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Cardiovascular diseases (CVDs) are the leading cause of premature death and disability globally, leading to significant increases in healthcare costs and economic strains. Artificial intelligence (AI) is emerging as a crucial technology in this context, promising to have a significant impact on the management of CVDs. A wide range of methods can be used to develop effective models for medical applications, encompassing everything from predicting and diagnosing diseases to determining the most suitable treatment for individual patients. This literature review synthesizes findings from multiple studies that apply AI technologies such as machine learning algorithms and neural networks to electrocardiograms, echocardiography, coronary angiography, computed tomography, and cardiac magnetic resonance imaging. A narrative review of 127 articles identified 31 papers that were directly relevant to the research, encompassing a broad spectrum of AI applications in cardiology. These applications included AI models for ECG, echocardiography, coronary angiography, computed tomography, and cardiac MRI aimed at diagnosing various cardiovascular diseases such as coronary artery disease, hypertrophic cardiomyopathy, arrhythmias, pulmonary embolism, and valvulopathies. The papers also explored new methods for cardiovascular risk assessment, automated measurements, and optimizing treatment strategies, demonstrating the benefits of AI technologies in cardiology. In conclusion, the integration of artificial intelligence (AI) in cardiology promises substantial advancements in diagnosing and treating cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Background Myocarditis is challenging to diagnose due to its varied presentations. Endomyocardial biopsy is the gold standard for diagnosis, but its invasive nature has led to alternative non-invasive modalities, notably cardiovascular magnetic resonance (CMR). Identifying the precise aetiology of myocarditis is crucial for effective treatment, yet extra-cardiac causes are often overlooked. In this paper, we spotlight the underexplored role of CMR in diagnosing extra-cardiac aetiologies, utilizing three insightful cases for illustration. Case summary The first case is a 31-year-old patient with myocarditis secondary to a pyogenic liver abscess, identified through CMR, who improved after abscess drainage. The second case involves a 54-year-old patient with myocarditis attributed to adult T-cell leukaemia–lymphoma, with the loco-regional thickening process identified thanks to CMR. This patient had an unfavourable disease progression due to the underlying malignancy. The third case concerns a 23-year-old patient suffering from myocarditis associated with pneumonia, again illustrated effectively through CMR imaging, who recovered after antibiotic treatment. Discussion These cases underline the overlooked potential of CMR in diagnosing extra-cardiac aetiologies of myocarditis, even though such causes are rare. Despite current guidelines recognizing the importance of identifying the aetiology of myocarditis, they do not explicitly address the role of CMR in diagnosing extra-cardiac aetiologies. This article, therefore, proposes that future guidelines could emphasize the utility of CMR in exploring these causes, potentially leading to more accurate diagnoses and improved patient outcomes. It also advocates for a comprehensive, multidisciplinary approach to myocarditis diagnosis, encouraging vigilance for potential loco-regional causes, and calls for further research in this area. [ABSTRACT FROM AUTHOR]

Background: IgG4-related disease is a fibro-inflammatory disorder with an unknown etiology, which can affect multiple organ systems, including the cardiovascular system. While most reported cases of cardiovascular involvement are primarily associated with the aorta, there have been sporadic reports of isolated cardiac involvement. Case presentation: This paper presents a documented case of IgG4-related systemic disease with symptoms indicative of restrictive cardiomyopathy. Subsequent Cardiac Magnetic Resonance imaging revealed diffuse myopericardial involvement, characterized by pericardial thickening and enhancement, accompanied by subepicardial and myocardial infiltration. Considering the rarity of cardiac involvement in our case, we conducted a thorough review of the existing literature pertaining to various patterns of cardiac involvement in IgG4-related disease, as well as the diagnostic modalities that can be employed for accurate identification and assessment. Conclusions: This case report sheds light on the importance of recognizing and evaluating cardiac manifestations in IgG4-related systemic disease to facilitate timely diagnosis and appropriate management. [ABSTRACT FROM AUTHOR]

Automatic and accurate segmentation of medical images plays an essential role in disease diagnosis and treatment planning. Convolution neural networks have achieved remarkable results in medical image segmentation in the past decade. Meanwhile, deep learning models based on Transformer architecture also succeeded tremendously in this domain. However, due to the ambiguity of the medical image boundary and the high complexity of physical organization structures, implementing effective structure extraction and accurate segmentation remains a problem requiring a solution. In this paper, we propose a novel Dual Encoder Network named DECTNet to alleviate this problem. Specifically, the DECTNet embraces four components, which are a convolution-based encoder, a Transformer-based encoder, a feature fusion decoder, and a deep supervision module. The convolutional structure encoder can extract fine spatial contextual details in images. Meanwhile, the Transformer structure encoder is designed using a hierarchical Swin Transformer architecture to model global contextual information. The novel feature fusion decoder integrates the multi-scale representation from two encoders and selects features that focus on segmentation tasks by channel attention mechanism. Further, a deep supervision module is used to accelerate the convergence of the proposed method. Extensive experiments demonstrate that, compared to the other seven models, the proposed method achieves state-of-the-art results on four segmentation tasks: skin lesion segmentation, polyp segmentation, Covid-19 lesion segmentation, and MRI cardiac segmentation. [ABSTRACT FROM AUTHOR]

Lipomatous hypertrophy of the interatrial septum (LHIAS) represents a benign proliferation of lipoid cells at the level of the interatrial septum (IAS) inducing an important thickening of this structure. It respects the fossa ovalis (FO) region, having a typical "hourglass" echocardiographic appearance. There are certain cases though, with unusual appearances and/or with associated pathologies that may induce similar lesions in the heart, in which the differential diagnosis cannot be guaranteed using only the standard methods. The final diagnosis has important implications in these patients' treatment plan. In this paper, we present an unusual case of a female patient undergoing chemotherapy for lung carcinoma, suspected of right atrial thrombosis/metastasis. As the diagnosis was unclear after transthoracic echocardiography (TTE), inducing the suspicion of an IAS mass with atrial wall infiltration, bi- and tridimensional transesophageal echocardiography (TOE) was performed, revealing a severely and homogenously hypertrophied IAS respecting the FO, but lacking a clear visualization of the atrial wall. The diagnosis of LHIAS was established by cardiac magnetic resonance (CMR) that certified the adipose nature of the structure, excluding the need for invasive investigations and/or treatment options. Multimodality imaging is very important for the clinician in adopting the best management plan for each individual patient. [ABSTRACT FROM AUTHOR]

Catastrophic Antiphospholipid Syndrome (CAPS) is a rare complication that can occur in patients with Antiphospholipid Syndrome (APS). CAPS occurs even more rarely during pregnancy/puerperium and pregnant patients, even less likely to show cardiac involvement without signs of damage on ultrasound and angiography with non-obstructive coronary arteries. We present a case of a 26-year-old breastfeeding woman, the youngest described with CAPS and acute myocardial infarction, whose diagnosis was made with cardiac magnetic resonance imaging (CMRI). A literature review of pregnant patients with similar problems was performed. There are diagnostic and therapeutic difficulties in treating these patients. CMRI demonstrated a transmural late enhancement area. A combination of therapies led to rapid clinical improvement. CMRI is an underused tool that reaffirms the pathophysiology of CAPS and leads clinicians to the possibility of a diffuse thrombotic process. CAPS involves more organs with high mortality rates. CMRI could be optimized in order to reach an early diagnosis and the most effective treatment. This study provides real-world evidence of the feasibility of MRI in a primary care setting during pregnancy/puerperium. Evidence from this study may influence future APS screening and inform policymakers regarding the use of leading MRI technology in the detection of the thrombotic process in a primary care setting. [ABSTRACT FROM AUTHOR]

To develop a deep learning-based model capable of segmenting the left ventricular (LV) myocardium on native T1 maps from cardiac MRI in both long-axis and short-axis orientations. Models were trained on native myocardial T1 maps from 50 healthy volunteers and 75 patients using manual segmentation as the reference standard. Based on a U-Net architecture, we systematically optimized the model design using two different training metrics (Sørensen-Dice coefficient = DSC and Intersection-over-Union = IOU), two different activation functions (ReLU and LeakyReLU) and various numbers of training epochs. Training with DSC metric and a ReLU activation function over 35 epochs achieved the highest overall performance (mean error in T1 10.6 ± 17.9 ms, mean DSC 0.88 ± 0.07). Limits of agreement between model results and ground truth were from -35.5 to + 36.1 ms. This was superior to the agreement between two human raters (-34.7 to + 59.1 ms). Segmentation was as accurate for long-axis views (mean error T1: 6.77 ± 8.3 ms, mean DSC: 0.89 ± 0.03) as for short-axis images (mean error ΔT1: 11.6 ± 19.7 ms, mean DSC: 0.88 ± 0.08). Fully automated segmentation and quantitative analysis of native myocardial T1 maps is possible in both long-axis and short-axis orientations with very high accuracy. [ABSTRACT FROM AUTHOR]

Introduction: Assessment of left ventricular ejection fraction (LVEF) is one of the primary objectives of echocardiography. The gold standard assessment technique in emergency medicine is eyeballing. A new tool is now available on pocket ultrasound devices (PUD): automatic LVEF. The primary aim of this study was to evaluate the concordance between LVEF values estimated by automatic LVEF with PUD and by cardiac magnetic resonance imaging (MRI). Materials: This was a prospective, monocentric, and observational study. All adult patients with an indication for cardiac MRI underwent a point-of-care ultrasound. Blinded to the MRI results, the emergency physician assessed LVEF using the automatic PUD tool and by visual evaluation. Results: Sixty patients were included and analyzed. Visual estimation of LVEF was feasible for all patients and automatic evaluation for 52 (87%) patients. Lin's concordance correlation coefficient between automatic ejection fraction with PUD and by cardiac MRI was 0.23 (95% CI, 0.03–0.40). Conclusion: Concordance between LVEF estimated by the automatic ejection fraction with PUD and LVEF estimated by MRI was non-existent. [ABSTRACT FROM AUTHOR]

An editorial is presented on the 2023 European Society of Cardiology (ESC) Guidelines for the Management of Acute Coronary Syndromes (ACS). Topics include the comprehensive management approach from admission to long-term care, the emphasis on a person-centered approach including symptom recognition and patient education, and the recommendations for antithrombotic therapy and long-term treatment strategies.

