AimsContemporary adjuvant treatment for early breast cancer is associated with improved survival but at the cost of increased risk of cardiotoxicity and cardiac dysfunction. We tested the hypothesis that concomitant therapy with the angiotensin receptor blocker candesartan or the β-blocker metoprolol will alleviate the decline in left ventricular ejection fraction (LVEF) associated with adjuvant, anthracycline-containing regimens with or without trastuzumab and radiation.Methods and resultsIn a 2 × 2 factorial, randomized, placebo-controlled, double-blind trial, we assigned 130 adult women with early breast cancer and no serious co-morbidity to the angiotensin receptor blocker candesartan cilexetil, the β-blocker metoprolol succinate, or matching placebos in parallel with adjuvant anticancer therapy. The primary outcome measure was change in LVEF by cardiac magnetic resonance imaging. A priori, a change of 5 percentage points was considered clinically important. There was no interaction between candesartan and metoprolol treatments (P = 0.530). The overall decline in LVEF was 2.6 (95% CI 1.5, 3.8) percentage points in the placebo group and 0.8 (95% CI −0.4, 1.9) in the candesartan group in the intention-to-treat analysis (P-value for between-group difference: 0.026). No effect of metoprolol on the overall decline in LVEF was observed.ConclusionIn patients treated for early breast cancer with adjuvant anthracycline-containing regimens with or without trastuzumab and radiation, concomitant treatment with candesartan provides protection against early decline in global left ventricular function.

Body composition, fat distribution and insulin sensitivity improved following training in sedentary middle-aged men with and without dysglycemia.

Purpose: To investigate the T2 decay in prostate tissue for multiexponentiality and to assess how the biexponential model relates to established T2W contrast. Materials and Methods:A 32-echo spin-echo sequence was performed on 16 volunteers. Six single-voxel decay curves were sampled from each prostate. Prediction accuracies were assessed by jackknifing for the mono-, bi-, and triexponential models. The differences were evaluated by cross-validated analysis of variance (CVANOVA). Multiple linear regression was performed to assess the relation between parameters in the biexponential model and the contrast in T2W images.Results: Mono-, bi-, and triexponential models were preferred in 8 (10%), 72 (86%), and 4 (5%) cases, respectively. The biexponential short T2 was 64 msec (range 43 to 92 msec) and the long T2 was 490 msec (range 161 to 1319 msec). The fitted signal fraction, f, of the long T2 component was 27% (range 3% to 80%). The adjusted R 2 was 75.1% for the full regression model and decreased by 0.9%, 1.3%, and 39.2% when short T2, long T2, and f were removed from the model, respectively. Conclusion:Prostatic T2 decay was, in general, biexponential. The differences between the T2 components were large enough for accurate quantification. The T2W image contrast was primarily predicted by the biexponential signal fractions.

Muscle lipid stores and insulin sensitivity have a recognized association although the mechanism remains unclear. We investigated how a 12‐week supervised combined endurance and strength exercise intervention influenced muscle lipid stores in sedentary overweight dysglycemic subjects and normal weight control subjects (n = 18). Muscle lipid stores were measured by magnetic resonance spectroscopy (MRS), electron microscopy (EM) point counting, and direct EM lipid droplet measurements of subsarcolemmal (SS) and intramyofibrillar (IMF) regions, and indirectly, by deep sequencing and real‐time PCR of mRNA of lipid droplet‐associated proteins. Insulin sensitivity and VO2max increased significantly in both groups after 12 weeks of training. Muscle lipid stores were reduced according to MRS at baseline before and after the intervention, whereas EM point counting showed no change in LD stores post exercise, indicating a reduction in muscle adipocytes. Large‐scale EM quantification of LD parameters of the subsarcolemmal LD population demonstrated reductions in LD density and LD diameters. Lipid droplet volume in the subsarcolemmal LD population was reduced by ~80%, in both groups, while IMF LD volume was unchanged. Interestingly, the lipid droplet diameter (n = 10 958) distribution was skewed, with a lack of small diameter lipid droplets (smaller than ~200 nm), both in the SS and IMF regions. Our results show that the SS LD lipid store was sensitive to training, whereas the dominant IMF LD lipid store was not. Thus, net muscle lipid stores can be an insufficient measure for the effects of training.

Background Changes in brain stiffness can be an important biomarker for neurological disease. Magnetic resonance elastography (MRE) quantifies tissue stiffness, but the results vary between acquisition and reconstruction methods. Purpose To measure MRE repeatability and estimate the effect of different reconstruction methods and varying data quality on estimated brain stiffness. Study Type Prospective. Subjects Fifteen healthy subjects. Field Strength/Sequence 3T MRI, gradient‐echo elastography sequence with a 50 Hz vibration frequency. Assessment Imaging was performed twice in each subject. Images were reconstructed using a curl‐based and a finite‐element‐model (FEM)‐based method. Stiffness was measured in the whole brain, in white matter, and in four cortical and four deep gray matter regions. Repeatability coefficients (RC), intraclass correlation coefficients (ICC), and coefficients of variation (CV) were calculated. MRE data quality was quantified by the ratio between shear waves and compressional waves. Statistical Tests Median values with range are presented. Reconstruction methods were compared using paired Wilcoxon signed‐rank tests, and Spearman's rank correlation was calculated between MRE data quality and stiffness. Holm–Bonferroni corrections were employed to adjust for multiple comparisons. Results In the whole brain, CV was 4.3% and 3.8% for the curl and the FEM reconstruction, respectively, with 4.0–12.8% for subregions. Whole‐brain ICC was 0.60–0.74, ranging from 0.20 to 0.89 in different regions. RC for the whole brain was 0.14 kPa and 0.17 kPa for the curl and FEM methods, respectively. FEM reconstruction resulted in 39% higher stiffness than the curl reconstruction (P < 0.05). MRE data quality, defined as shear‐compression wave ratio, was higher in peripheral regions than in central regions of the brain (P < 0.05). No significant correlations were observed between MRE data quality and stiffness estimates. Data Conclusion MRE of the human brain is a robust technique in terms of repeatability. Caution is warranted when comparing stiffness values obtained with different techniques. Level of Evidence 1 Technical Efficacy Stage 1