Metabolism remodeling has been recognized as an early event following cardiac pressure overload. However, its temporal association with ventricular hypertrophy has not been confirmed. Moreover, whether trimetazidine could favorably affect this process also needs to be determined. The aim of the study was to explore the temporal changes of myocardial metabolism remodeling following pressure-overload induced ventricular hypertrophy and the potential favorable effect of trimetazidine on myocardial metabolism remodeling.A rat model of abdominal aortic constriction (AAC)-induced cardiac pressure overload was induced. These rats were grouped as the AAC (no treatment) or TMZ group according to whether oral trimetazidine  was administered. Changes in cardiac structures were sequentially evaluated via echocardiography. The myocardial ADP/ATP ratio was determined to reflect the metabolic status, and changes in serum neuropeptide Y systems were evaluated.Myocardial metabolic disorder was acutely induced as evidenced by an increased ADP/ATP ratio within 7 days of AAC before the morphological changes in the myocardium, accompanied by up-regulation of serum oxidative stress markers and expression of fetal genes related to hypertrophy. Moreover, the serum NPY and myocardial NPY-1R, 2R, and 5R levels were increased within the acute phase of AAC-induced cardiac pressure overload. Pretreatment with TMZ could partly attenuate myocardial energy metabolic homeostasis, decrease serum levels of oxidative stress markers, attenuate the induction of hypertrophy-related myocardial fetal genes, inhibit the up-regulation of serum NPY levels, and further increase the myocardial expression of NPY receptors.Cardiac metabolic remodeling is an early change in the myocardium before the presence of typical morphological ventricular remodeling following cardiac pressure overload, and pretreatment with TMZ may at least partly reverse the acute metabolic disturbance, perhaps via regulation of the NPY system. Despite significance advances in therapeutic strategies against congestive heart failure (CHF) during the past few decades, CHF remains one of the most serious diseases, contributing to substantial mortality and morbidity throughout the world , 2. VentNeuropeptide Y (NPY) has been recognized as a key regulator of energy metabolism via its binding and signaling with its receptors (NPY-R) . PreviouBased on the evidence presented above, we hypothesized that myocardial metabolic disturbance may be an early event before the morphological changes of myocardial hypertrophy, and changes in the NPY system may be involved. Moreover, pretreatment with TMZ may attenuate the metabolic disturbance of the myocardium before the morphological changes of ventricular hypertrophy can be detected, and these metabolic benefits of TMZ may involve the regulation of serum and myocardial NPY system. Therefore, in this study, we applied a rat model of short-term (within 7 days) abdominal aortic constriction (ACC)-related cardiac pressure overload but without significant morphological changes of myocardial hypertrophy, to systematically observe the changes of myocardial energy metabolism, potential benefits of TMZ pretreatment, and the roles of the NPY system involved.The current study was performed in accordance with the Guide for the Care and Use of Laboratory Animals published by the US National Institutes of Health . The experiments protocols were approved ahead of performance by the Committee on Ethics of Animal Experiments of Guangzhou Medical University.Thirty-eight male Wistar rats, weighing 60 ± 10 g, were purchased from the Animal Experimental Center of the Southern Medical University. Rats were given free access to food and water as needed, housed in a stable space with the room temperature at 22 °C, and maintained on a 12-h light/dark cycle for 7 days before the ACC procedure.n =12), in which the surgical procedure of ACC was performed in the same way except for ligation of the abdominal aorta; (2) the AAC group (n = 13), in which AAC was performed by ligation of the abdominal aorta 5 mm above the branching of the left renal artery to induce pressure overload of the heart, as described previously [n = 13), in which the oral administration of TMZ  was performed before the surgical procedure for AAC-induced cardiac pressure overload. Briefly, all surgical procedures were performed after the rats were well anesthetized with intraperitoneal sodium pentobarbital (45 ml/kg). The abdominal aorta, proximal to the left renal artery was exposed and separated from the vena cava. A 2-0 silk suture was tied beside the aorta between the branches of the celiac and the anterior mesenteric arteries, using a blunt 24 G probe with the external diameter of 0.55 mm. After the above procedure, 1 ml saline was administered in the peritoneal cavity of each rat to replenish of the loss of the fluid during the procedure. Then, the abdominal wall was closed and the skin was sutured. The rats in the sham group received the same procedure expect that the silk suture around the aorta was pulled through and not tied. Ampicillin  was injected once daily for 3 days after surgery to prevent infection, and all rats were placed on a warm pad for recovery after the surgery. Overall, one rat from the AAC group and one rat from the TMZ group died from acute heart failure after the surgical procedure. Twelve rats in each group survived the surgical procedures, and these rats within each group were further divided in to two groups (6 rats in each for the different observation periods of 2 and 7 days).These rats were randomized to three groups: (1) the sham group  by an experienced investigator who was blinded to the treatment groups. Measurements were recorded as the mean of at least three consecutive cardiac cycles. The parameters recorded included interventricular septal thickness at end diastole (IVSd), left ventricular posterior wall thickness at end diastole (LVPWd), left ventricular end-diastolic dimension (LVEDD), left ventricular end-systolic dimension (LVESD), left ventricular factional shortening (LVFS), and left ventricular ejection fraction (LVEF).After echocardiologic examination, blood samples of rats from each group were obtained via intubation of the carotid artery. Immediately, blood samples were centrifuged at 12,000 g for 10 min at 4 °C, and then the supernatant was collected for measurement at −20 °C. Serum levels of NPY were measured using a commercially available enzyme immunoassay (EIA) kit , and the experimental procedures were performed according to the manufacturers’ procedures. Similarly, the serum level of malonaldehyde (MDA) and serum superoxide dismutase (SOD) activity were evaluated using a suite of commercial kits, in accordance with the manufacturer’s instructions .After blood sampling, the rats were sacrificed, and hearts from rats in each group were excised. The heart weight (HW) was obtained as well as the weight of the left ventricle (LVW). Subsequently, the ratio of HW to body weight (BW) (HW/BW) was calculated. After measurement, the left ventricle sample was excised, rinsed with ice-cold saline, and dried with blotting paper. Next, the myocardial sample was placed in a microtube, flash frozen in liquid nitrogen, and finally stored at −80 °C for use in subsequent molecular biological experiments.Some myocardial tissue samples were fixed in 4% formaldehyde and embedded in paraffin. These tissues were then sectioned at 5 μm and stained with hematoxylin and eosin (HE). The cell surface area (CAS) of cardiomyocytes was then measured and analyzed with IPP6.0 Software . At least 100 cells were selected for analysis from each section of the myocardial tissue.To assess the energy status of the myocardial tissue, an ADP/ATP ratio assay was performed using the ApoSENSOR™ ADP/ATP Ratio Assay Kit  according to the manufacturer’s instructions.Total RNA from myocardial tissue samples of rats in each group were extracted using Trizol reagent  and reverse transcribed into cDNA  for subsequent analysis of the mRNA levels of myocardial hypertrophy-related genes including atrial natriuretic factor (ANF) and β myosin heavy chain (MHC-β), as well as NPY-1R, 2R, and 5R. Briefly, 1 μg of total RNA was reverse transcribed using 2 μg of random primers and Moloney murine leukemia virus reverse transcriptase according to the manufacturer’s protocol (Advantage RT-for-PCR kit). We used a One-Step system  to perform the real-time PCR analysis. The sequences of the primers for the genes analyzed are listed in Table Total proteins in myocardial tissue samples were ground and homogenized with a protein lysis solution . Briefly, myocardium form the LV was frozen in liquid nitrogen and then homogenized in phosphate-buffered saline (PBS) with a protease inhibitor cocktail  using a tissue grinder. Homogenates were centrifuged at 14,000 rpm for 15 min at 4 °C. Nuclear and cytoplasmic proteins were separated according to the protocol described in the Nuclear and Cytoplasmic Extraction Kit . Supernatants were collected and assayed for total protein using the BCA method . Equal amounts of protein (125 μg) were resolved on 10% Tris-glycine sodium dodecyl sulphate (SDS) polyacrylamide gels. Protein bands were blotted onto nitrocellulose membranes. After blocking in 5% dried milk in Tris-buffered saline containing Tween-20 for 1 h at room temperature, membranes were incubated for 24 h at 4 °C with one of the following antibodies: anti-NPY-1R polyclonal antibody , anti-NPY-2R (D42) pAb , anti-NPY-5R (M264) pAb (Bioworld), and anti GAPDH (14C10) Rabbit mAb  to detect the proteins levels. Membranes were incubated for 1 h at room temperature with horseradish peroxidase-conjugated donkey anti-rabbit immunoglobulin . Peroxidase labeling was detected using the enhanced chemiluminescence Western blotting detection system  and analyzed by densitometry. The optical density values were normalized to that of GAPDH.p < 0.05 was considered to be statistically significant.Statistical analyses were performed using SPSS 11.0 . The results are reported as mean ± standard deviation (SD). Differences were analyzed for significance by one-way or two-way analysis of variance (ANOVA), and To observe the acute impact of pressure overload on cardiac hypertrophy and cardiac function, we measured the dimensions of the left ventricle and cardiac systolic function via echocardiography. The results of the echocardiographic examination showed that the parameters of left ventricular dimensions, such as IVSd, LVPWd, LVEDD, and LVESD, as well as the indices of cardiac systolic function, including LVFS and LVEF, were not significantly different between the rats from the sham and AAC groups at 2 or 7 days after AAC Table . These rp < 0.05, Fig. p < 0.05, Fig. Up-regulated expression of fetal genes, such as ANF and MHC-β, has been recognized as an important feature of the pathogenesis of myocardial hypertrophy . Therefop < 0.05, Fig. p < 0.05, Fig. p < 0.05, Fig. Previous studies confirmed that the ratio of ADP/ATP is an index of energy metabolism in the myocardium, and