Segmental longitudinal strain as the most accurate predictor of the patchy pattern late gadolinium enhancement in hypertrophic cardiomyopathy

In-silico heart model phantom to validate cardiac strain imaging

The quantification of cardiac strains as structural indices of cardiac function has a growing prevalence in clinical diagnosis. However, the highly heterogeneous four-dimensional (4D) cardiac motion challenges accurate "regional" strain quantification and leads to sizable differences in the estimated strains depending on the imaging modality and post-processing algorithm, limiting the translational potential of strains as incremental biomarkers of cardiac dysfunction. There remains a crucial need for a feasible benchmark that successfully replicates complex 4D cardiac kinematics to determine the reliability of strain calculation algorithms. In this study, we propose an in-silico heart phantom derived from finite element (FE) simulations to validate the quantification of 4D regional strains. First, as a proof-of-concept exercise, we created synthetic magnetic resonance (MR) images for a hollow thick-walled cylinder under pure torsion with an exact solution and demonstrated that "ground-truth" values can be recovered for the twist angle, which is also a key kinematic index in the heart. Next, we used mouse-specific FE simulations of cardiac kinematics to synthesize dynamic MR images by sampling various sectional planes of the left ventricle (LV). Strains were calculated using our recently developed non-rigid image registration (NRIR) framework in both problems. Moreover, we studied the effects of image quality on distorting regional strain calculations by conducting in-silico experiments for various LV configurations. Our studies offer a rigorous and feasible tool to standardize regional strain calculations to improve their clinical impact as incremental biomarkers.

In-silico heart model phantom to validate cardiac strain imaging

The quantification of cardiac strains as structural indices of cardiac function has a growing prevalence in clinical diagnosis. However, the highly heterogeneous four-dimensional (4D) cardiac motion challenges accurate "regional" strain quantification and leads to sizable differences in the estimated strains depending on the imaging modality and post-processing algorithm, limiting the translational potential of strains as incremental biomarkers of cardiac dysfunction. There remains a crucial need for a feasible benchmark that successfully replicates complex 4D cardiac kinematics to determine the reliability of strain calculation algorithms. In this study, we propose an in-silico heart phantom derived from finite element (FE) simulations to validate the quantification of 4D regional strains. First, as a proof-of-concept exercise, we created synthetic magnetic resonance (MR) images for a hollow thick-walled cylinder under pure torsion with an exact solution and demonstrated that "ground-truth" values can be recovered for the twist angle, which is also a key kinematic index in the heart. Next, we used mouse-specific FE simulations of cardiac kinematics to synthesize dynamic MR images by sampling various sectional planes of the left ventricle (LV). Strains were calculated using our recently developed non-rigid image registration (NRIR) framework in both problems. Moreover, we studied the effects of image quality on distorting regional strain calculations by conducting in-silico experiments for various LV configurations. Our studies offer a rigorous and feasible tool to standardize regional strain calculations to improve their clinical impact as incremental biomarkers.

Diagnostic efficacy of complexity metrics from cardiac MRI myocardial segmental motion curves in detecting late gadolinium enhancement in myocardial infarction patients

Background

Myocardial segmental motion is associated with cardiovascular pathology, often assessed through myocardial strain features. The stability of the motion can be influenced by myocardial fibrosis. This research aimed to explore the complexity metrics (CM) of myocardial segmental motion curves, observe their correlation with late gadolinium enhancement (LGE) transmural extension (TE), and assess diagnostic efficacy combined with segmental strains in different TE segments.

Methods

We included 42 myocardial infarction patients, dividing images into 672 myocardial segments (208 remote, 384 viable, and 80 unviable segments based on TE). Radial and circumferential segmental strain, along with CM for motion curves, were extracted. Correlation between CM and LGE, as well as the potential distinguishing role of CM, was evaluated using Pearson correlation, univariate linear regression (F-test), multivariate regression analysis (T-test), area under curve (AUC), machine learning models, and DeLong test.

Results

All CMs showed significant linear correlation with TE (P < 0.001). Six CMs were correlated with TE (r > 0.3), with radial frequency drift (FD) displayed the strongest correlation (r = 0.496, P < 0.001). Radial and circumferential FD significantly differed in higher TE myocardium than in remote segments (P < 0.05). Radial FD had practical diagnostic efficacy (remote vs. unviable AUC = 0.89, viable vs. unviable AUC = 0.77, remote vs. viable AUC = 0.65). Combining CM with segmental strain features boosted diagnostic efficacy than models using only segmental strain features (DeLong test, P < 0.05).

Conclusions

The CM of myocardial motion curves has been associated with LGE infarction, and combining CM with strain features improves the diagnosis of different myocardial LGE infarction degrees.

Advances in Multi-Modality Imaging in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is characterized by abnormal growth of the myocardium with myofilament disarray and myocardial hyper-contractility, leading to left ventricular hypertrophy and fibrosis. Where culprit genes are identified, they typically relate to cardiomyocyte sarcomere structure and function. Multi-modality imaging plays a crucial role in the diagnosis, monitoring, and risk stratification of HCM, as well as in screening those at risk. Following the recent publication of the first European Society of Cardiology (ESC) cardiomyopathy guidelines, we build on previous reviews and explore the roles of electrocardiography, echocardiography, cardiac magnetic resonance (CMR), cardiac computed tomography (CT), and nuclear imaging. We examine each modality's strengths along with their limitations in turn, and discuss how they can be used in isolation, or in combination, to facilitate a personalized approach to patient care, as well as providing key information and robust safety and efficacy evidence within new areas of research.

