BackgroundMuscle wasting can be accelerated by chronic diseases such as heart failure and is one of the major causes of disability, morbidity, and mortality in this population. We aimed to investigate the incidence of muscle wasting and its associated factors in dilated cardiomyopathy patients younger than 55 years of age.MethodsBetween April 2014 and December 2015, all symptomatic patients with a diagnosis of non‐ischaemic dilated cardiomyopathy who were referred to heart failure clinic were included in our study.Dual energy X‐ray absorptiometry was used to evaluate body composition and identify muscle wasting. Muscle mass was calculated as the ratio of an individual's total lean mass of legs and arms (also called appendicular skeletal muscle) to their squared height (kg/m2). The muscle mass values of less than 5.45 kg/m2 for women and 7.26 kg/m2 for men were considered low.ResultsA total of 55 patients (32 male) were included. The mean (standard deviation) of age was 37.3 (10.1) years, and the mean of left ventricular ejection fraction was 21.4%. Most of the patients were in the New York Heart Association classes of II and II–III. Twenty‐six patients (47.3%) met criteria for muscle wasting. Patients with muscle wasting had lower left ventricular ejection fraction, lower 6‐min walk distance, and higher New York Heart Association function class and hospitalization rate.ConclusionsWe concluded that muscle wasting might be present in younger patients with heart failure, particularly in those who are in worse clinical condition.

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Background:The aim of this study was to assess the robustness of cardiac SPECT radiomics features against changes in imaging settings including acquisition and reconstruction settings. Methods: Four scanners were used to acquire SPECT scans of a cardiac phantom with 5mCi of 99m Tc. The effects of different image acquisition and reconstruction settings including the Number of View, View Matrix Size, attenuation correction, image reconstruction algorithm, number of iterations, number of subsets, type of filter, full width at half maximum (FWHM) of Gaussian filter, Butterworth filter order, and Butterworth filter cut-off were studied. In total 5263 different images were reconstructed. Eighty-seven radiomic features including first, second, and high order textures were extracted from images. To assess reproducibility and repeatability the coefficient of variation (COV) was used for each image feature over the different imaging settings. Result: IDMN and IDN features from GLCM, RP from GLRLM, ZE from GLSZM, and DE from GLDM feature sets were the only features that were the most reproducible (COV ≤ 5%) against changes in all imaging settings. In addition, the IDMN feature from GLCM, LALGLE, SALGLE and LGLZE from GLSZM, and SDLGLE from GLDM feature sets were the features that were less reproducible (COV>20 %) against changes in all imaging settings. Matrix size has the greatest impact on feature variability as most of features are not repeatable and 82.76% of them had (COV>20 %). Conclusion: Repeatability and reproducibility of SPECT/CT radiomics texture features in different imaging settings is feature-dependent, and different image acquisitions and reconstructions have different effects on radiomics texture features. Low COV radiomics features could be consider for further clinical studies.

Despite a good correlation between QGS and ECTb software packages, different normal cut-off values of PSD and PHB should be defined for each software package. There was only a modest correlation between phase analysis of gated-SPECT MPI and TDI data, especially in the population of heart failure patients with both narrow and wide QRS complex.