disturbance of cardiac energy biogenesis is often associated with an increased ADP/ATP . In thisp < 0.05, Fig. p < 0.05, Fig. p < 0.05, Fig. p < 0.05, Fig. p > 0.05, Fig. The results of early studies indicated that NPY is an important neurohormonal factor that may function as a key regulator of energy metabolism . In viewOur study in a rat model of AAC-induced cardiac pressure overload revealed that myocardial energy metabolic disorder was acutely induced within 1 week after AAC, which was before the typical morphologic changes of ventricular hypertrophy occurred. Moreover, disturbance of myocardial energy metabolism was accompanied by up-regulation of serum levels of oxidative stress markers and expression of myocardial fetal genes related to ventricular hypertrophy. Interestingly, the serum level of NPY and myocardial mRNA and protein levels of NPY-1R, 2R, and 5R also were increased within the acute phase of AAC-induced cardiac pressure overload. More importantly, pretreatment with TMZ could partly attenuate myocardial energy metabolic disturbance, decrease serum levels of oxidative stress markers, attenuate the induction of hypertrophy-related myocardial fetal genes, inhibit the up-regulation of serum NPY levels, and further increase the myocardial expression of NPY receptors. These results confirmed previous findings that energy metabolic disorders may occur prior to typical morphological changes of ventricular hypertrophy following cardiac pressure overload, suggesting a potential pathophysiologic process of metabolic remodeling before myocardial remodeling begins. Moreover, our results for the first time suggest that pretreatment with TMZ, a medication known for its benefits in cardiac energy metabolism, may attenuate the early energy metabolic disturbance of the myocardium during the acute phase of AAC-induced cardiac pressure overload. With respect to the mechanisms underlying the energy remodeling following AAC, we found that changes in serum NPY and myocardial NPY receptor levels may be involved, and TMZ may exert its beneficial effect via regulation of the NPY system. These results highlight the importance of cardiac metabolic remodeling as an early change in the myocardium before the presence of typical morphological ventricular remodeling and suggest that early treatment with TMZ may attenuate the disturbance.Early studies revealed that disturbance of myocardial energy metabolism, which typically presents as an increased ratio of cellular ADP/ATP, plays important roles in the pathogenesis of CHF , 9. AlthIn view of the fact that TMZ may function to optimize myocardial energy metabolism, we further evaluated whether pretreatment with TMZ could attenuate the metabolism dysfunction during the acute phase of AAC. We found that TMZ not only significantly reversed the changes in myocardial ADP/ATP, but also reduced the serum levels of oxidative stress markers and the myocardial expression of up-regulated fetal genes related to hypertrophy. These results suggest that TMZ may effectively attenuate the metabolic disorder and therefore subsequently inhibit myocardial hypertrophy. Our results are supported by the findings of Liu et al., which showed that TMZ can inhibit myocardial fibrosis, a characterized feature of ventricular remodeling , as wellPrevious studies have suggested that NPY is a potential regulator of energy homeostasis, but whether it is an important regulator of metabolic remodeling during the acute phase of AAC-induced cardiac pressure overload has not been determined. In this study, we found that serum NPY was immediately induced by 2 days after AAC, as was myocardial expression of the NPY receptors, suggesting that the NPY system may be involved in the process of early energy disturbance of the myocardium. Previous studies in patients with end stage renal disease indicated that elevated NPY is independently associated with LV concentric hypertrophy and systolic dysfunction . MoreoveOur study has limitations that should be considered when interpreting the results. First, because our study was designed to explore the temporal changes in myocardial metabolism remodeling following pressure-overload induced ventricular hypertrophy and the potential favorable effect of TMZ on myocardial metabolism remodeling, we are most interested in the changes in metabolism-related parameters before significant morphological myocardial hypertrophy. Therefore, we chose 7 days of AAC as the main exposure factor. The changes in myocardial metabolism remodeling and potential effects of TMZ after 7 days of AAC should be evaluated in further studies. Moreover, myocardial ADP/ATP, although an important index of myocardial energy status, was not sufficient to reflect the metabolic status of the myocardium following acute pressure overload. Changes in many other parameters related to myocardial energy metabolism, such as myocardial expression of fatty acid or glucose oxidation genes and insulin signaling genes, should be investigated. Finally, the serum level of NPY may not be necessarily correlated with their levels in myocardium. This is important, because we did observe that although NPY expression in the serum decreases with TMZ treatment, the expression of NPY-Rs in the myocardium actually increases, which in our point of view, may be a feedback response of myocardium to the decreased serum NPY. The results of our study could only provide associations between changes of NPY system and TMZ treatment, and the physiological influence and subsequent signaling pathways of changes of NPY system deserve further investigation.In conclusion, our study found that cardiac metabolic remodeling is an early change occurring in the myocardium before the observance of typical morphological ventricular remodeling following cardiac pressure overload, and pretreatment with TMZ may at least partly reverse the acute metabolic disturbance, perhaps via regulation of the NPY system. Further studies are needed to clarify the exact molecular mechanisms and potentially distinct role of NPY receptors during this pathogenesis process.


Integration of volumetric heart chamber quantification by 3D echocardiography into clinical practice has been hampered by several factors which a new fully automated algorithm ) may help overcome. This study therefore aims to evaluate the feasibility and accuracy of the LHM software in quantifying left atrial and left ventricular volumes and left ventricular ejection fraction in a cohort of patients with a bicuspid aortic valve. Patients with a bicuspid aortic valve were prospectively included. All patients underwent 2D and 3D transthoracic echocardiography and computed tomography. Left atrial and ventricular volumes were obtained using the automated program, which did not require manual contour detection. For comparison manual and semi-automated measurements were performed using conventional 2D and 3D datasets. 53 patients were included, in four of those patients no 3D dataset could be acquired. Additionally, 12 patients were excluded based on poor imaging quality. Left ventricular end-diastolic and end-systolic volumes and ejection fraction calculated by the LHM correlated well with manual 2D and 3D measurements . Left atrial volume (LAV) also correlated significantly although LHM did estimate larger LAV compared to both 2DE and 3DE . The fully automated software works well in a real-world setting and helps to overcome some of the major hurdles in integrating 3D analysis into daily practice, as it is user-independent and highly reproducible in a group of patients with a clearly defined and well-studied valvular abnormality. Left atrial and ventricular volumes and ejection fraction are important diagnostic and prognostic parameters, widely used in daily practice. Indication for cardiac surgery in patients with valvular abnormalities such as bicuspid aortic valve disease, relies heavily on accurate left ventricular (LV) volume and function assessment. For many years, two-dimensional echocardiography (2DE) has been the most widely used modality for LV volumetric assessments; however, it is based on geometric assumptions which cause inaccuracy and the reproducibility remains suboptimal. Three-dimensional echocardiography (3DE) has largely overcome these drawbacks as it has the ability to visualize cardiac structures from any perspective, entailing an accurate quantitative and more reproducible evaluation of cardiac chambers. However, the use of 3DE in daily clinical practice has been hampered, because there is a learning curve for data acquisition, and 3D data analysis can be a time-consuming process, moreover there is need for experienced observers.A fully automated and user-interference free algorithm may improve the feasibility of 3DE in daily clinical practice. Such a method has now been proposed in the new ‘Heart Model’ Software (LHM), which promises a rapid and accurate automated quantification of left atrial (LAV) and LV volumes and ejection fraction (LVEF). The feasibility and accuracy of the new “Heart Model” was recently compared to cardiac magnetic resonance imaging by Tsang et al. who concluded that this technique is strongly correlated with CMR, with a high reproducibility and short analysis time , 2. HoweTherefore, this study aims to assess feasibility and reproducibility of the ‘Heart model’ software in a prospective cohort study by comparing the results between echo and CT using conventional 2D, 2D-xPlane, 3D transthoracic echocardiography TTE (3DE) techniques in patients with a bicuspid aortic valve (BAV) with moderate to severe aortic valve stenosis or regurgitation.Patients with a BAV who visited the outpatient clinic for regular follow-up between October 2014 and March 2016 were consecutively included into this prospective study. All patients underwent the full study protocol on the same day. The study protocol consisted of physical examination, electrocardiography (ECG), 2D and 3D echocardiography and a cardiac CT scan. The study was approved by the medical ethical committee of the Erasmus medical center and informed consent was given by all patients who participated in the study. Two protocols were used reference methods were used to compare the LFM data: in the first protocol 3DE was used as a reference standard, in the second protocol the LHM was compared to CT.Two experienced sonographers  performed a standard two-dimensional transthoracic echocardiogram (2DE). All studies were acquired in the left lateral decubitus position, in harmonic imaging using an EPIQ7 ultrasound system  equipped with a x5–1 matrix-array transducer (composed of 3040 elements with 1–5 MHz) A non-foreshortened apical four-chamber view (A4C) and two-chamber view (A2C) were recorded with manual or electronic rotation (iRotate) followed by a focused LV, A4C and A2C image. From the focused LV-A4C a true perpendicular image view (A2C) was acquired with xPlane mode, in order to retrieve both views from the same heart-beat. This was repeated with the focus on the true long axis of the LA [Analysis was performed by A.T.H. and J.S.M. All measurements were