Current Pathophysiological and Genetic Aspects of Dilated Cardiomyopathy

Dilated cardiomyopathy is the most common form of cardiomyopathy and the second leading cause of left ventricular dysfunction with highly variable clinical presentation and prognosis. The clinical courses vary and are strongly heterogeneous, ranging from asymptomatic patients to those suffering from intractable heart failure or sudden cardiac death due to arrhythmias. Previous studies have reported a 10 years cardiovascular mortality up to 40% in developed countries, due to advanced heart failure or sudden cardiac death. However, the prognosis of dilated cardiomyopathy patients is variable and depends on multiple risk factors. This chapter provides a review of dilated cardiomyopathy with specific focus on the pathophysiological aspects and genetic etiology of the disease

Diagnosis of Cardiac Amyloidosis Using Non-Invasive Technics

Amyloidosis is a rare multiorgan disease defined by a process of irreversible, extracellular accumulation of fibrillar proteins in the tissues, including the heart. Cardiac involvement is seen in most forms of amyloidosis, but it is frequently present and clinically significant in light chain (AL)-amyloidosis as well as transthyretin amyloidosis (ATTR). Cardiac amyloid accumulation leads to a restrictive filling pattern, which must be differentiated from other forms of restrictive and hypertrophic cardiomyopathies due to consequences for the treatment. Evolving knowledge of the disease has led to a definite diagnosis of the cardiac amyloidosis (CA) using non-invasive and low-risk diagnostic features, such as scintigraphy (gamma scan) and cardiovascular magnetic resonance (CMR) imaging using late gadolinium enhancement (LGE) and T1 mapping technics. The availability and diagnostic accuracy of these technics has reduced the need for cardiac biopsy. In the following chapter, we will describe common types of CA, the basic concepts, and updates of non-invasive diagnostic features

Prognostic value of novel imaging parameters derived from standard cardiovascular magnetic resonance in high risk patients with systemic light chain amyloidosis

Background: The differentiated assessment of functional parameters besides morphological changes is essential for the evaluation of prognosis in systemic immunoglobulin light chain (AL) amyloidosis. Methods: Seventy-four subjects with AL amyloidosis and presence of late gadolinium enhancement (LGE) pattern typical for cardiac amyloidosis were analyzed. Long axis strain (LAS) and myocardial contraction fraction (MCF), as well as morphological and functional markers, were measured. The primary endpoint was death, while death and heart transplantation served as a composite secondary endpoint. Results: After a median follow-up of 41 months, 29 out of 74 patients died and 10 received a heart transplant. Left ventricular (LV) functional parameters were reduced in patients, who met the composite endpoint (LV ejection fraction 51% vs. 61%, LAS − 6.9% vs − 10%, GLS − 12% vs − 15% and MCF 42% vs. 69%; p <  0.001 for all). In unadjusted univariate analysis, LAS (HR = 1.05, p <  0.001) and MCF (HR = 0.96, p <  0.001) were associated with reduced transplant-free survival. Kaplan-Meier analyses showed a significantly lower event-free survival in patients with reduced MCF. MCF and LAS performed best to identify high risk patients for secondary endpoint (Log-rank test p <  0.001) in a combined model. Using sequential Cox regression analysis, the addition of LAS and MCF to LV ejection fraction led to a significant increase in the predictive power of the model (χ2 (df = 1) = 28.2, p <  0.001). Conclusions: LAS and MCF as routinely available and robust CMR-derived parameters predict outcome in LGE positive AL amyloidosis. Patients with impaired LV function in combination with reduced LAS and MCF are at the highest risk for death and heart transplantation

Left ventricular long axis strain: a new prognosticator in non-ischemic dilated cardiomyopathy?

Background: Long axis strain (LAS) has been shown to be a fast assessable parameter representing global left ventricular (LV) longitudinal function in cardiovascular magnetic resonance (CMR). However, the prognostic value of LAS in cardiomyopathies with reduced left ventricular ejection fraction (LVEF) has not been evaluated yet. Methods and results: In 146 subjects with non-ischemic dilated cardiomyopathy (NIDCM, LVEF ≤45 %) LAS was assessed retrospectively from standard non-contrast SSFP cine sequences by measuring the distance between the epicardial border of the left ventricular apex and the midpoint of a line connecting the origins of the mitral valve leaflets in end-systole and end-diastole. The final values were calculated according to the strain formula. The primary endpoint of the study was defined as a combination of cardiac death, heart transplantation or aborted sudden cardiac death and occurred in 24 subjects during follow-up. Patients with LAS values > −5 % showed a significant higher rate of cardiac events independent of the presence of late gadolinium enhancement (LGE). The multivariate Cox regression analysis revealed that LVEDV/BSA (HR: 1.01, p  −10 % and the presence of LGE, patients with 3 points had a significantly higher risk for cardiac events than those with 2 or less points. Conclusion: Assessment of long axis function with LAS offers significant incremental information for the prediction of cardiac events in NIDCM and improves risk stratification beyond established CMR parameters

Advanced Imaging in Cardiac Amyloidosis

This review serves as a synopsis of multimodality imaging in cardiac amyloidosis (CA), which is a disease characterized by deposition of misfolded protein fragments in the heart. It emphasizes and summarizes the diagnostic possibilities and their prognostic values. In general, echocardiography is the first diagnostic tool in patients with an identified systemic disease or unclear left ventricular hypertrophy. Several echocardiographic parameters will raise suspicion and lead to further testing. Cardiac magnetic resonance and scintigraphy with bone avid radiotracers are crucial for diagnosis of CA and even enable a distinction between different subtypes. The subject is illuminated with established guidelines and innovative recent publications to further improve early diagnosis of cardiac amyloidosis in light of current treatment options

Risk stratification for 1-year mortality in acute heart failure

BACKGROUND: Simple tools for risk stratification of patients with acute heart failure (AHF) are an unmet clinical need, particularly regarding long-term mortality. METHODS: We prospectively enrolled 610 consecutive patients presenting to the emergency department with AHF. The diagnosis of AHF was adjudicated by two independent cardiologists. The classification and regression tree (CART) analysis was used to develop a simple risk algorithm. This was internally validated by cross-validation. RESULTS: One-year follow-up was complete in all patients (100%). A total of 201 patients (33%) died within 360 days. The CART analysis identified blood urea nitrogen (BUN) and age as the best single predictors of 1-year mortality and patients were categorised to three risk groups: high risk group (BUN /= 86 years) and low risk group (BUN >/= 27.5 mg/dl). The Kaplan-Meier curves showed a significant increase in mortality in the high risk group compared with the lower risk groups (log-rank test p >0.001). The hazard ratio regarding 1-year mortality between patients identified as low and high risk was 2.0 (95% confidence interval, 1.7-2.4), with statistically significant differences between all risk groups (p >0.001). The likelihood-based 95%-confidence set for the age- and the urea-threshold is contained in the rectangular set defined by 25 mg/dl >/= urea threshold >/=30.6 mg/dl and 76 years >/= age threshold >/=96 years. CONCLUSION: These results suggest that AHF patients at low, intermediate and high risk for death within 360 days can be easily identified using patient's demographics and laboratory data obtained at presentation. Application of this simple risk stratification algorithm may help to improve the management of these patients