Pereyra, Milagros

The assessment of left atrial strain (LAS) has emerged as an essential component in the evaluation of cardiac function, especially in pathologies such as heart failure and atrial fibrillation. This narrative review aims to outline the available methods for assessing LAS with a major emphasis on speckle-tracking echocardiography techniques. Other imaging modalities, including cardiac magnetic resonance and cardiac computed tomography, also provide important information on LA dynamics but have disadvantages with respect to cost and availability. The current narrative review underlines basic concepts such as the accurate assessment of LAS and discusses the clinical relevance of LAS by pointing out its significant diagnostic and prognostic role in several cardiovascular conditions. The aim of this article is to discuss the current integration of LAS into clinical practice with a view to further improving patient management and treatment strategies.

Abstract Background Cardiac metastasis from neuroendocrine tumors (NET) is rare and has been thought to potentially result in life threatening sequalae. Peptide receptor radionucleotide therapy (PRRT), such as Lutetium-177 (Lu-177) DOTATATE, has been validated as effective treatment for patients with NET who have progressed on somatostatin analogue (SSA) therapy and more recently suggested for use in SAA-naïve higher risk grade 2 and grade 3 NETs. However, Lu-177 DOTATATE therapy has been found to have potentially serious adverse effects both locally and systemically. Overall, the clinical significance of cardiac metastasis of NET, as well as the safety and efficacy of Lu-177 DOTATATE in this cohort, has not been thoroughly evaluated. Purpose This study assessed the outcomes and clinical consequences of cardiac metastatic involvement in patients with NET. Furthermore, this study investigated the safety of Lu-177 DOTATATE therapy in patients with cardiac metastases from NET. Methods All patients who underwent 68Ga-DOTATATE positron emission tomography for evaluation of NET across three tertiary centers between 2016 and 2022 were retrospectively evaluated. Patients with evidence of cardiac metastasis were further evaluated. Baseline characteristics, treatment modality, and clinical outcomes including mortality, arrhythmia or conduction disease, carcinoid heart disease, and heart failure admissions were recorded. Patients with cardiac metastases were grouped and compared based on therapeutic modality (conservative therapy with surveillance or SSA, Lu-177 DOTATATE therapy, or surgical resection of metastases). Results From 3253 patients with NET, 51 patients were identified to have cardiac metastases (mean age 66.7 ± 12.2 years, 54% male). Three patients underwent surgical resection of cardiac metastases, and in two of whom this was concomitant while undergoing valve surgery for carcinoid heart disease. Patients with cardiac metastasis had significantly higher mortality than patients without cardiac metastasis (HR 2.12, 95%CI 1.00 – 4.52, p = 0.049, Figure 1A). Median follow-up from diagnosis of cardiac metastasis was 3.64 years [IQR 1.59 – 5.64]. There was no significant difference in clinical outcomes between patients that received Lu-177 DOTATATE therapy (n = 27) and conservative therapy (n = 21). Specifically, there was no significant difference in mortality risk at five years post the diagnosis of cardiac metastasis between these groups (p = 0.47, Figure 1B). Conclusion Patients with cardiac metastasis from NETs have worse clinical outcomes than NET patients without cardiac metastatic involvement. Lu-177 DOTATATE therapy appears to be safe in patients with cardiac metastasis from NET.Figure 1AFigure 1B

Lipoprotein (a) is a complex lipid molecule that has sparked immense interest in recent years, after studies demonstrated its significant association with several cardiovascular conditions. Lp(a) promotes cardiovascular disease through its combined proatherogenic, pro-inflammatory, and prothrombotic effects. While the measurement of Lp(a) has become widely available, effective methods to reduce its concentration are currently limited. However, emerging data from ongoing clinical trials involving antisense oligonucleotides have indicated promising outcomes in effectively reducing Lp(a) concentrations. This may serve as a potential therapeutic target in the management and prevention of myocardial infarction, calcific aortic stenosis, and cerebrovascular accidents. In contrast, the role of Lp(a) in atrial fibrillation, in-stent restenosis, cardiac allograft vasculopathy, and bioprosthetic aortic valve degeneration remains unclear. This review article aims to thoroughly review the existing literature and provide an updated overview of the evidence surrounding the association of Lp(a) and these cardiovascular diseases. We seek to highlight controversies in the existing literature and offer directions for future investigations to better understand Lp(a)’s precise role in these conditions, while providing a summary of its unique molecular characteristics.

