Ursus arctos) during late hibernation and in early summer. Mean heart rate was 26 beats per minute (standard deviation (SD): 8) during hibernation vs 71 (SD: 14) during active state. All left ventricular (LV) systolic and diastolic measures were decreased during hibernation: mean ejection fraction: 44.2% (SD: 6.0) active state vs 34.0 (SD: 8.1) hibernation, P = 0.001; global longitudinal strain: −11.2% (SD: 2.0) vs −8.8 (SD: 3.3), P = 0.03; global longitudinal strain rate: −0.82 (SD: 0.15) vs −0.41 (SD: 0.18), P < 0.001; septal e’: 9.8 cm/s (SD: 1.8) vs 5.2 (SD: 2.7), P < 0.001. In general, measures of total myocardial motion  were decreased to a lesser extent than measures of myocardial velocities. In the hibernating brown bear, cardiac adaptation included decreased functional measures, primarily measures of myocardial velocities, but was not associated with cardiac atrophy. Understanding the mechanisms of these adaptations could provide pathophysiological insight of human pathological conditions such as heart failure.During six months of annual hibernation, the brown bear undergoes unique physiological changes to adapt to decreased metabolic rate. We compared cardiac structural and functional measures of hibernating and active bears using comprehensive echocardiography. We performed echocardiography on 13 subadult free-ranging, anaesthetised Scandinavian brown bears ( Ursus arctos) has developed remarkable physiological adaptations. Each fall with a shortage of food and decreasing ambient temperature, the bear enters a 5–7 months hibernation period. During this time, the bear does not eat, drink, defecate or urinate and is only minimally physical active1. In addition, and contrary to most other hibernators, the Scandinavian brown bear is a shallow hibernator with a certain amount of alertness during the entire hibernation period and only a slight decrease in body temperature to approximately 33–34 °C2. Despite this extreme exposure the bear stays apparently free from any pathophysiological states associated with prolonged physical inactivity and avoids loss of muscle and bone mass5.To cope with the harsh environment during winter, the Scandinavian brown bear (6 and to optimise energy consumption the cardiovascular system adapts accordingly. Previous studies in American brown and black bears (Ursus americanus) have suggested that cardiac adaptations during hibernation are characterized by a marked decrease in cardiac output caused by profound bradycardia with extreme respiratory sinus arrhythmia and a preserved left ventricular (LV) ejection fraction. Hibernation is also characterized by a decrease in LV mass/volume ratio indicating some degree of cardiac remodelling to adapt to the altered hemodynamic state9. We have previously documented low flow hemodynamics in the hibernating Scandinavian brown bear by reporting reduced cardiac output and presence of spontaneous echo contrast10.To conserve energy, the bear’s oxygen demand is reduced to approximately 25% of the active state11. Cardiac implications of immobility documented in bed-rest studies12 and studies of astronauts returning from space13 have suggested cardiac atrophy to occur in response to immobility.On the contrary, even a short period of immobility in humans can lead to a number of adverse effects including a reduction in muscle and bone mass, decubitus ulcers and thromboembolic eventsOver the past decade, several of echocardiographic modalities such as tissue Doppler imaging and 2D speckle tracking have been developed allowing detection of subtle changes in myocardial function. These methods allow assessment of LV myocardial tissue velocities and tissue deformation with high accuracy and have not been employed in a hibernating bear model previously. Additionally, previous studies examining cardiac structure and function have been conducted in hibernating bears that were hand-raised or in bears that were only examined during the hibernation period. Thus, we aimed to perform a comprehensive cardiac structural and functional evaluation in hibernating vs active free-ranging Scandinavian brown bears using tissue Doppler and 2D speckle tracking echocardiography and interpret the findings in a human context. Evidently, identification of the factors responsible for tissue preservation during hibernation has potential to impact human medicine in a variety of fields including cardiogenic shock, thromboembolism and space medicine.https://bearproject.info/) which allowed us to locate the bears in their dens during hibernation and in their habitat during the active state. Bears were immobilised in late February and again in June/early July from 2014 to 2018. During the winter captures, bears were located in their dens and anaesthetised with a mixture of medetomidine, zolazepam, tiletamine and ketamine. During summer captures, the same bears were darted from a helicopter with a mixture of medetomidine, zolazepam and tiletamine at 2–4 times the winter dose to account for the metabolic rate during active state14. Both winter and summer, ketamine could be administered if the effect of anaesthesia was decreasing. Doses administered and weight of each of the bears is shown in Supplemental Table We performed comprehensive echocardiography, including tissue Doppler imaging and 2D speckle tracking in free-ranging, subadult Scandinavian brown bears during the hibernating and active state in Dalarna, Sweden. All bears were marked with GPS collars and VHF transmitters as part of the Scandinavian Brown Bear Research Project 3]} + 0.6 g)15. LV dimensions were measured in end-diastole in the parasternal long-axis view and indexed according to estimated body surface16 to account for differences related to the growth of the subadult animals. 2D-speckle tracking strain and strain rate were measured in the apical 4-, 2- and long axis view in a total of 18 segments. The region of interest was traced by a semi-automated process and adjusted manually to cover the entire LV wall after visual inspection. Segments that were not traced by the software were excluded from the analyses. The mean values of mid-ventricular global longitudinal strain and strain rate from the three projections reported by the software were used in this study. An example is shown in Fig. 15. Right ventricular fractional area change was calculated as (end-diastolic area – end-systolic area)/end-diastolic area, measured in a modified apical 4-chamber view with a focus on the right ventricle. Tricuspid annular plane systolic excursion (TAPSE) was also obtained in this view with use of M-mode. All measurements were obtained in all bears except right ventricular area measurements that were not analyzable in one bear. Heart rate was the mean of 3 measurements performed during the 2D speckle tracking analyses. An experienced echocardiographer (PGJ) performed all echocardiographies and post-processing.We performed echocardiography in the field on bears in a left lateral recumbency position. We used a General Electrics Vivid i  with 5S-RS and 3S-RS probes to obtain 2D images, M-mode, pulsed, continuous wave and tissue Doppler echocardiography. We used GE EchoPAC software  to perform post-processing of the echocardiograms. Three apical views  were recorded and, where possible, a parasternal long-axis view was also obtained. Following the European Association of Cardiovascular Imaging guidelines, LV mass was approximated with the Cube formula that has been validated in humans http://www.R-project.org).The values are presented as mean ± standard deviation (SD), and differences between hibernating and active state were compared using a paired t-test. P-values less than 0.05 were considered statistically significant. The calculations were made using the statistical software package ‘R’, version 3.4.3 (64 bit)  in the active state versus 40.5 kg (SD: 10.9) during hibernation (p = 0.02). Heart rate was considerably lower during hibernation, 26 beats per minute (SD: 8) vs 71 (SD: 14) during active state (p < 0.001).motion were only modestly affected with a 23% relative reduction in LV ejection fraction and 21% reduction in global longitudinal strain, the measures of myocardial velocities were reduced to a larger extent - global longitudinal strain rate by 50% and septal and laterals’ by 39% and 45%, respectively. In contrast to the LV measures, neither left atrial structure nor function  were significantly altered during the active state. LV diastolic measurements, Table The echocardiographic measurements are presented in Table We have examined cardiac adaptations to the annual hibernation in free-ranging Scandinavian brown bears using contemporary, comprehensive echocardiography. While there was no evidence of structural adaptation such as atrophy during hibernation, we found that both left and right ventricular systolic and LV diastolic function were reduced during hibernation. Interestingly, using advanced measures of cardiac deformation and tissue velocities, we found that the relative decrease in function was largest for velocity measures such as global longitudinal strain rate, s’ and e’, compared to the volumetric and maximum deformation measures. This indicates that cardiac adaptation affects tissue velocities more than the actual magnitude of contraction. Of note, we did not find any difference in atrial size nor function  and only a borderline change in early and late diastolic relative contribution to LV filling expressed as E/A ratio, e’/a’.21. Though the bear shares similarities to patients with heart failure, including reduced ejection fraction and myocardial velocities, these are not associated with any pathophysiological symptoms or prognosis in hibernating bears. In heart failure, decreased left and right ventricular function is associated with cardiac remodelling as a compensatory mechanism. In the early stages, heart failure with preserved ejection fraction is associated with increased filling pressures leading to pressure increase in and dilation of the left atrium. At a later stage in heart failure with reduced ejection fraction, to compensate for decreased stroke volume, LV remodelling including increasing volumes and wall thickness ensure to maintain adequate stroke volume and cardiac output22. According to our results, the bear’s heart does not remodel as a compensatory mechanism to decreased myocardial function indicating perfect adaptation during hibernating. We believe that the reduced function is not accompanied by an increase in filling pressures because the cardiovascular system during hibernation is a low flow system as we have previously described10.To