Apical hypertrophic cardiomyopathy (ApHCM) is an HCM variant, affecting frequently males in midlife. It is characterized by apical obliteration and persistent diastolic contraction, often resulting in microvascular ischaemia. We report five cases of ApHCM, with evidence of intramyocardial calcification on echocardiogram. On cardiac magnetic imaging (MRI), a hypointense component at early gadolinium enhancement (EGE) sequences, compatible with calcium, and a deep layer, with hyperintensity at late gadolinium enhancement (LGE) sequences, referable to fibrosis, suggest an endomyocardial fibrosis (EMF) diagnosis. EMF pathologic hallmark is endocardium and myocardium scarring, evolving to dystrophic calcification. It is found only in few ApHCM patients. Our series is the largest one described until now. Analysing patients' history, coexistent inflammatory triggers were evident in all of them, so their co‐morbidities could represent a further cause of small vessel disease, in the context of ischaemic microvascular stress due to hypertrophy, leading to fibrosis and dystrophic calcification. This series could demonstrate the relation between apical fibrosis/calcification and microvascular ischaemia due to hypertrophy and inflammatory triggers. [ABSTRACT FROM AUTHOR]

Background: Cardiac magnetic resonance (CMR) in the four-chamber plane offers comprehensive insight into the volumetrics of the heart. We aimed to develop an artificial intelligence (AI) model of time-resolved segmentation using the four-chamber cine. Methods: A fully automated deep learning algorithm was trained using retrospective multicentre and multivendor data of 814 subjects. Validation, reproducibility, and mortality prediction were evaluated on an independent cohort of 101 subjects. Results: The mean age of the validation cohort was 54 years, and 66 (65%) were males. Left and right heart parameters demonstrated strong correlations between automated and manual analysis, with a ρ of 0.91−0.98 and 0.89−0.98, respectively, with minimal bias. All AI four-chamber volumetrics in repeatability analysis demonstrated high correlation (ρ = 0.99−1.00) and no bias. Automated four-chamber analysis underestimated both left ventricular (LV) and right ventricular (RV) volumes compared to ground-truth short-axis cine analysis. Two correction factors for LV and RV four-chamber analysis were proposed based on systematic bias. After applying the correction factors, a strong correlation and minimal bias for LV volumetrics were observed. During a mean follow-up period of 6.75 years, 16 patients died. On stepwise multivariable analysis, left atrial ejection fraction demonstrated an independent association with death in both manual (hazard ratio (HR) = 0.96, p = 0.003) and AI analyses (HR = 0.96, p < 0.001). Conclusion: Fully automated four-chamber CMR is feasible, reproducible, and has the same real-world prognostic value as manual analysis. LV volumes by four-chamber segmentation were comparable to short-axis volumetric assessment. Trials registration: ClinicalTrials.gov: NCT05114785. Relevance statement: Integrating fully automated AI in CMR promises to revolutionise clinical cardiac assessment, offering efficient, accurate, and prognostically valuable insights for improved patient care and outcomes. Key points: • Four-chamber cine sequences remain one of the most informative acquisitions in CMR examination. • This deep learning-based, time-resolved, fully automated four-chamber volumetric, functional, and deformation analysis solution. • LV and RV were underestimated by four-chamber analysis compared to ground truth short-axis segmentation. • Correction bias for both LV and RV volumes by four-chamber segmentation, minimises the systematic bias. [ABSTRACT FROM AUTHOR]

Background: Left ventricular hypertrophy (LVH) is a common consequence of hypertension and can lead to heart failure. The immune response plays an important role in hypertensive LVH; however, there is no comprehensive method to investigate the mechanistic relationships between immune response and hypertensive LVH or to find novel therapeutic targets. This study aimed to screen hub immune-related genes involved in hypertensive LVH as well as to explore immune target-based therapeutic drugs. Materials and methods: RNA-sequencing data from a mouse model generated by angiotensin II infusion were subjected to weighted gene co-expression network analysis (WGCNA) to identify core expression modules. Machine learning algorithms were applied to screen immune-related LVH characteristic genes. Heart structures were evaluated by echocardiography and cardiac magnetic resonance imaging (CMRI). Validation of hub genes was conducted by RT-qPCR and western blot. Using the Connectivity Map database and molecular docking, potential small-molecule drugs were explored. Results: A total of 1215 differentially expressed genes were obtained, most of which were significantly enriched in immunoregulation and collagen synthesis. WGCNA and multiple machine learning strategies uncovered six hub immunerelated genes (Ankrd1, Birc5, Nuf2, C1qtnf6, Fcgr3, and Cdca3) that may accurately predict hypertensive LVH diagnosis. Immune analysis revealed that fibroblasts and macrophages were closely correlated with hypertensive LVH, and hub gene expression was significantly associated with these immune cells. A regulatory network of transcription factor-mRNA and a ceRNA network of miRNA-lncRNA was established. Notably, six hub immune-related genes were significantly increased in the hypertensive LVH model, which were positively linked to left ventricle wall thickness. Finally, 12 small-molecule compounds with the potential to reverse the high expression of hub genes were ruled out as potential therapeutic agents for hypertensive LVH. Conclusion: This study identified and validated six hub immune-related genes that may play essential roles in hypertensive LVH, providing new insights into the potential pathogenesis of cardiac remodeling and novel targets for medical interventions. [ABSTRACT FROM AUTHOR]

Background: This study investigates myocardial structural changes in stable coronary artery disease (CAD) patients with type 2 diabetes (T2D) using cardiac magnetic resonance (CMR) strain and T1 mapping. Methods: A total of 155 stable CAD patients underwent CMR examination, including left ventricular (LV) morphology and function assessment, late gadolinium enhancement (LGE), and feature tracking (CMR-FT) for LV global longitudinal, circumferential, and radial strain. T1 mapping with extracellular volume (ECV) evaluation was also performed. Results: Among the enrolled patients, 67 had T2D. Diabetic patients exhibited impaired LV strain and higher ECV compared to non-diabetics. Multivariate analysis identified T2D as an independent predictor of increased ECV and decreased strain. Conclusions: CMR-based strain and T1 mapping highlighted impaired myocardial contractility, elevated ECV, and potential interstitial fibrosis in diabetic patients with stable CAD. This suggests a significant impact of diabetes on myocardial health beyond CAD, emphasizing the importance of a comprehensive assessment in these individuals. Trial registration: http://www.controlled-trials.com/ISRCTN09454308 [ABSTRACT FROM AUTHOR]

Different rat strains are used in various animal models of pulmonary hypertension and right ventricular (RV) failure. No systematic assessment has been made to test differences in RV response to pressure overload between rat strains. We compared RV adaptation to pulmonary trunk banding (PTB) in Wistar (W), Sprague Dawley (SD), and Fischer344 (F) rats by hemodynamic profiling focusing on diastolic function. Age‐matched male rat weanlings were randomized to sham surgery (W‐sham, n = 5; SD‐sham, n = 4; F‐sham, n = 4) or PTB (W‐PTB, n = 8; SD‐PTB, n = 8; F‐PTB, n = 8). RV function was evaluated after 5 weeks by echocardiography, cardiac MRI, and invasive pressure‐volume measurements. PTB caused RV failure and increased RV systolic pressures four‐fold in all three PTB groups compared with sham. W‐ and SD‐PTB had a 2.4‐fold increase in RV end‐systolic volume index compared with sham, while F‐PTB rats were less affected. Diastolic and right atrial impairment were evident by increased RV end‐diastolic elastance, filling pressure, and E/e' in PTB rats compared with sham, again F‐PTB the least affected. In conclusions, PTB caused RV failure with signs of diastolic dysfunction. Despite a similar increase in RV systolic pressure, F‐PTB rats showed less RV dilatation and a more preserved diastolic function compared with W‐ and SD‐PTB. [ABSTRACT FROM AUTHOR]

