Background-Left ventricular (LV) mass is an important predictor of morbidity and mortality, especially in patients with systemic hypertension. However, the accuracy of 2D echocardiographic LV mass measurements is limited because acquiring anatomically correct apical views is often difficult. We tested the hypothesis that LV mass could be measured more accurately from real-time 3D (RT3D) data sets, which allow offline selection of nonforeshortened apical views, by comparing 2D and RT3D measurements against cardiac MR (CMR) measurements. Methods and Results-Echocardiographic imaging was performed (Philips 7500) in 21 patients referred for CMR imaging (1.5 T, GE). Apical 2-and 4-chamber views and RT3D data sets were acquired and analyzed by 2 independent observers. The RT3D data sets were used to select nonforeshortened apical 2-and 4-chamber views (3DQ-QLAB, Philips). In both 2D and RT3D images, LV long axis was measured; endocardial and epicardial boundaries were traced, and mass was calculated by use of the biplane method of disks. CMR LV mass values were obtained through standard techniques (MASS Analysis, GE). The RT3D data resulted in significantly larger LV long-axis dimensions and measurements of LV mass that correlated with CMR better (rϭ0.90) than 2D (rϭ0.79). The 2D technique underestimated LV mass (bias, 39%), whereas RT3D measurements showed only minimal bias (3%). The 95% limits of agreement were significantly wider for 2D (52%) than RT3D (28%). Additionally, the RT3D technique reduced the interobserver variability (37% to 7%) and intraobserver variability (19% to 8%). Conclusions-RT3D imaging provides the basis for accurate and reliable measurement of LV mass.
Despite the post-operative reduction of RV performance along the long axis suggested by TAPSE and PSV, the absence of a decrease in 3D RVEF leads to caution in the interpretation of these 2D and Doppler parameters after cardiac surgery, supporting the hypothesis of geometrical rather than functional changes in the right ventricle.
Background-Real-time 3D echocardiographic (RT3DE) data sets contain dynamic volumetric information on cardiac function. However, quantification of left ventricular (LV) function from 3D echocardiographic data is performed on cut-planes extracted from the 3D data sets and thus does not fully exploit the volumetric information. Accordingly, we developed a volumetric analysis technique aimed at quantification of global and regional LV function. Methods and Results-RT3DE images obtained in 30 patients (Philips 7500) were analyzed by use of custom software based on the level-set approach for semiautomated detection of LV endocardial surface throughout the cardiac cycle, from which global and regional LV volume (LVV)-time and wall motion (WM)-time curves were obtained. The study design included 3 protocols. In protocol 1, time curves obtained in 16 patients were compared point-by-point with MRI data (linear regression and Bland-Altman analyses). Global LVV correlated highly with MRI (rϭ0.98; yϭ0.99xϩ2.3) with minimal bias (1.4 mL) and narrow limits of agreement (Ϯ20 mL). WM correlated highly only in basal and midventricular segments (rϭ0.88; yϭ0.85xϩ0.7).In protocol 2, we tested the ability of this technique to differentiate populations with known differences in LV function by studying 9 patients with dilated cardiomyopathy and 9 normal subjects. All calculated indices of global and regional systolic and diastolic LV function were significantly different between the groups. In protocol 3, we tested the feasibility of automated detection of regional WM abnormalities in 11 patients. In each segment, abnormality was detected when regional shortening fraction was below a threshold obtained in normal subjects. The automated detection agreed with expert interpretation of 2D WM in 86% of segments.
Conclusions-Volumetric
We aim at testing the possibility to build patientspecific structural finite element models (FEMs) of the mitral valve (MV) from cardiac magnetic resonance (CMR) imaging and to use them to predict the outcome of mitral annuloplasty procedures. MV FEMs were built for one healthy subject and for one patient with ischemic mitral regurgitation. On both subjects, CMR imaging of 18 longaxis planes was performed with a temporal resolution of 55 time-frames per cardiac cycle. Three-dimensional MV annulus geometry, leaflets surface and PM position were manually obtained using custom software. Hyperelastic anisotropic mechanical properties were assigned to MV tissues. A physiological pressure load was applied to the leaflets to simulate valve closure until peak systole. For the pathological model only, a further simulation was run, simulating undersized rigid annuloplasty before valve closure. Closure dynamics, leaflets stresses and tensions in the subvalvular apparatus in the healthy MV were consistent with previous computational and experimental data. The regurgitant valve model captured with good approximation the real size and position of regurgitant areas at peak systole, and highlighted abnormal tensions in the annular region and sub-valvular apparatus. The simulation of undersized rigid annuloplasty showed the restoration of MV continence and normal tensions in the subvalvular apparatus and at the annulus. Our method seems suitable for implementing detailed patient-specific MV FEMs to simulate different scenarios of clinical interest. Further work is mandatory to test the method more deeply, to reduce its computational time and to expand the range of modeled surgical procedures.
In the current scientific literature, particular attention is dedicated to the study of the mitral valve and to comprehension of the mechanisms that lead to its normal function, as well as those that trigger possible pathological conditions. One of the adopted approaches consists of computational modelling, which allows quantitative analysis of the mechanical behaviour of the valve by means of continuum mechanics theory and numerical techniques. However, none of the currently available models realistically accounts for all of the aspects that characterize the function of the mitral valve. Here, a new computational model of the mitral valve has been developed from in vivo data, as a first step towards the development of patient-specific models for the evaluation of annuloplasty procedures. A structural finiteelement model of the mitral valve has been developed to account for all of the main valvular substructures. In particular, it includes the real geometry and the movement of the annulus and papillary muscles, reconstructed from four-dimensional ultrasound data from a healthy human subject, and a realistic description of the complex mechanical properties of mitral tissues. Preliminary simulations allowed mitral valve closure to be realistically mimicked and the role of annulus and papillary muscle dynamics to be quantified.
A dynamic linear parametric model is designed to quantify the dependence of ventricular repolarisation duration variability on heart period changes and other immeasurable factors. The model analyses the beat-to-beat series of the RR duration and of the interval between R- and T-wave apexes (RT period). Directly from these two signals, a parametric identification procedure and spectral decomposition techniques allow RT variability to be divided into RR-related and RR-unrelated parts and allow the RT-RR transfer function to be calculated. RT variability is driven by RR changes at low frequency (LF, around 0.1 Hz) and high frequency (HF, at the respiratory rate), whereas, at very low frequencies, the RR-unrelated contribution to the total RT variability is remarkable. During tilt at LF the RR-related RT percentage power increases (p < 0.02), the RR-unrelated RT percentage power remains unchanged, the gain of the RT-RR relationship largely increases (p < 0.001), and the phase is not significantly modified. Both the RR-related and the RR-unrelated RT percentage powers at LF are not affected by controlled respiration, and an increase in the RT-RR gain at HF is observed (p < 0.02). The proposed analysis may help to describe the regulation of the ventricular repolarisation process and to extract indexes quantifying the coupling between heart period and ventricular repolarisation interval changes.
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