: Currently, transcatheter aortic valve implantation (TAVI) is the standard procedure recommended for patients over 75 years of age with symptomatic aortic valve stenosis. Percutaneous transfemoral ...(TF) access is the main route used to perform the procedure. Among periprocedural complications, access-related ones are the most frequent, potentially leading to prolonged in-hospital stays and transfusions.
: We performed a retrospective analysis of prospectively collected data on consecutive patients undergoing TF-TAVI with the latest generation balloon-expandable transcatheter valve between 2013 and 2022.
: A total of 600 patients were analyzed, differentiating the population between ultrasound-guided and blind common femoral artery puncture. Valve Academic Research Consortium 3 (VARC-3)criteria were used to report at 30 days and follow-up. In our propensity-matched comparison of the two groups, we found a strong reduction in access-related complications in the echo-guided group, particularly in terms of reduction of major and minor bleedings. We also found a significant trend in reduction of local complications, such as pseudoaneurysms, hematomas, arterio-venous fistulas, dissection of the femoral or iliac arteries, and stenosis.
: Although there is a lack of consensus on the role of ultrasound-guided puncture, we found better outcomes for patients having an echo-guided puncture of the main access, particularly with regard to access-related complications, early mobilization, and early discharge home.
Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. ...However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.
Coronary artery disease (CAD) represents one of the most important causes of death around the world. Multimodality imaging plays a fundamental role in both diagnosis and risk stratification of acute ...and chronic CAD. For example, the role of Coronary Computed Tomography Angiography (CCTA) has become increasingly important to rule out CAD according to the latest guidelines. These changes and others will likely increase the request for appropriate imaging tests in the future. In this setting, artificial intelligence (AI) will play a pivotal role in echocardiography, CCTA, cardiac magnetic resonance and nuclear imaging, making multimodality imaging more efficient and reliable for clinicians, as well as more sustainable for healthcare systems. Furthermore, AI can assist clinicians in identifying early predictors of adverse outcome that human eyes cannot see in the fog of “big data.” AI algorithms applied to multimodality imaging will play a fundamental role in the management of patients with suspected or established CAD. This study aims to provide a comprehensive overview of current and future AI applications to the field of multimodality imaging of ischemic heart disease.
Biological valve failure (BVF) is an inevitable condition that compromises the durability of biological heart valves (BHVs). It stems from various causes, including rejection, thrombosis, and ...endocarditis, leading to a critical state of valve dysfunction. Echocardiography, cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging play pivotal roles in the diagnostic multimodality workup of BVF. By providing a comprehensive overview of the pathophysiology of BVF and the diagnostic approaches in different clinical scenarios, this review aims to aid clinicians in their decision-making process. The significance of early detection and appropriate management of BVF cannot be overstated, as these directly impact patients’ prognosis and their overall quality of life. Ensuring timely intervention and tailored treatments will not only improve outcomes but also alleviate the burden of this condition on patients’ life. By prioritizing comprehensive assessments and adopting the latest advancements in diagnostic technology, medical professionals can significantly enhance their ability to manage BVF effectively.
Whereas transcatheter aortic valve implantation (TAVI) has become the gold standard for aortic valve stenosis treatment in high-risk patients, it has recently been extended to include intermediate ...risk patients. However, the mortality rate at 5 years is still elevated. The aim of the present study was to develop a novel machine learning (ML) approach able to identify the best predictors of 5-year mortality after TAVI among several clinical and echocardiographic variables, which may improve the long-term prognosis.
We retrospectively enrolled 471 patients undergoing TAVI. More than 80 pre-TAVI variables were collected and analyzed through different feature selection processes, which allowed for the identification of several variables with the highest predictive value of mortality. Different ML models were compared.
Multilayer perceptron resulted in the best performance in predicting mortality at 5 years after TAVI, with an area under the curve, positive predictive value, and sensitivity of 0.79, 0.73, and 0.71, respectively.
We presented an ML approach for the assessment of risk factors for long-term mortality after TAVI to improve clinical prognosis. Fourteen potential predictors were identified with the organic mitral regurgitation (myxomatous or calcific degeneration of the leaflets and/or annulus) which showed the highest impact on 5 years mortality.