Left atrial appendage (LAA) is the source of thrombi formation in more than 90% of strokes in patients with nonvalvular atrial fibrillation. Catheter-based LAA occlusion is being increasingly applied as a treatment strategy to prevent stroke. Anatomical complexity of LAA makes percutaneous occlusion commonly performed under transesophageal echocardiography (TEE) and X-ray (XR) guidance especially challenging. Image fusion techniques integrating 3D anatomical models derived from pre-procedural imaging into the live XR fluoroscopy can be applied to guide each step of the LAA closure. Cardiac magnetic resonance (CMR) imaging gains in importance for radiation-free evaluation of cardiac morphology as alternative to gold-standard TEE or computed tomography angiography (CTA). Manual delineation of cardiac structures from non-contrast enhanced CMR is, however, labor-intensive, tedious, and challenging due to the rather low contrast. Additionally, arrhythmia often impairs the image quality in ECG synchronized acquisitions causing blurring and motion artifacts. Thus, for cardiac segmentation in arrhythmic patients, there is a strong need for an automated image segmentation method. Deep learning-based methods have shown great promise in medical image analysis achieving superior performance in various imaging modalities and different clinical applications. Fully-convolutional neural networks (CNNs), especially U-Net, have become the method of choice for cardiac segmentation. In this paper, we propose an approach for automatic segmentation of cardiac structures from non-contrast enhanced CMR images of arrhythmic patients based on CNNs implemented in a multi-stage pipeline. Two-stage implementation allows subdividing the task into localization of the relevant cardiac structures and segmentation of these structures from the cropped sub-regions obtained from previous step leading to efficient and effective way of automated cardiac segmentation. • Deep learning approaches utilizing CNNs successfully achieved state-of-the-art for cardiac image segmentation. • Proposed two-stage CNN-based approach subdivides the segmentation task into localization and subsequent segmentation. • Introduced approach yields efficient method of cardiac image segmentation in arrhythmic patients with improved performance. [ABSTRACT FROM AUTHOR]

The efficacy of an implantable cardioverter-defibrillator (ICD) in patients with a non-ischaemic cardiomyopathy for primary prevention of sudden cardiac death is increasingly debated. We developed a multimodal deep learning model for arrhythmic risk prediction that integrated late gadolinium enhanced (LGE) cardiac magnetic resonance imaging (MRI), electrocardiography (ECG) and clinical data. Short-axis LGE-MRI scans and 12-lead ECGs were retrospectively collected from a cohort of 289 patients prior to ICD implantation, across two tertiary hospitals. A residual variational autoencoder was developed to extract physiological features from LGE-MRI and ECG, and used as inputs for a machine learning model (DEEP RISK) to predict malignant ventricular arrhythmia onset. In the validation cohort, the multimodal DEEP RISK model predicted malignant ventricular arrhythmias with an area under the receiver operating characteristic curve (AUROC) of 0.84 (95% confidence interval (CI) 0.71–0.96), a sensitivity of 0.98 (95% CI 0.75–1.00) and a specificity of 0.73 (95% CI 0.58–0.97). The models trained on individual modalities exhibited lower AUROC values compared to DEEP RISK [MRI branch: 0.80 (95% CI 0.65–0.94), ECG branch: 0.54 (95% CI 0.26–0.82), Clinical branch: 0.64 (95% CI 0.39–0.87)]. These results suggest that a multimodal model achieves high prognostic accuracy in predicting ventricular arrhythmias in a cohort of patients with non-ischaemic systolic heart failure, using data collected prior to ICD implantation. [ABSTRACT FROM AUTHOR]

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow imaging speed, resulting in low patient throughput and compromised clinical diagnostic quality. The limited temporal resolution also causes patient discomfort and introduces artifacts in the images, further diminishing their overall quality and diagnostic value. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have so far not been made publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. The 'CMRxRecon' dataset contains raw k-space data and auto-calibration lines. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community. [ABSTRACT FROM AUTHOR]

Objective: The meta-analysis aimed to explore the cardiac adaptation in hypothyroidism patients by cardiac magnetic resonance. Research methods and procedures: Databases including PubMed, Cochrane Library, Embase, CNKI, and Sinomed for clinical studies of hypothyroidism on cardiac function changes. Databases were searched from the earliest data to 15 June 2023. Two authors retrieved studies and evaluated their quality. Review Manager 5.4.1 and Stata18 were used to analyze the data. This study is registered with the International Platform of Registered Systematic Review and Metaanalysis Protocols (INPLASY), 202440114. Results: Six studies were selected for further analysis. Five of them reported differences in cardiac function measures between patients with hypothyroidism and healthy controls, and three studies reported cardiac function parameters after treatment in patients with hypothyroidism. The fixed-effect model combined WMD values for left ventricular ejection fraction (LVEF) had a pooled effect size of -1.98 (95% CI -3.50 to -0.44], P=0.01), implying that LVEF was lower in patients with hypothyroidism than in healthy people. Analysis of heterogeneity found moderate heterogeneity (P=0.08, I² = 50%). WMD values for stroke volume (SV), cardiac index (CI), left ventricular end-diastolic volume index(LVEDVI), left ventricular end-systolic volume (LESVI), and left ventricular mass index(LVMI) were also analyzed, and pooled effect sizes showed the CI and LVEDVI of patients with hypothyroidism ware significantly decrease (WMD=-0.47, 95% CI [-0.93 to -0.00], P=0.05, WMD=-7.99, 95%CI [-14.01 to -1.96], P=0.009, respectively). Patients with hypothyroidism tended to recover cardiac function after treatment [LVEF (WMD = 6.37, 95%CI [2.05, 10.69], P=0.004), SV (WMD = 7.67, 95%CI [1.61, 13.74], P=0.01), CI (WMD = 0.40, 95%CI [0.01, 0.79], P=0.05)], and there was no difference from the healthy controls. Conclusion: Hypothyroidism could affect cardiac function, although this does not cause significant heart failure. Itmay be an adaptation of the heart to the hypothyroid state. There was a risk that this adaptationmay turn intomyocardial damage. Cardiac function could be restored after treatment in patients with hypothyroidism. Aggressive levothyroxine replacement therapy should be used to reverse cardiac function. [ABSTRACT FROM AUTHOR]

Background: Stress hyperglycemia occurs frequently in patients following acute myocardial infarction (AMI) and may aggravate myocardial stiffness, but relevant evidence is still lacking. Accordingly, this study aimed to examine the impact of admission stress hyperglycemia on left ventricular (LV) myocardial deformation in patients following AMI. Methods: A total of 171 patients with first AMI (96 with normoglycemia and 75 with hyperglycemia) underwent cardiac magnetic resonance (CMR) examination were included. AMI patients were classified according to admission blood glucose level (aBGL): < 7.8 mmol/L (n = 96), 7.8–11.1 mmol/L (n = 41) and ≥ 11.1 mmol/L (n = 34). LV strains, including global radial/circumferential/longitudinal peak strain (PS)/peak systolic strain rate (PSSR)/peak diastolic strain rate (PDSR), were measured and compared between groups. Further, subgroup analyses were separately conducted for AMI patients with and without diabetes. Multivariate analysis was employed to assess the independent association between aBGL and LV global PS in AMI patients. Results: LV global PS, PSSR and PDSR were decreased in radial, circumferential and longitudinal directions in hyperglycemic AMI patients compared with normoglycemic AMI patients (all P < 0.05). These differences were more obvious in patients with diabetes than those without diabetes. AMI patients with aBGL between 7.8 and 11.1 mmol/L demonstrated significant decreased radial and longitudinal PS, radial PSSR, and radial and longitudinal PDSR than those with aBGL < 7.8 mmol/L (all P < 0.05). AMI patients with aBGL ≥ 11.1 mmol/L showed significantly decreased PS, PSSR and PDSR in all three directions than those with aBGL < 7.8 mmol/L, and decreased longitudinal PSSR than those with aBGL between 7.8 and 11.1 (all P < 0.05). Further, aBGL was significantly and independently associated with radial (β = − 0.166, P = 0.003) and longitudinal (β = 0.143, P = 0.008) PS. Conclusions: Hyperglycemia may exacerbate LV myocardial stiffness in patients experienced first AMI, leading to reduction in LV strains. aBGL was an independent indicator of impaired LV global PS in AMI patients. Blood glucose monitoring is more valuable for AMI patients with diabetes. [ABSTRACT FROM AUTHOR]

