Role of cardiac magnetic resonance in the evaluation of dilated cardiomyopathy: diagnostic contribution and prognostic significance

A cardiac MRI motion artifact reduction method based on edge enhancement network

Cardiac magnetic resonance imaging (MRI) usually requires a long acquisition time. The movement of the patients during MRI acquisition will produce image artifacts. Previous studies have shown that clear MR image texture edges are of great significance for pathological diagnosis. In this paper, a motion artifact reduction method for cardiac MRI based on edge enhancement network is proposed. Firstly, the four-plane normal vector adaptive fractional differential mask is applied to extract the edge features of blurred images. The four-plane normal vector method can reduce the noise information in the edge feature maps. The adaptive fractional order is selected according to the normal mean gradient and the local Gaussian curvature entropy of the images. Secondly, the extracted edge feature maps and blurred images are input into the de-artifact network. In this network, the edge fusion feature extraction network and the edge fusion transformer network are specially designed. The former combines the edge feature maps with the fuzzy feature maps to extract the edge feature information. The latter combines the edge attention network and the fuzzy attention network, which can focus on the blurred image edges. Finally, extensive experiments show that the proposed method can obtain higher peak signal-to-noise ratio and structural similarity index measure compared to state-of-art methods. The de-artifact images have clear texture edges.

Cardiovascular Magnetic Resonance Imaging in Myocardial Disease

Cardiovascular magnetic resonance (CMR) is the central non-invasive imaging investigation for the evaluation of myocardial disease. It is the well-established gold standard for measuring cardiac chamber volumes, systolic function, and left ventricular mass, and it brings unique information for therapeutic decisions. In addition, its tissue characterization capability, through T1, T2, and T2* mapping, as well as early and late gadolinium enhancement (LGE) sequences, allows to differentiate in many cases among ischemic, inflammatory, and infiltrative heart disease and permits the quantification of myocardial fibrosis, providing valuable diagnostic and prognostic information. This review aims to highlight the main CMR features of different cardiomyopathies.

Current Insights and Novel Cardiovascular Magnetic Resonance-Based Techniques in the Prognosis of Non-Ischemic Dilated Cardiomyopathy

Cardiac magnetic resonance (CMR) imaging has an important emerging role in the evaluation and management of patients with cardiomyopathies, especially in patients with dilated cardiomyopathy (DCM). It allows a non-invasive characterization of myocardial tissue, thus assisting early diagnosis and precise phenotyping of the different cardiomyopathies, which is an essential step for early and individualized treatment of patients. Using imaging techniques such as late gadolinium enhancement (LGE), standard and advanced quantification as well as quantitative mapping parameters, CMR-based tissue characterization is useful in the differential diagnosis of DCM and risk stratification. The purpose of this article is to review the utility of CMR in the diagnosis and management of idiopathic DCM, as well as risk prediction and prognosis based on standard and emerging CMR contrast and non-contrast techniques. This is consistent with current evidence and guidance moving beyond traditional prognostic markers such as ejection fraction.

Genetics of Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is defined as dilation and/or reduced function of one or both ventricles and remains a common disease worldwide. An estimated 40% of cases of familial DCM have an identifiable genetic cause. Accordingly, there is a fast-growing interest in the field of molecular genetics as it pertains to DCM. Many gene mutations have been identified that contribute to phenotypically significant cardiomyopathy. DCM genes can affect a variety of cardiomyocyte functions, and particular genes whose function affects the cell-cell junction and cytoskeleton are associated with increased risk of arrhythmias and sudden cardiac death. Through advancements in next-generation sequencing and cardiac imaging, identification of genetic DCM has improved over the past couple decades, and precision medicine is now at the forefront of treatment for these patients and their families. In addition to standard treatment of heart failure and prevention of arrhythmias and sudden cardiac death, patients with genetic cardiomyopathy stand to benefit from gene mechanism-specific therapies.

Cardiac magnetic resonance imaging findings of isolated left ventricular apical hypoplasia

Isolated left ventricular apical hypoplasia (ILVAH) is an uncommon and likely congenital cardiac abnormality that has been described as relatively new. ILVAH is characterized by a truncated, globular-shaped left ventricle (LV) with bulging of the interventricular septum toward the right ventricle (RV), wrapping of an elongated and lengthened RV around the absent LV apex, thinning and fat replacement of apical myocardium of the LV, and abnormalities in the papillary muscle arrangement of the LV. In this report, we present the cardiac magnetic resonance imaging findings of a 22-year-old female patient with non-specific cardiac complaints that were compatible with ILVAH. Recognition of this rare cardiomyopathy is important for clinicians and radiologists in order to follow up on patients with ILVAH, as it may lead to severe complications, and to distinguish it from other cardiomyopathies.

Learning objective

Isolated left ventricular apical hypoplasia (ILVAH) is a rare congenital cardiomyopathy that has some serious complications, such as left-sided heart failure, severe pulmonary hypertension, and fatal arrhythmias. By recognizing and identifying the cardiac magnetic resonance imaging findings of ILVAH, clinicians and radiologists can take appropriate measures to manage and treat patients with this condition, potentially improving outcomes and reducing the risk of complications.

Advancing Precision Medicine in Myocarditis: Current Status and Future Perspectives in Endomyocardial Biopsy-Based Diagnostics and Therapeutic Approaches

The diagnosis and specific and causal treatment of myocarditis and inflammatory cardiomyopathy remain a major clinical challenge. Despite the rapid development of new imaging techniques, endomyocardial biopsies remain the gold standard for accurate diagnosis of inflammatory myocardial disease. With the introduction and continued development of immunohistochemical inflammation diagnostics in combination with viral nucleic acid testing, myocarditis diagnostics have improved significantly since their introduction. Together with new technologies such as miRNA and gene expression profiling, quantification of specific immune cell markers, and determination of viral activity, diagnostic accuracy and patient prognosis will continue to improve in the future. In this review, we summarize the current knowledge on the pathogenesis and diagnosis of myocarditis and inflammatory cardiomyopathies and highlight future perspectives for more in-depth and specialized biopsy diagnostics and precision, personalized medicine approaches.