blinded to patient specific information. Before measurements were performed, the quality of each dataset was evaluated by both observers. Patients were excluded from further analysis in cases of poor image quality .LV end diastolic volume (LVEDV), LV end systolic volume (LVESV) and LVEF were calculate using the Simpsons bi-plane method of disk summation, as stated in the guidelines, from the standard A4C and A2C and apical xPlane images [Manual: LV volumes and LVEF were measured using commercially available software . The user aligned the multiplanar view to obtain the true long axis of the LV in the A4C and A2C view. Landmarks were placed on the mitral annulus and apex. The endocardial border was traced automatically and adjusted manually where needed. For the LA volume, the true long-axis was aligned using the multiplanar mode in the end-systolic frame and the contour traced as mentioned above. The 3D dataset was scored feasible when the entire cardiac contour could be traced.Automatic: Offline fully automatic analysis of the datasets was performed using the Q Lab advanced ‘Heart Model’ analysis software. This software has previously described in detail before by Tsang et al. , 2. In bAcquisition was performed on a 3rd generation dual-source CT . Retrospective ECG gated spiral acquisition was used, with a mean dose length product (DLP) of  362 mGy-cm kVp was modulated to patient size. Besides patient size and the selected kV the mA was modulated to the heartrate to provide a high mA pulse during 1–40% of the RR interval. The pitch was adapted to increase proportionally with higher heartrates. Reconstructions were made with a medium smooth kernel, with a slice thickness of 1.5 mm at an increment of 0.4 mm at every 5% of the RR interval.Images were analyzed semi-automatically using Syngo Via software . Image analysis was performed by AC, with 1 year of cardiac CT experience. All cardiac phases were analyzed the software automatically detects the ED and ES phase, this was manually changed if needed. The endo and epicardial contours are automatically placed by the software and manually adjusted were need. The papillary muscles and if present trabeculations were included into the LV lumen. The basal plane was selected perpendicular to the short axis at the level of the mitral valve. Care was used to make sure the basal plane was on the same level in the ED and ES phase.® statistics 21.0 software was used to analyze the data. Continuous variables were presented as mean ± standard deviation (SD) or as median with an interquartile range. Categorical variables were presented as frequencies and percentages. We tested for normality by calculating Z-values of skewness and kurtosis, using the Shapiro–Wilk test and by visually assessing the data. For comparison of normally distributed continuous variables between two groups the student’s t test was used. To quantify correlations the Pearson or Spearman correlation test was applied. Intra-observer and inter-observer agreement between two investigators  were assessed by repeated analysis of the same images in a third of the dataset a month after initial analysis at the same images and blinded to the initial results. The limits of agreement between two measurements were determined as the mean of the differences (bias) ± 1.96 SD and presented in a Bland–Altman plot [The IBM SPSSman plot . AdditioFifty-three patients with a BAV were included; baseline characteristics are presented in Table In all 53 patients, 2DE measurements could be performed and functional echo parameters were measured, as presented in Table There was a good correlation between the LHM and the manual bi-and xPlane measurements for LVEDV, LVESV, and LVEF. In Table The LHM correlated strongly with the 3D LV measurements as shown in Table In the second protocol, where CT was used as a golden standard method, agreement was found for EDV and ESV (r = 0.88 and r = 0.81); mean differences were 42 ml 23%) and 10 ml (15%) respectively (p < 0.001 and p = 0.002). However, compared to CT the LHM seems to estimate smaller LVEDV . In addition, when the measurements were repeated on a second acquisition of the same patients n = 12) there was some variation but generally there was good agreement reflected by a small bias and narrow limits of agreement  since this algorithm has no human interaction .We had to exclude 16 patients (30%) in total due to imaging quality limitations which is comparable to conventional 3DE in a routine clinical setting.The main concern with 3D echocardiography is the accessibility in terms of time and skill required to produce accurate and reproducible results. The algorithm described in this study promises to improve on these points. This study demonstrates a high feasibility and accuracy in a population of patients with BAV disease, a population where fast, reliable, user-independent and non-invasive follow-up imaging by echocardiography is imperative.Another remarkable finding is the relatively large LA volume estimated by the LHM compared to 2DE measurements. First, we suggested that this could be explained by the inclusion of the pulmonary vein orifice into the left atrial cavity by the algorithm. However, when carefully re-evaluating the LA contours, most seemed to adequately follow the left atrial walls. Another explanation could be that it is actually an underestimation of the 2DE measurements. This can partly be explained by the use of the length area formula which assumes the LA to be ellipsoid, which is evidently not always the case . The corThe golden standard for quantitative volumetric heart chamber assessment is cardiac magnetic resonance imaging (MRI). Unfortunately, no cine cardiac images were available in this study. Therefore, no comparison with MRI could be made; consequently, we used volumetric data from CT as an additional source of validation. Additionally, we feel that EDV by 2DE has been slightly underestimated and therefore 3DE is best used as a reference modality. We were strict when it came to image quality therefore we had to exclude 12 patients from analysis. However, a sufficiently large cohort could be analyzed.Automated chamber quantification is feasible and accurate in patients with bicuspid aortic valve disease in a routine clinical setting. The ‘Heart Model’ provides accurate automatic measurements of LVEDV, LVESV and LVEF and LAV and has a high reproducibility between dataset and no inter or intra-observer variability. It does however seem to underestimate end-diastolic volume compared to CT.


The clinical and prognostic significance of these biomechanical parameters merits further scrutinization.In this research, we hypothesized that novel biomechanical parameters are discriminative in patients following acute ST-segment elevation myocardial infarction (STEMI). To identify these biomechanical biomarkers and bring computational biomechanics ‘closer to the clinic’, we applied state-of-the-art multiphysics cardiac modelling combined with advanced machine learning and multivariate statistical inference to a clinical database of myocardial infarction. We obtained data from 11 STEMI patients  and 27 healthy volunteers, and developed personalized mathematical models for the left ventricle (LV) using an immersed boundary method. Subject-specific constitutive parameters were achieved by matching to clinical measurements. We have shown, for the first time, that compared with healthy controls, patients with STEMI exhibited increased LV wall active tension when normalized by systolic blood pressure, which suggests an increased demand on the contractile reserve of remote functional myocardium. The statistical analysis reveals that the required patient-specific contractility, normalized active tension and the systolic myofilament kinematics have the strongest explanatory power for identifying the myocardial function changes post-MI. We further observed a strong correlation between two biomarkers and the changes in LV ejection fraction at six months from baseline (the required contractility ( Although early survival post-ST segment elevation MI (STEMI) is improving , the lonThere is a growing recognition that a computational approach for ventricular biomechanics, when integrated with clinical imaging, can provide insights into heart function and dysfunction ,6. For eCardiac dynamics are complex multi-physics problems that involve dynamic blood flow, electrophysiology, nonlinear deformation and interactions among them . Substanet al.  takes 0 in the functional myocardium and 1 in the MI region, with a linear transition between them. We further assume the MI tissue does not contract, thus the active tension in the MI heart isTa and σf,The differences of the passive and active myocardial responses in the remote, transition and the infarct regions are modelled by changing the strain energy function and active stress ,26. Prev used in  to defin2.2.3.a, b, af, bf, as, bs, afs, bfs and Treq, are determined so that the simulated LV dynamics are in good agreement with corresponding CMR measurements. Specifically, the passive myocardial parameters are inversely determined from in vivo data  using a multi-step optimization scheme [Treq is determined by matching the measured LV end-systolic volume and systolic circumferential strain (CS) of the clinical measurements. All other parameters in the active tension generation model are kept the same as in [Treq. The objective function isɛi, V are the ith regional circumferential strain and LV cavity volume from the model, and ɛmearsuredi, Vmeasured are corresponding measured data. N is the total number of the control points. Figure 2a shows the optimization of Treq in a healthy LV model, and figure 2b is the strain comparison between the CMR measurements and values from the model predications using the optimized Treq, with good agreement.Material parameters, including n scheme . The actme as in . The strTreq in the remote region is determined by minimizing the objective functionNun is the number of segmental remote regions. The average strain data from the unaffected region in the MI group is 13 ± 3 out of 24 segments.For the MI subjects, we only determine the parameters in the remote regions because the MI region is modelled as non-contractile and 50 times stiffer. The passive parameters are determined similarly as for the healthy models, but in vivo CMR measurements are summarized in electronic supplementary material, table S1.Further comparisons on LV cavity volume and strains with 2.3.The general characteristics that define the difference between a healthy heart and one that experienced an MI are well known. However, it is less clear whether the functional myocardium and its associated biomechanical factors are sufficient to classify the myocardium from a healthy heart or heart after acute-MI. Here we will apply seven different techniques from multivariate statistics and machine learning to assess the potential of myocardial classification given several biomechanical factors and to identify the methods that yield the highest prediction accuracy.k-nearest neighbours