Background: The potential role of cardiac computed tomography (CT) has increasingly been demonstrated for the assessment of diffuse myocardial fibrosis through the quantification of extracellular volume (ECV). Photon-counting detector (PCD)-CT technology may deliver more accurate ECV quantification compared to energy-integrating detector CT. We evaluated the impact of reconstruction settings on the accuracy of ECV quantification using PCD-CT, with magnetic resonance imaging (MRI)-based ECV as reference. Methods: In this post hoc analysis, 27 patients (aged 53.1 ± 17.2 years (mean ± standard deviation); 14 women) underwent same-day cardiac PCD-CT and MRI. Late iodine CT scans were reconstructed with different quantum iterative reconstruction levels (QIR 1−4), slice thicknesses (0.4−8 mm), and virtual monoenergetic imaging levels (VMI, 40−90 keV); ECV was quantified for each reconstruction setting. Repeated measures ANOVA and t-test for pairwise comparisons, Bland–Altman plots, and Lin's concordance correlation coefficient (CCC) were used. Results: ECV values did not differ significantly among QIR levels (p = 1.000). A significant difference was observed throughout different slice thicknesses, with 0.4 mm yielding the highest agreement with MRI-based ECV (CCC = 0.944); 45-keV VMI reconstructions showed the lowest mean bias (0.6, 95% confidence interval 0.1–1.4) compared to MRI. Using the most optimal reconstruction settings (QIR4. slice thickness 0.4 mm, VMI 45 keV), a 63% reduction in mean bias and a 6% increase in concordance with MRI-based ECV were achieved compared to standard settings (QIR3, slice thickness 1.5 mm; VMI 65 keV). Conclusions: The selection of appropriate reconstruction parameters improved the agreement between PCD-CT and MRI-based ECV. Relevance statement: Tailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility. Key points: • CT is increasingly promising for myocardial tissue characterization, assessing focal and diffuse fibrosis via late iodine enhancement and ECV quantification, respectively. • PCD-CT offers superior performance over conventional CT, potentially improving ECV quantification and its agreement with MRI-based ECV. • Tailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility. [ABSTRACT FROM AUTHOR]

Computational fluid dynamics (CFD) can be used for non-invasive evaluation of hemodynamics. However, its routine use is limited by labor-intensive manual segmentation, CFD mesh creation, and time-consuming simulation. This study aims to train a deep learning model to both generate patient-specific volume-meshes of the pulmonary artery from 3D cardiac MRI data and directly estimate CFD flow fields. This proof-of-concept study used 135 3D cardiac MRIs from both a public and private dataset. The pulmonary arteries in the MRIs were manually segmented and converted into volume-meshes. CFD simulations were performed on ground truth meshes and interpolated onto point-point correspondent meshes to create the ground truth dataset. The dataset was split 110/10/15 for training, validation, and testing. Image2Flow, a hybrid image and graph convolutional neural network, was trained to transform a pulmonary artery template to patient-specific anatomy and CFD values, taking a specific inlet velocity as an additional input. Image2Flow was evaluated in terms of segmentation, and the accuracy of predicted CFD was assessed using node-wise comparisons. In addition, the ability of Image2Flow to respond to increasing inlet velocities was also evaluated. Image2Flow achieved excellent segmentation accuracy with a median Dice score of 0.91 (IQR: 0.86–0.92). The median node-wise normalized absolute error for pressure and velocity magnitude was 11.75% (IQR: 9.60–15.30%) and 9.90% (IQR: 8.47–11.90), respectively. Image2Flow also showed an expected response to increased inlet velocities with increasing pressure and velocity values. This proof-of-concept study has shown that it is possible to simultaneously perform patient-specific volume-mesh based segmentation and pressure and flow field estimation using Image2Flow. Image2Flow completes segmentation and CFD in ~330ms, which is ~5000 times faster than manual methods, making it more feasible in a clinical environment. Author summary: Computational fluid dynamics is an engineering tool that can be used in a clinical setting to non-invasively model blood flow through blood vessels, such as the pulmonary artery. This information can be used to inform treatment planning for patients, especially those with cardiovascular conditions. However, its routine use is limited by a labor-intensive process, requiring substantial expertise and computational resources. Recently, machine learning has offered solutions to automate parts of this process, but no single model has addressed the entire workflow. Therefore, we created Image2Flow, a machine learning model capable of generating a patient-specific representation of a pulmonary artery while predicting blood flow through the vessel. Image2Flow can generate highly accurate pulmonary artery representations and reasonably accurate blood flow predictions. Notably, it performs this whole process in 330ms, which is ~5000x faster than the manual methods. With its speed and accuracy, Image2Flow holds substantial promise for facilitating computational fluid dynamics in clinical settings. [ABSTRACT FROM AUTHOR]

Numerous diagnostic criteria for excessive trabeculation, or "noncompaction," score the extent of the trabecular layer. Whether the trabeculations themselves have a poor or good contractility is largely unknown. We retrospectively analyzed cardiac magnetic resonance (CMR) of patients with excessive trabeculation of the left ventricle (LV). The LV was labeled into four regions: compact wall, central cavity (CC), trabeculations, and intertrabecular recesses (IR). For each label we calculated the systolic fractional volume change (SFVC) in short‐axis images (n = 15) and systolic fractional area change (SFAC) in four‐chamber images (n = 30). We measured the ejection fraction (EF) of IR, CC, and total cavity. Three methods to calculate EF of the total cavity were compared: trabeculations included (per guidelines), IR excluded (Jacquier criterion), and trabeculations contoured and excluded (contour‐EF). The SFVC and SFAC of the compact wall were similar with SFVC and SFAC of trabeculations. In contrast, the IR were more diminished in systole by comparison with the CC, having lower SFVC (39% vs. 56%) and SFAC (37% vs. 72%). EF of the IR was also greater than EF of the CC (61% vs. 44%). Excluding IR from the total cavity or including trabeculations negatively impacts the EF (44% and 40%, respectively, vs. 51% for contour‐EF). The trabecular layer operates at a high EF. [ABSTRACT FROM AUTHOR]

Chronic coronary syndrome (CCS) is one of the leading cardiovascular causes of morbidity, mortality, and use of medical resources. After the introduction by international guidelines of the same level of recommendation to non-invasive imaging techniques in CCS evaluation, a large debate arose about the dilemma of choosing anatomical (with coronary computed tomography angiography (CCTA)) or functional imaging (with stress echocardiography (SE), cardiovascular magnetic resonance (CMR), or nuclear imaging techniques) as a first diagnostic evaluation. The determinant role of the atherosclerotic burden in defining cardiovascular risk and prognosis more than myocardial inducible ischemia has progressively increased the use of a first anatomical evaluation with CCTA in a wide range of pre-test probability in CCS patients. Functional testing holds importance, both because the role of revascularization in symptomatic patients with proven ischemia is well defined and because functional imaging, particularly with stress cardiac magnetic resonance (s-CMR), gives further prognostic information regarding LV function, detection of myocardial viability, and tissue characterization. Emerging techniques such as stress computed tomography perfusion (s-CTP) and fractional flow reserve derived from CT (FFRCT), combining anatomical and functional evaluation, appear capable of addressing the need for a single non-invasive examination, especially in patients with high risk or previous revascularization. Furthermore, CCTA in peri-procedural planning is promising to acquire greater importance in the non-invasive planning and guiding of complex coronary revascularization procedures, both by defining the correct strategy of interventional procedure and by improving patient selection. This review explores the different roles of non-invasive imaging techniques in managing CCS patients, also providing insights into preoperative planning for percutaneous or surgical myocardial revascularization. [ABSTRACT FROM AUTHOR]

A similarity-driven multi-dimensional binning algorithm (SIMBA) reconstruction of free-running cardiac magnetic resonance imaging data was previously proposed. While very efficient and fast, the original SIMBA focused only on the reconstruction of a single motion-consistent cluster, discarding the remaining data acquired. However, the redundant data clustered by similarity may be exploited to further improve image quality. In this work, we propose a novel compressed sensing (CS) reconstruction that performs an effective regularization over the clustering dimension, thanks to the integration of inter-cluster motion compensation (XD-MC-SIMBA). This reconstruction was applied to free-running ferumoxytol-enhanced datasets from 24 patients with congenital heart disease, and compared to the original SIMBA, the same XD-MC-SIMBA reconstruction but without motion compensation (XD-SIMBA), and a 5D motion-resolved CS reconstruction using the free-running framework (FRF). The resulting images were compared in terms of lung-liver and blood-myocardium sharpness, blood-myocardium contrast ratio, and visible length and sharpness of the coronary arteries. Moreover, an automated image quality score (IQS) was assigned using a pretrained deep neural network. The lung-liver sharpness and blood-myocardium sharpness were significantly higher in XD-MC-SIMBA and FRF. Consistent with these findings, the IQS analysis revealed that image quality for XD-MC-SIMBA was improved in 18 of 24 cases, compared to SIMBA. We successfully tested the hypothesis that multiple motion-consistent SIMBA clusters can be exploited to improve the quality of ferumoxytol-enhanced cardiac MRI when inter-cluster motion-compensation is integrated as part of a CS reconstruction. [ABSTRACT FROM AUTHOR]

Objective: Sodium glucose cotransporter 2 (SGLT2) inhibitors significantly improve cardiovascular outcomes in diabetic patients; however, the mechanism is unclear. We hypothesized that dapagliflozin improves cardiac outcomes via beneficial effects on systemic and cardiac inflammation and cardiac fibrosis. Research and design methods: This randomized placebo-controlled clinical trial enrolled 62 adult patients (mean age 62, 17% female) with type 2 diabetes (T2D) without known heart failure. Subjects were randomized to 12 months of daily 10 mg dapagliflozin or placebo. For all patients, blood/plasma samples and cardiac magnetic resonance imaging (CMRI) were obtained at time of randomization and at the end of 12 months. Systemic inflammation was assessed by plasma IL-1B, TNFα, IL-6 and ketone levels and PBMC mitochondrial respiration, an emerging marker of sterile inflammation. Global myocardial strain was assessed by feature tracking; cardiac fibrosis was assessed by T1 mapping to calculate extracellular volume fraction (ECV); and cardiac tissue inflammation was assessed by T2 mapping. Results: Between the baseline and 12-month time point, plasma IL-1B was reduced (− 1.8 pg/mL, P = 0.003) while ketones were increased (0.26 mM, P = 0.0001) in patients randomized to dapagliflozin. PBMC maximal oxygen consumption rate (OCR) decreased over the 12-month period in the placebo group but did not change in patients receiving dapagliflozin (− 158.9 pmole/min/106 cells, P = 0.0497 vs. − 5.2 pmole/min/106 cells, P = 0.41), a finding consistent with an anti-inflammatory effect of SGLT2i. Global myocardial strain, ECV and T2 relaxation time did not change in both study groups. Clinical Trial.gov Registration: NCT03782259. [ABSTRACT FROM AUTHOR]