Arrhythmia and Survival Outcomes Among Black Patients and White Patients With a Primary Prevention Defibrillator

BACKGROUND

Black Americans have a higher risk of nonischemic cardiomyopathy (NICM) than White Americans. We aimed to evaluate differences in the risk of tachyarrhythmias among patients with an implantable cardioverter-defibrillator (ICD).

METHODS

The study population comprised 3895 ICD recipients in the United States enrolled in primary prevention ICD trials. Outcome measures included ventricular tachyarrhythmia (VTA), atrial tachyarrhythmia (ATA), ICD therapies, VTA burden (using Andersen-Gill recurrent event analysis), death, and the predicted benefit of the ICD. All events were adjudicated blindly. Outcomes were compared between self-reported Black patients versus White patients with cardiomyopathy (ischemic and NICM).

RESULTS

Black patients were more likely to be female (35% versus 22%) and younger (57±12 versus 62±12 years) with a higher frequency of comorbidities. In NICM, Black patients had a higher rate of first VTA, fast VTA, ATA, and appropriate and inappropriate ICD therapy (VTA ≥170 bpm, 32% versus 20%; VTA ≥200 bpm, 22% versus 14%; ATA, 25% versus 12%; appropriate therapy, 30% versus 20%; and inappropriate therapy, 25% versus 11%; P<0.001 for all). Multivariable analysis showed that Black patients with NICM experienced a higher risk of all types of arrhythmia or ICD therapy (VTA ≥170 bpm, hazard ratio [HR] 1.71; VTA ≥200 bpm, HR 1.58; ATA, HR 1.87; appropriate therapy, HR 1.62; inappropriate therapy, HR 1.86; P≤0.01 for all), higher burden of tachyarrhythmias or therapies (VTA, HR 1.84; appropriate therapy, HR 1.84; P<0.001 for both), and a higher risk of death (HR 1.92; P=0.014). In contrast, in ischemic cardiomyopathy, the risk of all types of tachyarrhythmia, ICD therapy, or death was similar between Black patients and White patients. Both Black patients and White patients derived a significant and similar benefit from ICD implantation.

CONCLUSIONS

Among patients with NICM with an ICD for primary prevention, Black patients compared with White patients had a high risk and burden of VTA, ATA, and ICD therapies with a lower survival rate. Nevertheless, the overall benefit of the ICD was maintained and was similar to that of White patients.

From the phenotype to precision medicine: an update on the cardiomyopathies diagnostic workflow

Cardiomyopathies are disease of the cardiac muscle largely due to genetic alterations of proteins with 'structural' or 'functional' roles within the cardiomyocyte, going from the regulation of contraction-relaxation, metabolic and energetic processes to ionic fluxes. Modifications occurring to these proteins are responsible, in the vast majority of cases, for the phenotypic manifestations of the disease, including hypertrophic, dilated, arrhythmogenic and restrictive cardiomyopathies. Secondary nonhereditary causes to be excluded include infections, toxicity from drugs or alcohol or medications, hormonal imbalance and so on. Obtaining a phenotypic definition and an etiological diagnosis is becoming increasingly relevant and feasible, thanks to the availability of new tailored treatments and the diagnostic advancements made particularly in the field of genetics. This is, for example, the case for transthyretin cardiac amyloidosis, Fabry disease or dilated cardiomyopathies due to laminopathies. For these diseases, specific medications have been developed, and a more tailored arrhythmic risk stratification guides the implantation of a defibrillator. In addition, new medications directly targeting the altered protein responsible for the phenotype are becoming available (including the myosin inhibitors mavacantem and aficamten, monoclonal antibodies against Ras-MAPK, genetic therapies for sarcoglycanopathies), thus making a precision medicine approach less unrealistic even in the field of cardiomyopathies. For these reasons, a contemporary approach to cardiomyopathies must consider diagnostic algorithms founded on the clinical suspicion of the disease and developed towards a more precise phenotypic definition and etiological diagnosis, based on a multidisciplinary methodology putting together specialists from different disciplines, facilities for advanced imaging testing and genetic and anatomopathological competencies.

Automatic uncertainty-based quality controlled T1 mapping and ECV analysis from native and post-contrast cardiac T1 mapping images using Bayesian vision transformer

Deep learning-based methods for cardiac MR segmentation have achieved state-of-the-art results. However, these methods can generate incorrect segmentation results which can lead to wrong clinical decisions in the downstream tasks. Automatic and accurate analysis of downstream tasks, such as myocardial tissue characterization, is highly dependent on the quality of the segmentation results. Therefore, it is of paramount importance to use quality control methods to detect the failed segmentations before further analysis. In this work, we propose a fully automatic uncertainty-based quality control framework for T1 mapping and extracellular volume (ECV) analysis. The framework consists of three parts. The first one focuses on segmentation of cardiac structures from a native and post-contrast T1 mapping dataset (n=295) using a Bayesian Swin transformer-based U-Net. In the second part, we propose a novel uncertainty-based quality control (QC) to detect inaccurate segmentation results. The QC method utilizes image-level uncertainty features as input to a random forest-based classifier/regressor to determine the quality of the segmentation outputs. The experimental results from four different types of segmentation results show that the proposed QC method achieves a mean area under the ROC curve (AUC) of 0.927 on binary classification and a mean absolute error (MAE) of 0.021 on Dice score regression, significantly outperforming other state-of-the-art uncertainty based QC methods. The performance gap is notably higher in predicting the segmentation quality from poor-performing models which shows the robustness of our method in detecting failed segmentations. After the inaccurate segmentation results are detected and rejected by the QC method, in the third part, T1 mapping and ECV values are computed automatically to characterize the myocardial tissues of healthy and cardiac pathological cases. The native myocardial T1 and ECV values computed from automatic and manual segmentations show an excellent agreement yielding Pearson coefficients of 0.990 and 0.975 (on the combined validation and test sets), respectively. From the results, we observe that the automatically computed myocardial T1 and ECV values have the ability to characterize myocardial tissues of healthy and cardiac diseases like myocardial infarction, amyloidosis, Tako-Tsubo syndrome, dilated cardiomyopathy, and hypertrophic cardiomyopathy.