the best of our knowledge this study is the first to demonstrate considerably reduced LV myocardial velocities using new, sensitive measures, of myocardial function, i. e. tissue Doppler imaging and 2D speckle tracking imaging in hibernating bears. In humans, heart failure – defined as a chronic condition in which the heart’s ability to pump blood is unable to meet the tissue’s oxygen demands at normal filling pressures – is also characterised by decreased myocardial velocities that have consistently shown to be associated with poor prognosis2+ released from the sarcoplasmic reticulum during contraction and sensitivity of myosin filaments to Ca2+ 23. Also, previous studies have suggested that body temperatures below 30 °C are required to effectively alter Ca2+ dynamics25 and, therefore, temperature alone is unlikely to be responsible for the cardiac adaptations found as the hibernating brown bear keeps a temperature at approximately 33 °C during hibernation2. As a consequence, our study indicates, that handling of Ca2+ and the sensitivity to Ca2+ in contractile proteins are potentially involved in the myocardial adaptations in the hibernating brown bear.The fact that the bear is able to modulate contractile forces during hibernation underlines the prospects of the hibernating bear heart as a useful model of understanding heart diseases in humans. Revealing the mechanisms of these modulations could have potentially considerable benefits in human medicine. In our study, the myocardial velocities were more decreased compared to volumetric and deformational measures. In the cardiac myocyte, the force generated is dependent on intracellular Caet al. conducted research on captive, hibernating brown bears. In the first study, they found no difference in septal thickness8, whereas in the second, bears showed reduced septal thickness26. Both studies, however, reported unaltered LV end-diastolic diameters during hibernation. Laske et al. studied the structural changes in black bears from early through late hibernation period and found no differences in LV wall thicknesses7.Our finding of a preserved cardiac structure is in accordance with previous studies on cardiac structure in hibernating bears. In 2003 and 2008 Nelson et al., who initially also reported a decreased LV ejection fraction in anaesthetised captive brown bears8, but later reported preserved ejection fraction in unanaesthetised captive brown bears9. An apparent reason for this discrepancy could be the use of anaesthesia in our bears. In Nelson’s study of anesthetised bears, a cocktail of tiletamine and zolazepam was administered to induce and isoflurane was used to sustain anesthesia during the examination. The isolated effect of isoflurane on the bear heart is unknown, but in rabbits isoflurane lowers blood pressure and cardiac function27. In humans, on the other hand, isoflurane only has limited effect on cardiac function28, though this might be age dependent29. Thus, the reduced ejection fraction in anesthetised bears in Nelson’s early study might be caused by the use of isoflurane but this remains speculative. Another reason for the discrepancy could also be due to differences in image acquisition and calculations of LV ejection fraction. In our study, we used Simpson’s biplane method which is the currently recommended method in clinical practice in humans15 and Nelson et al. used area length method from the parasternal long axis view . The atrial function was unaltered during hibernation in our study. This result is in discrepancy with the findings of Nelson et al. who described decreased atrial function – by both 2D and strain echocardiography - during hibernation and ascribed this as a consequence/adaptation to increased LV stiffness interpreted as increased isovolumetric relaxation time30. Isovolumetric relaxation time was also dramatically increased during hibernation in our study. However, based partly on our findings of altered myocardial velocities, we believe that this is mainly caused by other factors than increased myocardial stiffness: isovolumetric relaxation time is a marker of decreased diastolic function and is affected in a number of diseases, but is also dependent of end-systolic left atrial pressure and shortens with increasing left atrial pressure and vice versa31. Beyond this, LV relaxation rate is determined by reuptake of Ca2+ in the sarcoplasmic reticulum of the myocyte. This process occurs through the action of sarco(endo)plasmic reticulum Ca2+ ATPase which is highly sensitive to adrenergic stimuli32. Thus, with respect to our previous finding of low cardiac output in hibernating brown bears, we believe that the prolonged isovolumetric relaxation time is caused by low end-systolic left atrial pressure as well as a presumed minimal adrenergic state in bears during hibernation.In our study, all systolic measures were reduced during hibernation, including measures of myocardial velocities such as global longitudinal strain, strain rate and s’ that were relatively more reduced than measures of total cardiac motion such as LV ejection fraction and global longitudinal strain. Our results contrast findings of Nelson 34. In the search for innovative treatments targeting fatty acid metabolism in heart failure, knowledge of adaptations in metabolism during hibernation might prove useful35. Latest could be investigated using injected tracers that are examined either directly from blood samples from cardiac catheterization33 or by positron emission tomography36. At present, Ca2+ metabolism is already an established target in heart failure therapy in humans with the agent levosimendan which is a Ca2+-sensitizer acting through binding to the cardiac troponin C molecule – a modulator of force of contraction in the cardiomyocyte37. However, further knowledge of the bear’s possible ability to effectively control Ca2+ transfer? is essential for providing insights into the mechanisms required to effectively control this process.We have demonstrated profound changes in cardiac function during hibernation in Scandinavian brown bears. The characteristics of myocardial metabolism during the hibernating state is unknown. Free fatty acid oxidation is responsible for approximately 70% of myocardial energy expenditure in the healthy human heart and up to a 70% decrease in free fatty acid oxidation has been observed in the failing heart accompanied by decreased substrate flexibilityA strength of this study is that we studied free-ranging Scandinavian brown bears in their natural habitat, including natural denning behaviour and denning physiology. Also, we examined the highest number of hibernating and active bears reported to date using echocardiography. A significant limitation is that we used bears anaesthetised with agents possibly affecting cardiac functional measures. This may explain the slightly depressed LV function during active state although no previous studies have established average values of LV ejection fraction using the gold standard Simpson’s biplane method and global longitudinal strain in unanaesthetised active brown bears.38, the use of ketamine would theoretically cause changes opposite to those observed in this study. Additionally, during anaesthesia, we used doses that were titrated based on careful monitoring according to the depth of anaesthesia during both summer and winter captures. Moreover, we found no consistent correlation between dose of the anaesthetic agents and the cardiac measures (data not shown). On the other hand, anaesthesia allowed us to examine the bear heart from the apical position by applying firm pressure to the thoracic wall and slightly displace the sternum which is unlikely to be possible in wake bears. By doing this, we could obtain reliable Doppler measurements  that are otherwise angle sensitive.Ketamine was only used on a routine basis during winter captures and since ketamine is believed to have centrally mediated sympathomimetic effects2+ transfer handling during hibernation. Identification of factors responsible for the remission of decreased cardiac functional measures could have implications for the management of human patients with a number of conditions including heart failure.We used comprehensive echocardiography to characterise cardiac adaptations in hibernating brown bears. While we found no evidence of cardiac atrophy during hibernation, we demonstrated a decrease in functional measures. The measurements of cardiac velocities changed the most, which may indicate changes to CaSupporting Information.Supporting Information 2.


Stenotic aortic valve disease (AS) causes pressure overload of the left ventricle (LV) that may trigger adverse remodeling and precipitate progression towards heart failure (HF). As myocardial energetics can be impaired during AS, LV wall stresses and biomechanical power provide a complementary view of LV performance that may aide in better assessing the state of disease.Using a high‐resolution electro‐mechanical (EM) in silico model of the LV as a reference, we evaluated clinically feasible Laplace‐based methods for assessing global LV wall stresses and biomechanical power.N = 4 in silico finite element (FE) EM models of LV and aorta of patients suffering from AS. All models were personalized with clinical data under pretreatment conditions. Left ventricle wall stresses and biomechanical power were computed accurately from FE kinematic data and compared with Laplace‐based estimation methods, which were applied to the same FE model data.We used Laplace estimates of LV wall stress are able to provide a rough approximation of global mean stress in the circumferential‐longitudinal plane of the LV. However, according to FE results, spatial heterogeneity of stresses in the LV wall is significant, leading to major discrepancies between local stresses and global mean stress. Assessment of mechanical power with Laplace methods is feasible, but these are inferior in accuracy compared with FE models. The accurate assessment of stress and power density distribution in the LV wall is only feasible based on patient‐specific FE modeling. AVDaortic valve diseaseEMelectro‐mechanicalFEfinite elementHFheart failureIHPinternal mechanical heart powerIVCisovolumetric contractionIVRisovolumetric relaxationLVleft ventriclePVpressure‐volume.1In stenotic aortic valve disease (AS), elevated pressure gradients impose a higher load upon the left ventricle (LV). Under such conditions, the pressure produced by the LV must increase in order to achieve an adequate cardiac output that meets the metabolic demands. This requires the LV wall to generate