Background: Aberrant left coronary artery from pulmonary artery (ALCAPA) is a very rare congenital heart defect. Its coexistence with patent ductus arteriosus (PDA) is extremely rare. The high pressures created by the left-to-right shunt in the pulmonary arteries can delay symptoms and create a real challenge in diagnosing ALCAPA. Missing this diagnosis can have severe results, including extensive ischemia and sudden death. Case presentation: We present a case of an infant born with a large PDA. Initially treated conservatively, however, due to congestive heart failure and lack of weight gain, she underwent surgical ligation of the PDA at the age of four and a half months. Following surgery, she developed pulmonary edema. Echocardiography revealed decreased ventricular function. ECG revealed ST elevations on lateral leads, and serum troponin was significantly increased. The patient underwent cardiac magnetic resonance imaging (MRI), which revealed signs of wall ischemia and decreased function of the left ventricle (LV) with unclear coronary anatomy. Diagnostic catheterization revealed an ALCAPA. She underwent surgical intervention, and the left coronary artery was re-implanted in the aortic sinus. Follow-up revealed slow improvement of cardiac function. Discussion and literature review: The coexistence of PDA and ALCAPA is a very rare occurrence. We found at least 10 reported cases in the literature. Delayed diagnosis might be detrimental. The prognosis of these patients is variable. Conclusion: An unusual post-surgical course following PDA repair requires a high index of suspicion and appropriate evaluation for ALCAPA, preferably with angiography. [ABSTRACT FROM AUTHOR]

Systemic sclerosis (SSc) is an autoimmune rheumatic disease, characterized by vascular, inflammatory and fibrotic alterations. Cardiac involvement is the « fatal tip of the iceberg» in SSc, as it leads to high morbidity/mortality. Cardiovascular imaging modalities play an important role in the early diagnosis and treatment assessment of cardiac involvement. Echocardiography is the corner stone for evaluation of cardiac involvement, providing information about function, wall motion, pulmonary pressure, pericardium and valvular disease. It is a low-cost modality, widely available, without radiation and with great experience among cardiologists. However, it is a window and operator dependent modality and cannot provide tissue characterization information, absolutely necessary for diagnosis and treatment of cardiac involvement in SSc. Cardiovascular magnetic resonance (CMR) can perform myocardial function and tissue characterization in the same examination without radiation, has excellent reproducibility and is window and operator independent. The great advantage of CMR is the capability to assess peri- myo-vascular inflammation, myocardial ischemia and presence of replacement and diffuse myocardial fibrosis in parallel with ventricular function assessment. The modified Lake Louise criteria including T2, native T1 mapping and extracellular volume fraction (ECV) has been recently used to diagnose inflammatory cardiomyopathy. According to expert recommendations, myocardial inflammation should be considered if at least 2 indices, one T2 and one T1 parameter are positive, whereas native T1 mapping and ECV assess diffuse fibrosis or oedema, even in the absence of late gadolinium enhancement (LGE). Moreover, transmural/subendocardial LGE following the distribution of coronary arteries and diffuse subendocardial fibrosis not related with epicardial coronary arteries are indicative of epicardial and micro-vascular coronary artery disease, respectively. To conclude, CMR can overcome the limitations of echocardiography by identifying acute/active or chronic myocardial inflammation/fibrosis, ischemia and myocardial infarction using classic and parametric indices in parallel with biventricular function assessment [ABSTRACT FROM AUTHOR]

Background: Congenital absence of pericardium is a rare cardiac disorder with a reported incidence of less than 1 in 10,000. Although most of the cases are of little clinical significance, some of them are associated with serious complications, including risk of herniation and strangulation or coronary artery compression. Detailed Case Description: We report a case of a 36-year-old male referred for routine cardiovascular examination. He had a medical history of a heart murmur since childhood. Electrocardiogram (ECG) revealed sinus rhythm, normal axis, poor R-wave progression in the precordial leads and repolarization abnormalities with negative T waves in leads V1–V4. On 2D transthoracic echocardiography (TTE), an unusual heart position was noted with poor image quality from the standard acoustic windows. The parasternal long axis view gave the impression of right ventricular dilatation. The findings raised the suspicion of left to right shunt and possible atrial septal defect. For further evaluation, the patient was referred for cardiac magnetic resonance which demonstrated complete left-sided absence of the pericardium. Discussion: Due to indistinct and atypical symptoms and lack of clinical awareness, pericardial congenital absence is frequently misdiagnosed. Patients may complain of atypical chest pain. Patient's history and physical examination are often nonspecific. In cases with complete pericardial absence, ECG findings may include right axis deviation, right bundle block and sinus bradycardia. Echocardiography findings are also not characteristic, but some may raise the clinical suspicion of this diagnosis. The imaging modalities of choice are computed tomography and cardiac magnetic resonance. Treatment depends on the type of defect and clinical symptoms. [ABSTRACT FROM AUTHOR]

Background Fluoroscopy-guided catheter ablation has become the gold standard for treatment of cardiac arrhythmias. High resolution electro-anatomical mapping systems have become fundamental to perform these procedures. Recently, interventional cardiac magnetic resonance (iCMR) has been proposed as an alternative for fluoroscopy to guide atrial flutter ablations. The clinical experience with iCMR and dedicated three-dimensional mapping systems is growing. NorthStar is currently the first available vendor-neutral mapping system. Case summary We performed a real-time CMR-guided cavotricuspid isthmus (CTI) catheter ablation (CA) on a 69-year-old man using a novel mapping system (NorthStar Mapping System, Imricor Medical Systems, MN, USA). Starting from the CMR imaging, a pre-rendered segmentation model was loaded on NorthStar and used to guide the catheters, display voltage and activation maps, show mapping and ablation points. NorthStar can also take full control of the CMR scanner (i.e. start/stop sequences for anatomical information, tissue characterization, and catheter visualization) and communicate with the recorder/stimulator system (Advantage-MR EP, Imricor Medical Systems, MN, USA). With comparable procedural time to standard fluoroscopy-guided CA, CTI bidirectional block was achieved, without any complication. Discussion Using the NorthStar Mapping System, we managed to achieve a successful CMR-guided CTI ablation without any complication. Its further use should be explored, especially in more complex arrhythmias where a substrate-guided ablation is critical, as it could significantly improve results in terms of arrhythmia recurrence. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to assess the importance of T1-mapping sequences in the diagnosis of hypertrophic cardiomyopathy (HCM) in patients without foci of non-ischemic myocardial injury in classic cardiac magnetic resonance (CMR) sequences. Methods: Two groups were compared: 28 patients with HCM, without any foci of myocardial injury in the late gadolinium enhancement (LGE) sequence (HCM group), and 28 patients without cardiomyopathy (CON group). Classic CMR sequences and T1-mapping sequences were performed. The following parameters were assessed: T1 time of the whole left ventricular myocardium, T1 time of myocardium in the basal, middle and apical layers of the left ventricle, and T1 time in individual segments of the left ventricular myocardium. Myocardial extracellular volume (ECV) was assessed similarly. Results: ECV was significantly higher in the HCM group than in the CON group, for the whole left ventricular myocardium, for the basal and apical layers of the left ventricle, and for segments 1–3, 8, and 13–16 of the left ventricle. Regression analysis showed that a higher left-ventricular mass index (LVMI), a higher body mass index and older age are factors independently associated with a higher ECV of the whole myocardium but only in the group with LVMI ≥ 131.84 g/m2. Conclusion: In patients with HCM without foci of non-ischemic myocardial injury, higher ECV values of the left ventricular myocardium are observed. [ABSTRACT FROM AUTHOR]

The existing image semantic segmentation models have low accuracy in detecting tiny targets or multi-targets at overlapping regions. This work proposes a hybrid vision transformer with unified-perceptual-parsing network (ViT-UperNet) for medical image segmentation. A self-attention mechanism is embedded in a vision transformer to extract multi-level features. The image features are extracted hierarchically from low to high dimensions using 4 groups of Transformer blocks with different numbers. Then, it uses a unified-perceptual-parsing network based on a feature pyramid network (FPN) and a pyramid pooling module (PPM) for the fusion of multi-scale contextual features and semantic segmentation. FPN can naturally use hierarchical features, and generate strong semantic information on all scales. PPM can better use the global prior knowledge to understand complex scenes, and extract features with global context information to improve segmentation results. In the training process, a scalable self-supervised learner named masked autoencoder is used for pre-training, which strengthens the visual representation ability and improves the efficiency of the feature learning. Experiments are conducted on cardiac magnetic resonance image segmentation where the left and right atrium and ventricle are selected for segmentation. The pixels accuracy is 93.85%, the Dice coefficient is 92.61% and Hausdorff distance is 11.16, which are improved compared with the other methods. The results show the superiority of Vit-UperNet in medical images segmentation, especially for the low-recognition and serious-occlusion targets. [ABSTRACT FROM AUTHOR]

