Cardiovascular magnetic resonance imaging to assess myocardial fibrosis in valvular heart disease

Role of Cardiac Magnetic Resonance Imaging in Valvular Heart Disease: Diagnosis, Assessment, and Management

PURPOSE OF REVIEW

This article will review the current techniques in cardiac magnetic resonance imaging (CMR) for diagnosing and assessing primary valvular heart disease.

RECENT FINDINGS

The recent advancements in CMR have led to an increased role of this modality for qualifying and quantifying various native valve diseases. Phase-contrast velocity encoded imaging is a well-established technique that can be used to quantify aortic and pulmonic flow. This technique, combined with the improved ability for CMR to obtain accurate left and right ventricular volumetrics, has allowed for increased accuracy and reproducibility in assessing valvular dysfunction. Advancements in CMR technology also allows for improved spatial and temporal resolution imaging of various valves and their regurgitant or stenotic jets. Therefore, CMR can be a powerful tool in evaluation of native valvular heart disease. The role of CMR in assessing valvular heart disease is growing and being recognized in recent guidelines. CMR has the ability to assess valve morphology along with qualifying and quantifying valvular disease. In addition, the ability to obtain accurate volumetric measurements may improve more precise management strategies and may lead to improvements in mortality and morbidity.

Sudden Cardiac Death Risk Prediction: The Role of Cardiac Magnetic Resonance Imaging

Sudden cardiac death (SCD) accounts for more than 4 million global deaths per year. While it is most commonly caused by coronary artery disease, a final common pathway of ventricular arrhythmias is shared by different etiologies. The most effective primary and secondary prevention strategy is an implantable cardioverter-defibrillator (ICD). The decision to implant an ICD for primary prevention is largely based on a left ventricular ejection fraction ≤ 35%, but this criterion in isolation is neither sensitive nor specific. Novel imaging parameters hold promise to improve ICD candidate selection. Cardiac magnetic resonance (CMR) imaging is a powerful and versatile technique, with the ability to comprehensively assess cardiac structure and function. A range of variables based on CMR techniques (late gadolinium enhancement, T₁ mapping, T₂* relaxometry, deformation imaging) have been associated with ventricular arrhythmias and SCD risk. The role of CMR in the estimation of ventricular arrhythmias and SCD risk in coronary artery disease, nonischemic cardiomyopathies, cardiac transplant, iron-overload cardiomyopathy and valvular heart disease is reviewed in this article. Prospective, randomized trials and standardization of CMR techniques are required before its routine use can be recommended for guiding SCD prevention strategies.

Specific biomarkers of myocardial inflammation and remodeling processes as predictors of mortality in high-risk patients undergoing percutaneous mitral valve repair (MitraClip)

BACKGROUND

Specific matrix metalloproteinases (MMP-2, MMP-9) and inflammatory biomarkers (hsCRP, IL-6) were found to be consistently up-regulated in severe mitral valve regurgitation (MR) and are associated with mortality in heart failure patients. The aim of the present study was to examine the prognostic value of biomarkers of cardiac inflammation and remodeling processes in predicting mortality in patients with MR undergoing percutaneous mitral valve repair (PMVR).

HYPOTHESIS

We hypothesize that increased cardiac inflammation and extracellular matrix turnover is predictive for mortality in patients with severe mitral regurgitation undergoing MitraClip.

METHODS

A total of 210 consecutive patients undergoing PMVR were included. PMVR was performed according to standard clinical practice. Venous blood samples for biomarker analyses were collected prior to and 6 months after PMVR. Physiological parameters, medication use, safety events, and all-cause mortality were followed over 12 months.

RESULTS

PMVR was performed successfully in all patients. Twelve months after PMVR there was an effective reduction in the severity of MR (P < 0.001), and an improvement in New York Heart Association class (P < 0.01) was documented. Elevated inflammatory biomarkers (AUC_hsCRP : 0.738 [IQR, 0.626-0.849], P = 0.001; AUC_IL-6 : 0.811 [IQR, 0.724-0.899], P = 0.001) and biomarkers reflecting cardiac remodeling processes (AUC_MMP-2 : 0.723 [IQR, 0.641-0.804], P = 0.001; AUC_MMP-9 : 0.618 [IQR, 0.534-0.701], P = 0.01) were predictors of adverse cardiac events and mortality in patients with congestive heart failure undergoing PMVR.

CONCLUSIONS

The present study is the first to identify biomarkers reflecting inflammation (hsCRP, IL-6) and cardiac remodeling processes (MMP-2, MMP-9) as predictors of mortality in high-risk patients undergoing PMVR.

Imaging the Cardiac Extracellular Matrix

Cardiovascular disease is the global leading cause of death. One route to address this problem is using biomedical imaging to measure the molecules and structures that surround cardiac cells. This cellular microenvironment, known as the cardiac extracellular matrix, changes in composition and organization during most cardiac diseases and in response to many cardiac treatments. Measuring these changes with biomedical imaging can aid in understanding, diagnosing, and treating heart disease. This chapter supports those efforts by reviewing representative methods for imaging the cardiac extracellular matrix. It first describes the major biological targets of ECM imaging, including the primary imaging target of fibrillar collagen. Then it discusses the imaging methods, describing their current capabilities and limitations. It categorizes the imaging methods into two main categories: organ-scale noninvasive methods and cellular-scale invasive methods. Noninvasive methods can be used on patients, but only a few are clinically available, and others require further development to be used in the clinic. Invasive methods are the most established and can measure a variety of properties, but they cannot be used on live patients. Finally, the chapter concludes with a perspective on future directions and applications of biomedical imaging technologies.