Athlete’s heart (AH) represents the heart’s remarkable ability to adapt structurally and functionally to prolonged and intensive athletic training. Characterized by increased left ventricular (LV) wall thickness, enlarged cardiac chambers, and augmented cardiac mass, AH typically maintains or enhances systolic and diastolic functions. Despite the positive health implications, these adaptations can obscure the difference between benign physiological changes and early manifestations of cardiac pathologies such as dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), and arrhythmogenic cardiomyopathy (ACM). This article reviews the imaging characteristics of AH across various modalities, emphasizing echocardiography, cardiac magnetic resonance (CMR), and cardiac computed tomography as primary tools for evaluating cardiac function and distinguishing physiological adaptations from pathological conditions. The findings highlight the need for precise diagnostic criteria and advanced imaging techniques to ensure accurate differentiation, preventing misdiagnosis and its associated risks, such as sudden cardiac death (SCD). Understanding these adaptations and employing the appropriate imaging methods are crucial for athletes’ effective management and health optimization.

The long-term survivorship of patients diagnosed with cancer has improved due to accelerated detection and rapidly evolving cancer treatment strategies. As such, the evaluation and management of cancer therapy related complications has become increasingly important, including cardiovascular complications. These have been captured under the umbrella term “cardiotoxicity” and include left ventricular dysfunction and heart failure, acute coronary syndromes, valvular abnormalities, pericardial disease, arrhythmia, myocarditis, and vascular complications. These complications add to the burden of cardiovascular disease (CVD) or are risk factors patients with cancer treatment are presenting with. Of note, both pre- and newly developing CVD is of prognostic significance, not only from a cardiovascular perspective but also overall, potentially impacting the level of cancer therapy that is possible. Currently, there are varying recommendations and practices regarding CVD risk assessment and mitigating strategies throughout the cancer continuum. This article provides an overview on this topic, in particular, the role of cardiac imaging in the care of the patient with cancer. Furthermore, it summarizes the current evidence on the spectrum, prevention, and management of chemotherapy-related adverse cardiac effects.

Abstract Aims Lipoprotein(a) [Lp(a)] has demonstrated its association with atherosclerosis and myocardial infarction. However, its role in the development of in-stent restenosis (ISR) after percutaneous coronary intervention (PCI) is not clearly established. The aim of this study is to investigate the association between Lp(a) and ISR. Methods and results A retrospective study of adult patients who underwent successful PCI between January 2006 and December 2017 at the three Mayo Clinic sites and had a preprocedural Lp(a) measurement was conducted. Patients were divided into two groups according to the serum Lp(a) concentration [high Lp(a) ≥ 50 mg/dL and low Lp(a) < 50 mg/dL]. Univariable and multivariable analyses were performed to compare risk of ISR between patients with high Lp(a) vs. those with low Lp(a). A total of 1209 patients were included, with mean age 65.9 ± 11.7 years and 71.8% were male. Median follow-up after baseline PCI was 8.8 [interquartile range (IQR) 7.4] years. Restenosis was observed in 162 (13.4%) patients. Median serum levels of Lp(a) were significantly higher in patients affected by ISR vs. non-affected cases: 27 (IQR 73.8) vs. 20 (IQR 57.5) mg/dL, P = 0.008. The rate of ISR was significantly higher among patients with high Lp(a) vs. patients with low Lp(a) values (17.0% vs. 11.6%, P = 0.010). High Lp(a) values were independently associated with ISR events (hazard ratio 1.67, 95% confidence interval 1.18–2.37, P = 0.004), and this association was more prominent after the first year following the PCI. Conclusion Lipoprotein(a) is an independent predictor for long-term ISR and should be considered in the evaluation of patients undergoing PCI.