classifier (KNN). Furthermore, linear discriminant analysis (LDA) will be applied, as well as sparse logistic regression with L1 regularization (Lasso). We will evaluate two tree-based methods that exploit the change of entropy in the data, as defined in electronic supplementary material, eqn. (S13). This includes decision trees trained with the C5.0 algorithm, and random forests based on bagging with feature sub-selection. Finally, we will apply a non-parametric Bayesian approach with Gaussian processes and automatic relevance determination (GP-ARD). All these methods are described in more detail in electronic supplementary material, §S0.5.Our portfolio of methods includes univariate logistic regression, multivariate logistic regression with several predictors and the Another important topic is the identification of relevant factors that exhibit the greatest influence on the classification outcome. In this study, we attempt to find those biomechanical factors that possess the strongest explanatory power for the differentiation of myocardial contractile function from a healthy heart or a heart with acute-MI. Several of the previously mentioned methods provide a measure of factor importance, including the Lasso, Decision-Trees, Random Forests and GP-ARD. We will combine the importance measure of these methods into a single-ranked relevance score to identify the biomechanical factors with the highest explanatory power. The results for both studies are presented in §§2.3.1.true positive is the correct identification of an MI heart, a true negative is the correct identification of a healthy heart, a false positive is the misclassification of a healthy heart as an MI heart and a false negative is the misclassification of an MI heart as a healthy heart. These counts are obtained out of sample with leave-one-out-cross validation (LOOCV). With LOOCV, a method predicts the class for one observation i ∈ {1, …, n} at a time based on the training set of the remaining (n − 1) observations, where n is the total number of observations in the labelled dataset. From the TP, TN, FP and FN counts, we compute the sensitivity,1 specificity2 and the total misclassification error3 to assess the classification accuracy of a method.We assess the accuracy of correctly predicting myocardial contractile function from either a healthy or MI heart in terms of the true positive (TP), true negative (TN), false positive (FP) and false negative (FN) counts. Positive labels refer to MI heart; negative labels refer to healthy heart. Hence, a 4 By numerical integration, we obtain the area under the ROC curve (AUROC) as an overall indication of the classification performance. An AUROC value of 0.5 indicates random expectation, whereas the maximum value of 1 gives perfect predictive accuracy.We plot, for all methods included in our study, the sensitivity against the complementary specificity (i.e. 1 minus the specificity). The results will be shown later in For the non-parametric Bayesian approach, the regularization parameters are optimized by maximizing the marginal likelihood of the training data. For the non-Bayesian approaches, the regularization parameters are obtained based on LOOCV. It is important to note that the out-of-sample data used for evaluating the classification performance must not be used for tuning regularization parameters, to avoid an overoptimistic bias. We, therefore, need two nested LOOCV schemes, one for regularization parameter tuning, the other for method evaluation. This is best illustrated with an example. Considering four data points {1, 2, 3, 4}. For method evaluation, we use an outer LOOCV scheme as follows: training on {1, 2, 3}, evaluating on {4}; training on {1, 2, 4}, evaluating on {3}; training on {1, 3, 4}, evaluating on {2}; training on {2, 3, 4}, evaluating on {1}. For each training set, we use an inner LOOCV scheme for regularization parameter tuning. So for the first fold, {1, 2, 3}, we have: training on {1, 2}, regularization parameter tuning on {3}; training on {1, 3}, regularization parameter tuning on {2}; and training on {2, 3}, regularization parameter tuning on {1}.3.3.1.The CMR findings of the MI group and the healthy group are summarized in 3.2.a,b is the simulated LV geometries from the healthy control at end-diastole and end-systole, superimposed on CMR cine images, and figure 4c,d is from the MI model. Figure 4e,f is the distributions of systolic active tension Ta and myofibre stress σf in the healthy subject. Since there is no active contraction in the MI region, the MI region is over-stretched to bear the systolic pressure, as shown in figure 4k, in which the myofibre strain is positive (in blue), and the remote myocardium region is shortening. The distribution of myofibre stress σf is more homogeneous in the healthy heart compared with the MI heart. Similar pattern is shown in myofibre strain in figure 4i,k. Figure 4j,l shows the LV twist relative to the LV base, which linearly increases towards the apex with a maximum apical rotation of around 14° in the healthy model, but only 4° in the MI model.Figure 4Treq in the healthy group is 157 ± 25 kPa, and 156 ± 27 kPa in the MI group, as shown in figure 6a. No significant difference is found in Treq for the two groups. Similar results are found for Ta and systolic myofibre stress σf as shown in figure 6b,c. However, the average Tnorma in the healthy group is much lower than the MI group . Similar trend is shown in σnormf . The systolic myofilament kinetics Cs is 0.42 ± 0.04 in healthy group, which is slightly lower than 0.44 ± 0.13, p = 0.50 in the MI group. Tnorma, σnormf and Cs. Interestingly, even with a wider range of SBP, the standard deviations of Tnorma, σnormf and Cs in the healthy group are much smaller compared with the MI group.The average Ta, Treq, Tnorma, σf and Cs as potential biomarkers for myocardial contractile function, but not passive stiffness and diastolic stress because of uncertainties in assumed end-diastolic pressure. A linear correlation analysis is further carried out to decide which features should be included in statistical feature classification and summarized in the electronic supplementary material. The criteria are that if two features are highly correlated in both the healthy and the MI groups, and further related to other features and CMR measurements in a similar way, then the more reliable feature will be selected. For example, Ta and σf are generally inter-related through the myocardial mechanical model, see equation , where (p − 1) is the highest rank. The height of the bars in Cs and Tnorma have the strongest explanatory power in predicting myocardial contractile function from healthy or MI hearts.5 However, our classification results, discussed below and succinctly summarized in For each of these methods, we rank the explanatory variables, and combine the results in an accumulative rank score, which serves as an indicator for the overall factor relevance. These accumulative scores are shown in 3.5.We have applied the classification methods mentioned in §3.6.Tnorma and Cs are the strongest explanatory factors in predicting myocardial contractile function between healthy subjects and MI patients, followed by Treq. Therefore, in this section, the association between Tnorma, Cs, Treq and LV pump function recovery at six months is further analysed. Treq, Cs at baseline in the MI group. It can be seen that a strong linear relationship between Treq, Cs at baseline and LVEF changes at six months. With a lower Treq, the MI patient could have a better LVEF recovery after six months. Thus, we hypothesize that for acute-MI patients with a similar calcium handling dynamics, a lower Treq suggests a potential to further increase the contractile function, without going into de-compensated states, compared with cases when the myocardial contractility already reaches the maximum. Since the maximum myocardial contractility is limited, less usage of the contractile reserve will give the heart more resilience in the longer term. We also observe that Cs is positively related to LV EF changes at six months. Since Cs is associated with the myofilament kinetics, this presumably suggests there are more binding sites available at systole for generating the active tension. However, no correlations are found between Ta, Tnorma, σf, σnormf and LV function at six-month follow-up, which are summarized in Section 4.4.1.in vivo CMR data. Using this approach, we inversely determine the passive parameters and contractility for all the LV models. We have shown for the first time that, compared with healthy controls, patients with recent STEMI exhibit increased active tension, i.e. increased contractility and increased active tension, when normalized by SBP.The major determinant of long-term survival after an acute-MI is the efficiency of LV pump function. Despite decades of research, the pathophysiology and disease mechanisms of the failing heart remain incompletely understood, engendering a knowledge gap for the development of new therapies. It is believed that novel mathematical tools are required to solve those fundamental patho-physiological questions. In this study, we have modelled the LV dynamics at end-diastole and end-systole in healthy controls and in patients with recent STEMI. The computational contracting LV models are based on in vivo. Our previous study [Treq) estimation because of the matched EDV and the strain data.It is challenging to estimate myocardial passive stiffness inversely, especially with limited measurements us study  showed tus study  and our Treq), all other parameters of the active tension generation are kept fixed. This allows us to match measured LV dynamics in end-systole, and avoid the complexity of determining many parameters in the electromechanical models from different functional and structural scales. This approach has been widely applied when mathematically simulating LV systolic dynamics [et al. [et al. [et al. [The patient-dependent myocardial systolic contractility in our simulations is controlled by the parameter .It has been found that myocardial mechanics are dependent on the underlying fibre architecture . Howeverd fibres ,26,42. TCs may only represent an ‘apparent’ myofilament kinetics under same intracellular calcium dynamics.We are aware that our current mechanical model is still necessarily simplified, in particular, with one chamber and the LV dynamics are simulated at two time points only (end-diastole and end-systole). Moreover, a simplified intracellular transient is used to trigger active contraction simultaneously, due to lack of parametrization in cellular level, However, this is a starting point towards clinical translation in terms of real time prediction, and our combined mechanical, statistical and MRI study already show promising value in evaluating myocardial functions between the healthy subjects and MI patients.4.2.in vivo imaging data described in the electronic supplementary material. However, working directly on the images, e.g. representing them as grey-level pixel vectors and building a classifier in this