The ebb and flow of cardiac lymphatics: a tidal wave of new discoveries

The heart is imbued with a vast lymphatic network that is responsible for fluid homeostasis and immune cell trafficking. Disturbances in the forces that regulate microvascular fluid movement can result in myocardial edema, which has profibrotic and proinflammatory consequences and contributes to cardiovascular dysfunction. This review explores the complex relationship between cardiac lymphatics, myocardial edema, and cardiac disease. It covers the revised paradigm of microvascular forces and fluid movement around the capillary as well as the arsenal of preclinical tools and animal models used to model myocardial edema and cardiac disease. Clinical studies of myocardial edema and their prognostic significance are examined in parallel to the recent elegant animal studies discerning the pathophysiological role and therapeutic potential of cardiac lymphatics in different cardiovascular disease models. This review highlights the outstanding questions of interest to both basic scientists and clinicians regarding the roles of cardiac lymphatics in health and disease.

A Comprehensive Review of Dilated Cardiomyopathy in Pre-clinical Animal Models in Addition to Herbal Treatment Options and Multi-modality Imaging Strategies

Dilated cardiomyopathy (DCM) is distinguished by ventricular chamber expansion, systolic dysfunction, and normal left ventricular (LV) wall thickness, and is mainly caused due to genetic or environmental factors; however, its aetiology is undetermined in the majority of patients. The focus of this work is on pathogenesis, small animal models, as well as the herbal medicinal approach, and the most recent advances in imaging modalities for patients with dilated cardiomyopathy. Several small animal models have been proposed over the last few years to mimic various pathomechanisms that contribute to dilated cardiomyopathy. Surgical procedures, gene mutations, and drug therapies are all characteristic features of these models. The pros and cons, including heart failure stimulation of extensively established small animal models for dilated cardiomyopathy, are illustrated, as these models tend to procure key insights and contribute to the development of innovative treatment techniques for patients. Traditional medicinal plants used as treatment in these models are also discussed, along with contemporary developments in herbal therapies. In the last few decades, accurate diagnosis, proper recognition of the underlying disease, specific risk stratification, and forecasting of clinical outcome, have indeed improved the health of DCM patients. Cardiac magnetic resonance (CMR) is the bullion criterion for assessing ventricular volume and ejection fraction in a reliable and consistent direction. Other technologies, like strain analysis and 3D echocardiography, have enhanced this technique's predictive and therapeutic potential. Nuclear imaging potentially helps doctors pinpoint the causative factors of left ventricular dysfunction, as with cardiac sarcoidosis and amyloidosis.

CMR feature tracking in patients with dilated cardiomyopathy: patterns of myocardial strain and focal fibrosis

BACKGROUND

There is a paucity of data on cardiovascular magnetic resonance feature tracking (CMR-FT) in patients with dilated cardiomyopathy (DCM). We aimed at describing global and segmental myocardial strain patterns and a potential association with the presence of focal myocardial scarring in DCM patients by CMR-FT.

METHODS

Thirty-nine patients with DCM and reduced left ventricular (LV) ejection fraction (mean 21±8%) underwent CMR including standard cine steady-state free precession (SSFP) sequences and late gadolinium enhancement (LGE). We measured global LV longitudinal as well as global and segmental circumferential and radial strain. The presence of focal myocardial fibrosis was assessed on LGE images.

RESULTS

Nineteen patients had focal myocardial fibrosis on LGE images with the highest prevalence in the basal septal segments II and III, which were affected in 12 (63%) and 13 (68%) patients. Furthermore, there was a significantly lower average short-axis LV radial strain (LV_SAX-RS) in these segments (4.89 (-1.55 to 11.34) %) compared with the average of the other myocardial segments (21.20 (17.36 to 25.05)%; p<0.001) after adjusting for LGE and left-bundle branch block (LBBB). In general, LV segments with LGE had lower model-based mean LV_SAX-RS values (17.65 (10.37 to 24.93) %) compared with those without LGE (19.40 (15.43 to 23.37) %), but this effect was not significant after adjusting for the presence of LBBB (p=0.630).

CONCLUSION

Our findings revealed a coincidence of impaired radial strain and focal myocardial fibrosis in the basal septal LV myocardial segments of patients with DCM. Regardless of this pattern, we did not find a general, significant effect of myocardial fibrosis on strain in our cohort. Future studies are required to assess the potential prognostic implications of myocardial strain patterns in addition to the assessment of myocardial fibrosis in patients with DCM.

The Role of AI in Characterizing the DCM Phenotype

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.