higher active forces, which can be achieved either by an increase in wall stresses or a change in ventricular shape and mass. Such pressure overload conditions, if persistent for long enough, trigger adverse remodeling processes, eventually precipitating progression towards heart failure (HF).Another method used to determine the work performed by the muscle is pressure‐volume (PV) relations. These are usually measured using conductance catheter techniques. However, these procedures are invasive, time‐consuming, and expensive. Alternatively, PV loops are measured with 3D echo or MRI,Despite the diagnostic potential of markers based on wall stresses and expended mechanical power, this assessment has not evolved towards a routinely used diagnostic tool in the clinic mainly due to methodological limitations. Attempts to address this relied upon different variants of Laplace law, which require the acquisition of only a small number of measures representing LV cavity volume, wall width, and pressure., 9 HowevTo evaluate the accuracy of Laplace analysis for estimating global wall stresses and mechanical power in the LV, we employed four FE‐based EM LV models that have been previously fitted and validated with clinical data22.1Data from four AS patients with clinical indication for aortic valve treatment, all preceding a cardiac magnetic resonance study, were used Table . Stenoti2.2f0(x), which coincides with the prevailing orientation of the myocytes at location x, the sheet axis s0(x), and the sheet‐normal axis n0(x). The mechanical deformation of the tissue is described by Cauchy equation of motion under stationary equilibrium assumptions leading to a quasi‐static boundary value problem: For a given pressure p(t), find the unknown displacement u such that t ∈ . By Ω, we denote the deformed geometry, and by Γ = ∂Ω, we define its boundary with Γ=ΓD‾∪ΓH‾∪ΓN‾ and ΓD>0. The normal outward vector of Γ is denoted by n. The total Cauchy stress tensor σ refers to the sum of a passive stress tensor σpas and an active stress tensor σact. That is, σ=σpas + σact with F is the deformation gradient, Ψ is the strain energy function, f0 is fiber orientation in the reference configuration, J =  det F is the Jacobian, C = F⊤F is the right Cauchy‐Green strain tensor, and Sa is the scalar active contractile stress generated by the myocytes acting along f0.The ventricular myocardium was modeled as a nonlinear, hyperelastic, nearly incompressible, and anisotropic material with a layered organization of myocytes and fibres that is characterized by a right‐handed orthonormal set of basis vectors., 18 ThesE‾=12(J−23C−I) is the modified isochoric Green‐Lagrange strain tensor, or the isotropic Demiray modelC‾=J−23C the modified isochoric right Cauchy‐Green tensor. In both models, Equations κ, which serves as a penalty parameter to enforce near incompressibility, was chosen as κ = 650 kPa.The passive behavior of myocardial tissue was modeled using two material models, either the transversely isotropic Guccione et al model,ΨGu(C)=κ2ray modelΨDem(C)=κSpeak is the peak isometric tension, φ(λ) is a nonlinear function dependent on fiber stretch λ=Ff0 describing the length‐dependence of active stress generation, ts is the onset of contraction, τc is the upstroke time constant, tdur is the active stress transient duration, and τr is the downstroke time constant. This simplified model allows efficient fitting to patient data, as the parameters for peak stress, Speak, and time constant of contraction, τc, and twitch duration, tdur, are related to the two clinical key parameters of interest, peak pressure, and maximum rate of pressure increase, in an intuitive manner.A simplified phenomenological contractile modelu serve as input then in a postprocessing procedure to evaluate wall stresses σ and to compute internal power expended by the LV The wall material is isotropic.(A2)r, and outer radius, R.The shape is a symmetric spherical shell with inner radius, (A3)h = R − r, is sufficiently small, that is, the wall thickness to radius of curvature ratio is small, h/r ≪ 1.The thickness of the wall, To verify the FE‐based calculation of stress‐derived metrics, a geometrically simple and well‐studied benchmark problem was chosen for which circumferential hoop stresses can be found from Laplace law under the following assumptions:(A1), nonspherical in shape (A2), and thick‐walled (A3) with h/r≈1, differences between Laplace analysis and FE computation are to be expected. Three configurations were considered, an ideal thin‐walled spherical shell, Sph5, which complies with all assumptions (A1)‐(A3) and thus can serve as a reference for FE validation, and two thicker‐walled spheres, Sph25 and Sph150, where assumption (A3) is increasingly violated. Geometries and mechanical boundary conditions are illustrated in Figure Since all these assumptions are violated in the LV which is orthotropic A, nonspher = 15.0 mm in all models with h varying from h = 0.5 to h = 15.0 mm in Sph5 and Sph150, respectively. The choices for Sph150 are representative of the h/r ratios found in the LVs of patients in this study (Table (A1), the nonlinear isotropic material law stated in Equation a = 10 kPa and b = 8. Passive inflation experiments were performed by solving σact≡0 and applying a pressure p in the range from 0 to 4 kPa to the endocardial surface, Γendo, which covers the range of pressures observed in vivo during diastole. Pressure at the epicardial surface, Γepi, was assumed to be zero. To render the solution of this pure Neumann problem unique, displacement boundary conditions were enforced at the intersections of the Cartesian axes with the epicardial surface by restricting displacements to the respective intersecting axes . Segmentations were smoothed and upsampled to a 0.1‐mm isotropic resolution.http://www.cgal.org/) with a target discretization of 1.25 mm in the LV myocardium and 1 mm in the aortic wall. For the transversely isotropic Guccione material model, see Equation Finite element meshes of the LV anatomy and aortic root were generated from 3D whole heart MRI acquired at end diastole (ED) with 1.458 × 1.548 × 2 mm resolution at the German Heart Center Berlin. Multilabel segmentation of the LV myocardium, LV cavity, and aortic lumen was done using the ZIB Amira software (2.4.2p(Vcav), was used as target to steer the fitting of constitutive parameters. In absence of accurate measurements of EDP, we refrained from fitting all material parameters to p(Vcav). Rather, default values for the parameters bf = 18.48, bt = 3.58, and bfs = 1.627 were used as reported in the literature,a was adjusted individually for each patient. With a given data point  a was fitted to minimize the difference in stress‐free residual volume, V0,dia, between model and Klotz curve. This yielded values for a of 0.5, 0.65, 0.5, and 0.5 for the cases LVA, LVB, LVC, and LVD, respectively.To remove rigid body motion and provide physiological boundary conditions that allow a vertical movement of the LV base, as observed in vivo, mechanical boundary conditions were applied by fixing the terminal rim of the clipped aorta Figure A and resVcav(t), determined from Cine‐MRI with a temporal resolution of 45.28, 29.63, 32.00, and 35.29 ms for LVA, LVB, LVC, and LVD, respectively. Continuously monitored invasive pressure recordings were not available, as catheterization was not indicated. Peak pressure in the LV was determined by estimating peak pressure in the aortic root from cuff pressure measurements and by determining the pressure drop at peak flow across the aortic valve from ultrasound flow measurements using Bernoulli law.Z, comprising the flow resistance of aortic valve, Zv, and the characteristic input impedance of the aorta, Zc, as well as resistance R and compliance C of the arterial system were fit to reproduce estimated LV peak pressure using measured volume traces Vcav(t) as input.A three‐element Windkessel model of LV afterload was used to provide the pressure‐flow relationship during ejectionSpeak; time constant of contraction, τc; and twitch duration, tdur, were adjusted manually to fit peak pressure, p^LV, duration of pressure pulse and flow. Because of the intuitive link of the active stress model given in Equation p^LV, were matched within a margin of error of ±5%. Clinical input data and fitted model parameters are summarized in Table In a final step, active mechanical properties were fit to the same hemodynamic data used for fitting the afterload model. A reaction‐eikonal model was used to generate activation sequences and simulate action potential propagation in the LV.2.5u using constitutive material models based on ex vivo experimental data that link stresses to strains. In the FE model, stress tensors σ are computed by evaluating Equations Sph5, Sph25, and Sph150, the stress tensor simplifies. Because of the assumption of isotropy in (A1) and symmetry in (A2), any solution, if expressed in a spherical coordinate system, must also be symmetric. Quantities computed in the FE Cartesian coordinate system are recast in spherical coordinates as defined in Figure P. For the total Cauchy stress tensor σ, we obtain P =  and r∈R+,θ∈,ϕ∈[0,2π).Stresses can be computed from deformations u being the FE solution at time t and ⋆ ∈ {r,θ,ϕ}.While all quantities in the spherical models must be perfectly symmetric, this is not necessarily the case in the FE solutions. Depending on spatial resolution and boundary conditions, a minor numerical jitter around mean values will inevitably occur. For comparing FE with Laplace analysis, averaged mean quantities were therefore computed over the entire domain by σcirc = σϕϕ = σθθ, and with h ≪ r, radial stresses can be assumed to be negligible relative to circumferential hoop stresses, that is, 0≈σrr ≪ σcirc. The stress tensor in spherical coordinates simplifies therefore to In a thin‐walled spherical shell, stresses in azimuthal and meridional direction must be equal due to symmetry, that is, σL,H. Exploiting assumption (A3), that is, hr≪1 and thus 1+h2r≈1, allows a further simplification yielding σL,h. Finally, we consider a volume‐based estimation of σcircVcav and Vmyo may be less ambiguous than the determination of a representative inner radius r and wall thickness h  denotes the double contraction of two tensors; see, eg, HolzapfelPint, Wint, performed For a given displacement luating pintlPint, Pint(t)=∫⋆∈h,H,V, and ε˙circ approximates circumferential strains. For a derivation of Equation Based on Laplace law, biomechanical power can be estimated using Pint,⋆(t)tp^. Based on Preston and Wilson,Tsct, defined