high-dimensional space, leads to the well-known curse-of-dimensionality problem [a priori highly likely to contain physiologically relevant information.Our ultimate aim is to build a classifier (case versus control) based on  problem . StandarWe have worked in the biomechanical parameter space with a variety of methodological tools. We have started with a simple univariate analysis, followed by a multivariate approach, where we have used the latter to evaluate the relative explanatory relevance of the various biomechanical parameters with respect to the classification task and to compare the performance improvement obtained with several multivariate classification methods over the univariate approach.Tnorma, Treq, Cs and Ta. However, the simplified comparison, such as using the S student t-test, has its limitations, as shown in Tnorma is found to be significantly different between the control group and the MI group. In the second part of the study, we have shown that multivariate statistical methods provide more powerful tools for classifying the difference in myocardial contractile function after acute-MI.In the univariate approach, by simply comparing the different biomechanical parameters, several parameters are identified for classifying myocardial contractile function from either a healthy heart or a MI heart, including SBP, EDV, Cs and Tnorma are the most relevant factors for this classification task, but that no individual factor is completely irrelevant. For details, see §In the second part, we have used several machine learning and computational statistical methods to identify the biomechanical factors that possess the strongest explanatory power for predicting the changes in myocardial contractile function after acute MI. Our study has revealed that k.In the next evaluation step, we have predicted myocardial contractile function between healthy and MI hearts based on the previously mentioned biomechanical factors with eight different methods. Cs and Tnorma are added to the single factors present in dataset D2. This AUROC value is considerably larger than random expectation (0.5) and quite close to perfect prediction (1.0). To rule out that Cs and Tnorma are for themselves sufficient predictors for the two heart conditions, we excluded Treq and SBP and found a significant drop in the AUROC value to 0.77. This implies a synergy, i.e. interaction effect, of the involved factors. Hence all the available factors present in D1 are important myocardial contractile function indicators that should be used in conjunction to differentiate myocardial contractile function between healthy and MI hearts.The overall predictive accuracy given all methods can be summarized with the AUROC score, which is displayed in 4.3.Treq, Tnorma and Cs, as suggested in the classification part, might potentially be biomarkers for risk stratification of MI patients. However, since our study has a limited sample size with selected patients, it is not immediately obvious which, if any, of the biomechanical parameters might have clinical prognostic value, and further research is warranted. The linear correlation analysis , normalized active tension Tnorma and the systolic myofilament kinetics Cs are found to have the strongest explanatory power, and the statistical method KNN has shown the best performance for the classification of myocardial contractile function, followed by GP-ARD. We further observe strong correlations between the biomarkers  and the changed LVEF at six months from baseline . We conclude that the patient-specific contractility Treq, the normalized active tension Tnorma, and the myofilament kinetics Cs all have potential clinical values for prognostication on LV contractile status post-MI, their significance merits further study in larger and unselected patient cohorts.Using combined personalized computational cardiac biomechanical modelling and statistics analysis, we have studied systolic LV dynamics for one patient group consisting of 11 acute STEMI patients with no-reflow and a group of healthy control subjects, based on CMR imaging. The passive response and active contractile properties of myocardium are determined by matching the simulated LV dynamics  to the CMR measurements. We find that, compared with healthy controls, patients with STEMI exhibit increased LV wall active tension when normalized by SBP. This suggests that the functional myocardium in the patients are overcompensating in order to preserve the stroke volume. Different machine learning and multivariate statistical analysis methods are applied to identify the biomechanical factors that possess the explanatory power in terms of the changed myocardial contractile function after STEMI. The individual required contractility (


Currently established 2D techniques are used to acquire several slices in short- and long-axis orientation, which should suffice for the detection of moderate to severe rejection  in 3 short-axis slices and a prototype self-navigated 3D radial whole-heart isotropic T2 map [3) were acquired with 3 T2-preparation durations and free breathing. After reformatting of the 3D T2 maps and matching for slice thickness, the 2D and 3D T2 maps at the same location were segmented according to AHA guidelines [2 values of each patient were compared statistically, and then divided into groups according to their EMB rejection degree. These groups were then tested for differences in T2 value. The 3D T2 maps were furthermore directly rendered in 3D, after which they were inspected for foci of T2 elevation.28 Patients  underwent routine EMB as well as 2D and 3D cardiac T2 values of the groups were 49.9 ± 4.0 ms (0R), 48.9 ± 0.8 ms (1R), and 65.0 ms (2R). The reformatted 3D T2 values agreed very well with the 2D T2 values for all patients . The highest 2D segmental T2 mapping agreed with the established 2D technique, and enables the identification of foci of elevated T2 in regions of the myocardium that are not covered by the 2D technique. The 3D cardiac T2 mapping technique thus appears to be well-suited for the investigation of mild allograft rejection (degree 1R), but this remains to be confirmed in a larger patient cohort.The investigated 3D cardiac T


Although high-intensity non-invasive ventilation has been shown to improve outcomes in stable COPD, it may adversely affect cardiac performance. Therefore, the aims of the present pilot study were to compare cardiac and pulmonary effects of 6 weeks of low-intensity non-invasive ventilation and 6 weeks of high-intensity non-invasive ventilation in stable COPD patients.In a randomised crossover pilot feasibility study, the change in cardiac output after 6 weeks of each NIV mode compared to baseline was assessed with echocardiography in 14 severe stable COPD patients. Furthermore, CO during NIV, gas exchange, lung function, and health-related quality of life were investigated.Three patients dropped out: two deteriorated on low-intensity non-invasive ventilation, and one presented with decompensated heart failure while on high-intensity non-invasive ventilation. Eleven patients were included in the analysis. In general, cardiac output and NTproBNP did not change, although individual effects were noticed, depending on the pressures applied and/or the co-existence of heart failure. High-intensity non-invasive ventilation tended to be more effective in improving gas exchange, but both modes improved lung function and the health-related quality of life.Long-term non-invasive ventilation with adequate pressure to improve gas exchange and health-related quality of life did not have an overall adverse effect on cardiac performance. Nevertheless, in patients with pre-existing heart failure, the application of very high inspiratory pressures might reduce cardiac output.DRKS00007977).The trial was registered in the Deutsches Register Klinischer Studien (DRKS-ID: The online version of this article (doi:10.1186/s12931-017-0542-9) contains supplementary material, which is available to authorized users. Chronic obstructive pulmonary disease (COPD) is a condition with high mortality and morbidity rates worldwide , 2. PatiThe use of long-term nocturnal non-invasive ventilation (NIV) in COPD patients with chronic hypercapnic respiratory failure remains controversial –7. HowevNevertheless, mechanical ventilation can affect cardiac output (CO), especially if it is applied with higher inspiratory and/or expiratory positive airway pressures (EPAP) –14. A reLong-term effects of NIV on the heart in COPD patients have so far only been sparsely investigated. Although long-term NIV was shown to increase heart rate variability , 16, and2) level ≥ 6.7 kilopascal (kPa); c) and/or a nocturnal PaCO2 ≥ 7.3 kPa or a rise in transcutaneous carbon dioxide pressure (PtCO2) during the night ≥1.3 kPa (doi:10.1055/s-0029-1243978). Patients had to be in stable condition . Patients with neuromuscular and restrictive thoracic diseases or obstructive sleep apnoea were excluded.COPD patients with Global initiative of Obstructive Lung Diseases stage III or IV , and witThe study protocol was approved by the Medical Ethics Committee of the University Witten Herdecke. Written informed consent was obtained from all subjects. The trial was registered in the Deutsches Register Klinischer Studien (DRKS-ID: DRKS00007977).The study was designed as a pilot feasibility study with a randomised, open-label, two-treatment, two-period crossover design. Patients were randomized to receive either the HI-NIV/LI-NIV or the LI-NIV/HI-NIV sequence. After baseline measurements were done, NIV was titrated in-hospital. Thereafter, patients were discharged, re-admitted after 6 weeks of home NIV to perform outcome measurements, and switched to the complementary mode of NIV. After another 6 weeks of home NIV, patients were re-admitted for final measurements. The study was a single-centre study at the Department of Pneumology, Merheim Hospital Cologne, Germany.The primary outcome was the percentage change in CO during spontaneous breathing after 6 weeks of NIV compared to baseline. We investigated whether it was feasible to assess CO both during spontaneous breathing and NIV by echocardiography in our patients with severe COPD.A complete standard M-mode and two-dimensional echocardiography was performed by one operator using a Philips iE33 ultrasound system with a S5-1 sector array probe . We assessed cardiac function by using transthoracic echocardiography because quantification of cardiac function is the cornerstone of cardiac imaging, with echocardiography being the most commonly used non-invasive modality because of its unique ability to provide real-time images of the beating heart, combined with its availability and portability.http://asecho.org/guidelines/guidelines-standards/) [Measurements were carried out on three representative beats and results were averaged. Heart rate (HR) was recorded. The following parameters were evaluated: (ndards/) .2. LVOT Doppler pulsed-wave measurements were obtained over 3 consecutive cardiac cycles. The pulsed sample volume was placed in the LVOT in the anteriorly