Cardiovascular magnetic resonance tagging imaging correlates with myocardial dysfunction and T2 mapping in idiopathic dilated cardiomyopathy

Acute clinical presentation of nonischemic cardiomyopathies: early detection by cardiovascular magnetic resonance

Nonischemic cardiomyopathies include a wide range of dilated, hypertrophic and arrhythmogenic heart muscle disorders, not explained by coronary artery disease, hypertension, valvular or congenital heart disease. Advances in medical treatments and the availability of implantable cardioverter defibrillators to prevent sudden cardiac death have allowed a substantial increase in the survival of affected individuals, thus making early diagnosis and tailored treatment mandatory. The characterization of cardiomyopathies has received a great boost from the recent advances in cardiovascular magnetic resonance (CMR) imaging, which, to date, represents the gold standard for noninvasive assessment of cardiac morphology, function and myocardial tissue changes. An acute clinical presentation has been reported in a nonnegligible proportion of patients with nonischemic cardiomyopathies, usually complaining of acute chest pain, worsening dyspnoea or palpitations; 'hot phases' of cardiomyopathies are characterized by a dynamic rise in high-sensitivity troponin, myocardial oedema on CMR, arrhythmic instability, and by an increased long-term risk of adverse remodelling, progression of myocardial fibrosis, heart failure and malignant ventricular arrhythmias. Prompt recognition of 'hot phases' of nonischemic cardiomyopathies is of utmost importance to start an early, individualized treatment in these high-risk patients. On the one hand, CMR represents the gold standard imaging technique to detect early and typical signs of ongoing myocardial remodelling in patients presenting with a 'hot phase' nonischemic cardiomyopathy, including myocardial oedema, perfusion abnormalities and pathological mapping values. On the other hand, CMR allows the differential diagnosis of other acute heart conditions, such as acute coronary syndromes, takotsubo syndrome, myocarditis, pericarditis and sarcoidosis. This review provides a deep overview of standard and novel CMR techniques to detect 'hot phases' of cardiomyopathies, as well as their clinical and prognostic utility.

Cardiovascular magnetic resonance native T2 and T2* quantitative values for cardiomyopathies and heart transplantations: a systematic review and meta-analysis

BACKGROUND

The clinical application of cardiovascular magnetic resonance (CMR) T2 and T2* mapping is currently limited as ranges for healthy and cardiac diseases are poorly defined. In this meta-analysis we aimed to determine the weighted mean of T2 and T2* mapping values in patients with myocardial infarction (MI), heart transplantation, non-ischemic cardiomyopathies (NICM) and hypertension, and the standardized mean difference (SMD) of each population with healthy controls. Additionally, the variation of mapping outcomes between studies was investigated.

METHODS

The PRISMA guidelines were followed after literature searches on PubMed and Embase. Studies reporting CMR T2 or T2* values measured in patients were included. The SMD was calculated using a random effects model and a meta-regression analysis was performed for populations with sufficient published data.

RESULTS

One hundred fifty-four studies, including 13,804 patient and 4392 control measurements, were included. T2 values were higher in patients with MI, heart transplantation, sarcoidosis, systemic lupus erythematosus, amyloidosis, hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM) and myocarditis (SMD of 2.17, 1.05, 0.87, 1.39, 1.62, 1.95, 1.90 and 1.33, respectively, P <  0.01) compared with controls. T2 values in iron overload patients (SMD = - 0.54, P = 0.30) and Anderson-Fabry disease patients (SMD = 0.52, P = 0.17) did both not differ from controls. T2* values were lower in patients with MI and iron overload (SMD of - 1.99 and - 2.39, respectively, P <  0.01) compared with controls. T2* values in HCM patients (SMD = - 0.61, P = 0.22), DCM patients (SMD = - 0.54, P = 0.06) and hypertension patients (SMD = - 1.46, P = 0.10) did not differ from controls. Multiple CMR acquisition and patient demographic factors were assessed as significant covariates, thereby influencing the mapping outcomes and causing variation between studies.

CONCLUSIONS

The clinical utility of T2 and T2* mapping to distinguish affected myocardium in patients with cardiomyopathies or heart transplantation from healthy myocardium seemed to be confirmed based on this meta-analysis. Nevertheless, variation of mapping values between studies complicates comparison with external values and therefore require local healthy reference values to clinically interpret quantitative values. Furthermore, disease differentiation seems limited, since changes in T2 and T2* values of most cardiomyopathies are similar.

Quantitative mechanical dyssynchrony in dilated cardiomyopathy measured by deformable registration algorithm

OBJECTIVES

To investigate the diagnostic value and reproducibility of deformable registration algorithm (DRA)-derived mechanical dyssynchrony parameters in dilated cardiomyopathy (DCM) patients.

METHODS

The present study included 80 DCM patients (40 with normal QRS duration (NQRS-DCM); 40 with left bundle branch block (LBBB-DCM)) and 20 healthy volunteers. The balanced steady-state free-precession (bSSFP) cine images were acquired using a 3.0T scanner. Mechanical dyssynchrony parameters were calculated based on DRA-derived segmental strain, including uniformity ratio estimate (URE) and standard derivation of time-to-peak (T2Psd) parameters in circumferential, radial, and longitudinal orientations.