as the time elapsed between the onset of isovolumetric contraction (IVC) at tED and the instant of peak stress in the LV at tp^, is approximated by tED and tp^ is derived then by In addition, a recently introduced also Laplace‐based relative power indicator, IHP, was evaluated, which attempts to estimate the power generated by the LV around the instant of peak pressure, ε˙. Thus, while consistent in terms of physical units, IHP must be considered a relative indicator and not a physical measure of power.Note that Equation 2.7Pext, is given by p is the hydrostatic pressure acting at endocardial surface, Γendo, and q represent blood flow out of the LV cavity during ejection. Hydrodynamic work, Wext, is then the work expended by the LV myocardium when changing the volume of its cavity, Vcav, given by Hydrodynamic power, σact = 0, and isovolumetric contstraints imposed by valves upon Vcav, Pint≡Pext must hold. Under such conditions, external work can therefore serve as a reference for validating the FE‐based computation of internal power and work. This is not necessarily the case during the isovolumetric phases of a heartbeat where internal work may be expended, which does not necessarily manifest as external work. During these phases, changes in σ occur, which may entail shape changes of the LV myocardium and thus induce a nonzero strain rate tensor ε˙. However, because of the isovlumetric constraints imposed by the incompressibility of the blood pool and the closed state of all valves, no global change in cavity volume can occur, ie, dVcav = 0.In absence of active stresses, ie, p, are significant, the effective hydrodynamic power externally delivered to the arterial system is reduced. Following Fernandes et al,pao = pLV − Δp is the pressure in the aorta ascendens. Power efficiency, Peff, has been defined previously in Fernandes et alPeff essentially relates the mean hydrodynamic power delivered to the arterial system to the peak biomechanical power generated by the LV myocardium during systole, Peff can be expressed as P^int, P^ext, and P¯ext,ao are determined based on Equations Peff can be estimated from hemodynamic data using P^ext or from LV deformation analysis using P^int. Unlike Peff,clin in Equation Under healthy conditions, hydrodynamic power in the LV cavity equals the power delivered to the arterial system, as transvalvular power losses are small. However, in AS cases where transvalvular pressure gradients, Δes et al,EHP=P¯extdes et alPeff,clinssed as Peff=P¯ex2.8ϵ and stresses σ in the LV wall. Using these as reference, Laplace analysis was applied to the in silico models to assess its accuracy and validity.Human EM LV models that were validated against clinical data , was computed to define the center slice plane using the long‐axis unit vector, ez, and the center zi(t) of individual slices was shifted, keeping slice width and distance to the LV center z¯c(t) constant. Within a selected plane, radial vectors, ri,j(t), were computed that emanated from zi and were oriented in polar angles ϕj ranging from 0° to 360° with an angular sampling of Δϕ = 9°. For each vector ri,j(t), the intersection with surfaces, Γendo(t) and Γepi(t), was determined, yielding N = 2π/Δϕ inner radii, ri,j(t); outer radii, Ri,j(t); and wall widths, hi,j(t) = Ri,j(t) − ri,j(t) , and wall width, h¯i(t), were determined as the arithmetic average Similar issues arise when applying Laplace analysis to in silico datasets. In order to extract ) Figure B. Mean rr¯ and h¯ were computed by averaging over M slices Finally, multislice mean r¯(t) and h¯(t)  and (A2), passive inflation experiments were performed with LV models and the anisotropic material given in Equation Sph5, Sph25, and Sph150 in section σL,h, σL,H, and σL,V were compared with the mean stresses obtained from the FE solution. Stresses were evaluated with respect to an ellipsoidal coordinate system to facilitate a comparison with stresses in the spherical shell models , σϕϕ(x), and σθθ(x) were averaged according to Equation σ‾rr, σ‾ϕϕ, and σ‾θθ, respectively. Laplace‐based estimation of power, Pint,⋆, was compared with FE‐based power, Pint, and to external hydrodynamic power in the LV cavity, Pext.To evaluate the influence of violating the assumptions A and (A2)LVA–LVD to compare LV stress σL,⋆; power Pint,⋆; and IHP over an entire systolic cycle to the FE‐based stresses σ‾rr, σ‾ϕϕ, σ‾θθ, and σ‾mean and biomechanical power Pint. Further, biomechanical power due to LV deformation, Pint, and hydrodynamic power, Pext, derived from PV data were also compared to assess differences during isovolumetric phases.Laplace analysis was applied to clinically fitted EM LV models 2.9Discretization of all PDEs and the solution of the arising systems of equations relied upon the Cardiac Arrhythmia Research Package framework.33.1Sph5) or, at least, sufficiently accurate (Sph25 and Sph150). The resulting EDPVRs and principal components of the Cauchy stress σsph, evaluated in spherical coordinates and globally averaged to yield mean stresses σ‾circ and σ‾rr, are shown in Figure p = 4 kPa is provided in Tables The FE implementation was verified by performing passive inflation experiments with spherical shell models for which Laplace laws are known to be almost exact Sph or, at lσ‾circ with Laplace laws was very close, that is, σ‾circ=12(σ‾θθ+σ‾ϕϕ)≈σ‾θθ≈σ‾ϕϕ≈σL,H≈σL,h held. With increasing hσL,H provided estimates that were closer to the FE‐based stress σ‾circ than σL,h  .Using Cine‐MRI‐based LV volume traces and estimated ) Figure . All modσ‾ϕϕ, σ‾θθ, σ‾rr, and σ‾circ=12(σ‾ϕϕ+σ‾θθ), respectively, and power Pint to the Laplace‐based estimation of stresses σL,⋆ and power Pint,⋆. In all cases, the Laplace‐based stresses σL,h and σL,H tended to underestimate the FE‐based mean circumferential stress σ‾circ, being closer to the azimuthal stress σ‾ϕϕ, whereas σL,V overestimated σ‾circ and was closer to σ‾θθ. Further, both Laplace stresses or globally averaged mean stresses deviate noticeably from the true local stresses acting at a given location  from the true FE‐based mechanical power, even around the instant of p^LV the IHP marker was intended for.Laplace‐based power estimates P^int and Pint at the instant of peak pressure, tp^, were minor, with the maximum difference being P^int−Pint(tp^)<0.19 W or 2.15%. Laplace estimation of Pint, evaluated at tp^, misestimated P^int by 5.1% to 54.7%. Interestingly, Pint,h performed better than Pint,H in all cases, but with nonnegligible maximum relative errors of 23.37%, 32.23%, 18.51%, and 7.68% for LVA, LVB, LVC, and LVD, respectively. Internalmyocardial heart power overestimated P^int significantly, in the range between 24.10% to 140.28%. Since the mechanical power developed during isovolumetric phases was marginal , the most accurate estimate of Pint is obtained by computing Pext from standard hemodynamic PV data. In terms of peak mechanical power, the difference P^int−P^ext was less than 0.5 W or 7.18% in all cases where P^ext can be estimated with high accuracy by taking the product of peak power and flow, p^LV·q^LV.A numerical comparison between markers of LV peak power is given in Table 4p, r, h, Vmyo, and Vcav are accessible within routine clinical procedures. However, Laplace analysis is based on a global force balance calculation and relies upon simplifying assumptions on LV shape, tissue structure, and biomechanical behavior. This study attempts to establish validity, accuracy, and potential limitations of Laplace analysis of stresses and mechanical power generated by the LV by comparing against an FE model for which these quantities can be determined with high accuracy.Wall stress and mechanical power generated by the LV are considered important biomarkers that promise potential clinical utility for diagnosis and as a predictor of post‐treatment LV remodeling after interventions., 9 Moreo4.1σcirc in all models agreed closely with the Laplace stresses σL,⋆ . However, since the agreement between FE‐computed internal work Wint and external work Wext was essentially perfect, as expected on grounds of conservation of energy, we concluded that our FE implementation for evaluating stresses, power, and work is correct and that the observed deviations are rather attributable to inherent inaccuracies in the Laplace approximations. In particular, we consider the mean strain rate approximation in Equation Finite element computation of stresses and mechanical power was verified by performing passive inflation experiments with geometrically well‐defined spherical shell models of varying wall width for which Laplace laws hold with sufficient accuracy. Finite element computed circumferential stresses 4.2σ, Pint and Wint. While the FE models that were built from, fitted to, and validated against clinical data may deviate from clinical data within the limits of clinical data uncertainty, for assessing Laplace analysis, the FE model represents the ground truth, as it provides accurate data on stresses σ and strains ε, which can serve to compute local power and work densities pint and wint, respectively, as well as global Pint, Wint, and Wext with highest possible accuracy. All input parameters needed for Laplace analysis can be derived from the FE model with higher accuracy than what is achievable clinically. In this regard, the application of Laplace analysis to the in silico model can be considered a best case scenario.The validated high‐resolution in silico model served as a reference for evaluating the accuracy of the Laplace‐based approximation of 4.2.1σ(x) in the LV is a tensorial quantity that varies in space  followed a similar trend as σ‾circ although waveforms deviated to different degrees owing to the marked differences in the LV anatomies. However, quantitatively discrepancies were significant during both passive inflation and over an LV cycle as evident in Figure σL,V>σ‾circ>σL,h>σL,H.Wall stress r and h required for the evaluation of Equations r and h must be determined from averaging over a number of short axis Cine MRI scans to find representative values. Because of longitudinal shortening, additional averaging occurs, as different slices of the heart are being imaged during ejection. Thus, the determination of parameters r and h cannot be unique as the particular method employed for averaging, such as the one described in Equation Vcav and Vmyo are used as inputs that may be determined uniquely for the LV. However, in our simulations, σL,V led to larger misestimations than σL,h and σL,H.Besides the fundamental problem of stress heterogeneity and tensorial properties of LV wall stress, Laplace calculations are afflicted with significant uncertainties. The meaning of geometric parameters It is well known that Laplace‐based calculation of stresses is afflicted with various inaccuracies.4.2.2Pint and cardiac power efficiency Peff defined as the ratio between peak mechanical power expended by the LV, P^int, and the mean hydrodynamic power delivered to the arterial system, EHP, have been proposed recently as a diagnostic marker.Pint expended by the LV and the hydrodynamic power transferred to the LV blood pool, Pext, must be equal. Discrepancies may occur due to isovolumetric phases during which hydrodynamic power is close to zero, but mechanical power is expended by the LV to some extent as conformational changes of the LV myocardium, and the shape of the LV cavity occur. However, in all models studied, Pint during isovolumetric phases was negligible . This does not conflict with experimental studies providing evidence of heterogeneous circumferential strains, longitudinal shortening, and wall thickening during IVC.