Right Heart Morphology and Its Association With Excessive and Deficient Cardiac Visceral Adipose Tissue

Visceral adipose tissue is an independent risk factor for the development of atherosclerotic coronary disease, arterial hypertension, diabetes and metabolic syndrome. Right heart morphology often involves the presence of adipose tissue, which can be quantified by non-invasive imaging methods. The last decade brought a wealth of new insights into the function and morphology of adipose tissue, with great emphasis on its role in the pathogenesis of heart disease. Cardiac adipose tissue is involved in thermogenesis, mechanical protection of the heart and energy storage. However, it can also be an endocrine organ that synthesises numerous pro-inflammatory and anti-inflammatory cytokines, the effect of which is accomplished by paracrine and vasocrine mechanisms. Visceral adipose tissue has several compartments that differ in their embryological origin and vascularisation. Deficiency of cardiac adipose tissue, often due to chronic pathological conditions such as oncological diseases or chronic infectious diseases, predicts increased mortality and morbidity. To date, knowledge about the influence of visceral adipose tissue on cardiac morphology is limited, especially the effect on the morphology of the right heart in a state of excess or deficient visceral adipose tissue.

MicroRNAs in Hypertrophic, Arrhythmogenic and Dilated Cardiomyopathy

MicroRNAs (miRNAs) are a class of non-coding RNAs of about 20 nucleotides in length, involved in the regulation of many biochemical pathways in the human body. The level of miRNAs in tissues and circulation can be deregulated because of altered pathophysiological mechanisms; thus, they can be employed as biomarkers for different pathological conditions, such as cardiac diseases. This review summarizes published findings of these molecular biomarkers in the three most common structural cardiomyopathies: human dilated, arrhythmogenic and hypertrophic cardiomyopathy.

Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies

The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging plays an important role in diagnosis and management of cardiomyopathies and provides useful prognostic information. Most molecular factors exert their functions by interacting with other cellular components, thus many diseases reflect perturbations of intracellular networks. Indeed, complex diseases and traits such as cardiomyopathies are caused by perturbations of biological networks. The network medicine approach, by integrating systems biology, aims to identify pathological interacting genes and proteins, revolutionizing the way to know cardiomyopathies and shifting the understanding of their pathogenic phenomena from a reductionist to a holistic approach. In addition, artificial intelligence tools, applied to morphological and functional imaging, could allow imaging scans to be automatically analyzed to extract new parameters and features for cardiomyopathy evaluation. The aim of this review is to discuss the tools of network medicine in cardiomyopathies that could reveal new candidate genes and artificial intelligence imaging-based features with the aim to translate into clinical practice as diagnostic, prognostic, and predictive biomarkers and shed new light on the clinical setting of cardiomyopathies. The integration and elaboration of clinical habits, molecular big data, and imaging into machine learning models could provide better disease phenotyping, outcome prediction, and novel drug targets, thus opening a new scenario for the implementation of precision medicine for cardiomyopathies.

Isolated ventricular apical hypoplasia: A report of four cases and literature review

Isolated ventricular apical hypoplasia (IVAH) is a rare congenital cardiac anomaly, with clinical manifestations depending on the age of the patient, ranging from no symptoms in children to congestive heart failure or even malignant tachycardia in adults. Herein, we describe the clinical and anatomical findings in four cases with hypoplasia of the right or left ventricular apex, and we discuss the possible mechanisms and differential diagnosis of this malformation. Echocardiography is a rapidly accessible, low cost, noninvasive technique for the detection and evaluation of IVAH.

An overview of the immune mechanisms of viral myocarditis

Viral myocarditis has been identified as a major cause of dilated cardiomyopathy (DCM) that can lead to heart failure. Historically, Coxsackieviruses and adenoviruses have been commonly suspected in myocarditis/DCM patients in North America and Europe. However, this notion is changing as other viruses such as Parvovirus B19 and human herpesvirus-6 are increasingly reported as causes of myocarditis in the United States, with the most recent example being the severe acute respiratory syndrome coronavirus 2, causing the Coronavirus Disease-19. The mouse model of Coxsackievirus B3 (CVB3)-induced myocarditis, which may involve mediation of autoimmunity, is routinely used in the study of immune pathogenesis of viral infections as triggers of DCM. In this review, we discuss the immune mechanisms underlying the development of viral myocarditis with an emphasis on autoimmunity in the development of post-infectious myocarditis induced with CVB3.

Multimodality imaging in chronic heart failure

The prevalence of heart failure (HF) is approximately 1-2% of the adult population in developed countries, rising to  ≥ 10% among people over 70. The common symptoms of HF include shortness of breath, ankle swelling and fatigue, determined by a reduced cardiac output. Multimodality imaging is crucial to define HF etiology, determine prognosis and guiding tailored treatments. Echocardiography is the most widely used imaging modality and maintains a pivotal role in the initial diagnostic work-up and in the follow-up of HF patients. Cardiac magnetic resonance (CMR) may support the morpho-functional assessment provided by echocardiography when the acoustic window is limited or a gold standard evaluation is required. Furthermore, CMR is frequently used due to the unmatched capability to characterize myocardial structure. Coronary computed tomography angiography has become the non-invasive imaging of choice to diagnose or rule-out coronary artery disease, acquiring remarkable importance in the management of HF patients. Moreover, emerging capabilities of CT-based tissue characterization may be useful, especially when CMR is contraindicated. Finally, chest CT may contribute to precisely define the framework of HF patients, revealing new insight about cardiopulmonary pathophysiological interactions with potential high prognostic value.

Guideline for Cardiovascular Magnetic Resonance Imaging from the Korean Society of Cardiovascular Imaging-Part 1: Standardized Protocol

Cardiac magnetic resonance (CMR) imaging is widely used in many areas of cardiovascular disease assessment. This is a practical, standard CMR protocol for beginners that is designed to be easy to follow and implement. This protocol guideline is based on previously reported CMR guidelines and includes sequence terminology used by vendors, essential MR physics, imaging planes, field strength considerations, MRI-conditional devices, drugs for stress tests, various CMR modules, and disease/symptom-based protocols based on a survey of cardiologists and various appropriate-use criteria. It will be of considerable help in planning and implementing tests. In addressing CMR usage and creating this protocol guideline, we particularly tried to include useful tips to overcome various practical issues and improve CMR imaging. We hope that this document will continue to standardize and simplify a patient-based approach to clinical CMR and contribute to the promotion of public health.