RESULTS

DCM patients showed significant mechanical dyssynchrony reflected by both URE and T2Psd parameters compared with controls. Among DCM patients, LBBB-DCM showed decreased CURE (0.78 ± 0.21 vs. 0.93 ± 0.05, p < 0.001) and RURE (0.69 ± 0.14 vs. 0.83 ± 0.15, p = 0.001), and increased T2Psd-Ecc (median with interquartile range, 94.1 (54.4-123.2) ms vs. 63.7 (44.9-80.4) ms, p = 0.003) and T2Psd-Err (91.1 (61.1-103.2) ms vs. 62.3 (46.3-104.5) ms, p = 0.041) compared with NQRS-DCM patients. CURE showed a strong correlation with QRS duration (r = - 0.54, p < 0.001), with maximum AUC (0.791) to differentiate LBBB-DCM from NQRS-DCM patients. Improved intra- and inter-observer reproducibility was found using URE indices (coefficient of variation (CoV), 1.20-3.17%) than T2Psd parameters (CoV, 15.28-41.18%).

CONCLUSIONS

The DRA-based CURE showed significant correlation with QRS duration and the highest discriminatory value between LBBB-DCM and NQRS-DCM patients. URE indices showed greater reproducibility compared with T2Psd parameters for assessing myocardial dyssynchrony in DCM patients.

KEY POINTS

• The strain analyses based on DRA suggested that DCM patients have varying degrees of mechanical dyssynchrony and there is a significant difference from normal controls. • CURE showed the strongest correlation with QRS duration and was the best parameter for differentiating DCM patients with normal QRS duration from patients with LBBB, and with normal controls. • URE indices showed improved reproducibility compared with T2Psd parameters in all three orientations (circumferential, radial, and longitudinal).

Myocardial T1 and T2 Mapping: Techniques and Clinical Applications

Cardiac magnetic resonance (CMR) imaging is widely used in various medical fields related to cardiovascular diseases. Rapid technological innovations in magnetic resonance imaging in recent times have resulted in the development of new techniques for CMR imaging. T1 and T2 image mapping sequences enable the direct quantification of T1, T2, and extracellular volume fraction (ECV) values of the myocardium, leading to the progressive integration of these sequences into routine CMR settings. Currently, T1, T2, and ECV values are being recognized as not only robust biomarkers for diagnosis of cardiomyopathies, but also predictive factors for treatment monitoring and prognosis. In this study, we have reviewed various T1 and T2 mapping sequence techniques and their clinical applications.

Estimation of Myocardial Strain and Contraction Phase From Cine MRI Using Variational Data Assimilation

This paper presents a new method to estimate left ventricle deformations using variational data assimilation that combines image observations from cine MRI and a dynamic evolution model of the heart. The main contribution of the model is that it embeds parameters modeling the contraction / relaxation process. It estimates myocardial motion and contraction parameters simultaneously, providing accurate complementary information for diagnosis. The method was applied to synthetic datasets with known ground truth motion and to 47 patients MRI datasets acquired at three slice locations (base, mid-ventricle and apex). Radial and circumferential strain components were compared to those obtained with a reference tag tracking software, exhibiting good agreement with intraclass correlation coefficients (ICC) above 0.8. Results were also evaluated against wall motion score indices used to assess cardiac kinetics in clinical practice. The assimilation process overcame issues caused by temporal artifacts as a result of the dynamic model, compared to using the observation term alone. Moreover we found that the new dynamic model, consisting of a piecewise transport model acting independently on systole and diastole performed better than the standard continuous transport model, which oversmooths temporal variations. Estimated strain and contraction parameters significantly correlated to clinical scores, making them promising features for diagnosing not only hypokinesia but also dyskinesia.

Inherited Structural Heart Diseases With Potential Atrial Fibrillation Occurrence

Inherited cardiac diseases inducing structural remodeling of the myocardium sometimes develop arrhythmias of various kinds. Among these rhythm disturbances, atrial fibrillation is well known to frequently worsen the prognosis of the primary disorder by increasing morbidity and mortality, especially because of a higher rate of heart failure. In this manuscript, we have reviewed the literature on the most important inherited structural cardiac diseases in whose clinical history atrial fibrillation may occur fairly often.

T1 and T2 mapping for early diagnosis of dilated non-ischaemic cardiomyopathy in middle-aged patients and differentiation from normal physiological adaptation

AIMS

The differential diagnosis of patients with early non-ischaemic dilated cardiomyopathy (DCM) and those with physiological adaptation to exercise ('athlete's heart') may be difficult as many of the morphological adaptations are shared in the two conditions. Increased physical fitness is becoming more common in later adulthood, a group in whom there may be even more diagnostic difficulty. We hypothesized that tissue characterization using cardiovascular magnetic resonance (CMR) T1 and T2 mapping would be able to differentiate between patients with left ventricular (LV) dilatation due to early DCM and exercisers.

METHODS AND RESULTS

Fifty-eight middle-aged males [21 healthy controls, 21 males with a history of aerobic exercise and LV ejection fraction (LVEF) 45-55%, and 16 patients with DCM and LVEF 45-55%] underwent a CMR protocol including T1 and T2 mapping and calculation of extracellular volume (ECV) using a 1.5 T MRI scanner. Native T1, ECV, and T2 relaxation times were significantly increased in DCM patients compared with controls (native T1 1017 ± 42 vs. 952 ± 31 ms, P < 0.001; ECV 31.2 ± 4.1 vs. 26.2 ± 2.9%, P = 0.003; T2 55.9 ± 4.4 vs. 52.9 ± 3.3 ms, P = 0.05) and exercisers (native T1 957 ± 32 ms, P < 0.001; ECV 26.3 ± 3.6%, P = 0.004; T2 52.8 ± 3.2 ms, P = 0.042). Using multivariable logistic regression, native T1 gave the best differentiation between exercisers and sedentary patients with early DCM (area under the curve 0.91).

CONCLUSION

T1 and T2 mapping are potentially useful tools for differentiating between athlete's heart and patients with early DCM, and could be used whenever differentiation between these two phenotypes is inconclusive using standard imaging techniques.