ε˙ remained small during IVC, and mechanical power expenditure was minor. In all LV models under study, global mechanical power Pint and the hydrodynamic power in the LV cavity Pext were virtually identical , Pint,h(tp^),Pint,H(tp^), and Pint,V(tp^) in Table Following Fernandes et al,Peff,clin marker can be used as in Fernandes et al,ε˙. While simpler, its use brings about a number of drawbacks. Since ε˙ is ignored, IHP is only a relative marker that is nonlinearly related to Pint. Therefore, IHP provided highly inconsistent relative estimates of Pint with errors varying in the range from 24.1% to 140.28%  in the LV wall is highly heterogeneous as well with significant regional variability around the global mean power density. In this view, Laplace‐based global markers derived from mechanical deformation such as σ‾circ or Pint,⋆ are not representative of local stresses and power within the LV myocardium and appear to offer limited insight and predictive power beyond standard PV analysis.The mechanical power generated by the LV is an indicator of metabolic demands. Local wall stresses and power densities governing energetic demand and supply ratios in the LV myocardium are known to play important roles as drivers of remodeling in the pressure‐overloaded LV of AS patients. However, analogous to the stresses shown in Figure σ and power pint over a cardiac cycle depends on reliable sets of strains ϵ. While techniques for measuring strains in 3D throughout the LV myocardium are available,ϵ at a high spatio‐temporal resolution. Using an appropriate parameterized patient‐specific constitutive model such as given in Equation ϵ can be used to compute LV wall stresses σ and Pint or any other stress‐related biomarker efficiently with high accuracy. Such models are able to provide either global power Pint(t), but also fine‐grained distributed power density pint. A spatio‐temporal view on ε, σ, and pint in the LV may provide additional insights as regions of elevated strain, stress, or power are assumed to be implicated in the mechanisms driving remodeling in the pressure overloaded LV.(An accurate representation of local mechanical stresses oaded LV., 415Laplace estimates of LV wall stress are able to provide a rough approximation of global mean stress in the circumferential‐longitudinal plane of the LV. However, according to FE results, spatial heterogeneity of stresses in the LV wall is significant, leading to major discrepancies between local stresses and global mean stress. Assessment of mechanical power with Laplace methods is feasible, but these are inferior in accuracy compared with FE models and do not offer any benefits compared with standard methods based on hemodynamic data. In this view, the scope for Laplace‐based analysis in clinical applications seems narrow. The accurate assessment of stress and power density distribution in the LV wall is only feasible based on patient‐specific FE modeling.Supporting info itemClick here for additional data file.


P = 0.014) and decreased transmitral E/A ratio(P = 0.022) remained significant prognosticators. In LVSF analysis, patients with LVEF≤60% (quartile [Q]1) had higher mortality than those with LVEF>60% . In LVDF analysis, patients with an E/A ratio<0.9(Q1) had a 2.19-fold higher risk of death  than those with an E/A ratio>1.4(Q4). In combined LVDF and LVSF analysis, patients with an E/A ratio<0.9 and LVEF≤60% had poorer survival outcomes than patients with an E/A ratio≥0.9 and LVEF>60% . Patients with an early mitral inflow velocity/annular velocity (E/e’ ratio)>11.5(Q4) and LV stroke volume index (LVSVI)<33mL/m2(Q1) showed worse survival than those with an E/e’ ratio≤11.5 and LVSVI ≥33mL/m2. A combination of LVSF and LVDF is a better predictor of survival than LVSF or LVDF alone.Although pretransplant cardiac dysfunction is considered a major predictor of poor outcomes after liver transplantation (LT), the ability of left ventricular (LV) systolic/diastolic function (LVSF/LVDF), together or individually, to predict mortality after LT is poorly characterized. We retrospectively evaluated pretransplant clinical and Doppler echocardiographic data of 839 consecutive LT recipients from 2009 to 2012 aged 18–60 years. The primary endpoint was all-cause mortality at 4 years. The overall survival rate was 91.2%. In multivariate Cox analysis, reduced LV ejection fraction (LVEF,  Recent advances in surgical techniques and better immunosuppressive drug therapy-related perioperative management have improved graft-related survival after liver transplantation (LT). Thus, in the current LT era, pretransplantation cardiovascular disease is emphasized as the leading cause of poor nongraft-related short- and long-term outcomes –3.Doppler echocardiography is highly recommended before LT and is now routine practice at many institutions for the assessment of left and right ventricular dysfunction, pulmonary hypertension, and cirrhotic cardiomyopathy . PatientHowever, the aforementioned results have mostly been based on limited diastolic/systolic parameters or an incomplete diastolic grading system that appears to be somewhat discordant –9. This No studies have systematically evaluated whether the quantitative echocardiographic parameters can predict mortality in LT candidates. Accordingly, using a sufficiently-sized study cohort, we aimed to examine whether the quantitative echocardiographic parameters are applicable to the outcome prediction and stratify the cardiac risk of LT candidates using pretransplant Doppler echocardiography in order to predict all-cause mortality after LT. The Doppler echocardiography parameters quantitatively analyzed were left ventricular systolic function (LVSF) alone, left ventricular diastolic function (LVDF) alone, or LVSF and LVDF together.-1∙1.73m-2 by Modified Diet in Renal Disease equation or need for hemodialysis), and 8 who had history of open heart surgery or significant valvular heart disease . Thus, 839 recipients of primary LT were included in our final study series. Demographic, laboratory, and clinical data from routine preoperative evaluations were collected by analysis of electronic medical records after approval of the Institutional Review Board of Asan Medical Center. The primary endpoint was 4-year all-cause mortality. All patients were followed for at least 1 year and up to 4 years. Mortality data were collected from the electronic medical records and our hospital’s registry, which is updated by the Asan Organ Transplantation Center.We retrospectively evaluated prospectively collected data of 964 consecutive patients aged 18–60 years who underwent LT at Asan Medical Center, Seoul, Republic of Korea, between October 2009 and October 2012. We excluded LT candidates older than 60 years of age because the frequency of LVDD in this population is high , 12. PrePrior to surgery, preoperative echocardiography at our institution’s echocardiography laboratory was performed routinely by experienced and well-trained sonographers and was reconfirmed by 3 attending staff cardiologists. Comprehensive two-dimensional and Doppler echocardiography with tissue Doppler imaging (TDI) were performed using a Hewlett-Packard Sonos 2500 or 5500 imaging system equipped with a 2.5-MHz transducer  to evaluate cardiac morphology and function. Parameters measured included end-systolic LV posterior wall thickness, end-diastolic LV posterior wall thickness, end-systolic interventricular septum thickness, end-diastolic interventricular septum thickness, left ventricular mass index, left atrial diameter, and aortic diameter. LV end-diastolic volume (EDV) and end-systolic volume (ESV) were measured using the Teichholz method or biplane modified Simpson’s rule, as appropriate, from which stroke volume (SV = EDV–ESV) and LV ejection fraction (LVEF) were calculated. Measurements were indexed to body surface area when appropriate. We measured the peak transmitral inflow velocity (E and A) on pulsed-wave Doppler, E wave deceleration time (DT) to assess restriction to LV filling, and the E/A ratio from the apical four-chamber view. The systolic s’ and diastolic e’ and a’ peak velocities were obtained by TDI at the septal mitral annulus on the apical four-chamber view, and the e’/a’ and E/e’ ratios as an estimation of LV filling pressure were calculated according to established guidelines , 13. TheP<0.1 in univariate analysis for predicting mortality and (2) multiple combinations of systolic and diastolic parameters that are known to be clinically relevant [Global LV systolic function was assessed using (1) TDI s’ velocity, (2) ejection fraction (EF), (3) fractional shortening, and (4) LV SV index (LVSVI). Diastolic function was assessed using (1) the E/A ratio, (2) DT, (3) TDI septal e’ velocity, (4) E/e’ ratio, and (5) e’/a’ ratio. Combined diastolic and systolic function was assessed by (1) echocardiographic parameters showing relevant , 14, suct test, nonparametric Wilcoxon signed-rank test, chi-square test, or Fisher exact test was used for comparisons of continuous or categorical variables, as appropriate. Univariate Cox proportional hazards analysis was performed to identify variables associated with all-cause mortality. The variables with P<0.1 in univariate Cox analysis were included in the multivariate Cox proportional hazards analysis. Age and sex were forced into the final multivariable model because they are known risk factors for mortality. Furthermore, the influence of age on Doppler echocardiographic indices of LVDF, such as the E/A ratio, is well recognized [Normally distributed continuous data were