference. Methods: This retrospective study analyzed data from 13 pediatric patients who presented with elevated cardiac troponin levels between 2017 and 2024. Clinical evaluations included transthoracic echocardiography (TTE), electrocardiography (ECG), coronary computed tomography angiography (CTA), cardiac magnetic resonance imaging (MRI), and rheumatologic testing. Laboratory findings included measurements of cardiac troponins (cTnI and hs-cTnT) and pro-BNP levels. Results: Among 70 patients evaluated for elevated troponin levels, 13 (18.6%) were determined to have no identifiable cardiac etiology. The median age of these 13 patients was 13.0 years (range: 9–16), with 53.8% being female. The most common presenting complaints were chest pain (53.8%) and palpitations (30.8%). TTE findings were normal in 61.5% of the patients, and all patients had normal coronary CTA and cardiac MRI findings. Although initial troponin I levels were elevated in all cases, persistent positivity was observed up to 12 months. Median cTnI levels were 1.00 ng/mL (range: 0.33–7.19) at week 1 and 0.731 ng/mL (range: 0.175–4.56) at month 12. PEG precipitation testing identified macrotroponin in three patients (23.1%). No etiological explanation could be identified in 10 cases (76.9%), which were considered idiopathic. All patients had negative results for heterophile antibody and rheumatologic tests. Conclusions: When interpreting elevated troponin levels in children, biochemical interferences—especially macrotroponin—should not be overlooked. This study emphasizes the diagnostic uncertainty associated with non-cardiac troponin elevation. To better guide clinical practice and clarify false positivity rates, larger, multicenter prospective studies are needed. Full article

This review investigates recent developments in cardiac mechano-electrical-fluid interaction (MEFI) modeling, with a focus on multiphysics simulation platforms and digital twin frameworks developed between 2015 and 2025. The purpose of the study is to assess how computational modeling methods—particularly finite element and immersed boundary techniques, monolithic and partitioned coupling schemes, and artificial intelligence (AI)-enhanced surrogate modeling—capture the integrated dynamics of cardiac electrophysiology, tissue mechanics, and hemodynamics. The goal is to evaluate the translational potential of MEFI models in clinical applications such as cardiac resynchronization therapy (CRT), arrhythmia classification, atrial fibrillation ablation, and surgical planning. Quantitative results from the literature demonstrate <5% error in pressure–volume loop predictions, >0.90 F1 scores in machine-learning-based arrhythmia detection, and <10% deviation in myocardial strain relative to MRI-based ground truth. These findings highlight both the promise and limitations of current MEFI approaches. While recent advances improve physiological fidelity and predictive accuracy, key challenges remain in achieving multiscale integration, model validation across diverse populations, and real-time clinical applicability. The review concludes by identifying future milestones for clinical translation, including regulatory model certification, standardization of validation protocols, and integration of patient-specific digital twins into electronic health record (EHR) systems. Full article

Background and Clinical Significance: Tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by pathogenic variants in TSC1 or TSC2. Cardiac rhabdomyoma is a common prenatal finding and can be associated with severe complications, including pericardial effusion. We administered prenatal sirolimus to mitigate pericardial effusion, which led to postnatal complications. Case Presentation: A 28-year-old pregnant woman with no significant family history underwent routine fetal ultrasound at 28.1 weeks of gestation, which identified a large right ventricular mass consistent with rhabdomyoma. Further fetal brain MRI revealed cortical-subcortical tubers and subependymal nodules, leading to a clinical diagnosis of TSC. At 30.4 weeks, oral sirolimus (3 mg/day) was started due to the significant pericardial effusion. The effusion remained after treatment, requiring pericardiocentesis at 33.6 weeks. The sirolimus dosage was raised to 6 mg/day at 35.6 weeks, reaching a plasma level of 3.76 ng/mL, but there was no discernible improvement because of the continued fluid accumulation. The mother did not experience any adverse side effects from the procedure. Genetic testing confirmed a pathogenic variant in TSC2 (c.1372C>T). After birth, the neonate received a single dose of sirolimus but subsequently developed necrotizing enterocolitis (NEC), highlighting the potential adverse effects and the need for cautious consideration of treatment options. Conclusions: This case illustrates the complexities of managing prenatal tuberous sclerosis complex (TSC). While sirolimus has been explored for fetal cardiac rhabdomyoma and associated complications, its effectiveness in resolving pericardial effusion remains uncertain. Additionally, the development of NEC postnatally raises concerns about the safety of mTOR inhibitors in this context. Further studies are necessary to assess the risks and benefits of this approach in fetal therapy. 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

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

Myocardial injury following polytrauma is a significant yet often underdiagnosed condition that contributes to acute cardiac dysfunction and long-term cardiovascular complications. This review examines the role of systemic inflammation, oxidative stress, neuro-hormonal activation, and immune dysregulation in trauma-induced myocardial damage. Key immunological markers, including interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), monocyte chemoattractant protein-1 (MCP-1), and adhesion molecules (ICAM-1, VCAM-1), are implicated in endothelial dysfunction, myocardial apoptosis, and ventricular remodeling. The interplay between these factors potentially exacerbates cardiac injury, increasing the risk of heart failure. Biomarker-guided approaches for early detection, combined with advanced imaging techniques such as speckle-tracking echocardiography and cardiac MRI, offer promising avenues for risk stratification and targeted interventions. Anti-inflammatory and oxidative stress-modulating therapies may mitigate myocardial damage and improve outcomes. This article highlights the clinical relevance of integrating immunological markers into diagnostic and therapeutic strategies to enhance the management of trauma-related cardiac dysfunction and reduce long-term morbidity. Full article