angulated 4-chamber apical view just proximal to the aortic valve to record the maximum flow signal. Proper location in the LVOT was confirmed by the aortic valve closure signal. After these measurements the diameter of the aortic annulushis was then multiplied by the velocity time integral of the trace of the Doppler flow profile across the aortic valve to determine the flow volume per beat . The result was then multiplied by the HR to obtain CO.Left heart systolic function was assessed by Simpson’s rule: Left ventricle (LV) ejection fraction (LVEF) = (end-diastolic volume - end-systolic volume)/end-systolic volume. For LV CO, the left ventricular outflow tract (LVOT) diameter was measured at the level of the aortic annulus from the parasternal long-axis view in midsystole . After tFor the right heart size and systolic function we measured right ventricle (RV) size, RV subcostal wall thickness, systolic pulmonary artery pressure (sPAP) with an estimate of right atrial pressure on the basis of inferior vena cava size and collapse, tricuspid annular plane systolic excursion (TAPSE), and fractional area change (FAC) and S´ (the pulsed Doppler peak velocity at the tricuspid annulus).These parameters were assessed at each visit during (i) spontaneous breathing, and (ii) after 10 min acclimatization time, whilst undergoing NIV. Furthermore, 24-h ECG and blood pressure measurements were performed to detect rhythm disturbances and monitor blood pressure respectively, whilst on NIV. NTproBNP was assessed by routine laboratory methods.Echocardiographic studies were performed in the standard left decubitus position by a single cardiologist, blinded to clinical and laboratory information. After optimizing image quality, stroke volume was measured from the anteriorly angled apical four-chamber view or three chamber view using pulsed wave Doppler with the interrogation beam directed across the LVOT. For the LVOT diameter, the zoom was used in the parasternal long axis view in systole to minimize the errors in the measurement. It is known that the LVOTdiameter is normally related to body surface area and should be around 20 mm for an average size person.The effectiveness of NIV was assessed by arterial  and transcutaneous blood gases  , 21. Fur2) value possible, according to the patient’s tolerance [2, EPAP was set at 4–6 cm H2O. For LI-NIV, pressure support ventilation with an IPAP ≤ 14 cm H2O and BURR of ≤ 12 breaths/min was used. During LI-NIV titration, an IPAP of up to 18 cm H2O and a BURR of up to 14 breaths/min were allowed for patient tolerance. The IPAP difference between the LI-NIV and HI-NIV setting had to be at least 4 cm H2O. Nasal and oronasal masks were used and not changed during the study. For further details, see Additional file HI-NIV was titrated to establish normocapnia, or the lowest arterial carbon dioxide  in CO between LI-NIV and HI-NIV compared to baseline, at a two-sided level alpha of 0.05 with a power of 88% . For an t-test separately for LI-NIV and HI-NIV for all patients who received the respective treatment.Comparison of LI-NIV and HI-NIV in the crossover setting was performed in the full analysis set, which included all randomised patients who received both treatments. Outcome measurements were tested for normality using visual inspection. An analysis of variance model was used with “treatment”, “period” and “randomised sequence” defined as fixed effects, and “patient within sequence” defined as a random effect. The treatment effect was estimated with a 95% CI and tested with a two-sided level of 0.05. In addition, tests for periodic and carryover (treatment-period interactions) effects were performed. Treatment result and baseline measurement were compared by calculating the mean difference with 95% CI and performing a paired Nine patients had arterial hypertension, three a reduced LVEF , one reported previous ischemic heart disease with a percutaneous coronary intervention 2 years earlier, one had atrial fibrillation, two peripheral vascular disease, two hypercholesterolemia and one type 2 diabetes mellitus. All patients used long-acting beta-agonists, ten patients long-acting anticholinergics, seven inhaled corticosteroids, one roflumilast and one theophylline. None of the patients used oral corticosteroids. No medication changes were made during the follow-up Table .Table 1BVentilatory settings and compliance rates of the study completers are shown in Table 2 increased up to 10 kPa and pH decreased below 7.35. One patient with pre-existing heart failure and atrial fibrillation (LVEF at baseline: 25%) presented with decompensated heart failure after 5 weeks of HI-NIV (subject ID 7). Coronary angiography revealed a main coronary artery stenosis. After treatment, echocardiography showed no changes in right or left ventricular function, both during spontaneous breathing and under HI-NIV  during NIV. Tachycardia due to AF occurred in one patient; moderate or severe aortic regurgitation was not present in our patients. In contrast to the left ventricle, the assessment of the right ventricle was markedly more difficult due to the poor image quality.LV hypertrophy was observed in three patients. Six/13 patients, in whom the RV could be visualized, had RV enlargement , and in six patients the RV wall was thickened (>0.5 cm) . All patIn general, 6 weeks of NIV did not affect CO during spontaneous breathing Tables  and 4, aCompared to spontaneous breathing, CO did not acutely change with the application of NIV Additional file 3: Video S2. The subxiphoidal view shows the diaphragmatic motion under spontaneous breathing. (AVI 11130 kb)Additional file 4: Video S3. Under high NIV therapy, only the subxiphoidal view is found. Have a look to the diaphragm that seems to be completely flattened. (AVI 19351 kb)The increased sPAP in one patient could only be reduced with HI-NIV Table . RV dimeNo significant changes in blood pressure or rhythm disturbances were observed. NTproBNP did not change significantly after 6 weeks of either LI-NIV or HI-NIV Table .1 and HRQoL. HI-NIV tended to be more effective in improving gas exchange, although the change was not significant , however, results were so diverse that this is not expected to change our conclusions for now. However, a larger study should confirm the results found in our pilot. Secondly, another limitation is that we included a group of patients with different kind of cardiac comorbidities. Because sufficient knowledge in COPD patients with cardiac comorbidities is very limited, this pilot trial first intended to include patients with a broad spectrum of cardiac comorbidities, without further inclusion limits to specific comorbidities. This strategy resulted in heterogeneity of comorbidities, which makes it extremely important to judge the data not only in terms of means but also in terms of individual patient outcomes. Therefore, we provided individual patient data. Thirdly, we used echocardiography to test cardiac function. Especially in patients with COPD this method has its drawbacks and echo-windows might be insufficient to make reliable measurements. To optimize the measurements, all the echocardiography’s were performed by the same experienced cardiologist blinded to the NIV mode. With this approach, we succeeded to measure CO with Simpson’s rule in all patients. However, PH estimates were difficult and it is also known that echocardiography is not the standard method to diagnose PH. However, echocardiography’s are non-invasive and do not give discomfort to these already very disabled patients. We suggest that further studies should both include echocardiography’s and probably more invasive or uncomfortable measurements, such as cardiac MRI, to judge cardiac function under NIV. Finally, to avoid the problems associated with multiple testing with a limited amount of patients, we restricted our analyses to our main outcomes.Long-term home NIV with adequate pressure to improve gas exchange and HRQoL has differential effects on cardiac output, depending on the patient and ventilator settings. Although the treatment effects found in our pilot study should be used cautiously, in general, our preliminary data suggest that there is no reason to withhold COPD patients from HI-NIV due to concerns of adverse cardiac outcomes. Nevertheless, care should be taken in patients with co-morbid heart failure and their heart function should be checked regularly. Future trials should be performed in specific patient groups, including those with co-existing cardiac diseases.Additional file 1:Supplement to Methods and Results. (DOCX 41 kb)


There are still ambiguities existing in regard to left ventricular non-compaction (LVNC) diagnostic imaging. The aim of our study was to analyze diagnostic potential of late gadolinium enhancement (LGE) and ventricle geometry in patients with LVNC and controls.n=1975 exams). Matching sample of controls included cases with no structural heart disease, hypertrophic or dilative cardiomyopathy, arrhythmogenic right ventricular dysplasia or subacute myocarditis. Eccentricity of the left ventricle was measured at end diastole in the region with pronounced NC and maximal to minimal ratio (MaxMinEDDR) was calculated.Data on cardiac magnetic resonance imaging (CMR) studies for LVNC were reassessed from the hospital’s database , specificity of 82.6% (95%-CI: 75.7–88.2) for LVNC, AUC 0.917 (95%-CI:0.876–0.948); p<0.001. LGE correlated with Max-Min-EDD-R  and there was significant difference in ROC analysis ΔAUC0.244 (95%-CI:0.175–0.314); p<0.001. LGE also correlated negatively with stroke volume and systolic function .Study included 255 patients referred for CMR, 100 (39.2%) with LVNC  and 155 (60.8%) controls. Existing LGE had sensitivity of 52.5% (95%-CI:42.3–62.5), specificity of 80.4% (95%-CI:73.2–86.5) for LVNC, area under curve (AUC) 0.664 (95%-CI:0.603–0.722);LGE was found to be frequently expressed in patients with LVNC, but without sufficient power to be used as a discriminative diagnostic parameter. Both LGE and eccentricity of the left ventricle were found to be relatively solid diagnostic landmarks of complex infrastructural and functional changes within the failing heart. Left ventricle non-compaction (LVNC) is cardiomyopathy of infrequent prevalence, but associated with serious adverse prognostic outcomes , 2. TherSpecific characteristics of LVNC, such as compact (C) myocardial wall thinning, pronounced meshwork of non-compact (NC) myocardium with 2.0–2.3 ratio of NC/C and a proof of blood flow through the trabecula, taken cumulatively together make that only some cases with trabeculated myocardium fit within the LVNC cardiomyopathy –11. PropPrevious studies have shown that existence of LGE in LVNC is associated with deprived prognostic course , 19. LefPatients referred for CMR imaging of non-ischemic cardiomyopathies were prospectively included in our registry after signing an informed consent, prior to imaging procedure. Study was conducted in accordance with the Declaration of Helsinki and good clinical practice principles. Approval was obtained from the