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.

Role of Genetics in Diagnosis and Management of Hypertrophic Cardiomyopathy: A Glimpse into the Future.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiomyopathy. It follows an autosomal dominant inheritance pattern in most cases, with incomplete penetrance and heterogeneity. It is familial in 60% of cases and most of these are caused by pathogenic variants in the core sarcomeric genes (MYH7, MYBPC3, TNNT2, TNNI3, MYL2, MYL3, TPM1, ACTC1). Genetic testing using targeted disease-specific panels that utilize next-generation sequencing (NGS) and include sarcomeric genes with the strongest evidence of association and syndrome-associated genes is highly recommended for every HCM patient to confirm the diagnosis, identify the molecular etiology, and guide screening and management. The yield of genetic testing for a disease-causing variant is 30% in sporadic cases and up to 60% in familial cases and in younger patients with typical asymmetrical septal hypertrophy. Genetic testing remains challenging in the interpretation of results and classification of variants. Therefore, in 2015 the American College of Medical Genetics and Genomics (ACMG) established guidelines to classify and interpret the variants with an emphasis on the necessity of periodic reassessment of variant classification as genetic knowledge rapidly expands. The current guidelines recommend focused cascade genetic testing regardless of age in phenotype-negative first-degree relatives if a variant with decisive evidence of pathogenicity has been identified in the proband. Genetic test results in family members guide longitudinal clinical surveillance. At present, there is emerging evidence for genetic test application in risk stratification and management but its implementation into clinical practice needs further study. Promising fields such as gene therapy and implementation of artificial intelligence in the diagnosis of HCM are emerging and paving the way for more effective screening and management, but many challenges and obstacles need to be overcome before establishing the practical implications of these new methods.

Cardiac Allograft Vasculopathy: Challenges and Advances in Invasive and Non-Invasive Diagnostic Modalities.

Cardiac allograft vasculopathy (CAV) is a distinct form of coronary artery disease that represents a major cause of death beyond the first year after heart transplantation. The pathophysiology of CAV is still not completely elucidated; it involves progressive circumferential wall thickening of both the epicardial and intramyocardial coronary arteries. Coronary angiography is still considered the gold-standard test for the diagnosis of CAV, and intravascular ultrasound (IVUS) can detect early intimal thickening with improved sensitivity. However, these tests are invasive and are unable to visualize and evaluate coronary microcirculation. Increasing evidence for non-invasive surveillance techniques assessing both epicardial and microvascular components of CAV may help improve early detection. These include computed tomography coronary angiography (CTCA), single-photon emission computed tomography (SPECT), positron emission tomography (PET), and vasodilator stress myocardial contrast echocardiography perfusion imaging. This review summarizes the current state of diagnostic modalities and their utility and prognostic value for CAV and also evaluates emerging tools that may improve the early detection of this complex disease.

Identifying the Causes of Unexplained Dyspnea at High Altitude Using Normobaric Hypoxia with Echocardiography.

Exposure to high altitude results in hypobaric hypoxia, leading to physiological changes in the cardiovascular system that may result in limiting symptoms, including dyspnea, fatigue, and exercise intolerance. However, it is still unclear why some patients are more susceptible to high-altitude symptoms than others. Hypoxic simulation testing (HST) simulates changes in physiology that occur at a specific altitude by asking the patients to breathe a mixture of gases with decreased oxygen content. This study aimed to determine whether the use of transthoracic echocardiography (TTE) during HST can detect the rise in right-sided pressures and the impact of hypoxia on right ventricle (RV) hemodynamics and right to left shunts, thus revealing the underlying causes of high-altitude signs and symptoms. A retrospective study was performed including consecutive patients with unexplained dyspnea at high altitude. HSTs were performed by administrating reduced FiO2 to simulate altitude levels specific to patients' history. Echocardiography images were obtained at baseline and during hypoxia. The study included 27 patients, with a mean age of 65 years, 14 patients (51.9%) were female. RV systolic pressure increased at peak hypoxia, while RV systolic function declined as shown by a significant decrease in the tricuspid annular plane systolic excursion (TAPSE), the maximum velocity achieved by the lateral tricuspid annulus during systole (S' wave), and the RV free wall longitudinal strain. Additionally, right-to-left shunt was present in 19 (70.4%) patients as identified by bubble contrast injections. Among these, the severity of the shunt increased at peak hypoxia in eight cases (42.1%), and the shunt was only evident during hypoxia in seven patients (36.8%). In conclusion, the use of TTE during HST provides valuable information by revealing the presence of symptomatic, sustained shunts and confirming the decline in RV hemodynamics, thus potentially explaining dyspnea at high altitude. Further studies are needed to establish the optimal clinical role of this physiologic method.