Vascular inflammation is recognized as the primary trigger of acute coronary syndrome (ACS). However, current noninvasive methods are not capable of accurately detecting coronary inflammation. ...Epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT), in addition to their role as an energy reserve system, have been found to contribute to the development and progression of coronary artery calcification, inflammation, and plaque vulnerability. They also participate in the vascular response during ischemia, sympathetic stimuli, and arrhythmia. As a result, the evaluation of EAT and PCAT using imaging techniques such as computed tomography (CT), cardiac magnetic resonance (CMR), and nuclear imaging has gained significant attention. PCAT-CT attenuation, which measures the average CT attenuation in Hounsfield units (HU) of the adipose tissue, reflects adipocyte differentiation/size and leukocyte infiltration. It is emerging as a marker of tissue inflammation and has shown prognostic value in coronary artery disease (CAD), being associated with plaque development, vulnerability, and rupture. In patients with acute myocardial infarction (AMI), an inflammatory pericoronary microenvironment promoted by dysfunctional EAT/PCAT has been demonstrated, and more recently, it has been associated with plaque rupture in non-ST-segment elevation myocardial infarction (NSTEMI). Endothelial dysfunction, known for its detrimental effects on coronary vessels and its association with plaque progression, is bidirectionally linked to PCAT. PCAT modulates the secretory profile of endothelial cells in response to inflammation and also plays a crucial role in regulating vascular tone in the coronary district. Consequently, dysregulated PCAT has been hypothesized to contribute to type 2 myocardial infarction with non-obstructive coronary arteries (MINOCA) and coronary vasculitis. Recently, quantitative measures of EAT derived from coronary CT angiography (CCTA) have been included in artificial intelligence (AI) models for cardiovascular risk stratification. These models have shown incremental utility in predicting major adverse cardiovascular events (MACEs) compared to plaque characteristics alone. Therefore, the analysis of PCAT and EAT, particularly through PCAT-CT attenuation, appears to be a safe, valuable, and sufficiently specific noninvasive method for accurately identifying coronary inflammation and subsequent high-risk plaque. These findings are supported by biopsy and in vivo evidence. Although speculative, these pieces of evidence open the door for a fascinating new strategy in cardiovascular risk stratification. The incorporation of PCAT and EAT analysis, mainly through PCAT-CT attenuation, could potentially lead to improved risk stratification and guide early targeted primary prevention and intensive secondary prevention in patients at higher risk of cardiac events.
Aortic size is known to vary significantly by age and body size and to be an important predictor of cardiovascular diseases. The aim of this study was to determine reference values for proximal ...thoracic aorta diameters, using the inner edge technique and two-dimensional transthoracic echocardiography.
Diameters of the aortic annulus, sinuses of Valsalva, sinotubular junction, arch, and ascending aorta and the angle of insertion of the aorta were measured in 500 subjects (231 women; mean age, 48 ± 18 years) with normal echocardiographic findings, retrospectively enrolled. The relations of age and body size with aortic measurements were investigated using bivariate and multiple linear regressions.
Measurements were highly feasible (83% for the aortic arch, 100% for the other segments). All aortic diameters significantly related to age, weight and body surface area, while height was correlated only with annular diameter. In predictive models adjusted for gender, older age was associated with increased aortic diameters (R(2) values ranged from 0.36 for the sinotubular junction to 0.52 for the sinuses of Valsalva). Adjustments for height and weight led to significant improvements (R(2) values ranged from 0.43 for the sinotubular junction to 0.58 for the sinuses of Valsalva). Similar correlations were observed for men and women. Angle was found to be dependent only on age and gender. Reproducibility analysis showed good to excellent accordance between repeated measurements.
The results of this study show the effect of aging on the proximal thoracic aorta and emphasize the importance of accounting for gender and body size when assessing aortic size. The obtained reference ranges will help standardize the assessment of aortic dimensions by applying inner edge convention and facilitate comparisons with other imaging techniques.
The aim of this study was to test the feasibility of the assessment of right ventricular (RV) volumes and function using real-time three-dimensional (3D) transesophageal echocardiographic (TEE) ...imaging in patients undergoing cardiac surgery.