expressed as the mean ± standard deviation or, if skewed, as median values and interquartile range. Categorical data were expressed as numbers and percentages. LT recipients were divided into two groups, survivors and non-survivors at the end of a 4-year follow-up. According to the normality assumptions, a Student cognized .P<0.05) were equally added to adjust the systolic function (model 1), diastolic function (model 2), and combined systolic and diastolic function (models 3 and 4), respectively. By using these models, hazard ratios with 95% CI for all-cause mortality were determined and compared. Survival analysis to compare the mortality among subgroups was performed using the Kaplan-Meier method with log-rank statistic. All statistical analyses were performed using SPSS version 21.0 software . Differences were considered significant if P was less than 0.05.Multivariate Cox proportional hazards stepwise inclusion/exclusion regression modeling with backward elimination  was used to identify independent prognostic variables and to calculate adjusted hazard ratios with 95% confidence intervals (CIs). The proportional hazards assumption was confirmed by examination of log  curves. Additionally, to stratify the cardiac risk of LT candidates with quantitative analysis and to compare survival among groups, final echocardiographic variables remaining in the multivariable model were categorized into di-, tri-, or quadrichotomized distributions, and then the statistical significance of arbitrary cut-off points derived from the median, tertile, and quartile analyses was combined and rigorously validated. Also, to exclude significant effects of multicollinearity among measures of systolic function, diastolic function, and combined systolic and diastolic function, separate models were constructed. Namely, statistically significant clinical variables in univariate analysis  and 10th and 5th percentiles of LVEF were 61%, 59%, and 58%, respectively  of the E/e' ratio was 11.5 in this study cohort .P = 0.01), Model for End-stage Liver Disease (MELD) score (P = 0.001), serum creatinine (P<0.001), and total bilirubin level (P = 0.023) significantly predicted 4-year mortality (P = 0.025), but not in TDI s’ velocity, fractional shortening, or LVSVI. In diastolic function analysis, non-survivors showed a decreased E/A ratio , reduced e’ velocity , and increased E/e’ ratio  compared with survivors at 4 years  score  were entered into the Cox multivariate survival analysis, an increased serum creatinine level and CTP score  and reduced EF and E/A ratio  were the only predictors of 4-year all-cause mortality after LT . Kaplan-Meier survival curve showed this difference between two groups  and 1 year  , the 4-year mortality rate was significantly lower in the LVEF>60% group than in the LVEF≤60% group  .P = 0.004). Kaplan-Meier survival curve showed this difference among groups according to the E/A ratio quartile  predicted 4-year mortality independently of the CTP score and creatinine level.Additionally, we calculated adjusted hazard ratios by separating the models according to LVSF, LVDF, and combined LVSF and LVDF . In modeP = 0.024) than those in E/A ratio Q4 (>1.4), independently of the creatinine level.In model 2, when quartiles of the E/A ratio were adjusted for age, sex, and clinically significant variables, E/A ratio quartiles were independent predictors of late mortality. Patients in E/A ratio Q1 (<0.9) had a 2.19-fold higher risk of death  with a combined E/A ratio<0.9 and LVEF≤60% had a worse 4-year survival than patients with an E/A ratio≥0.9 and LVEF>60% . Kaplan-Meier survival curve showed this significant difference among groups according to the combined criteria (the E/A ratio quartile and LVEF) , LVSVI was significant when combined with the E/e’ ratio . Therefore, in model 4, the combined LVDF and LVSF analysis, patients were divided into four subgroups according to the LVSVI Q1 (33mL/m2) and E/e’ ratio Q4 (11.5) cut-off values and were also adjusted for age, sex, and clinically significant variables  with a combined E/e’ ratio>11.5 and SVI<33mL/m2 showed worse survival than those with an E/e’ ratio≤11.5 and SVI ≥33 mL/m2  in model 4. Kaplan-Meier survival curve showed this significant difference among groups according to the combined criteria (the E/e’ ratio quartile and LVSVI)   and LVEF Q1 (60%) cut-off values and were also adjusted for age, sex, and clinically significant variables . Patientariables . Patient= 0.027) . The hazThere were two main findings of our current study. First, reduced LVEF and a decreased transmitral E/A ratio from the quantitative quartile analysis were found to be independent predictors of late overall mortality after LT, even after adjusting for clinically relevant variables. Second, the combination of LVSF and LVDF revealed a higher mortality rate than LV systolic dysfunction (LVSD) or LVDD alone.Preoperative cardiac dysfunction is an independent risk factor for adverse cardiovascular events and mortality after cardiac and non-cardiac surgery –20. LikeP = 0.025) and LVEF was an independent predictor of overall 4-year mortality. However, unlike mortality at 4 years, the mortality rates at 3 months and 1 year were not significantly different between the LVEF>60% and LVEF≤60% groups . These results suggested that the prediction potential of LVEF is limited to late mortality following LT. Previous studies also supported these findings, echoing our conclusions that the systolic function of ESLD patients would not have a discrimination potential in early outcome prediction. For example, Dowsely et al.[P = 0.30) after LT. In addition, Ruiz-del-Arbol et al.[P = 0.050) in ESLD patients who died than in those who survived, but it was not a predictor of 1-year mortality in multivariable analysis, as in our study. Importantly, especially given that outcomes such as heart failure and death are clinically critical events, their LVEF results of 69% and 70% are unexpectedly high. Likewise, our LVEF of 63% at 4 years to predict mortality is also considered high.Of the parameters reflecting LV systolic function, non-survivors at 4 years in our present study series had a lower LVEF than survivors  were categorized as a systolic dysfunction group according to an LVEF<55% in the WGO echocardiographic guidelines. Dowsely et al.[n = 107 and 80, respectively) had a normal LVEF (>50%). Hence, we stratified patients according to an LVEF≤60%, which was the lowest LVEF quartile in our study cohort, although it is higher than the standard criterion used by major societies. Nonetheless, we successfully showed that patients with an LVEF≤60% had higher late mortality than those with an LVEF>60%, even after adjusting for clinically relevant variables . Therefore, our results suggest that stratification of ESLD patients with an LVEF≤60% is recommended to predict late mortality after LT, in contrast to the ASE and WGO guidelines of LVEF<55%. Given that post-transplantation immunosuppressive drugs and other medications may contribute to the progression of cardiac and atherosclerotic vascular changes [In this regard, the cardiac function of LT candidates with LVEF>55% according to WGO guidelines might be the subject of controversy, namely, whether cardiac systolic function above this value is still predictive of early and late outcomes. Indeed, in our current study, patients with an abnormal LVEF, according to the conventional criteria of LVEF≤55%, comprised 1.7% of our series while those with LVEF<55% comprised only 0.2%. In addition, all of our patients showed an LVEF>50%. This finding is consistent with those of other studies. In Raevens et al. , 2% of Lly et al. also fou changes  it is pln = 80) using a "practical approach" to grade LVDD according to previous ASE guidelines [P<0.001). Meanwhile, Mittal et al.1 reported that LVDD was found in 19% of LT candidates (n = 970)—mild in 48%, moderate in 30%, and severe in 22%—and found that pretransplant LVDD is significantly associated with increased risk of allograft rejection, graft failure, and mortality.Increasing numbers of recent studies have emphasized the importance of LVDF in predicting poor early and late outcomes after LT , 7–9. LVidelines . In thein = 173), mortality was not strongly affected by its presence. Notably, to date, the prevalence and classification of LVDD is highly variable. Accordingly, different outcomes may also be inevitable. Furthermore, some articles argue that current LVDD grading systems cannot classify every patient into an LVDD grade, depending on the definition used, and leave a substantial portion of patients as unclassified [In contrast, another report  showed tassified , 29. Sucassified , 30.Collectively, inconsistencies in outcome studies after LT in ESLD patients are not so surprising given that (1) studies use incomplete grading systems, and (2) there may be considerable differences in the normal values of echocardiographic parameters between ESLD patients and the general population. Hence, we believe, as shown in our current analyses, that our criteria derived from quantitative quartile analysis could be useful for predicting all-cause mortality after LT.Because TDI is an evolving echocardiographic tool and one of the most load-independent measurements of cardiac function, it plays an important role in prognosis assessment , 12, 14.Of the echocardiographic parameters indicating LVDD, an E/A ratio of <1, is a robust predictor of death in ESLD patients after transjugular intrahepatic portosystemic stent shunt insertion . In our Given that LVSF and LVDF are tightly interconnected, close monitoring of both cardiac function parameters is always recommended . BecauseThis was a single-center retrospective study and, therefore, it is possible that the management strategy before LT at our institution may have affected the cardiac systolic and diastolic function and that the intraoperative and postoperative management may have affected the survival rate. In addition, although the echocardiographic image of our institution known to be reliable and adhere to the American Society of Echocardiography guideline , 34, we The combination of LVSF and LVDF is a better predictor of survival than LVSF or LVDF alone. This approach might help to stratify the cardiac risk of LT candidates using pretransplant Doppler echocardiography and better predict all-cause mortality. A careful follow-up of LT recipients is crucial because pretransplant quantification of cardiac dysfunction can help to predict poor survival.S1 Table(DOCX)Click here for additional data file.S1 File(CSV)Click here for additional data file.