Objectives: Our study aimed to assess the safety and efficacy of cardiac contractility modulation (CCM) therapy in patients with heart failure with reduced ejection fraction (HFrEF) depending on HF etiology. Methods: We enrolled 166 patients with optimal medical therapy-resistant HFrEF (median age 59 years, 83.7% males, median NYHA class − 2, median left ventricular ejection fraction (LVEF) − 29.0%) who underwent CCM therapy device implantation from 2013 to 2019 in four medical centers in Russia. The HF etiology was determined based on invasive coronary angiography or cardiac MRI data. Transthoracic echocardiography (TTE), 6-minute walking test (6MWT), and NTproBNP-tests were performed at a baseline and 12 months after the implantation. Results: The ischemic etiology of HF was revealed in 100 patients (61.5%) (ICM group); the non-ischemic group (NICM) evolved 66 patients (38.5%). Patients in the ICM group were significantly older (61[57–69] vs. 55 [42.8–61], p < 0.001), more frequently had hypertension (79% vs. 42.4%, p < 0.001) and chronic kidney disease (43% vs. 22.7%, p = 0.012). Patients in the NICM group had significantly more often atrial fibrillation (AF) (58% vs. 74%, p = 0.048), larger end-diastolic volume (EDV) (249 [208–309] vs. 220 [192–271], p = 0.019) and end-systolic volume (ESV) (183 [147–230] vs. 154 [128–199], p = 0.003). There were no significant differences in mortality between ICM and NICM groups (14.4 vs. 10.8%, p = 0.51). In 12 months, there was a significant increase in LVEF in the NICM group (+ 2.0 [2–6] vs. +7.7 [2–12], p < 0.001), while the improvement in the 6MWT (+ 75 [22–108] vs. +80 [10–160], p = 0.851) and NYHA class did not reach the level of significance. The subanalysis between patients with improved NYHA class and those without improvement revealed that patients without improvement more frequently had AF (56% vs. 89%; p < 0.01), chronic obstructive lung disease (18% vs. 35% p = 0.047), higher blood pressure (110 [105–120] vs. 120[110–129]; p = 0.032). Conclusion: In this multicenter retrospective study, patients with non-ischemic HFrEF showed a significantly higher improvement in LVEF and LV reverse remodeling following CCM therapy device implantation. There was no significant association between HF etiology and survival in drug-resistant HFrEF patients following CCM therapy. [ABSTRACT FROM AUTHOR]

Background: Stress hyperglycemia, which is associated with poor prognosis in patients with acute myocardial infarction (AMI), can be determined using the stress hyperglycemia ratio (SHR). Impaired left ventricular function and microvascular obstruction (MVO) diagnosed using cardiac magnetic resonance (CMR) have also been proven to be linked to poor prognosis in patients with AMI and aid in risk stratification. However, there have been no studies on the correlation between fasting SHR and left ventricular function and MVO in patients with acute ST-segment elevation myocardial infarction (ASTEMI). Therefore, this study aimed to investigate the additive effect of fasting SHR on left ventricular function and global deformation in patients with ASTEMI and to explore the association between fasting SHR and MVO. Methods: Consecutive patients who underwent CMR at index admission (3–7 days) after primary percutaneous coronary intervention (PPCI) were enrolled in this study. Basic clinical, biochemical, and CMR data were obtained and compared among all patients grouped by fasting SHR tertiles: SHR1: SHR < 0.85; SHR2: 0.85 ≤ SHR < 1.01; and SHR3: SHR ≥ 1.01. Spearman's rho (r) was used to assess the relationship between fasting SHR and left ventricular function, myocardial strain, and the extent of MVO. Multivariable linear regression analysis was performed to evaluate the determinants of left ventricular function and myocardial strain impairment in all patients with AMI. Univariable and multivariable regression analyses were performed to investigate the correlation between fasting SHR and the presence and extent of MVO in patients with AMI and those with AMI and diabetes mellitus (DM). Results: A total of 357 patients with ASTEMI were enrolled in this study. Left ventricular ejection fraction (LVEF) and left ventricular global function index (LVGFI) were significantly lower in SHR2 and SHR3 than in SHR1. Compared with SHR1 and SHR2 groups, left ventricular strain was lower in SHR3, as evidenced by global radial (GRS), global circumferential (GCS), and global longitudinal (GLS) strains. Fasting SHR were negatively correlated with LVEF, LVGFI, and GRS (r = − 0.252; r = − 0.261; and r = − 0.245; all P<0.001) and positively correlated with GCS (r = 0.221) and GLS (r = 0.249; all P <0.001). Multivariable linear regression analysis showed that fasting SHR was an independent determinant of impaired LVEF, LVGFI, GRS, and GLS. Furthermore, multivariable regression analysis after adjusting for covariates signified that fasting SHR was associated with the presence and extent of MVO in patients with AMI and those with AMI and DM. Conclusion: Fasting SHR in patients with ASTEMI successfully treated using PPCI is independently associated with impaired cardiac function and MVO. In patients with AMI and DM, fasting SHR is an independent determinant of the presence and extent of MVO. [ABSTRACT FROM AUTHOR]

Background: The prevalence of hypertensive heart disease (HHD) is high and there is currently no easy way to detect early HHD. Explore the application of radiomics using cardiac magnetic resonance (CMR) non-enhanced cine sequences in diagnosing HHD and latent cardiac changes caused by hypertension. Methods: 132 patients who underwent CMR scanning were divided into groups: HHD (42), hypertension with normal cardiac structure and function (HWN) group (46), and normal control (NOR) group (44). Myocardial regions of the end-diastolic (ED) and end-systolic (ES) phases of the CMR short-axis cine sequence images were segmented into regions of interest (ROI). Three feature subsets (ED, ES, and ED combined with ES) were established after radiomic least absolute shrinkage and selection operator feature selection. Nine radiomic models were built using random forest (RF), support vector machine (SVM), and naive Bayes. Model performance was analyzed using receiver operating characteristic curves, and metrics like accuracy, area under the curve (AUC), precision, recall, and specificity. Results: The feature subsets included first-order, shape, and texture features. SVM of ED combined with ES achieved the highest accuracy (0.833), with a macro-average AUC of 0.941. AUCs for HHD, HWN, and NOR identification were 0.967, 0.876, and 0.963, respectively. Precisions were 0.972, 0.740, and 0.826; recalls were 0.833, 0.804, and 0.863, respectively; and specificities were 0.989, 0.863, and 0.909, respectively. Conclusions: Radiomics technology using CMR non-enhanced cine sequences can detect early cardiac changes due to hypertension. It holds promise for future use in screening for latent cardiac damage in early HHD. [ABSTRACT FROM AUTHOR]

Increased left atrial volume and decreased left atrial function have long been associated with atrial fibrillation. The availability of large-scale cardiac magnetic resonance imaging data paired with genetic data provides a unique opportunity to assess the genetic contributions to left atrial structure and function, and understand their relationship with risk for atrial fibrillation. Here, we use deep learning and surface reconstruction models to measure left atrial minimum volume, maximum volume, stroke volume, and emptying fraction in 40,558 UK Biobank participants. In a genome-wide association study of 35,049 participants without pre-existing cardiovascular disease, we identify 20 common genetic loci associated with left atrial structure and function. We find that polygenic contributions to increased left atrial volume are associated with atrial fibrillation and its downstream consequences, including stroke. Through Mendelian randomization, we find evidence supporting a causal role for left atrial enlargement and dysfunction on atrial fibrillation risk. In this study, a deep learning-based model of left atrial size in UK Biobank enabled genome-wide association studies in 35,049 healthy participants. Several lines of evidence, including the PITX2 locus, linked left atrial dysfunction to atrial fibrillation risk. [ABSTRACT FROM AUTHOR]

Cardiac magnetic resonance (CMR) imaging allows precise non-invasive quantification of cardiac function. It requires reliable image segmentation for myocardial tissue. Clinically used software usually offers automatic approaches for this step. These are, however, designed for segmentation of human images obtained at clinical field strengths. They reach their limits when applied to preclinical data and ultrahigh field strength (such as CMR of pigs at 7 T). In our study, eleven animals (seven with myocardial infarction) underwent four CMR scans each. Short-axis cine stacks were acquired and used for functional cardiac analysis. End-systolic and end-diastolic images were labelled manually by two observers and inter- and intra-observer variability were assessed. Aiming to make the functional analysis faster and more reproducible, an established deep learning (DL) model for myocardial segmentation in humans was re-trained using our preclinical 7 T data (n = 772 images and labels). We then tested the model on n = 288 images. Excellent agreement in parameters of cardiac function was found between manual and DL segmentation: For ejection fraction (EF) we achieved a Pearson's r of 0.95, an Intraclass correlation coefficient (ICC) of 0.97, and a Coefficient of variability (CoV) of 6.6%. Dice scores were 0.88 for the left ventricle and 0.84 for the myocardium. [ABSTRACT FROM AUTHOR]

