Scar-Related Monomorphic Ventricular Tachycardia After Treated Right Ventricular Metastatic Diffuse Large B-Cell Lymphoma.

A patient with ventricular tachycardia (VT) and right ventricular (RV) metastatic diffuse large B-cell lymphoma had persistent RV gadolinium enhancement following chemotherapy and disease remission. Electrophysiology study demonstrated inducible sustained monomorphic VT requiring subcutaneous implantable cardioverter-defibrillator implantation. This highlights the arrhythmogenic potential of residual scar after resolution of cardiac masses.

The prognostic value of artificial intelligence to predict cardiac amyloidosis in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.

Aims: Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results: In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01-1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01-1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13-2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion: Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.

Multi-Modality Imaging in Vasculitis.

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.

How Artificial Intelligence Can Enhance the Diagnosis of Cardiac Amyloidosis: A Review of Recent Advances and Challenges.

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.

Echocardiography-Based Deep Learning Model to Differentiate Constrictive Pericarditis and Restrictive Cardiomyopathy.

BACKGROUND: Constrictive pericarditis (CP) is an uncommon but reversible cause of diastolic heart failure if appropriately identified and treated. However, its diagnosis remains a challenge for clinicians. Artificial intelligence may enhance the identification of CP. OBJECTIVES: The authors proposed a deep learning approach based on transthoracic echocardiography to differentiate CP from restrictive cardiomyopathy. METHODS: Patients with a confirmed diagnosis of CP and cardiac amyloidosis (CA) (as the representative disease of restrictive cardiomyopathy) at Mayo Clinic Rochester from January 2003 to December 2021 were identified to extract baseline demographics. The apical 4-chamber view from transthoracic echocardiography studies was used as input data. The patients were split into a 60:20:20 ratio for training, validation, and held-out test sets of the ResNet50 deep learning model. The model performance (differentiating CP and CA) was evaluated in the test set with the area under the curve. GradCAM was used for model interpretation. RESULTS: A total of 381 patients were identified, including 184 (48.3%) CP, and 197 (51.7%) CA cases. The mean age was 68.7 ± 11.4 years, and 72.8% were male. ResNet50 had a performance with an area under the curve of 0.97 to differentiate the 2-class classification task (CP vs CA). The GradCAM heatmap showed activation around the ventricular septal area. CONCLUSIONS: With a standard apical 4-chamber view, our artificial intelligence model provides a platform to facilitate the detection of CP, allowing for improved workflow efficiency and prompt referral for more advanced evaluation and intervention of CP.

Challenges and solutions of echocardiography generalization for deep learning: a study in patients with constrictive pericarditis.

Purpose: The inherent characteristics of transthoracic echocardiography (TTE) images such as low signal-to-noise ratio and acquisition variations can limit the direct use of TTE images in the development and generalization of deep learning models. As such, we propose an innovative automated framework to address the common challenges in the process of echocardiography deep learning model generalization on the challenging task of constrictive pericarditis (CP) and cardiac amyloidosis (CA) differentiation. Approach: Patients with a confirmed diagnosis of CP or CA and normal cases from Mayo Clinic Rochester and Arizona were identified to extract baseline demographics and the apical 4 chamber view from TTE studies. We proposed an innovative preprocessing and image generalization framework to process the images for training the ResNet50, ResNeXt101, and EfficientNetB2 models. Ablation studies were conducted to justify the effect of each proposed processing step in the final classification performance. Results: The models were initially trained and validated on 720 unique TTE studies from Mayo Rochester and further validated on 225 studies from Mayo Arizona. With our proposed generalization framework, EfficientNetB2 generalized the best with an average area under the curve (AUC) of 0.96 (±0.01) and 0.83 (±0.03) on the Rochester and Arizona test sets, respectively. Conclusions: Leveraging the proposed generalization techniques, we successfully developed an echocardiography-based deep learning model that can accurately differentiate CP from CA and normal cases and applied the model to images from two sites. The proposed framework can be further extended for the development of echocardiography-based deep learning models.

Three-Dimensional Transesophageal Echocardiography in Percutaneous Catheter-Based Cardiac Interventions.