Truncus arteriosus communis (TAC) is a congenital heart defect in which the physiologic arterial common trunk was not divided into aorta and pulmonary artery trunk.In this paper, we report on three observed cases from which we looked for (in conjunction with literature review) the different causes of TAC many of which have genetic origins.We collected three clinical files of fetuses having a TAC. Two of them were examinated after a medical termination of pregnancy motivated by severe cardiopathy. The malformation had been diagnosed based on different techniques: echocardiography, skeletal radiography, arteriography, fetal autopsy, karyotype and fluorescence in situ hybridization (FISH).Imaging and fetopathological examination revealed the presence of TAC type 3 and 4 in the Van Praaghs classification. FISH analysis showed a 22q11.2 deletion in one fetus in favour of Digeorge syndrome. The karyotype analysis performed in two cases was normal.Truncus arteriosus is a rare pathology caused by numerous etiologies from which many of them have genetic origin. This malformation can be diagnosed early during prenatal period. Postmortem fetopathological examination allows a better diagnosis approach and eventually a genetic counseling in recurrent cases such as case of consanguinity. Congenital malformations (CM) are commonly diagnosed in Africa, and the heart is one of the most affected organ in birth defects.The TAC is an embryonic conotruncal cardiac defect which consists in the persistence of the physiologic common arterial trunk .The two great arteries arising from the base of the heart  do not differentiate, so there is occurrence of a single large vessel  that overhangs either a single ventricle or astride the two ventricles. The malformation is highly lethal, depending on the presence or absence of a pulmonary artery and associated extracardiac anomalies. The death without surgery occurs between two weeks and three months after birth, and the mortality rate is 85 % at one year.We collected three clinical files of fetuses: two fetuses (F) of Congolese origin, M15 (F1) and 10F-0013 (F2) coming respectively from external consultation and our University collection; one fetus of French origin F11-048 (F3) originating from Department of Fetopathology of CHU Pellegrin (Bordeaux). Two of them (F1 and F3) were examined after a medical termination of pregnancy motivated by severe congenital heart defect. The fetal data is reported in For better diagnosis approach, three types of examinations were performed: (i) Imaging ; (ii) fetal autopsy  on F2 and F3; and (iii) genetic analysis based on the karyotype and the FISH in two cases (F1 and F3).Karyotype was performed on chorionic villus sampling and amniotic fluid. The conventional steps of blocking the cells (by adding colchicin), hypotonic shock, fixing with carnoy liquid and staining with Giemsa, were carried out after prior cell culture.Fluorescence in situ hybridization (FISH) analysis was done in medical genetic laboratory of the Pellegrin University Hospital in order to identify the 22q11.2 microdeletion. The technique was performed by the use of TBX1-22qter cytocell probe . The cell pellet was obtained from amniocytes culture.The three fetuses had in common TAC visualized by radiography, ultrasound and/or by autopsy. FISH analysis confirmed a genetic etiology in one case.Two-dimensional and three-dimensional fetal echocardiography performed in two cases: F1  and F3 aArteriography performed only in the F3 specified the TAC and visualized the right aortic arch .Fetal autopsy showed TAC type A4 in F2  in the VUnfortunately karyotype analysis was not performed in case 2, due to the lack of fresh tissue while in the other two fetuses it was normal.FISH analysis revealed 22q11.2 microdeletion in fetus 3 . On the The knowledge of the key aspects of heart development is important to understand where truncus arteriosus originates. The formation of the human heart begins at the third week of embryonic development (WED), at the stage of gastrulation and ends at eight weeks. It begins with the migration of two symmetrical waves of angiogenic cells on the primitive line and the formation of the mesenchyme of the cardiac field at the cranial extremity of the embryo, ahead of the pharyngeal region of the primitive intestine.15th WED during the embryonic plicature, the two tubes migrate at the thoracic level into a single primitive cardiac tube (PCT)  , which hbe (PCT) ; (ii) a be (PCT) .15,16,17th and the 8th WED, the PCT undergoes rapidly modifications which give rise to the four normal cardiac cavities and to the normal situs of the heart .29The mutations of the following genes: NKX2-5 mapped on 5q35.1 and NKX2-6 in 8p21.2 l band can also generate isolated family TACs (OMIM #217095).35In the associations: TAC may also be part of a VACTERL, combination of vertebral, anal, cardiac, tracheo-esophageal, renal, and limb abnormalities. CHARGE in which a mutation of the CHD7 gene is observed in two thirds of patients is also concerned.41The following factors occurring during gestation are also implicated: stress, alcohol, cigarettes smoking, abusive coffee, retinoic acid, maternal drug consumptions for example valproic acid .47Previous data have shown that the origin of TAC is varied, particularly in genetic origins. The good fetal echocardiography in the first trimester of gestation (since 12 weeks of embryonic development) allows an early diagnosis and guides the behavior very early because some types can be surgically repaired. Postmortem fetopathological examination allows for better delineation of anomalies and can lead to genetic counseling in recurrent cases such as in parental consanguinity.What is already known on this topic shows TAC is a rare, serious congenital heart defect of various causes and it can be detected in prenatal period by routine ultrasound screening. Interestingly, our paper reports uncommon type A3 and A4 of TAC, lists the TAC associated genetic defects and highlights the fetopathological examination as a value tool in positive diagnosis of TAC. The discipline, often mistakenly regarded as a luxury medicine in Africa, now needs to be developed in the South countries as the incidence of congenital malformations is increasing.


The purpose of this article is to describe the key cardiac magnetic resonance imaging (MRI) features to differentiate hypertrophic cardiomyopathy (HCM) phenotypes from other causes of myocardial thickening that may mimic them.Many causes of myocardial thickening may mimic different HCM phenotypes. The unique ability of cardiac MRI to facilitate tissue characterisation may help to establish the aetiology of myocardial thickening, which is essential to differentiate it from HCM phenotypes and for appropriate management.Many causes of myocardial thickening may mimic different HCM phenotypes.• Differential diagnosis between myocardial thickening aetiology and HCM phenotypes may be challenging.• Cardiac MRI is essential to differentiate the aetiology of myocardial thickening from HCM phenotypes.•  Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiovascular disorder worldwide, with a prevalence of 1 in 500 in the general population –5. For HEchocardiography is the most commonly used imaging modality in the evaluation of HCM. When the HCM phenotype is fully expressed, echocardiography generally allows a reliable and unequivocal diagnosis. Occasionally, however, the differential diagnosis among the broad range of phenotypic expressions of HCM and other causes of myocardial thickening may be challenging. Tissue characterisation, which is limited with echocardiography, could provide additional diagnostic information .Cardiac magnetic resonance imaging (MRI) has evolved into a multiparametric imaging modality allowing a truly comprehensive picture of HCM, providing information regarding various phenotypes, their functional and haemodynamic consequences, presence and extent of microvascular dysfunction and myocardial fibrosis . The tisThe aim of this article is to illustrate and review the contributions of cardiac MRI to the differential diagnosis among HCM phenotypes and other causes of myocardial thickening.There is a broad range of phenotypic expressions of HCM. Asymmetric involvement of the interventricular septum is the most common pattern (60–70%), followed by symmetric or concentric myocardial hypertrophy up to 40%) and the less common apical variant 0% and th.From a practical point of view, it is useful to classify the thickening of the myocardium as concentric or symmetric, asymmetric and apical. Table HCM with concentric LV hypertrophy should be differentiated from other causes of symmetrical myocardial hypertrophy, including mild (athlete’s heart) and mild or moderate (hypertensive heart disease and aortic stenosis) and from other causes of myocardial thickening (cardiac amyloidosis).The term ‘athlete’s heart’ refers to a clinical picture characterised by two distinct and specific cardiac effects induced by a sustained and regular physical training programme, namely, slow heart rate and enlargement of the heart. Increased of LV size and LV hypertrophy are generated in order to normalise LV wall stress. The need for reliable methods to differentiate physiological from pathological LV hypertrophy are brought into focus by the rare but prominent cases of sudden death in elite athletes and the young .Cardiac MRI can help to differentiate HCM from the athlete’s heart. In the athlete’s heart, LV wall hypertrophy is concentric, usually mild  and is paralleled by a proportional increase in volume of both ventricles  is typically absent Fig. c. AlthouRecent studies have shown that native T1 values and myocardial extracellular volume (ECV) by T1 mapping can be used in the differential diagnosis between HCM and athlete’s heart. While the ECV fraction increases with increasing LV hypertrophy in HCM , the ECV fraction reduces in athletes with an increasing wall thickness  .Practical recommendations: As a general rule, the development of physiological LV hypertrophy in the context of athlete’s heart is consistently associated with an LV cavity—a difference from HCM. When the differential diagnosis remains still unresolved, serial echocardiography or cardiac MRI after exercise detraining (3 months) may show regression of LV hypertrophy and reduction in LV end-diastolic volume in most athletes.The diagnosis of HCM in young competitive athletes may be challenging when the extent of LV hypertrophy is mild and LV wall thickness