Abstract Background Bicuspid aortic valve (BAv) is associated with increased oxidative stress and inflammation, resulting in valve fibrosis, calcification, and ultimately early degenerative valve disease, often necessitating premature aortic valve intervention. In recent years, growing evidence has been published supporting the role of lipoprotein(a) [Lp(a)], an important carrier of oxidized phospholipids, in the development of aortic valve disease in the general population. However, the specific influence of Lp(a) levels in patients with BAv remains to be firmly established. Purpose To assess the role of Lp(a) levels in the development of aortic valve disease and the necessity for aortic valve interventions among individuals with BAv. Methods This retrospective multicenter study encompassed consecutive patients diagnosed with BAv from January 1997 to December 2022, all of whom had undergone serum Lp(a) measurement. This study evaluated the association between Lp(a) concentrations and the occurrence of aortic valve interventions. A cutoff point of ≥30 mg/dl for high Lp(a) levels was established. Binary logistic regression was utilized to calculate the odds ratio (OR) for an aortic intervention according to high versus low Lp(a) levels. Additionally, Kaplan Meier curves were employed to estimate the cumulative requirement for an aortic valve replacement based on Lp(a) concentrations. Results A total of 452 patients with BAv and a Lp(a) measurement were included in the study, with a mean age of 37.2 ±10.5 years at the time of BAv diagnosis, with 71.2% being male. Among these, 101 (22.3%) patients underwent an aortic valve replacement. In 72 cases (71.3%) aortic stenosis was the primary indication for intervention, while aortic regurgitation accounted for 29 cases (28.7%). The presence of elevated Lp(a) levels (≥30 mg/dl) demonstrated a significant association with the requirement for an aortic valve intervention (OR 2.2, 95%CI 1.4-3.6, p<0.001) in both the regression analysis and using the Kaplan-Meier estimator (Figure). High Lp(a) concentrations posed a risk factor for aortic valve replacements regardless of whether the primary indication for intervention was significant stenosis (OR 1.8, 95%CI 1.1-3.1, p=0.028) or regurgitation (OR 2.5, 95%CI 1.2-5.4, p=0.018). Conclusion Increased concentrations of Lp(a) may influence the clinical trajectory of patients with a BAv and may be a significant risk factor for aortic valve replacement, irrespective of the primary indication for intervention. Further investigations will be critical in unveiling the precise pathological mechanisms of Lp(a) in BAv. Confirming whether reducing Lp(a) levels could slow the progression of aortic disease in this demographic requires further exploration. Kaplan-Meier estimator.

A 69-year-old female presented with symptomatic atrial fibrillation. Cardiac amyloidosis was suspected due to an artificial intelligence clinical tool applied to the presenting electrocardiogram predicting a high probability for amyloidosis, and the subsequent unexpected finding of left atrial appendage thrombus reinforced this clinical suspicion. This facilitated an early diagnosis by the biopsy of AL cardiac amyloidosis and the prompt initiation of targeted therapy. This case highlights the utilization of an AI clinical tool and its impact on clinical care, particularly for the early detection of a rare and difficult to diagnose condition where early therapy is critical.

Systemic vasculitides are a rare and complex group of diseases that can affect multiple organ systems. Clinically, presentation may be vague and non-specific and as such, diagnosis and subsequent management are challenging. These entities are typically classified by the size of vessel involved, including large-vessel vasculitis (giant cell arteritis, Takayasu’s arteritis, and clinically isolated aortitis), medium-vessel vasculitis (including polyarteritis nodosa and Kawasaki disease), and small-vessel vasculitis (granulomatosis with polyangiitis and eosinophilic granulomatosis with polyangiitis). There are also other systemic vasculitides that do not fit in to these categories, such as Behcet’s disease, Cogan syndrome, and IgG4-related disease. Advances in medical imaging modalities have revolutionized the approach to diagnosis of these diseases. Specifically, color Doppler ultrasound, computed tomography and angiography, magnetic resonance imaging, positron emission tomography, or invasive catheterization as indicated have become fundamental in the work up of any patient with suspected systemic or localized vasculitis. This review presents the key diagnostic imaging modalities and their clinical utility in the evaluation of systemic vasculitis.

Cardiac amyloidosis (CA) is an underdiagnosed form of infiltrative cardiomyopathy caused by abnormal amyloid fibrils deposited extracellularly in the myocardium and cardiac structures. There can be high variability in its clinical manifestations, and diagnosing CA requires expertise and often thorough evaluation; as such, the diagnosis of CA can be challenging and is often delayed. The application of artificial intelligence (AI) to different diagnostic modalities is rapidly expanding and transforming cardiovascular medicine. Advanced AI methods such as deep-learning convolutional neural networks (CNNs) may enhance the diagnostic process for CA by identifying patients at higher risk and potentially expediting the diagnosis of CA. In this review, we summarize the current state of AI applications to different diagnostic modalities used for the evaluation of CA, including their diagnostic and prognostic potential, and current challenges and limitations.