Cardiac structural and valve interventions have remained surgical procedures for several decades. The ability to directly visualize the region of interest during surgery made imaging of these structures pre- and postsurgery a secondary tool to compliment surgical visualization. The last two decades, however, have seen rapid advances in catheter-based percutaneous structural heart interventions (SHIs). Due to the "blind" nature of these interventions, imaging plays a crucial role in the success of these procedures. Fluoroscopy is used universally in all percutaneous cardiac SHIs and helps primarily in the visualization of catheters and devices. However, success of these procedures requires visualization of intracardiac soft tissue structures. Due to its portable nature and rapid ability to show cardiac structures online, transesophageal echocardiography (TEE) has become an integral tool for guidance for all percutaneous SHI. Transcatheter aortic valve replacement-one of the earliest catheter-based procedures-while initially dependent on TEE, has largely been replaced by preprocedural cardiac CT for accurate assessment of valve sizing. Developments in echocardiography now allow live three-dimensional (3D) visualization of cardiac structures mimicking surgical anatomy during TEE. Besides showing actual 3D intracardiac structures, 3D-TEE allows visualization of the interaction of intracardiac catheters and devices with soft tissue cardiac structures, thereby becoming a "second pair of eyes" for the operator. Real-time 3D-TEE now plays an important role complementing multiplane two dimensional and biplane TEE during such interventions. In this review, we discuss the incremental role of 3D-TEE during various SHIs performed today.

Complete heart block is a significant predictor of mortality in immune checkpoint inhibitor myocarditis.

BACKGROUND: Immune checkpoint inhibitor (ICI) myocarditis is associated with significant mortality risk. Electrocardiogram (ECG) changes in ICI myocarditis have strong prognostic value. However the impact of complete heart block (CHB) is not well defined. This study sought to evaluate the impact of CHB on mortality in ICI myocarditis, and to identify clinical predictors of mortality and CHB incidence. METHODS: We conducted a retrospective cohort study of patients with ICI myocarditis at three Mayo Clinic sites from 1st January 2010 to 31st September 2022 to evaluate mortality rates at 180 days. Clinical, laboratory, ECG, echocardiographic, and cardiac magnetic resonance imaging (CMR) characteristics were assessed. Cox and logistic regression were performed for associations with mortality and CHB respectively. RESULTS: Of 34 identified cases of ICI myocarditis, 7 (20.6%) had CHB. CHB was associated with higher mortality (HR 7.41, p = 0.03, attributable fraction 86.5%). Among those with CHB, troponin T (TnT) < 1000 ng/dL, low white blood cell count and high ventricular rate at admission were protective. There was trend towards increased survival among patients who underwent permanent pacemaker insertion (p = 0.051), although most experienced device lead complications. Factors associated with development of CHB included prolonged PR and QRS intervals and low Sokolow Lyon Index. Where these were normal and TnT was < 1000 ng/dL, no deaths occurred. Impaired myocardial longitudinal strain was sensitive for ICI myocarditis but was not prognostically significant. CONCLUSION: There is a strong temporal association between CHB and early mortality in people with ICI myocarditis. Focusing on arrhythmogenic complications can be helpful in predicting outcomes for this group of critically ill individuals.

Prognostic Value of Coronary Computed Tomography Angiography in Coronary Artery Bypass Graft Patients Systematic Review and Meta-Analysis.

We sought to assess the prognostic value of coronary computed tomographic angiography (CCTA) in patients with coronary artery bypass graft (CABG) by meta-analysis. MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched for relevant original articles published up to July 2021. CCTA prognostic studies enrolling patients with CABG were screened and included if outcomes included all-cause mortality or major adverse cardiac events. Maximally adjusted hazard ratios (HRs) were extracted for CCTA-derived prognostic factors. HRs were log-transformed and pooled across studies using the DerSimonian-Laird random-effects model and statistical heterogeneity was assessed using the I2 statistic. Of 1,576 screened articles, 4 retrospective studies fulfilled all inclusion criteria. Collectively, a total of 1,809 patients with CABG underwent CCTA (mean [SD] age 67.0 [8.5] years across 3 studies, 81.5% male across 4 studies). Coronary artery disease severity and revascularization were categorized using 2 models: unprotected coronary territories and coronary artery protection score. The pooled HRs from the random-effects models using the most highly adjusted study estimate were 3.64 (95% confidence interval 2.48 to 5.34, I2 = 57.8%, p <0.001; 4 studies) and 4.85 (95% confidence interval 3.17 to 7.43, I2 = 39.9%, p <0.001; 2 studies) for unprotected coronary territories and coronary artery protection score, respectively. In conclusion, in a limited number of studies, CCTA is an independent predictor of adverse events in patients with CABG. Larger studies using uniform models and endpoints are needed.