Prognostic value of late gadolinium enhancement in cardiac MRI of non-ischemic dilated cardiomyopathy patients

Background

The role of late gadolinium enhancement (LGE) in cardiac MRI (CMR) as prognostic marker in non-ischemic dilated cardiomyopathy (NIDCM) is evolving.

Objective

To study the effect of LGE in the prognosis of NIDCM patients.

Methods

112 consecutive NIDCM patients, who underwent CMR, were prospectively followed up for 745 ± 320 days. Primary end point was occurrence of MACE {composite of all-cause mortality, resuscitated cardiac arrest, sustained ventricular tachycardia (VT)/appropriate ICD shock, heart failure (HF) hospitalization}.

Results

LGE was present in 44 out of 112 patients (39%). The primary end point (MACE) was significantly higher in LGE + ve group compared to the LGE –ve group (72.7% vs. 29.4%; p < 0.0001). Similarly, cardiac mortality (9.1% vs 2.9%; p < 0.049), VT (13.6% vs. 2.9%; p < 0.031), HF hospitalization (63.6% vs. 30.9%; p < 0.001) were significantly more in LGE + ve group. In univariate model, LGE demonstrated the strongest association with MACE (Hazard ratio [HR] = 2.96 [95% CI 1.685 to 5.201; p < 0.0001). LGE extent of >14% of LV predicted MACE with 90.6% sensitivity and 86% specificity. HR of LGE extent >14% of LV for MACE is 6.12; p < 0.01. LGE was associated with MACE irrespective of its location, pattern or distribution. Multivariate model showed LGE and its extent >14% of LV volume were strongest predictor of MACE.

Conclusion

LGE and its extent >14% predicts adverse cardiac events in NIDCM irrespective of LVEF and LGE location, pattern or distribution. This study emphasises the role of CMR in risk stratification of NIDCM patients and guiding therapy.

Cardiac Imaging in the Athlete: Shrinking the "Gray Zone"

PURPOSE OF THE REVIEW

This review will explore frequently encountered diagnostic challenges and summarize the role cardiac imaging plays in defining the boundaries of what constitutes the athlete's heart syndrome versus pathology.

RECENT FINDINGS

Investigations have predominantly focused on differentiating the athlete's heart from potentially lethal pathological conditions that may produce a similar cardiac morphology. Guidelines have identified criteria for identifying definitive pathology, but difficulty arises when individuals fall in the gray zone of expected athletic remodeling and pathology. Transthoracic echo has traditionally been the imaging modality of choice utilizing parameters such as wall thickness, wall:volume ratio, and certain diastolic parameters. Newer echocardiogram techniques such as strain imaging and speckle tracking have potential additive utility but still need further investigation. Cardiac magnetic resonance (CMR) imaging has emerged as an additive technique to help differentiate the phenotypic overlap between these groups. Utilizing gadolinium enhancement and T1 mapping along with its excellent spatial resolution can help distinguish pathology from physiology. Both established and novel cardiac imaging modalities have been used for uncovering the at risk athletes with cardiomyopathies. The issue is of practical importance because athletes are frequently referred to the cardiologist with symptoms of fatigue, palpitations, presyncope, and/or syncope concerned about the safety of their future participation. Imaging is a key component of risk stratification and identifying normal findings of the developed athlete and those "at-risk" athletes.

Emerging role of microRNAs in dilated cardiomyopathy: evidence regarding etiology

Dilated cardiomyopathy (DCM) is a heart muscle disease characterized by ventricular dilation and systolic dysfunction in the absence of abnormal loading conditions or coronary artery disease. This cardiac disorder is a major health problem due to its high prevalence, morbidity, and mortality. DCM is a complex disease with a common phenotype but heterogeneous pathological mechanisms. Early etiological diagnosis and prognosis stratification is crucial for the clinical management of the patient. Advances in imaging technology and genetic tests have provided useful tools for clinical practice. Nevertheless, the assessment of the disease remains challenging. Novel noninvasive indicators are still needed to assist in decision-making. microRNAs (miRNAs), a group of small noncoding RNAs, have been identified as key mediators of cell biology. They are found in a stable form in body fluids and their concentration is altered in response to stress. Previous research has suggested that the miRNA signature constitutes a novel source of noninvasive biomarkers for a wide array of cardiovascular diseases. Specifically, several studies have reported the potential role of miRNAs as clinical indicators among the etiologies of DCM. However, this field has not been reviewed in detail. Here, we summarize the evidence of intracellular and circulating miRNAs in DCM and their usefulness in the development of novel diagnostic, prognostic and therapeutic approaches, with a focus on DCM etiology. Although the findings are still preliminary, due to methodological and technical limitations and the lack of robust population-based studies, miRNAs constitute a promising tool to assist in the clinical management of DCM.