The potential impact of hereditary hemochromatosis on the heart considering the disease stage and patient age-the role of echocardiography

Background

Hereditary hemochromatosis (HH) is a genetic disease that leads to increased iron accumulation in several organs. Cardiomyocytes are highly susceptible to this damage owing to their high iron uptake, and cardiovascular complications account for 1/3 of the deaths in the natural course of HH. Additionally, excess iron intake and associated oxidative stress may accelerate the aging of the cardiovascular system, regardless of the age of patients with HH. We aimed to investigate the role of standard and speckle-tracking echocardiography (STE) in revealing heart differences in patients with HH considering the disease stage and the patient age.

Methodology

Consecutive patients with HH (n = 58) without heart pathologies (except hypertension) and 29 age- and sex-matched healthy individuals underwent echocardiography. Patients were compared according to the time since HH diagnosis (the recently diagnosed HH group [31 patients] with diagnosed HH for less than 6 months and had no more than one venesection; the medium group [11 patients] with diagnosed HH between 6 and 24 months; and the long-lasting group [16 patients] with diagnosed HH for more than 2 years) and the quartile contribution of their age.

Results

Standard echocardiography revealed differences in diastolic parameters between patients with HH and controls, which were the most prominent between healthy and long-lasting HH patients. Regarding systolic function, left ventricular ejection fraction was lower in HH patients, with the most evident differences between the healthy and recently diagnosed HH patients. STE revealed additional differences in systolic parameters, with LV rotation the worst in recently diagnosed patients and its increase in patients with medium and long-lasting HH. Significantly worse peak systolic longitudinal strain values were observed in all patients with HH. Analyses of the results according to the age quartiles of patients with HH revealed that some changes ocurred earlier than expected according to age.

Conclusions

Echocardiography can reveal possible heart damage in HH patients at different stages of the disease and highlight potential features of accelerated myocardial aging in these patients.

Cardiac MRI in Fabry disease

Fabry disease is a rare, progressive X-linked inherited disorder of glycosphingolipid metabolism due to a deficiency of α-galactosidase A enzyme. It leads to the accumulation of globotriaosylceramide within lysosomes of multiple organs, predominantly the vascular, renal, cardiac, and nervous systems. Fabry cardiomyopathy is characterized by increased left ventricular wall thickness/mass, functional abnormalities, valvular heart disease, arrhythmias, and heart failure. Early diagnosis and treatment are critical to avoid cardiac or renal complications that can significantly reduce life expectancy in untreated FD. This review will focus on the role of cardiovascular magnetic resonance imaging in the diagnosis, clinical decision-making, and monitoring of treatment efficacy.

Multimodality Imaging in Sarcomeric Hypertrophic Cardiomyopathy: Get It Right…on Time

Hypertrophic cardiomyopathy (HCM) follows highly variable paradigms and disease-specific patterns of progression towards heart failure, arrhythmias and sudden cardiac death. Therefore, a generalized standard approach, shared with other cardiomyopathies, can be misleading in this setting. A multimodality imaging approach facilitates differential diagnosis of phenocopies and improves clinical and therapeutic management of the disease. However, only a profound knowledge of the progression patterns, including clinical features and imaging data, enables an appropriate use of all these resources in clinical practice. Combinations of various imaging tools and novel techniques of artificial intelligence have a potentially relevant role in diagnosis, clinical management and definition of prognosis. Nonetheless, several barriers persist such as unclear appropriate timing of imaging or universal standardization of measures and normal reference limits. This review provides an overview of the current knowledge on multimodality imaging and potentialities of novel tools, including artificial intelligence, in the management of patients with sarcomeric HCM, highlighting the importance of specific "red alerts" to understand the phenotype-genotype linkage.

Detection of myocardial fibrosis: Where we stand

Myocardial fibrosis, resulting from the disturbance of extracellular matrix homeostasis in response to different insults, is a common and important pathological remodeling process that is associated with adverse clinical outcomes, including arrhythmia, heart failure, or even sudden cardiac death. Over the past decades, multiple non-invasive detection methods have been developed. Laboratory biomarkers can aid in both detection and risk stratification by reflecting cellular and even molecular changes in fibrotic processes, yet more evidence that validates their detection accuracy is still warranted. Different non-invasive imaging techniques have been demonstrated to not only detect myocardial fibrosis but also provide information on prognosis and management. Cardiovascular magnetic resonance (CMR) is considered as the gold standard imaging technique to non-invasively identify and quantify myocardial fibrosis with its natural ability for tissue characterization. This review summarizes the current understanding of the non-invasive detection methods of myocardial fibrosis, with the focus on different techniques and clinical applications of CMR.

Comprehensive Echocardiography of Left Atrium and Left Ventricle Using Modern Techniques Helps in Better Revealing Atrial Fibrillation in Patients with Hypertrophic Cardiomyopathy

Atrial fibrillation (AF) is an important arrhythmia in hypertrophic cardiomyopathy (HCM). We aimed to explore whether a complex evaluation of the left ventricle (LV) using modern echocardiography techniques, additionally to the left atrium (LA) boosts the probability of AF diagnosis. Standard echocardiography, 2D and 3D speckle tracking, were performed for LA and LV evaluation in HCM patients and healthy volunteers. Of 128 initially qualified HCM patients, 60 fulfilled included criteria, from which 43 had a history of AF, and 17 were without AF. LA volume index and peak strain, LV ejection fraction, and strains were significant predictors of AF. In addition, 2D global longitudinal strain (GLS) for LV at cut off -16% turned out to be the most accurate predictor of AF (OR 48.00 [95% CI 2.68-859.36], p = 0.001), whereas the combination of LA peak strain ≤ 22% and LV GLS ≥ -16% had the highest discriminatory power (OR 76.36 [95% CI 4.13-1411.36], p = 0.001). AF in HCM patients seems to be LA as well as LV disease. Revealing lower strain for LV, in addition to lower LA strain, may have an important impact on accurate characteristics of HCM patients with AF history.