Developing an Echocardiography-Based, Automatic Deep Learning Framework for the Differentiation of Increased Left Ventricular Wall Thickness Etiologies.

AIMS: Increased left ventricular (LV) wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness. METHODS AND RESULTS: Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 and 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4-chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: HCM: 0.93, CA: 0.90, and HTN/other: 0.92). CONCLUSION: The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.

Lidocaine for Neuropathic Cancer Pain (LiCPain): study protocol for a mixed-methods pilot study.

INTRODUCTION: Many patients experience unrelieved neuropathic cancer-related pain. Most current analgesic therapies have psychoactive side effects, lack efficacy data for this indication and have potential medication-related harms. The local anaesthetic lidocaine (lignocaine) has the potential to help manage neuropathic cancer-related pain when administered as an extended, continuous subcutaneous infusion. Data support lidocaine as a promising, safe agent in this setting, warranting further evaluation in robust, randomised controlled trials. This protocol describes the design of a pilot study to evaluate this intervention and explains the pharmacokinetic, efficacy and adverse effects evidence informing the design. METHODS AND ANALYSIS: A mixed-methods pilot study will determine the feasibility of an international first, definitive phase III trial to evaluate the efficacy and safety of an extended continuous subcutaneous infusion of lidocaine for neuropathic cancer-related pain. This study will comprise: a phase II double-blind randomised controlled parallel-group pilot of subcutaneous infusion of lidocaine hydrochloride 10% w/v (3000 mg/30 mL) or placebo (sodium chloride 0.9%) over 72 hours for neuropathic cancer-related pain, a pharmacokinetic substudy and a qualitative substudy of patients' and carers' experiences. The pilot study will provide important safety data and help inform the methodology of a definitive trial, including testing proposed recruitment strategy, randomisation, outcome measures and patients' acceptability of the methodology, as well as providing a signal of whether this area should be further investigated. ETHICS AND DISSEMINATION: Participant safety is paramount and standardised assessments for adverse effects are built into the trial protocol. Findings will be published in a peer-reviewed journal and presented at conferences. This study will be considered suitable to progress to a phase III study if there is a completion rate where the CI includes 80% and excludes 60%. The protocol and Patient Information and Consent Form have been approved by Sydney Local Health District (Concord) Human Research Ethics Committee 2019/ETH07984 and University of Technology Sydney ETH17-1820. TRIAL REGISTRATION NUMBER: ANZCTR ACTRN12617000747325.

Gastroenteropancreatic Neuroendocrine Tumor Metastasis to the Heart: Evaluation of Imaging Manifestations.

Neuroendocrine tumors (NET) may affect the heart by cardiac metastasis or carcinoid heart disease. NET metastasis to the heart is rare, with limited data characterizing it. We sought to evaluate 68Ga-DOTATATE PET scan imaging features and associated cardiac imaging characteristics where available in those with NET cardiac metastases. 68Ga-DOTATATE positron emission tomography (PET)/CT scans performed on patients with gastroenteropancreatic (GEP) NET at our institution were reviewed for cardiac involvement. Those identified with cardiac metastases had their electronic medical record, transthoracic echocardiogram (TTE) and cardiac magnetic resonance imaging (MRI) reviewed for characterization. From a total of 1426 68Ga-DOTATATE PET/CT scans performed on patients with GEP-NET, 25 (1.75%) had cardiac uptake consistent with metastasis. Of these, 22 had myocardial metastases (29 distinct myocardial lesions: left ventricle - 16, right ventricle - 6, and ventricular septum -7) and 3 had periradial lymph node involvement only. NET patients with cardiac metastases as identified by DOTATATE scan did not appear to have any hemodynamically significant TTE features, aside from those (2/25) who had concomitant carcinoid heart disease. Of the 14 patients who had available TTE for review, only one with high metastatic cardiac tumor burden had detectable cardiac mass. Of the 6 cases who had available MRI, all had metastatic cardiac lesions seen with excellent correlation with tumor localization on 68Ga-DOTATATE PET scan. 68Ga-DOTATATE PET has excellent capability for the diagnosis of cardiac NET metastasis. Cardiac MRI may provide further anatomic and tissue characterization evaluation. Those with myocardial NET metastases without carcinoid heart disease did not have significant hemodynamic effect based on echocardiographic criteria.