Cocaine Abuse: An Attack to the Cardiovascular System-Insights from Cardiovascular MRI

Cocaine is the most commonly used illicit drug in the European Union. Its cardiac effects are numerous and diverse, both in acute and chronic abuse, and include myocardial infarction, myocarditis, catecholamine-induced cardiomyopathy, and chronic cardiomyopathy (subclinical, hypertrophic, and dilated phases). Their clinical manifestations are vastly overlapping, and differential diagnosis should be performed using a thorough diagnostic workup featuring clinical history, laboratory tests, electrocardiography, stress test, noninvasive imaging modalities, and coronary angiography. Cardiac MRI has the unique ability of in vivo tissue characterization. This unique feature can play a pivotal role in the differential diagnosis through proper characterization of the myocardial tissue. Especially in acute settings, cardiac MRI makes it possible to distinguish between cocaine-induced myocardial infarction, cocaine-induced myocarditis, and catecholamine-induced cardiomyopathy. Conversely, in chronic cardiomyopathy, cardiac MRI permits evaluation of ventricular function and myocardial tissue, allowing the investigation of the underlying cause. On the one hand, assessing the ventricular function permits differentiation among subclinical, hypertrophic, and dilated phases of chronic cardiomyopathy; on the other hand, cardiac MRI could classify the causes underlying remodeling, including chronic ischemic injury, chronic myocarditis, and cardiac motion impairment. This review analyzes the relationship between pathophysiology, histology, and disease using the existing literature on cardiac MRI cocaine abuse evaluation. © RSNA, 2019.

Using machine learning to predict one-year cardiovascular events in patients with severe dilated cardiomyopathy

PURPOSE

Dilated cardiomyopathy (DCM) is a common form of cardiomyopathy and it is associated with poor outcomes. A poor prognosis of DCM patients with low ejection fraction has been noted in the short-term follow-up. Machine learning (ML) could aid clinicians in risk stratification and patient management after considering the correlation between numerous features and the outcomes. The present study aimed to predict the 1-year cardiovascular events in patients with severe DCM using ML, and aid clinicians in risk stratification and patient management.

MATERIALS AND METHODS

The dataset used to establish the ML model was obtained from 98 patients with severe DCM (LVEF < 35%) from two centres. Totally 32 features from clinical data were input to the ML algorithm, and the significant features highly relevant to the cardiovascular events were selected by Information gain (IG). A naive Bayes classifier was built, and its predictive performance was evaluated using the area under the curve (AUC) of the receiver operating characteristics by 10-fold cross-validation.

RESULTS

During the 1-year follow-up, a total of 22 patients met the criterion of the study end-point. The top features with IG > 0.01 were selected for ML model, including left atrial size (IG = 0.240), QRS duration (IG = 0.200), and systolic blood pressure (IG = 0.151). ML performed well in predicting cardiovascular events in patients with severe DCM (AUC, 0.887 [95% confidence interval, 0.813-0.961]).

CONCLUSIONS

ML effectively predicted risk in patients with severe DCM in 1-year follow-up, and this may direct risk stratification and patient management in the future.

Expression of ADAMTS-1 mRNA in myocardium of viral heart disease mice and its clinical significance

The expression of ADAMTS-1 mRNA in myocardium of viral heart disease (VHD) mice was investigated to explore its role in myocardial fibrosis. A total of 150 purebred inbred Balb/c mice were used in this study. According to the principle of similar body weight, 50 mice were selected to make an acute viral myocarditis (VMC) animal model (acute VMC group), and 50 mice were selected to make a chronic VMC animal model (chronic VMC group), and the remaining 50 mice were selected as a control group. RT-qPCR was used to detect the relative expression of transforming growth factor-β1 (TGF-β1) mRNA and ADAMTS-1 mRNA in myocardial tissue of three groups of mice, and their relationship in myocardial fibrosis was analyzed. Compared with the control group, the collagen volume fraction (CVF) in the myocardial tissue of the acute VMC group was significantly increased, and the increase of CVF in the myocardial tissue of the chronic VMC group was the most significant (p<0.001). Compared with the control group, the relative expression of TGF-β1 mRNA and ADAMTS-1 mRNA in myocardial tissue of the mice in the acute and chronic VMC group were significantly increased (p<0.001). The relative expression of TGF-β1 mRNA and ADAMTS-1 mRNA in myocardial tissue of chronic VMC group was significantly higher than that of acute VMC group (p<0.001). Pearson's correlation test results showed that ADAMTS-1 mRNA was positively correlated with CVF and TGF-β1 mRNA, and the correlation coefficients were (r=0.351, p<0.01, r=0.401, p<0.01). ADAMTS-1 is involved in the occurrence and development of myocardial fibrosis, and it is positively correlated with CVF and TGF-β1. It may play a role in promoting myocardial fibrosis during the development of VHD. It can be used as a biological index for predicting myocardial fibrosis.

Galectin-3 as a Predictor of Left Ventricular Reverse Remodeling in Recent-Onset Dilated Cardiomyopathy

Objectives

Studies have evaluated the association of galectin-3 and outcome in patients with heart failure. However, there is still scarce evidence concerning the clinical usefulness and predictive value of galectin-3 for left ventricular reverse remodeling (LVRR) in patients with recent-onset dilated cardiomyopathy (RODCM).

Patients and Methods

Baseline galectin-3 was measured in 57 patients with RODCM. All patients were followed for at least 12 months. The study end point was LVRR at 12 months, defined as an absolute improvement of the left ventricular ejection fraction of ≥10% to a final value of ≥35%, accompanied by a decrease in the left ventricular end diastolic diameter of at least 10%, as assessed by echocardiography. In receiver operating characteristic curve analysis, the optimum cut-off value for baseline galectin-3 with the highest Youden index was 59 ng/ml.

Results

Overall, LVRR at 12 months was observed in 38 patients (66%). In a univariate analysis, NYHA functional class and baseline galectin-3 levels were associated with LVRR. After adjustment for covariates, galectin-3 remained an independent predictor for LVRR.

Conclusions

Our study suggests that baseline galectin-3 is an independent predictor of LVRR. Low levels of galectin-3 may be regarded a useful biomarker of favorable ventricular remodeling in patients with RODCM.