Imaging using cardiac computed tomography (CT) or magnetic resonance (MR) imaging has become an important option for anatomic and substrate delineation in complex atrial fibrillation (AF) and ventricular tachycardia (VT) ablation procedures. Computed tomography more common than MR has been used to detect procedure-associated complications such as oesophageal, cerebral, and vascular injury. This clinical consensus statement summarizes the current knowledge of CT and MR to facilitate electrophysiological procedures, the current value of real-time integration of imaging-derived anatomy, and substrate information during the procedure and the current role of CT and MR in diagnosing relevant procedure-related complications. Practical advice on potential advantages of one imaging modality over the other is discussed for patients with implanted cardiac rhythm devices as well as for planning, intraprocedural integration, and post-interventional management in AF and VT ablation patients. Establishing a team of electrophysiologists and cardiac imaging specialists working on specific details of imaging for complex ablation procedures is key. Cardiac magnetic resonance (CMR) can safely be performed in most patients with implanted active cardiac devices. Standard procedures for pre- and post-scanning management of the device and potential CMR-associated device malfunctions need to be in place. In VT patients, imaging—specifically MR—may help to determine scar location and mural distribution in patients with ischaemic and non-ischaemic cardiomyopathy beyond evaluating the underlying structural heart disease. Future directions in imaging may include the ability to register multiple imaging modalities and novel high-resolution modalities, but also refinements of imaging-guided ablation strategies are expected. [ABSTRACT FROM AUTHOR]

Background One of the main causes of myocardial infarction during pregnancy is spontaneous coronary artery dissection. This is ascribed to hormonal changes during pregnancy leading to a weakening of the vessel wall and haemodynamic changes especially during childbirth. Management options include conservative medical treatment and percutaneous coronary intervention, depending on clinical presentation. Case summary A 37-year-old woman presented with typical chest pain six weeks after giving birth to her third child. Echocardiography revealed a moderate reduction in systolic function. Initial invasive coronary angiography showed no abnormalities. After cardiac magnetic resonance demonstrated extensive scar, invasive coronary angiography was repeated including intravascular imaging. A dissection of the left anterior descending artery was visualized and treated by percutaneous coronary intervention and stenting. Left ventricular function was normalized at three-month follow-up. In this educational case report, we highlight the diagnostic and therapeutic challenges when treating this special patient cohort and the importance of cardiovascular imaging. Discussion Pregnancy-associated spontaneous coronary dissection is a potential differential diagnosis when treating post-partum women with recent onset chest pain. Management is challenging and intravascular imaging to visualize dissection should be performed during invasive coronary angiography. Patients require interdisciplinary care within a pregnancy heart team. [ABSTRACT FROM AUTHOR]

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice. [ABSTRACT FROM AUTHOR]

This comprehensive review explores the intricate aspects of left ventricular thrombus (LVT), a potential complication in both ischemic and non-ischemic cardiomyopathies. It provides a thorough understanding of left ventricular thrombus, revealing its uncommon incidence in the general population (7 cases per 10,000 patients), predominantly linked to ischemic heart diseases (ICMs) at an 80% prevalence rate. Diagnostic tools, notably transthoracic echocardiography (TTE) and cardiac magnetic resonance imaging (CMR), demonstrate varying sensitivity but remain indispensable in specific clinical contexts related to LVT as non-invasive diagnostic modalities. A detailed comparison between ICM patients and those with non-ischemic cardiomyopathy (NICM) who have left ventricular thrombus reveals subtle distinctions with significant clinical implications. This analysis underscores the importance of these imaging techniques in distinguishing between the two conditions. Additionally, we explored the occurrence of LVT in specific non-ischemic cardiomyopathies, including Takotsubo syndrome, hypertrophic cardiomyopathy, eosinophilic myocarditis, Chagas disease, cardiac amyloidosis, and several other conditions. The article further delves into anticoagulation strategies, thoroughly examining their impact on LVT regression and patient outcomes. Pharmacological interventions, with a focus on direct oral anticoagulants, emerge as promising alternatives; however, there is insufficient information on their efficiency and safety, especially in NICM population. In conclusion, this review highlights the complex nature of LVT, incorporating a range of etiopathogenic factors, diagnostic complexities, and evolving therapeutic approaches. It emphasizes the pressing need for ongoing research in this field. [ABSTRACT FROM AUTHOR]

Background: Pulmonary hypertension (PH) is a leading cause of death in patients with systemic sclerosis (SSc). An important component of SSc patient management is early detection and treatment of PH. Recently the threshold for the diagnosis of PH has been lowered to a mean pulmonary artery pressure (mPAP) threshold of > 20 mmHg on right heart catheterization (RHC). However, it is unknown if PH-specific therapy is beneficial in SSc patients with mildly elevated pressure (SSc-MEP, mPAP 21–24 mmHg). Methods: The SEPVADIS trial is a randomized, double-blind, placebo-controlled phase 2 trial of sildenafil in SSc-MEP patients with a target enrollment of 30 patients from two academic sites in the United States. The primary outcome is change in six-minute walk distance after 16 weeks of treatment. Secondary endpoints include change in pulmonary arterial compliance by RHC and right ventricular function by cardiac magnetic resonance imaging at 16 weeks. Echocardiography, serum N-terminal probrain natriuretic peptide, and health-related quality of life is being measured at 16 and 52 weeks. Discussion: The SEPVADIS trial will be the first randomized study of sildenafil in SSc-MEP patients. The results of this trial will be used to inform a phase 3 study to investigate the efficacy of treating patients with mild elevations in mPAP. Trial registration: ClinicalTrials.gov Identifier NCT04797286. [ABSTRACT FROM AUTHOR]

This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered for the study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE, n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. Cardiac function was characterized from CMR in 3 potential directions: by (1) volume temporal transients (i.e. contraction dynamics); (2) feature tracking strain analysis (i.e. bulk tissue peak contraction); and (3) 3D shape analysis (i.e. 3D contraction morphology). A fully automated pipeline was developed to extract conventional and novel artificial-intelligence-derived metrics of cardiac contraction, and their relationship with MACE was investigated. Any of the 3 proposed directions demonstrated its additional prognostic value on top of established CMR indexes, myocardial injury markers, basic characteristics, and cardiovascular risk factors (P < 0.001). The combination of these 3 directions of enhancement towards a final CMR risk model improved MACE prediction by 13% compared to clinical baseline (0.774 (0.771—0.777) vs. 0.683 (0.681—0.685) cross-validated AUC, P < 0.001). The study evidences the contribution of the novel contraction characterization, enabled by a fully automated pipeline, to post-infarction assessment. [ABSTRACT FROM AUTHOR]

The aim of this retrospective study was to identify myocardial injury after COVID-19 inflammation and explore whether myocardial damage could be a possible cause of the persistent symptoms following COVID-19 infection in previously healthy individuals. This study included 139 patients who were enrolled between January and June 2021, with a mean age of 46.7 ± 15.2 years, of whom 68 were men and 71 were women without known cardiac or pulmonary diseases. All patients underwent clinical work-up, laboratory analysis, cardiac ultrasound, and CMR on a 1.5 T scanner using a recommended protocol for morphological and functional assessment before and after contrast media application with multi-parametric sequences. In 39% of patients, late gadolinium enhancement (LGE) was found as a sign of myocarditis. Fibrinogen was statistically significantly higher in patients with LGE than in those without LGE (4.3 ± 0.23 vs. 3.2 ± 0.14 g/L, p < 0.05, respectively), as well as D-dimer (1.8 ± 0.3 vs. 0.8 ± 0.1 mg/L FEU). Also, troponin was statistically significantly higher in patients with myocardial LGE (13.1 ± 0.4 ng/L) compared to those with normal myocardium (4.9 ± 0.3 ng/L, p < 0.001). We demonstrated chest pain, fatigue, and elevated troponin to be independent predictors for LGE. Septal LGE was shown to be a predictor for arrhythmias. The use of CMR is a potential risk stratification tool in evaluating outcomes following COVID-19 myocarditis. [ABSTRACT FROM AUTHOR]

Background: In clinical diagnostics, magnetic resonance imaging (MRI) technology plays a crucial role in the recognition of cardiac regions, serving as a pivotal tool to assist physicians in diagnosing cardiac diseases. Despite the notable success of convolutional neural networks (CNNs) in cardiac MRI segmentation, it remains a challenge to use existing CNNs-based methods to deal with fuzzy information in cardiac MRI. Therefore, we proposed a novel network architecture named DAFNet to comprehensively address these challenges. Methods: The proposed method was used to design a fuzzy convolutional module, which could improve the feature extraction performance of the network by utilizing fuzzy information that was easily ignored in medical images while retaining the advantage of attention mechanism. Then, a multi-scale feature refinement structure was designed in the decoder portion to solve the problem that the decoder structure of the existing network had poor results in obtaining the final segmentation mask. This structure further improved the performance of the network by aggregating segmentation results from multi-scale feature maps. Additionally, we introduced the dynamic convolution theory, which could further increase the pixel segmentation accuracy of the network. Result: The effectiveness of DAFNet was extensively validated for three datasets. The results demonstrated that the proposed method achieved DSC metrics of 0.942 and 0.885, and HD metricd of 2.50mm and 3.79mm on the first and second dataset, respectively. The recognition accuracy of left ventricular end-diastolic diameter recognition on the third dataset was 98.42%. Conclusion: Compared with the existing CNNs-based methods, the DAFNet achieved state-of-the-art segmentation performance and verified its effectiveness in clinical diagnosis. [ABSTRACT FROM AUTHOR]