Artificial Intelligence-Based Prediction of Cardiovascular Diseases from Chest Radiography.

Chest radiography (CXR) is the most frequently performed radiological test worldwide because of its wide availability, non-invasive nature, and low cost. The ability of CXR to diagnose cardiovascular diseases, give insight into cardiac function, and predict cardiovascular events is often underutilized, not clearly understood, and affected by inter- and intra-observer variability. Therefore, more sophisticated tests are generally needed to assess cardiovascular diseases. Considering the sustained increase in the incidence of cardiovascular diseases, it is critical to find accessible, fast, and reproducible tests to help diagnose these frequent conditions. The expanded focus on the application of artificial intelligence (AI) with respect to diagnostic cardiovascular imaging has also been applied to CXR, with several publications suggesting that AI models can be trained to detect cardiovascular conditions by identifying features in the CXR. Multiple models have been developed to predict mortality, cardiovascular morphology and function, coronary artery disease, valvular heart diseases, aortic diseases, arrhythmias, pulmonary hypertension, and heart failure. The available evidence demonstrates that the use of AI-based tools applied to CXR for the diagnosis of cardiovascular conditions and prognostication has the potential to transform clinical care. AI-analyzed CXRs could be utilized in the future as a complimentary, easy-to-apply technology to improve diagnosis and risk stratification for cardiovascular diseases. Such advances will likely help better target more advanced investigations, which may reduce the burden of testing in some cases, as well as better identify higher-risk patients who would benefit from earlier, dedicated, and comprehensive cardiovascular evaluation.

Aortic Valve Calcium Score by Computed Tomography as an Adjunct to Echocardiographic Assessment-A Review of Clinical Utility and Applications.

Aortic valve stenosis (AS) is increasing in prevalence due to the aging population, and severe AS is associated with significant morbidity and mortality. Echocardiography remains the mainstay for the initial detection and diagnosis of AS, as well as for grading of severity. However, there are important subgroups of patients, for example, patients with low-flow low-gradient or paradoxical low-gradient AS, where quantification of severity of AS is challenging by echocardiography and underestimation of severity may delay appropriate management and impart a worse prognosis. Aortic valve calcium score by computed tomography has emerged as a useful clinical diagnostic test that is complimentary to echocardiography, particularly in cases where there may be conflicting data or clinical uncertainty about the degree of AS. In these situations, aortic valve calcium scoring may help re-stratify grading of severity and, therefore, further direct clinical management. This review presents the evolution of aortic valve calcium score by computed tomography, its diagnostic and prognostic value, as well as its utility in clinical care.

Current Management and Future Directions for Pulmonary Arterial Hypertension Associated with Congenital Heart Disease.

Current management of patients with congenital heart disease has increased their survival into adulthood. This is accompanied by potential cardiac complications, including pulmonary hypertension associated with congenital heart disease (PAH-CHD). PAH-CHD constitutes a challenging subgroup of pulmonary hypertension and requires expert management to improve quality of life and prognosis. Novel agents have shown a significant improvement in morbidity and mortality in patients with pulmonary arterial hypertension. However, the long-term effects of these medications on PAH-CHD patients remain somewhat uncertain, necessitating treatment plans largely founded on the clinical experience of the healthcare providers. The aim of this review is to summarize the current evidence and future perspectives regarding treatment strategies for PAH-CHD to help better guide management of this complex disease.

The prognostic value of estimating stroke volume before and after exercise during treadmill stress echocardiography.