Therapeutic implications of a combined diagnostic workup including endomyocardial biopsy in an all-comer population of patients with heart failure: a retrospective analysis

BACKGROUND

Aetiology of heart failure (HF) often remains obscure. We therefore evaluated the usefulness of a combined diagnostic approach including cardiac magnetic resonance imaging (CMRI) and endomyocardial biopsy (EMB) to assess the cause of unexplained cardiomyopathy underlying HF.

METHODS AND RESULTS

We retrospectively investigated 100 consecutive patients (36% women, mean age 53.6 ± 18.8 years) presenting with unexplained cardiomyopathy (HF with reduced ejection fraction or left ventricular hypertrophy; excluding ischaemic and valvular heart disease; left ventricular ejection fraction 31.6 ± 13.9%, Left ventricular end-diastolic pressure 18.2 ± 9.3 mmHg, heart rate 89 ± 26.6 b.p.m.; mean ± SEM) at the University Medical Center Mainz. We performed electrocardiography, echocardiography, CMRI, and cardiac catheterization with EMB analysed at a Food and Drug Administration-approved reference centre in 100%, 94%, 69%, and 100% of patients, respectively. On the basis of CMRI findings, electrocardiography, echocardiography, and medical history, the exact cause of cardiomyopathy remained uncertain in 37 of 69 cases (53.6%). In EMB, 25% of patients had viral replication, 23% had inflammation defined as lymphocytic infiltrations without active virus replication, 1% had giant cell myocarditis, and 1% had eosinophilic myocarditis. After diagnostic workup including EMB findings, the cause of cardiomyopathy remained unidentified in 14% of the cases, classified as idiopathic dilated cardiomyopathy or hypertrophic cardiomyopathy in 10% or 4%, respectively. EMB helped to discuss a causal treatment strategy of HF involving immunosuppression or antiviral treatment in 53% of patients, which was opted for in 12% of the patients.

CONCLUSIONS

A comprehensive workup including imaging and EMB in an all-comer population of patients with HF may help physicians to improve diagnostics of unexplained cardiomyopathy in the majority of cases.

Fatty Images of the Heart: Spectrum of Normal and Pathological Findings by Computed Tomography and Cardiac Magnetic Resonance Imaging

Ectopic cardiac fatty images are not rarely detected incidentally by computed tomography and cardiac magnetic resonance, or by exams focused on the heart as in general thoracic imaging evaluations. A correct interpretation of these findings is essential in order to recognize their normal or pathological meaning, focusing on the eventually associated clinical implications. The development of techniques such as computed tomography and cardiac magnetic resonance allowed a detailed detection and evaluation of adipose tissue within the heart. This pictorial review illustrates the most common characteristics of cardiac fatty images by computed tomography and cardiac magnetic resonance, in a spectrum of normal and pathological conditions ranging from physiological adipose images to diseases presenting with cardiac fatty foci. Physiologic intramyocardial adipose tissue may normally be present in healthy adults, being not related to cardiac affections and without any clinical consequence. However cardiac fatty images may also be the expression of various diseases, comprehending arrhythmogenic right ventricular dysplasia, postmyocardial infarction lipomatous metaplasia, dilated cardiomyopathy, and lipomatous hypertrophy of the interatrial septum. Fatty neoplasms of the heart as lipoma and liposarcoma are also described.

Automatic segmentation of right ventricle in cardiac cine MR images using a saliency analysis

PURPOSE

Accurate measurement of the right ventricle (RV) volume is important for the assessment of the ventricular function and a biomarker of the progression of any cardiovascular disease. However, the high RV variability makes difficult a proper delineation of the myocardium wall. This paper introduces a new automatic method for segmenting the RV volume from short axis cardiac magnetic resonance (MR) images by a salient analysis of temporal and spatial observations.

METHODS

The RV volume estimation starts by localizing the heart as the region with the most coherent motion during the cardiac cycle. Afterward, the ventricular chambers are identified at the basal level using the isodata algorithm, the right ventricle extracted, and its centroid computed. A series of radial intensity profiles, traced from this centroid, is used to search a salient intensity pattern that models the inner-outer myocardium boundary. This process is iteratively applied toward the apex, using the segmentation of the previous slice as a regularizer. The consecutive 2D segmentations are added together to obtain the final RV endocardium volume that serves to estimate also the epicardium.

RESULTS

Experiments performed with a public dataset, provided by the RV segmentation challenge in cardiac MRI, demonstrated that this method is highly competitive with respect to the state of the art, obtaining a Dice score of 0.87, and a Hausdorff distance of 7.26 mm while a whole volume was segmented in about 3 s.

CONCLUSIONS

The proposed method provides an useful delineation of the RV shape using only the spatial and temporal information of the cine MR images. This methodology may be used by the expert to achieve cardiac indicators of the right ventricle function.