Background: Left atrial (LA) assessment is an important marker of adverse cardiovascular outcomes. Cardiovascular magnetic resonance (CMR) accurately quantifies LA volume and function based on biplane long-axis imaging. We aimed to validate single-plane-derived LA indices against the biplane method to simplify the post-processing of cine CMR. Methods: In this study, 100 patients from Leeds Teaching Hospitals were used as the derivation cohort. Bias correction for the single plane method was applied and subsequently validated in 79 subjects. Results: There were significant differences between the biplane and single plane mean LA maximum and minimum volumes and LA ejection fraction (EF) (all p < 0.01). After correcting for biases in the validation cohort, significant correlations in all LA indices were observed (0.89 to 0.98). The area under the curve (AUC) for the single plane to predict biplane cutoffs of LA maximum volume ≥ 112 mL was 0.97, LA minimum volume ≥ 44 mL was 0.99, LA stroke volume (SV) ≤ 21 mL was 1, and LA EF ≤ 46% was 1, (all p < 0.001). Conclusions: LA volumetric and functional assessment by the single plane method has a systematic bias compared to the biplane method. After bias correction, single plane LA volume and function are comparable to the biplane method. [ABSTRACT FROM AUTHOR]

A blood test identifying patients at increased risk of pulmonary hypertension (PH) could streamline the investigative pathway. The prospective, multicenter CIPHER study aimed to develop a microRNA‐based signature for detecting PH in breathless patients and enrolled adults with a high suspicion of PH who had undergone right heart catheterization (RHC). The CIPHER‐MRI study was added to assess the performance of this CIPHER signature in a population with low probability of having PH who underwent cardiac magnetic resonance imaging (cMRI) instead of RHC. The microRNA signature was developed using a penalized linear regression (LASSO) model. Data were modeled both with and without N‐terminal pro‐brain natriuretic peptide (NT‐proBNP). Signature performance was assessed against predefined thresholds (lower 98.7% CI bound of ≥0.73 for sensitivity and ≥0.53 for specificity, based on a meta‐analysis of echocardiographic data), using RHC as the true diagnosis. Overall, 926 CIPHER participants were screened and 888 were included in the analysis. Of 688 RHC‐confirmed PH cases, approximately 40% were already receiving PH treatment. Fifty microRNA (from 311 investigated) were algorithmically selected to be included in the signature. Sensitivity [97.5% CI] of the signature was 0.85 [0.80–0.89] for microRNA‐alone and 0.90 [0.86–0.93] for microRNA+NT‐proBNP, and the corresponding specificities were 0.33 [0.24–0.44] and 0.28 [0.20–0.39]. Of 80 CIPHER‐MRI participants with evaluable data, 7 were considered PH‐positive by cMRI whereas 52 were considered PH‐positive by the microRNA signature. Due to low specificity, the CIPHER miRNA‐based signature for PH (either with or without NT‐proBNP in model) did not meet the prespecified diagnostic threshold for the primary analysis. [ABSTRACT FROM AUTHOR]

Background: Pericardial masses are an extremely rare group of diseases which can be classified based on etiology. The presentation of pericardial masses varies considerably from one individual to another, ranging from an asymptomatic presentation with an incidental finding on imaging, to presenting with non-specific signs and symptoms. Due to the enigmatic nature and presentation of pericardial masses, diagnostic imaging is mandatory. Case Presentation: A 69-year-old patient presented to our cardiology clinic complaining of intermittent shortness of breath upon moderate exertion in the absence of chest pain, paroxysmal nocturnal dyspnea, orthopnea, dizziness, palpitations, or lower limb edema. The patient's past medical history was significant because of his history of pericarditis associated with pericardial effusion 6 years prior to presentation at our clinic. Despite adequate medical treatment, the patient complained of a relapsing and remitting pattern of symptoms that mandated the performance of advanced cardiovascular imaging, namely, cardiac magnetic resonance imaging, which revealed the presence of a profound pericardial mass. Conclusion: Despite the fact that relapsing pericarditis is a well-established complication following acute pericarditis, the presentation of a complication such as a fibrous pericardial mass evident on cardiac MRI has essentially been unreported in the literature previously. [ABSTRACT FROM AUTHOR]

Background: Ebstein anomaly (EA) is a rare congenital heart disease characterized by the apical displacement of the tricuspid leaflets, creating an enlarged functional right atrium. Supraventricular arrhythmias (SVA) are common, and catheter ablation remains challenging. SVA is considered a risk factor for sudden cardiac death in this population. Still, there are very few real-life data on the impact of SVA treated invasively or conservatively on a patient's prognosis. We aimed to analyze the incidence of SVA in adults with EA, evaluate the effectiveness of catheter ablation, and analyze the impact of SVA and catheter ablation on survival in this population. Methods and results: 71 pts (median age 53 years; range 24–84 years) with EA were evaluated retrospectively from 1988 to 2020. Forty patients (56.3%) had SVA, and eighteen of them (45.0%) required at least one catheter ablation (35 procedures in total). Indications for ablation were mostly intra-atrial reentrant tachycardia (IART) and atrioventricular reentrant tachycardia (AVRT) (14 pts [77.8% and 9 pts [50.0%], respectively. IART and AVRT coexisted in nine pts. One patient suffered from persistent atrial fibrillation. Procedural effectiveness was reported in 28 (80%) cases; over a longer follow-up (mean 12.6 ± 5.4 years), only eight (44.4%) patients were completely free from SVA after the first ablation. In total, 10 patients (14%) died due to cardiovascular events. There was no difference in survival between patients with or without SVA (p = 0.9) and between ablated and non-ablated EA individuals (p = 0.89). Conclusions: Supraventricular arrhythmia is frequent in adults with Ebstein anomaly. Patients often require more than one catheter ablation but eventually become free from arrhythmias. The imaging parameters assessed by echocardiography or cardiac magnetic resonance do not seem to be associated with ablation outcomes. The impact of supraventricular arrhythmia itself or treatment with radiofrequency ablation is questionable and should be thoroughly investigated in this population. [ABSTRACT FROM AUTHOR]

Purpose of Review: Left ventricular arrhythmogenic cardiomyopathy (ALVC) is a rare and poorly characterized cardiomyopathy that has recently been reclassified in the group of non-dilated left ventricular cardiomyopathies. This review aims to summarize the background, diagnosis, and sudden cardiac death risk in patients presenting this cardiomyopathy. Recent Findings: Although there is currently a lack of data on this condition, arrhythmogenic left ventricular dysplasia can be considered a specific disease of the left ventricle (LV). We have collected the latest evidence about the management and the risks associated with this cardiomyopathy. Summary: Left ventricular arrhythmogenic cardiomyopathy is still poorly characterized. ALVC is characterized by fibrofatty replacement in the left ventricular myocardium, with variable phenotypic expression. Diagnosis is based on a multiparametric approach, including cardiac magnetic resonance (CMR) and genetic testing, and is important for sudden cardiac death (SCD) risk stratification and management. Recent guidelines have improved the management of left ventricular arrhythmogenic cardiomyopathy. Further studies are necessary to improve knowledge of this cardiomyopathy. [ABSTRACT FROM AUTHOR]

The application of cardiac magnetic resonance (CMR) imaging in clinical practice has grown due to technological advancements and expanded clinical indications, highlighting its superior capabilities when compared to echocardiography for the assessment of myocardial tissue. Similarly, the utilization of implantable cardiac electronic devices (CIEDs) has significantly increased in cardiac arrhythmia management, and the requirements of CMR examinations in patients with CIEDs has become more common. However, this type of exam often presents challenges due to safety concerns and image artifacts. Until a few years ago, the presence of CIED was considered an absolute contraindication to CMR. To address these challenges, various technical improvements in CIED technology, like the reduction of the ferromagnetic components, and in CMR examinations, such as the introduction of new sequences, have been developed. Moreover, a rigorous protocol involving multidisciplinary collaboration is recommended for safe CMR examinations in patients with CIEDs, emphasizing risk assessment, careful monitoring during CMR, and post-scan device evaluation. Alternative methods to CMR, such as computed tomography coronary angiography with tissue characterization techniques like dual-energy and photon-counting, offer alternative potential solutions, although their diagnostic accuracy and availability do limit their use. Despite technological advancements, close collaboration and specialized staff training remain crucial for obtaining safe diagnostic CMR images in patients with CIEDs, thus justifying the presence of specialized centers that are equipped to handle these type of exams. [ABSTRACT FROM AUTHOR]