ethical board of the Hospital. There was no funding, compensations or other sources of financing, and there was no relation with medical industry. There were no additional or indirect reimbursements for patients or study personnel.cases with suspected LVNC. This sub-group of controls included patients with NC/C ratio range of 1.8–2.2:1 and trabeculations affecting >10% to <17% of LV. Control group of patients included statistically comparable sample of individuals with: no evidence of structural heart disease , hypertensive heart disease (HHD), hypertrophic cardiomyopathy (HCM), dilative cardiomyopathy (DCM) (considering exclusion of significant coronary artery disease), arrhythmogenic right ventricle cardiomyopathy (ARVD) and subacute or late phase myocarditis (inclusion of outpatients). Study did not include patients with congenital heart disease, previous heart surgery, cardiac tumors, significant pericardial effusion, primary valvular disorder  and those with coronary artery disease (having significant coronary artery disease (known stenoses >30%), positive adenosine stress test for screening of coronary artery disease, or ischemic type of late gadolinium enhancement).Patients included in this study were retrospectively recruited from a digital CMR data base , based on LVNC diagnosis, for a period of 3.75 years. Entire set of imaging studies was reanalyzed by two experienced cardiologists and a radiologist. LVNC diagnosis included the following CMR diagnostic criteria: non-compact-to-compact layer >2.3:1, thinning of the compact myocardium layer and trabeculations affecting >20% of the left ventricle , 12. TheImaging studies were performed on 1.5 T Magnetom Avanto, Siemens® , using ECG gating and breath-hold following two respiratory cycles, Body Matrix chest and spine coils. CMR protocol consisted of setting localizers, Half-Fourier Acquisition Single-shot Turbo spin Echo (HASTE) sequences, steady state free precession (SSFP) of standard heart 2-, 4- and 3-chamber planes and 6 mm stack of short axial slices (8–12 slices through ventricle), with adding of the right ventricle and its outflow tract in case of any clinical questions. In certain cases, that was followed by short tau inversion recovery (STIR) or turbo spin echo (TSE) T1 and T2 sequences dark blood, and fat saturation sequences, which was indicated prior to or during the exam, on a case-to-case basis. Gadolinium contrast was applied in a 0.2 mL/kg (0.1 mmol/kg) dose. An intravenous bolus of Omniscan®  or Dotarem®  was used in the exams, as well as late gadolinium enhancement (LGE) sequences 20–30 min following the contrast application.Postprocessing was performed on Siemens AG- NUMARIS/4, Syngo MR B17® software package , whilst volumetric analyses were done using Siemens AG- Syngo Console Argus®, by a team made of two CMR high throughput cardiologists (300–450 exams per year) and a radiologist. Standard reports included a clinical questionnaire from the referring cardiologist, medical history, interpretation of all planes, sequences, tissue sequences, volumetrics, dedicated measurements of myocardial thickness in trabecula and solid part, indirect analysis of valvular function, late gadolinium enhancement and conclusions arrived at based on the exam. Final interpretation of the results was done in accordance with the standardized myocardial segmentation, as recommended by professional associations. For the purpose of this study, geometry included eccentricity analyses in the dedicated region of the left ventricle, affected by non-compaction, and the same i.e. comparable region in the control group of patients, developed by the principal author of the study (MB). Slices from the mid to apical part  of the left ventricle short axis single slice, created parallel to mitral valve by calculating the ratio of the longest end diastolic diameter (EDD) divided by the diameter of perpendicular line (solid to solid myocardium), i.e. maximal/minimal end diastolic ratio (MaxMinEDDR).P value less than 0.05 was considered significant. Statistical analyses were done by an experienced statistician using IBM-SPSS12® v 20  MedCalc v. 12.2® for Windows  and Statistica 10® for Windows .Population and studied groups were analyzed using descriptive statistic and presented as means combined with standard deviations or numbers with percentages. Numeric variables were analyzed for differences by the Mann-Whitney U test or Kruskal Wallis. Group data analyses were calculated with Chi square or Kruskal Wallis. Connections between the studied CMR parameters and LVNC were described by Spearman Rho. Bi-nominal regression analysis was used for the studied CMR parameters and LGE existence. LVNC diagnostic value of the late gadolinium enhancement and left ventricular geometry was first calculated separately and then in head to head settings using receiver operating characteristic (ROC) curve analysis and NC/C plus NC > 20% LV as previously standardized parameters. n = 155; 60.8%) included cases with no structural heart disease and those with non-ischemic cardiomyopathy other than LVNC. Patients with LVNC that fulfilled all three CMR criteria  were included, making sample of one hundred (39.2%) consecutive patients  From those patients, only 2 cases were confirmed by addition of clinical criteria (not having >20% of trabeculations in the left ventricular mass despite having NC/C > 2.3:1). Fifty-six cases (36.1%) from the control group had clinically suspicious, but not clearly defined LVNC. Detailed data on patients and studied groups are presented in Table The study included 255 cases referred for CMR a 3.75-year period, covering 1975 exams. Control group of patients (n = 44) and basal/middle sections (n = 8) of the left ventricle, whilst the patients with no structural heart disease most commonly had no LGE imbibition.LGE was found in 133 patients (52.2%) as follows: focal mid-ventricular (MV) type was found in 35 (26.3%) cases, linear MV in 83 (62.4%) and diffuse LGE in 15 (11.3%) cases. The most common type of LGE in LVNC was linear MV, located in basal , +likelihood ratio (+LR) of 3.4 (95%-CI:2.8–4.1), −LR of 0.6 (0.4–0.9), area under curve (AUC) of 0.674 , p = 0.002 and Max-Min-EDDR 1.01 (95%-CI: 1.00–28.99), p = 0.045, while the NC/C was not significant.Using binomial regression analyzes, existence of LGE was significantly connected with following studied parameters: LV-myocardial mass = 1.01 (95%-CI: 1.00–1.02), Differences between existence of LGE in patients with LVNC and controls, with further sub-analyzes of type of LGE are presented in Tables p < 0.001. Similarly, Max-Min-EDDR of LVNC was significantly different among all the sub-studied control groups , p < 0.001. In addition, Max-Min-EDDR was significantly different between the patients with no LGE imbibition and controls, 1.09 ± 0.08 vs. 1.12 ± 0.09, respectively, p = 0.039. Figure Max-Min-EDDR was 1.11 ± 0.09 (95%-CI: 1.01–1.26), with significant difference between the patients with LVNC and controls, 1.17 ± 0.09 vs. 1.06 ± 0.05, p = 0.121).Model of receiver operating characteristic curve analysis of Max-Min-EDDR for detection of systolic function impairment (defined with LVEF < 50%) was not significant  curve analysis was used for diagnostic utility of the studied CMR parameters for establishing a LVNC diagnosis, in which NC/C > 2.3:1 and NC > 20%LV were considered as the gold standard.p < 0.001.Existing LGE had sensitivity of 52.5% (95%-CI:42.3–62.5), specificity of 80.4% (95%-CI:73.2–86.5), +LR of 2.7 (95%-CI:2.2–3.3), −LR of 0.6 (0.4–0.9), area under curve (AUC) of 0.664 (95%-CI: 0.603–0.722); p < 0.001.MaxMinEDDR being >1.10 (i.e. exactly 1.0975) had sensitivity of 95.0% (95%-CI:88.7–98.4), specificity of 82.6% (95%-CI:75.7–88.2), +LR of 5.0 (95%-CI:5.0–5.9), −LR of 0.1 (0.02–0.2), area under curve (AUC) of 0.917 (95%-CI: 0.876–0.948); p < 0.001, as shown in Fig. Comparison of ROC curves for the studied diagnostic parameters of LVNC was as follows: ROC-AUC NC > 20%LV) = 0.985 (95%-CI: 0.961–0.996), ROC-AUC (NC/C > 2.3:1) = 0.983 (95%-CI: 0.959–0.995), ROC-AUC (MaxMinEDDR) = 0.909 (95%-CI: 0.866–0.941) and ROC-AUC (linear-MV-LGE) = 0.664 (95%-CI:0.603–0.722). There was also a significant difference between ROC AUC for LGE and eccentricity, ΔAUC0.244 (95%-CI:0.175–0.314), 0%LV = 0.gold standard” for LVNC diagnosis using CMR was defined by thinning of compact LV wall, NC/C > 2.3:1 and NC > 20%LV [This study analyzed the existence and morphology of LGE imbibitions, their connections with left ventricle geometry, as well as their diagnostic utility for LVNC. The “ > 20%LV . In thes > 20%LV .Nearly a half of the studied patients with LVNC had LGE imbibition, where the latter attained specificity and sensitivity of 55–60% as a diagnostic parameter. Proportion of patients with LGE in our study was in line with previous reports on the left ventricle non-compaction cardiomyopathy . The mos, affected with non-compaction [Cases with LVNC displayed structural rearrangements in terms of geometric eccentricity of mid to apical short axis sectionsmpaction . Eccentrmpaction , 32. In mpaction .Geometry of the left ventricle was found to be connected with functional prognostic parameters such as systolic function or left atrial size . The latOne must point out that these are preliminary investigations, focused on diagnostic utility of a single imaging modality scrutinized according to guidelines-based diagnostic criteria that are not perfect. The study was performed in the only large-volume tertiary center specialized for CMR in our country, on a selected population of cases with cardiovascular diseases and previous cardiovascular diagnostic and/or therapeutic workup. Retrospective study settings and selection of controls also might conceal limitations. Prospective validation, using multicentric settings, with inclusion of further clinical parameters, such as patients’ comorbidities and follow up of major adverse event rates is necessary to increase reproducibility.In conclusion, late gadolinium enhancement was found to be frequently expressed in patients with LVCN. These imbibitions were of insufficiently defined power to be used as a specific diagnostic parameter, in the context of LVNC. On the other hand, LGE was found to be a relatively valuable diagnostic landmark of complex infrastructural and functional changes within the failing heart. It correlated only mildly with left ventricle geometry in dedicated regions, where the latter was found to be a very promising novel LVNC diagnostic parameter. Geometric eccentricity associated with LVNC had a fine grade of diagnostic utility to tell apart the cases with non-ischemic cardiomyopathies from those with structurally normal heart. Segmental eccentricity was also in correlation with infrastructural and functional changes that even stretched beyond mid-apical regions, i.e. to the whole left ventricle and both atria. Changes of left ventricle geometry in addition to tissue characterization by late gadolinium imbibition seem to have potential for further contribution to the diagnostic imaging of the failing heart.