Dilated Cardiomyopathy: Phosphorus 31 MR Spectroscopy at 7 T

Purpose To test whether the increased signal-to-noise ratio of phosphorus 31 (³¹P) magnetic resonance (MR) spectroscopy at 7 T improves precision in cardiac metabolite quantification in patients with dilated cardiomyopathy (DCM) compared with that at 3 T. Materials and Methods Ethical approval was obtained, and participants provided written informe consent. In a prospective study, ³¹P MR spectroscopy was performed at 3 T and 7 T in 25 patients with DCM. Ten healthy matched control subjects underwent ³¹P MR spectroscopy at 7 T. Paired Student t tests were performed to compare results between the 3-T and 7-T studies. Results The phosphocreatine (PCr) signal-to-noise ratio increased 2.5 times at 7 T compared with that at 3 T. The PCr to adenosine triphosphate (ATP) concentration ratio (PCr/ATP) was similar at both field strengths (mean ± standard deviation, 1.48 ± 0.44 at 3 T vs 1.54 ± 0.39 at 7 T, P = .49), as expected. The Cramér-Rao lower bounds in PCr concentration (a measure of uncertainty in the measured ratio) were 45% lower at 7 T than at 3 T, reflecting the higher quality of 7-T ³¹P spectra. Patients with dilated cardioyopathy had a significantly lower PCr/ATP than did healthy control subjects at 7 T (1.54 ± 0.39 vs 1.95 ± 0.25, P = .005), which is consistent with previous findings. Conclusion 7-T cardiac ³¹P MR spectroscopy is feasible in patients with DCM and gives higher signal-to-noise ratios and more precise quantification of the PCr/ATP than that at 3 T. PCr/ATP was significantly lower in patients with DCM than in control subjects at 7 T, which is consistent with previous findings at lower field strengths.

The evaluation of non-ischemic dilated cardiomyopathy with T1 mapping and ECV methods using 3T cardiac MRI

PURPOSE

The aim of this study was to examine the correlation between ventricular function and the extracellular volume fraction (ECV) in patients with non-ischemic dilated cardiomyopathy (NIDCM) using 3.0 T magnetic resonance imaging (MRI). We also hypothesized that native T1 and ECV values would be increased in patients with NIDCM, independent of the left ventricular ejection fraction (LVEF). The findings of our study could lead to further studies of the follow-up protocols.

MATERIALS AND METHODS

In total, 53 consecutive dilated cardiomyopathy patients who had undergone cardiac MRI were functionally evaluated and underwent tissue characterization.

RESULTS

The mean native T1 value was 1235 ± 10 ms, and the mean ECV value was 35.4 ± 2.7% in the myocardia. The LVEF values ranged from 29 to 44%. No significant correlations were observed between functional analysis measurements and native T1 or ECV values.

CONCLUSIONS

Our results showed that myocardial fibrosis is unrelated to cardiac functional findings in NIDCM patients. Therefore, we propose that these patients should be evaluated using MRI and tissue characterization techniques, in addition to cardiac functional analysis.

Dilated Cardiomyopathy: Phosphorus 31 MR Spectroscopy at 7 T

Cardiac phosphorus spectroscopy is demonstrated to be feasible in patients at 7 T, giving higher signal-to-noise ratios and more precise quantification of the phosphocreatine to adenosine triphosphate concentration ratio than at 3 T in a group of 25 patients with dilated cardiomyopathy.

Purpose

To test whether the increased signal-to-noise ratio of phosphorus 31 (³¹P) magnetic resonance (MR) spectroscopy at 7 T improves precision in cardiac metabolite quantification in patients with dilated cardiomyopathy (DCM) compared with that at 3 T.

Materials and Methods

Ethical approval was obtained, and participants provided written informe consent. In a prospective study, ³¹P MR spectroscopy was performed at 3 T and 7 T in 25 patients with DCM. Ten healthy matched control subjects underwent ³¹P MR spectroscopy at 7 T. Paired Student t tests were performed to compare results between the 3-T and 7-T studies.

Results

The phosphocreatine (PCr) signal-to-noise ratio increased 2.5 times at 7 T compared with that at 3 T. The PCr to adenosine triphosphate (ATP) concentration ratio (PCr/ATP) was similar at both field strengths (mean ± standard deviation, 1.48 ± 0.44 at 3 T vs 1.54 ± 0.39 at 7 T, P = .49), as expected. The Cramér-Rao lower bounds in PCr concentration (a measure of uncertainty in the measured ratio) were 45% lower at 7 T than at 3 T, reflecting the higher quality of 7-T ³¹P spectra. Patients with dilated cardioyopathy had a significantly lower PCr/ATP than did healthy control subjects at 7 T (1.54 ± 0.39 vs 1.95 ± 0.25, P = .005), which is consistent with previous findings.

Conclusion

7-T cardiac ³¹P MR spectroscopy is feasible in patients with DCM and gives higher signal-to-noise ratios and more precise quantification of the PCr/ATP than that at 3 T. PCr/ATP was significantly lower in patients with DCM than in control subjects at 7 T, which is consistent with previous findings at lower field strengths.

Role of cardiac MRI in nonischemic cardiomyopathies

Cardiac magnetic resonance (CMR) with its higher spatial resolution is considered the gold standard for evaluating ventricular mass, volumes, and ejection fraction. CMR can be used for accurate diagnosis of several conditions, especially cardiomyopathies. The purpose of this article is to review the utility of CMR in the diagnosis and management of nonischemic cardiomyopathies. We have reviewed both common and rare types of nonischemic cardiomyopathies in detail and elaborated on the specific CMR findings in each. We believe that CMR is an invaluable tool, not only in differentiating nonischemic from ischemic cardiomyopathy, but also in aiding the accurate diagnosis and management of the subtype of nonischemic cardiomyopathy. CMR should routinely be integrated in the diagnostic workup of various cardiomyopathies.

Three-Dimensional Endo-Cardiovascular Volume-Rendered Cine Computed Tomography of Isolated Left Ventricular Apical Hypoplasia: A Case Report and Literature Review

We report multidetector computed tomography (MDCT) and cardiac magnetic resonance (CMR) findings of a 34-year-old female with isolated left ventricular apical hypoplasia. The MDCT and CMR scans displayed a spherical left ventricle (LV) with extensive fatty infiltration within the myocardium at the apex, interventricular septum and inferior wall, anteroapical origin of the papillary muscle, right ventricle wrapping around the deficient LV apex, and impaired systolic function. MDCT visualized morphologic and also functional findings of this unique cardiomyopathy.