is in the range of 13–15 mm (12–13 mm in women), which identifies the ‘grey-zone’ of overlap between the physiological adaptations to training and mild phenotypic expression of the disease –12. WhenArterial hypertension is the most common cause of cardiovascular death. It may lead to hypertensive heart disease and it isthe most common cause of increased afterload that leads to heart failure, ischaemic heart disease and LV hypertrophy .Cardiac MR provides a comprehensive non-invasive evaluation of hypertensive heart disease, including accurate and reproducible assessment of global and regional biventricular function, valvular disease and myocardial fibrosis , 22.In hypertensive heart disease, compensatory LV hypertrophy in response to increased afterload is usually concentric and mild (≤ 13 mm) with an increased indexed LV mass, increased chamber volumes and normal or reduced ejection fraction , 21, 23.The absence of LGE does not equate to the absence of myocardial fibrosis because this LGE identifies focal replacement fibrosis but fails to demonstrate diffuse fibrosis. T1 mapping techniques provide quantification of the myocardial intra and extracellular compartments, and native T1 has demonstrated increased diffuse myocardial interstitial fibrosis at an early stage in hypertensive heart disease patients who do not yet exhibit LGE abnormalities. These abnormalities are associated with decreased LV global function and LV remodelling , 26.Practical recommendations: Independent predictors of hypertensive heart disease rather than HCM are elevated indexed LV mass, absence of myocardial LGE or less pronounced patchy myocardial LGE in hypertensive heart disease than seen in HCM.When myocardial hypertrophy is ≥15 mm or is asymmetric, distinguishing hypertensive heart disease from HCM can be difficult . AsymmetAortic stenosis causes a LV pressure overload leading to structural, functional and molecular changes in the process of myocardial hypertrophy. Untreated hypertrophy leads over a longer period of time to ventricular dysfunction that is irreversible and is associated with advanced remodelling .Typically, aortic stenosis presents with mild or moderate concentric hypertrophy because of LV pressure overload with normal LV ejection fraction; however, recent studies have also demonstrated the existence of asymmetrical patterns . ProgresPractical recommendations: Aortic stenosis is readily evaluated on phase-contrast cardiac MRI, and evidence of this finding should be sought when imaging patients for suspected HCM.Cine MR imaging allows differentiation of LV hypertrophy caused by aortic stenosis from that caused by obstructive HCM. In aortic stenosis, the jet of turbulent flow is exactly across the valve with associated decreases in aortic valve area in systole Fig. a. PatienCardiac amyloidosis is a rare but important phenocopy of HCM characterised by extracellular deposition of monoclonal light chain or transthyretin amyloid and symptoms of heart failure with preserved ejection fraction. Cardiac involvement in amyloidosis significantly worsens prognosis of the disease. Endomyocardial biopsy is considered the “gold standard” in the diagnosis of cardiac amyloidosis. However, the relatively high risks and clinical complications may hinder its widespread use in clinical settings .Cardiac amyloidosis most commonly presents with markedly symmetric LV thickening Figs.  and 5, dCardiac MRI with LGE provides unique information regarding myocardial tissue characterisation and it is extremely helpful in differentiating cardiac amyloidosis from HCM. Due to interstitial expansion from amyloid deposition, LGE is seen in 69–97% of all cardiac amyloidosis patients , 32.Alterations in gadolinium kinetics in the blood and myocardium are common and can be useful in differentiating cardiac amyloidosis from HCM . The higIn cardiac amyloid disease, the deposition of the abnormal protein typically occurs in a circumferential manner starting in the endocardium and then extending to the myocardium in a transmural fashion. Characteristic patterns of myocardial enhancement include global, subendocardial and, less often, patchy or diffuse LGE distribution within the LV Fig. d, e 32,, 36, 37.Practical recommendations: Late imaging with inversion recovery should be performed at 4 min and completed quickly to identify myocardial amyloid deposition.Higher ECV post-contrast T1 mapping correlates with LGE, indexed LV mass and other clinical adverse prognostic factors . In earlAsymmetric LV hypertrophy is the most common phenotypic expression of HCM, which typically involves the basal ventricular septum. Infiltrative cardiomyopathies usually cause symmetrical LV wall thickening; however, occasionally cardiac sarcoidosis may manifest as asymmetric LV wall thickening simulating HCM.Sarcoidosis is a multisystem disorder of unknown aetiology that is characterised histopathologically by non-caseating granulomatous infiltration. Cardiac involvement is common (50%), but only 5% of patients are symptomatic and may initially manifest with arrhythmias or even sudden cardiac death .Disease may involve either the left or right ventricle but more commonly involves the LV, usually the basal septum; nevertheless, involvement of RV free wall, atrium, pericardium and endocardium can also be seen , 40.Abnormalities of cardiac sarcoidosis tend to be non-specific and variable; interventricular thinning  is the most typical feature of cardiac sarcoidosis . There mThe appearance of sarcoidosis at cardiac MRI largely depends on the timing of imaging. In the acute phase of disease, myocardial inflammation or oedema manifests as myocardial thickening and patchy increased signal intensity on T2-weighted images and T2 mapping. Recent studies have shown that T2 mapping seems to serve as a novel quantitative biomarker to detect myocardial inflammation in systemic sarcoidosis and during the follow-up of the disease. T2 values are higher in cardiac sarcoidosis than in patients without cardiac involvement and decrease in response to anti-inflammatory treatment. .LGE MR images in patients with sarcoidosis typically show a patchy mid-myocardial, subepicardial or epicardial pattern that is not in a vascular distribution, most often seen in basal segments  and typically in the epicardium and mid myocardium . In chroPractical recommendations: T2 mapping can be useful for early detection of cardiac involvement in systemic sarcoidosis and for monitoring the activity of myocardial inflammation during the follow-up of the disease.Diagnosis of cardiac sarcoidosis is sometimes challenging because sarcoidosis often involves small areas of the myocardium without abnormally affecting LV function and, less commonly, an increase in myocardial wall thickness may also be seen, usually at the basal septum, simulating asymmetric HCM Fig. a and b , 44. In The differential diagnosis of apical HCM includes mural thrombus, hypertrabeculation or non-compaction and endomyocardial fibrosis. These entities may be diagnosed on MRI using steady-state free precession (SSFP) imaging techniques and LGE imaging.Practical recommendations: Late imaging with inversion recovery should be performed with a long inversion time (500–600 ms). At this time, the signals of thrombi are very dark.The development of LV apical thrombus is an important complication of myocardial infarction. Thrombus occurs on the endocardial surfaces overlying the infarct secondary to endocardial inflammation during the acute phase of myocardial infarct. Although the underlying pathological mechanisms are unknown, approximately 2% of patients with mid-ventricular obstruction in HCM present with apical LV aneurysms. The dyskinetic/akinetic apex can provide the structural basis for intracavitary thrombus formation . EchocarLeft ventricular non-compaction is a genetic cardiomyopathy characterised by an excessively prominent trabecular meshwork and deep intertrabecular recesses that communicate with the cavity but not with the coronary artery system . Non-comPatients may have no symptoms or may present with heart failure, atrial and ventricular arrhythmias, thromboembolic events and sudden cardiac death .Although a “gold standard” for the diagnosis of LV non-compaction continues to be lacking, cardiac imaging criteria provide the best tool currently available . ImagingAdvances in cardiac MRI have resulted in superior image quality and increased sensitivity in the detection of myocardial trabeculations. Moreover, cardiac MR can also reveal the presence of LGE, a marker of myocardial fibrosis that represents the substrate for potentially lethal arrhythmias . Higher On cardiac MRI, diagnosis of LV non-compaction is supported if the end-diastolic thickness of the non-compacted layer is greater than 2.3 times that of the compacted one . This reThe diagnosis of LV non-compaction can be challenging due to the lack of universally validated diagnostic criteria , 52. DiaLeft ventricular non-compaction shares morphological features with HCM that can mimic isolated LV non-compaction . A true Practical recommendations: The intertrabecular recesses that communicate with the LV cavity and that are characteristic of LV non-compaction are easily demonstrated by the high signal intensity of the blood pool on cine SSFP MR images.Trabeculations of LV non-compaction at echocardiography can simulate an apical HCM because myocardial trabeculations can be difficult to visualise in the apical segments Fig. a 47, 5555. The hHypereosinophilic syndrome with cardiac involvement and endomyocardial fibrosis is the most prevalent form of restrictive cardiomyopathy worldwide. This entity usually involves the apex of one or both ventricles that may lead to both endomyocardial fibrosis and obliteration of the LV apical cavity Figs.  and 9 5.Fig. 8A Practical recommendations: Mural thrombus and subendocardial LGE in endomyocardial fibrosis are most useful findings to differentiate this entity from apical HCM.Fibrosis at the cardiac apex frequently results in obliteration of the apical cavity, and can be confused with apical HCM . On cardIn summary, familiarity with the spectrum of myocardial thickening mimickers allows consideration of the differential diagnosis of HCM. Understanding relevant clinical features, the myocardial thickening location and distribution patterns of late gadolinium enhancement facilitates the recognition of key cardiac MRI features, which can allow identification of those causes of myocardial thickening that may mimic the various HCM phenotypes.