BACKGROUND: Stress echocardiography (SE) is an established technique for assessment of coronary artery disease (CAD) which is difficult to perform and interpret. Left ventricular stroke volume (SV) is readily estimated with Doppler echocardiography. It can be affected by myocardial ischemia, with possible adjunctive value during SE. METHODS: Patients underwent Bruce protocol SE with SV estimated before and after maximal treadmill exertion post routine regional wall analysis. Incremental change in SV (ΔSV) with exercise was measured. RESULTS: A derivation cohort (n = 273) was established to test the hypothesis. An optimal cutoff for detection on inducible ischemia was ΔSV ≤ +10 mL. The validation cohort of consecutive patients (n = 1093, 376 [34%] female; age 59 ± 12 years) were followed clinically after SE for 20 460 patient-months. There were 1000 patients with nonischemic SE, and 93 patients with studies suggestive of myocardial ischemia. Secondary analysis yielded 831 patients with a normal exercise response (ΔSV > +10 mL) and 192 with an abnormal ΔSV ≤ +10 mL. Time to first combined adverse cardiac event (composite of angina, acute coronary syndrome, cardiac revascularization, worsening New York Heart Association (NYHA) class, a reduction in EF, and cardiovascular death) was analyzed and adjusted using Cox proportional hazards regression. The hazard ratio for an adverse event with an abnormal ΔSV response (≤10 mL) was 10.3 (95% confidence intervals 5.6-19.1, P < .0001). CONCLUSIONS: Stroke volume assessment during SE is feasible and readily performed. It is simple, practical, and has incremental diagnostic and prognostic value when added to exercise regional wall-motion analysis.

Incremental Value of ePLAR-The Echocardiographic Pulmonary to Left Atrial Ratio in the Assessment of Sub-Massive Pulmonary Emboli.

BACKGROUND: Acute pulmonary embolism (PE) is characterized hemodynamically by abrupt obstruction in trans-pulmonary blood flow. The echocardiographic Pulmonary to Left Atrial ratio (ePLAR, tricuspid regurgitation Vmax/mitral E/e') has been validated as a non-invasive surrogate for trans-pulmonary gradient (TPG) that accurately differentiates pre-capillary from post-capillary chronic pulmonary hypertension. This study assessed ePLAR as an incremental echocardiographic assessment tool compared with traditional measures of right ventricular pressure and function. METHODS: In total, 110 (57.4 ± 17.6 years) patients with confirmed sub-massive pulmonary emboli with contemporaneous echocardiograms (0.3 ± 0.9 days) were compared with 110 age-matched controls (AMC). RESULTS: Tricuspid velocities were higher than AMC (2.6 ± 0.6 m/s vs. 2.4 ± 0.3 m/s, p < 0.05), although still consistent with "normal" right ventricular systolic pressures (34.2 ± 13.5 mmHg vs. 25 ± 5.3 mmHg, p < 0.05) with lower mitral E/e' values (8.2 ± 3.8 vs. 10.8 ± 5.1, p < 0.05). ePLAR values were higher than AMC (0.36 ± 0.14 m/s vs. 0.26 ± 0.10, p < 0.05) suggesting significantly elevated TPG. Detection of abnormal echocardiographic findings increased from 29% (TRVmax ≥ 2.9 m/s) and 32% (reduced tricuspid annular plane systolic excursion) to 70% with ePLAR ≥ 0.3 m/s. CONCLUSIONS: Raised ePLAR values in acute sub-massive pulmonary embolism suggest elevated trans-pulmonary gradients even in the absence of acutely increased pulmonary artery pressures. ePLAR dramatically increases the sensitivity of echocardiography for detection of hemodynamic perturbations in sub-massive pulmonary embolism patients, which may offer clinical utility in diagnosis and management.

The Prognostic Value of the Diastolic Stress Test in Patients Undergoing Treadmill Stress Echocardiography.

BACKGROUND: Exercise stress echocardiography (SE) is well validated for the evaluation of myocardial ischemia. Diastolic stress testing (DST) is recommended in the 2016 American Society of Echocardiography and European Association of Cardiovascular Imaging Guidelines for unexplained dyspnea. This study's aim was to prognostically evaluate the DST prospectively in a large stress testing population. METHODS: Patients underwent SE with mitral E/e' measured before and after maximal treadmill exertion to estimate diastolic function. Patients were divided into four groups: group 1 (n = 201)-ischemic; group 2 (n = 1,563)-negative DST (E/e'pre < 12, E/e'post < 12); group 3 (n = 68)-positive DST (E/e'pre < 12, E/e'post ≥ 12); group 4 (n = 314)-high baseline E/e' (E/e'pre ≥ 12). RESULTS: Consecutive patients (n = 2,201, 770 [35%] female; 58 ± 12 years) were followed after SE for 27,964 patient-months. Time to first heart failure event (composite of heart failure admission, worsening New York Heart Association class, worsening ejection fraction, or cardiovascular death) was analyzed and adjusted using Cox proportional hazards regression. Ischemic patients hazard ratio (HR) was 28, 95% CI, 17-44, P < .0005, for subsequent heart failure compared with negative DST patients. Nonischemic, positive DSTs were highly predictive (HR = 4.2; 95% CI, 1.6-11.0; P = .001); while high E/e'pre was not predictive (HR = 1.3; 95% CI, 0.7-2.4; P = .49) of future heart failure events. CONCLUSIONS: DST differentiates heart failure prognosis in patients with induced diastolic dysfunction. Ischemia predictably portends the worst heart failure outcomes, and nonischemic, positive diastolic stress tests predicted more events compared with negative tests. These prognostic data support and add to the recommendations of the 2016 guidelines.