Cardiac tumors in dogs, although rare in the past, have shown an increasing incidence due to advances in veterinary imaging, especially echocardiography, CT, and MRI with contrast agents. Right atrial hemangiosarcoma is the most common form of tumor associated with pericardial effusion and cardiac tamponade, followed by chemodectoma, which is more common in brachycephalic breeds. The diagnosis is based on echocardiographic examination, supplemented by advanced methods and possibly biopsy. Clinical signs are often non-specific, requiring an integrated approach. Treatment includes pericardiocentesis, chemotherapy, and, in some cases, surgery, but the prognosis remains reserved. 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

Background/Objectives: Two-dimensional echocardiography (2D echo) is widely used for assessing left ventricular ejection fraction (LVEF). This single-center comparative study aims to evaluate the accuracy of LVEF measurements obtained using the AI-assisted handheld ultrasound device Kosmos against cardiac magnetic resonance (CMR), the current gold standard. Methods: A total of 49 adult patients undergoing clinically indicated CMR were prospectively enrolled. AI-based LVEF measurements were compared with CMR using the Wilcoxon signed-rank test, Pearson correlation, multivariable linear regression, and Bland–Altman analysis. All analyses were performed using STATA v18.0. Results: Median LVEF was 57% (CMR) vs. 55% (AI-Echo), with no significant difference (p = 0.51). Strong correlation (r = 0.99) and minimal bias (1.1%) were observed. Conclusions: The Kosmos AI-based autoEF algorithm demonstrated excellent agreement with CMR-derived LVEF values. Its speed and automation make it promising for bedside assessment in emergency departments, intensive care units, and outpatient clinics. This study aims to fill the gap in current clinical evidence by evaluating, for the first time, the agreement between LVEF measurements obtained via Kosmos’ AI-assisted autoEF and those from cardiac MRI (CMR), the gold standard for ventricular function assessment. This comparison is critical for validating the reliability of portable AI-driven echocardiographic tools in real-world clinical practice. However, these findings derive from a selected population at a single Italian center and should be validated in larger, diverse cohorts before assuming global generalizability. Full article

Background/Objectives: Hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) is an emerging imaging modality that combines metabolic and anatomical data in a single session, offering promising diagnostic performance in various cardiac conditions. However, its role in inflammatory cardiac diseases (ICDs), such as myopericarditis and endocarditis, remains underexplored. This study aims to evaluate the diagnostic value of PET/MRI in ICDs through a systematic review of the literature, complemented by our institutional experience. Methods: We conducted a systematic review of PubMed, Scopus, and Embase up to April 2025, using keywords including “PET/MRI,” “PET/MR”, “myocarditis”, “endocarditis”, “pericarditis”, “inflammatory heart disease”, and “inflammatory cardiac disease”. Studies reporting the use of hybrid PET/MRI in ICDs were included and analyzed. Additionally, we retrospectively reviewed clinical and imaging data from 33 consecutive patients who underwent PET/MRI in our center for suspected myopericarditis or endocarditis between September 2022 and March 2025. Results: The systematic review identified 12 eligible studies evaluating PET/MRI in ICDs, highlighting its added value in cases with inconclusive findings on standalone MRI or PET. Common advantages reported included improved localization of active inflammation, better characterization of tissue damage, and enhanced diagnostic confidence. In our cohort, hybrid PET/MRI was considered diagnostically useful in 16/21 (76%) of myopericarditis cases and 9/12 (75%) of endocarditis cases, particularly for reclassifying uncertain findings and guiding clinical management. Conclusions: The combined analysis of the current literature and real-world clinical experience supports the diagnostic utility of hybrid PET/MRI in the evaluation of ICDs. This multimodal approach improves the interpretation of equivocal cases, facilitates accurate diagnosis, and may influence therapeutic decisions. However, larger prospective studies are needed to confirm these findings and establish standardized protocols. Full article

Summary: COVID-19, caused by SARS-CoV-2, has been associated with a range of cardiovascular complications, including myocarditis. This review aims to systematically present the clinical manifestations, underlying pathophysiological mechanisms, diagnostic approaches, and management strategies for both COVID-19-associated myocarditis and myocarditis related to SARS-CoV-2 vaccination. We conducted a literature search using the PubMed database, covering studies published up to early 2024. Search terms included combinations of “COVID-19”, “Coronavirus”, “SARS-CoV-2”, and/or “vaccination” with “cardiac injury”, “cardiac inflammation”, “myocarditis”. The reported prevalence of COVID-19-associated myocarditis varies between 2.3% and 5.0%, though myocardial injury is more frequently observed than confirmed myocarditis. Pathophysiological mechanisms include direct viral damage, immune-mediated injury, and molecular mimicry. Clinically, patients may present with chest pain, dyspnea, and fever. Diagnostic workup includes electrocardiography (ECG), troponin measurement, echocardiography, cardiac magnetic resonance imaging (cMRI), and in selected cases, endomyocardial biopsy (EMB). The management and disposition of COVID-19-associated myocarditis varies according to severity, especially to allow targeted treatment of complications. Glucocorticoids are a mainstay of treatment in severe cases. Myocarditis following SARS-CoV-2 vaccination is rare, more frequently reported in males under 30 years, and is generally associated with a favorable prognosis. Despite this, the benefits of vaccination continue to outweigh the risks. COVID-19 is associated with an increased risk of heart failure and other cardiovascular complications, underlining the importance of long-term follow-up and preventive strategies. Further research is needed to better understand the pathogenesis and optimal management of myocarditis in the context of COVID-19, with the goal of developing evidence-based therapeutic algorithms. Full article