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Background CMR has become an increasingly valuable tool in the diagnosis and risk stratification of patients with nonischaemic dilated cardiomyopathy (DCM) due to its assessment of left ventricular systolic function and tissue characterization ability and may have a role in early identification of cardiomyopathy. Some of the changes associated with early DCM (left ventricular dilatation and mild reduction in LV ejection fraction) can also occur in patients with a history of significant aerobic exercise, known as “athlete’s heart”. Using standard echocardiographic and CMR parameters it may be difficult to differentiate between DCM and normal physiological athletic adaptation, which may have significant implications for the patient. We hypothesized that use of CMR tagging and T1 and T2 mapping might be useful to differentiate between patients with left ventricular dilatation due to DCM and athlete’s heart.

Background Left ventricular ejection fraction (LVEF) is powerful predictor of mortality and is used to guide treatment decisions. It is however subject to limitations, particularly when measured using echocardiography, as is most commonly done. Additionally, many major cardiovascular events occur in patients typically adjudged to be at lower risk using echocardiography (LVEF >35%). Assessment of myocardial deformation (strain) using tagging has the potential to overcome some of the limitations of LVEF. The value of global circumferential strain (GCS) measured by CMR tagging in patients with suspected cardiac disease has not been fully explored despite it being considered as the non-invasive gold standard method of assessment of LV deformation. We aimed to assess the incremental prognostic value of GCS measured using tagging for the prediction of major adverse cardiovascular events in addition to baseline clinical characteristics, LVEF and late gadolinium enhancement (LGE) in an unselected cohort of patients.

Background In patients with myocardial infarction (MI), an important factor in determining the long-term prognosis is the degree of regional contractile dysfunction. DENSE (Displacement ENcoding with Stimulated Echoes) is a technique which allows quantification of myocardial strain[1], and which has been shown to be more sensitive to the presence of late gadolinium enhancement (LGE) than wall thickening measured from cine images[2]. The aim of this study was to further investigate the performance of DENSE for the diagnosis and assessment of myocardial infarction. Methods 50 male patients (age 56 ± 10 years) within 7 days of MI and 30 healthy male controls (age 45 ± 18 years) underwent CMR on a 1.5T Siemens Avanto. The protocol included DENSE and LGE (patients only) obtained from a single mid-ventricular short-axis slice, which was divided into 6 segments for analysis. The percentage of each segment which contained LGE was calculated using a threshold of mean+5SD of remote myocardium intensity. DENSE images were analysed to obtain a value for peak circumferential strain (Ecc). The following analyses were performed: (i) intra- and inter-operator and inter-scan repeatability, (ii) sensitivity and specificity for the detection of LGE, using a reference range established from control data, and ROC analysis and (iii) the ability to distinguish between non-infarcted, 50% infarction, and between remote, adjacent and infarcted segments. Results along with the percentages of segments correctly identified when grouped according to extent of LGE. The reference range was calculated to be (-11.8, -27.0). Inter-operator repeatability was assessed using Levene’s test (variance) and a paired t-test (mean), and no statistically significant differences were found. A paired t-test found no statistically significant difference for inter-scan repeatability. The results of (iii) are illustrated in Figure 1. Comparisons between categories were performed using a one-way ANOVA with Tukey’s post-hoc test. Conclusions DENSE can be successfully applied in a clinical setting, and provides repeatable results. The sensitivity and specificity of the technique for detecting the presence of LGE are good, and the number of segments with LGE correctly identified increases as the extent of LGE increases. Peak