Left Ventricular Global Strain Analysis by Two-Dimensional Speckle-Tracking Echocardiography: The Learning Curve.

BACKGROUND: The application of left ventricular (LV) global strain by speckle-tracking is becoming more widespread, with the potential for incorporation into routine clinical echocardiography in selected patients. There are no guidelines or recommendations for the training requirements to achieve competency. The aim of this study was to determine the learning curve for global strain analysis and determine the number of studies that are required for independent reporting. METHODS: Three groups of novice observers (cardiology fellows, cardiac sonographers, medical students) received the same standardized training module prior to undertaking retrospective global strain analysis on 100 patients over a period of 3 months. To assess the effect of learning, quartiles of 25 patients were read successively by each blinded observer, and the results were compared to expert for correlation. RESULTS: Global longitudinal strain (GLS) had uniform learning curves and was the easiest to learn, requiring a minimum of 50 patients to achieve expert competency (intraclass correlation coefficient > 0.9) in all three groups over a period of 3 months. Prior background knowledge in echocardiography is an influential factor affecting the learning for interobserver reproducibility and time efficiency. Short-axis strain analysis using global circumferential stain and global radial strain did not yield a comprehensive learning curve, and expert level was not achieved by the end of the study. CONCLUSIONS: There is a significant learning curve associated with LV strain analysis. We recommend a minimum of 50 studies for training to achieve competency in GLS analysis.

ePLAR - The echocardiographic Pulmonary to Left Atrial Ratio - A novel non-invasive parameter to differentiate pre-capillary and post-capillary pulmonary hypertension.

BACKGROUND: Right heart catheterisation is the gold-standard for differentiating pre-capillary pulmonary hypertension (high mean pulmonary artery pressure, normal pulmonary wedge pressure) from post-capillary physiology (elevated pulmonary wedge pressure). The new non-invasive parameter, ePLAR (echocardiographic Pulmonary to Left Atrial Ratio) is calculated from the maximum tricuspid regurgitation continuous wave Doppler velocity (m/s) divided by the transmitral E-wave:septal mitral annular Doppler Tissue Imaging e'-wave ratio (TRVmax/E:e'). METHODS: Pulmonary hypertension patients (mean pulmonary artery pressure>25mmHg, n=133, 66 male, average 65.0±16.8years) were classified by right heart catheterisation as pre-capillary or post-capillary [subdivided into isolated post-capillary (diastolic pulmonary gradient <7mmHg) or combined pre- and post-capillary cases]. The ePLAR values of these groups were compared to each other and to a population sample of 16,356 population reference echocardiograms. RESULTS: ePLAR values for the normal reference population of 16,356 echocardiograms (age 56±16.6years) were 0.30±0.09m/s. Pre-capillary pulmonary hypertension patients (n=35, 26 male, PAPsys 63.9±16.6mmHg, PAPdiast 24.1±7.3mmHg, PAPmean 37.9±9.4mmHg, PCWP 10.6±2.7mmHg) had significantly higher ePLAR values than post-capillary cases (n=98, 40 male, PAPsys 59.9±17.6mmHg, PAPdiast 25.0±7.4mmHg, PAPmean 38.1±9.8mmHg, PCWP 23.5±6.4mmHg)-ePLAR 0.44±0.22m/s vs 0.20±0.11m/s (p<0.001). ePLAR values were significantly lower in isolated post-capillary pulmonary hypertension than in combined pre- and post-capillary cases (0.18±0.08m/s vs 0.28±0.18m/s, p<0.001). CONCLUSIONS: ePLAR is a simple echocardiographic parameter which can accurately differentiate the smaller subset of patients with pre-capillary pulmonary hypertension from the more common post-capillary aetiology. The use of this easily obtained echocardiographic parameter has the potential to enhance non-invasive triage of patients for specific pulmonary vasodilator therapy.