Advances in Multimodality Imaging in Cardio-Oncology: JACC State-of-the-Art Review.

The population of patients with cancer is rapidly expanding, and the diagnosis and monitoring of cardiovascular complications greatly rely on imaging. Numerous advances in the field of cardio-oncology and imaging have occurred in recent years. This review presents updated and practical approaches for multimodality cardiovascular imaging in the cardio-oncology patient and provides recommendations for imaging to detect the myriad of adverse cardiovascular effects associated with antineoplastic therapy, such as cardiomyopathy, atherosclerosis, vascular toxicity, myocarditis, valve disease, and cardiac masses. Uniquely, we address the role of cardiovascular imaging in patients with pre-existing cardiomyopathy, pregnant patients, long-term survivors, and populations with limited resources. We also address future avenues of investigation and opportunities for artificial intelligence applications in cardio-oncology imaging. This review provides a uniform practical approach to cardiovascular imaging for patients with cancer.

Multimodality imaging evaluation of incidentally discovered intracardiac mass.

Incidentally discovered intracardiac masses often represent diagnostic dilemmas. No guideline-directed algorithm exists for evaluation and management in these cases. Understanding the utility and limitations of different imaging modalities expedites evaluation of differential diagnoses and management, particularly when there are discordant imaging findings. This case further demonstrates that benign cardiac tumors may grow rapidly, and that new and rapid emergence of an intracardiac mass does not necessarily correlate with a diagnosis of thrombus or malignancy. It also highlights the importance of a broad differential diagnosis and a systematic management approach in patients with intracardiac masses.

Global longitudinal strain is a better metric than left ventricular ejection fraction: lessons learned from cancer therapeutic-related cardiac dysfunction.

PURPOSE OF THE REVIEW: This review aims to highlight the utility of global longitudinal strain (GLS) in cancer therapeutic-related cardiac dysfunction (CTRCD), with an attempt to stipulate that GLS might be a better measure than left ventricular ejection fraction (LVEF). RECENT FINDINGS: Increasingly, GLS quantification has been employed in various cardiovascular diseases especially with its ability to detect left ventricular dysfunction subclinically, even before a change in LVEF is visualized. In fact, several studies reveal that GLS may be a superior predictor of mortality and morbidity than LVEF in this context. A recent metaanalysis supported the prognosticating value of GLS in CTRCD, however, endorsed the need for larger multicenter studies to establish the value of this metric. Studies in other cardiovascular disease processes showed GLS as a better metric than LVEF. SUMMARY: GLS has been heralded as a new echocardiographic measure that can detect subclinical cardiac disease. At a minimum, GLS can provide incremental value in prognosticating, diagnosing, and predicting LVEF recovery and at best, a better measure of left ventricular dysfunction.

Surgical repair of a left main coronary artery aneurysm.

We report the repair of a 6.5 × 5.3-cm left main coronary artery aneurysm by marsupialization of the aneurysm sac and coronary artery bypass grafting.

Advanced cardiac imaging techniques assist in characterizing a cardiac mass and directing management.

Advanced imaging techniques, including contrast echocardiography and CMR, provided valuable characterization and evaluation of a boy with an unusual cardiac mass. Imaging features assisted with differentiation of benign from malignant etiology and excluding thrombus. Accurate imaging techniques saved our patient risks associated with unnecessary surgery or anticoagulation. The ability to accurately define size serially assisted in guiding expectant management. He died from a noncardiac cause at age 28, and autopsy demonstrated a hamartoma of mature cardiac myocytes.

Fixed left ventricular outflow tract obstruction mimicking hypertrophic obstructive cardiomyopathy: pitfalls in diagnosis.

We present a case series that highlights the diagnostic challenges with left ventricular hypertrophy (LVH) and left ventricular outflow tract obstruction (LVOTO). Fixed structural lesions causing LVOTO with secondary LVH may mimic hypertrophic obstructive cardiomyopathy (HOCM). Management of these two entities is critically different. Misdiagnosis and failure to recognize fixed left ventricular outflow tract (LVOT) lesions may result in morbidity as a result of inappropriate therapy and delay of definitive surgical treatment. It is thus necessary to identify the correct type and level of obstruction in the LVOT by careful correlation of clinical examination, Doppler evaluation, and advanced imaging findings.