These significant correlations between HRV and CMR-T2* and LVEF in TDT confirmed the beneficial role of HRV as a potential early screening tool of cardiac iron overload in thalassemia patients, especially in a medical center in which CMR T2* is not available. A larger number of TDT patients with cardiac iron overload are needed to confirm this finding.Early detection of iron overload cardiomyopathy is an important strategy for decreasing the mortality rate of patients with transfusion-dependent thalassemia (TDT). Although cardiac magnetic resonance (CMR) T2* is effective in detecting cardiac iron deposition, it is costly and not generally available. We investigated whether heart rate variability (HRV) can be used as a screening method of iron overload cardiomyopathy in TDT patients. HRV, evaluated by 24-h Holter monitoring, non-transferrin bound iron (NTBI), serum ferritin, left ventricular (LV) ejection fraction (LVEF), and CMR-T2* were determined. Patients with a cardiac iron overload condition had a significantly higher low frequency/high frequency (LF/HF) ratio than patients without a cardiac iron overload condition. Log-serum ferritin ( Thalassemia is a hereditary hematologic disorder resulting from abnormal production of the globin chains of hemoglobin. These changes can cause a variety of clinical pictures, from normal red blood cell concentration to stillbirth due to severe hemoglobinopathy. Transfusion-dependent thalassemia (TDT) is the most severe form of thalassemia in which regular red blood cell transfusions are a necessity for survival . A definSeveral methods including the measurement of both biochemical and radiological parameters have been proposed for use as screening tools for iron overload cardiomyopathy in TDT. Serum ferritin is one of the biomarkers frequently used for iron overload detection ,7. HowevHeart rate variability (HRV), an easily performed, reliable, low cost, and non-invasive cardiac electrophysiologic test, can be used to evaluate cardiac autonomic function in patients with heart disease , includiThe study protocol was approved by the Institutional Ethics Committee of the Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand and were in accordance with the current version of the Helsinki Declaration. The inclusion criteria included: being diagnosed with TDT, having regular red blood cell transfusions at least once a month after diagnosis, being in the age range from 18 to 50 years and having no infectious diseases or acute illnesses during the investigation. The exclusion criteria included patients with a contraindication to MRI, and clinical evidence of other secondary causes of pulmonary hypertension, including HIV infection, hepatitis virus infection, collagen vascular diseases, cirrhosis, chronic obstructive airway diseases, and acquired heart disease associated with pulmonary hypertension. Patients with neurological diseases causing dysautonomia, severe depression, or chronic inflammatory diseases as well as patients, who were the known cases of the disease that can be the causes of diastolic and systolic cardiomyopathy  were also excluded. Medical records of the patients were reviewed to amass epidemiological data, transfusion history, and comorbidities. The body weight, height, and body mass index (BMI) were measured in each patient. Routine laboratory tests, serum ferritin, plasma NTBI, echocardiography, 24-h Holter ECG recording for HRV analysis and CMR T2* were investigated and analyzed at the time of entry. Serum ferritin and plasma NTBI were determined using standard techniques as described previously ,22.Standard 2D and transthoracic Doppler echocardiography was performed at rest in all enroled patients with Philips iE33 . Left ventricular (LV) average S.D. of all 5-min R–R intervals were measured, and LV ejection fraction (LVEF), stroke volume, cardiac output, and fractional shortening (FS) were determined based on the calculation of LV volumes by the method of discs, following the recommendations by the American Society of Echocardiography (ASE), and using apical two- and four-chamber views to measure cardiac function ,24. Impa2). The designated physician, who operated and fitted the Holter monitor to the patients, was blinded to the patient information. The subjects were fitted with the Holter monitor after blood sample collection at the Holter unit of the Faculty of Medicine, Chiang Mai University. In the present study, none of the patients included in the study took medication such as β-blockers, calcium channel blockers, statins, and ACE inhibitors, which could affect the HRV [HRV was evaluated using the SEER Light Holter system . A lead II ECG was continuously recorded for 24 h. Prior to the HRV measurement, either exercise or caffeine consumption was prohibited in all the participants. The computer software MARS version 7, GE Healthcare, Milwaukee, WI, U.S.A., was used to scan for rhythm disturbance and to detect and label each QRS complex. Excessive noise and artifacts were noted, and ectopy was quantitated. The time-domain analyses including average heart rate, average R–R intervals (NN), standard deviation (S.D.) of the R–R intervals over a 24-h period (SDNN), S.D. of all 5-min mean R–R intervals (SDANN), average S.D. of all 5-min R–R intervals (ASDNN), the percentage of R–R intervals with more than 50-ms variation (pNN50), and the square root of mean squared differences of successive R–R intervals (rMSSD). The frequency domain analyses were determined with the same analytical software using Fast-Fourier transform analysis. The obtained frequency domain indices were the total power (0–0.4 Hz), high-frequency power  spectral density, low-frequency power  spectral density, and very LF (0.003–0.04 Hz) spectral density. Total power expresses the magnitude of the entire HRV, whereas HF power reflects the parasympathetic tone, and LF power indicates the sympathovagal interactions . These p the HRV .Magnetic resonance acquisition was performed using a 1.5-T MR scanner , with an eight-channel body array. For the measurements of myocardial iron overload, we used a T2 gradient-echo multi-echo sequence . A single mid ventricular short-axis view of the left ventricle was acquired at eight echo times (TEs)  in a single end-expiratory breath-hold. CMR T2* analysis was performed on a workstation  using commercial analysis software . According to the previous study, the 95% confidence interval of a normal CMR T2* value (>20 ms) was assessed ,27. The ttest. The correlations amongst HRV, biochemical markers, echocardiographic parameters, and CMR T2* were determined using the Pearson’s correlation coefficient. The multivariate linear and binary logistic regression analysis, forward likelihood method, as well as the receiver operative characteristic (ROC) curve were applied to determine independent predictive factors of CMR T2* values. Statistical analyses were performed using SPSS version 13.0 for Windows . A P-value of less than 0.05 was considered statistically significant.Categorical variables were described using percentages of its frequency. Normally distributed numerical variables were presented using arithmetic means and S.D. Non normally distributed variables were modified by taking a natural logarithm, and then presented using geometric mean and S.D. Differences of parameters between patients with and without cardiac iron overload were compared using the independent Student’s P=0.028 and 8.01 compared with 7.26, P=0.010, respectively). On the other hand, there was no difference in clinical characteristics , Hb, plasma NTBI, LVEF, or the other HRV parameters between these two groups.Sixty-six TDT patients were enroled in the present study. However, since 7 patients were not evaluated by CMR T2*, only 59 TDT patients were included in a statistical analysis. Nineteen patients (32.2%) were diagnosed with homozygous β-thalassemia. Thirty-eight patients (64.4%) were diagnosed with β-thalassemia/Hemoglobin E. One patient was diagnosed with AE Bart’s disease and the other patient was diagnosed with AE Bart’s Constant Spring (CS) disease. Clinical and biochemical characteristics, echocardiographic and HRV parameters, as well as CMR T2* values of the patients are summarized in r = −0.286, P=0.021). Log-serum ferritin and plasma NTBI also had a significant negative correlation with CMR T2* values . However, only the LF/HF ratio parameter of HRV did have a significant negative correlation with LVEF.The correlation analyses between biochemical markers, echocardiographic data, HRV parameters, and CMR T2* values were determined. None of the clinical characteristics showed a correlation with biochemical markers, HRV parameters, or CMR T2*. None of the HRV parameters showed a significant correlation with log-serum ferritin or plasma NTBI. As regarding the correlation between HRV parameters and CMR T2*, only the LF/HF ratio had a significant negative correlation with CMR T2* values . Furthermore, the area under ROC curve was used to demonstrate the predictive accuracy of the parameters. The predicted area under the ROC curve of the LF/HF ratio was in the good level  while the predicted area under the ROC curve of log-serum ferritin and plasma NTBI were in the fair  and the poor levels , respectively. In addition, LF/HF ratio more than 1.49 was the best predictor for CMR T2* ≤20 ms, with 83% sensitivity and 50% specificity and its positive and negative predictive values were 16 and 96%, respectively  cases  or pediaThe prevalence of cardiac iron overload in the present study was 8.47%, which was lower than that reported in a recent study. Aydinok et al.  reportedr = –0.227 and P=0.026), with an odds ratio of 8.71 [th year, corresponding with a development of sympathetic nervous system [th year, LF/HF ratio gradually decreased over time, reflecting an increase in parasympathetic activity [In the present study, only the LF/HF ratio, which is a frequency-domain parameter of HRV, was negatively correlated with cardiac iron overload status. This finding emphasized the important findings from our previous studies. In non-TDT patients, we have previously demonstrated that there was a significant negative correlation between the LF/HF parameters of HRV  [Interestingly, this is the first study demonstrating the correlations between HRV parameters and CMR T2*, as well as LVEF in adult TDT patients. Only the LF/HF ratio parameter of HRV, but not CMR T2*, was positively correlated with LVEF in the present study. This finding was different from the results of the study of Anderson et al. (2001) , which d, P=0.7) . Since tThere were several limitations in the present study. First, there was a small sample size in the present study. Second, there was no healthy control group or an additional group with a disease associated with cardiac iron overload from another cause, such as hereditary hemochromatosis. However, because this type of disease is extremely rare in our population, the addition of this group is not possible for the present study. Next, since there were only 5 out of 59 patients who had cardiac iron overload (CMR-T2* ≤20 ms), the correlation found between HRV and cardiac iron overload had the weakest statistical power. Future studies with larger number of TDT patients with cardiac iron overload are needed to confirm this finding. Further prospective longitudinal cohort studies, with larger sample sizes, from more centers, which may include patients with other causes of iron overload and more patients with positive cardiac iron overload, are needed to increase the confidence in the results.The significant correlations between LF/HF ratio of HRV and CMR-T2* and LVEF in TDT patients indicate that HRV might have the beneficial role as a potential predictor of cardiac iron overload as well as LV contractile function in this group of patients. However, due to weak correlation and small studied population in the present study, larger population of TDT patients with positive cardiac iron overload is needed to confirm this finding.