One hundred-fifty surgical patients were enrolled: 65 undergoing mitral valve repair, 10 undergoing mitral valve and tricuspid valve repair, four with congenital heart disease, two undergoing Jarvik implantation, 13 undergoing aortic valve surgical replacement, and 56 undergoing transcatheter aortic valve implantation. Real-time 3D TEE acquisition for RV evaluation was performed before and after the surgical procedure and compared with standard two-dimensional multiplane TEE measurements. In a subgroup of 81 patients, 3D transthoracic echocardiographic imaging was also performed. RV volumetric quantification was performed for all data using dedicated software.
Three-dimensional RV analysis was feasible in 98.7% in the preoperative TEE data set and in 92.7% in the postoperative TEE data set. Agreement between 3D transthoracic and transesophageal echocardiography for end-diastolic volume (r = 0.98; 95% confidence interval CI, -0.2 ± 13.6 mL), end-systolic volume (r = 0.97; 95% CI, -2.1 ± 10.2 mL), ejection fraction (r = 0.77; 95% CI, 1.8 ± 8.2%), and stroke volume (r = 0.91; 95% CI, 2.0 ± 12.9 mL) was significant. RV parameters were highly reproducible in patients with both normal and dilated RV volumes.
Intraoperative 3D TEE assessment of RV volumes and function is feasible in patients with normal and dilated right ventricles, with good correlation between 3D transthoracic echocardiographic and TEE RV parameters. These measurements could improve the quantitative evaluation of RV function during cardiac surgery.
Diagnosis of myocardial fibrosis is commonly performed with late gadolinium contrast-enhanced (CE) cardiac magnetic resonance (CMR), which might be contraindicated or unavailable. Coronary computed ...tomography (CCT) is emerging as an alternative to CMR. We sought to evaluate whether a deep learning (DL) model could allow identification of myocardial fibrosis from routine early CE-CCT images.
Fifty consecutive patients with known left ventricular (LV) dysfunction (LVD) underwent both CE-CMR and (early and late) CE-CCT. According to the CE-CMR patterns, patients were classified as ischemic (
= 15, 30%) or non-ischemic (
= 35, 70%) LVD. Delayed enhancement regions were manually traced on late CE-CCT using CE-CMR as reference. On early CE-CCT images, the myocardial sectors were extracted according to AHA 16-segment model and labeled as with scar or not, based on the late CE-CCT manual tracing. A DL model was developed to classify each segment. A total of 44,187 LV segments were analyzed, resulting in accuracy of 71% and area under the ROC curve of 76% (95% CI: 72%-81%), while, with the bull's eye segmental comparison of CE-CMR and respective early CE-CCT findings, an 89% agreement was achieved.
DL on early CE-CCT acquisition may allow detection of LV sectors affected with myocardial fibrosis, thus without additional contrast-agent administration or radiational dose. Such tool might reduce the user interaction and visual inspection with benefit in both efforts and time.
Heart failure with preserved ejection fraction (HFpEF) is a syndrome defined by the presence of heart failure symptoms and increased levels of circulating natriuretic peptide (NP) in patients with ...preserved left ventricular ejection fraction and various degrees of diastolic dysfunction (DD). HFpEF is a complex condition that encompasses a wide range of different etiologies. Cardiovascular imaging plays a pivotal role in diagnosing HFpEF, in identifying specific underlying etiologies, in prognostic stratification, and in therapeutic individualization. Echocardiography is the first line imaging modality with its wide availability; it has high spatial and temporal resolution and can reliably assess systolic and diastolic function. Cardiovascular magnetic resonance (CMR) is the gold standard for cardiac morphology and function assessment, and has superior contrast resolution to look in depth into tissue changes and help to identify specific HFpEF etiologies. Differently, the most important role of nuclear imaging i.e., planar scintigraphy and/or single photon emission CT (SPECT) consists in the screening and diagnosis of cardiac transthyretin amyloidosis (ATTR) in patients with HFpEF. Cardiac CT can accurately evaluate coronary artery disease both from an anatomical and functional point of view, but tissue characterization methods have also been developed. The aim of this review is to critically summarize the current uses and future perspectives of echocardiography, nuclear imaging, CT, and CMR in patients with HFpEF.
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