5,834 research outputs found
Transthoracic three-dimensional echocardiography for the assessment of straddling tricuspid or mitral valves
Background The advent of 3D echocardiography has provided a technique which, potentially, could afford significant additional information over conventional cross-sectional echocardiography in the assessment of patients with straddling atrioventricular valves prior to surgical correction. Methods Eight patients, aged from 1 month to 9˙2 years, were examined with 3D echocardiography. All but three had discordant ventriculoarterial connections or double outlet right ventricle. Data suitable for reconstruction was acquired with transthoracic scanning. Right and left ventricular volumes were calculated in the 3D dataset. Results 3D echocardiography proved capable of defining the exact degree of straddling by imaging theproportion of tension apparatus attached to either side of the ventricular septum. It was able also to display the atrioventricular junction “en face”, thus permitting identification of the precise site of insertion of the muscular ventricular septum relative to the atrioventricular junction. This made it possiblefirst, to calculate the degree of valvar override, and second, to predict the location of the penetrating atrioventricular bundle. End-diastolic volume of the right ventricle in those with straddling tricuspid valves was 73 (61–83)% of normal, and, of the left ventricle in those with mitral valvar straddling 71 (40‐97)% of normal. Conclusions 3D echocardiography can aid in planning the optimal surgical procedure in patients with straddling or overrriding atrioventricular valves, as it provides diagnostic information superiorto standard crosssectional techniques. It also allows for exact measurement of the volumes of the respective ventricles
Qualitative grading of aortic regurgitation: a pilot study comparing CMR 4D flow and echocardiography.
Over the past 10 years there has been intense research in the development of volumetric visualization of intracardiac flow by cardiac magnetic resonance (CMR).This volumetric time resolved technique called CMR 4D flow imaging has several advantages over standard CMR. It offers anatomical, functional and flow information in a single free-breathing, ten-minute acquisition. However, the data obtained is large and its processing requires dedicated software. We evaluated a cloud-based application package that combines volumetric data correction and visualization of CMR 4D flow data, and assessed its accuracy for the detection and grading of aortic valve regurgitation using transthoracic echocardiography as reference. Between June 2014 and January 2015, patients planned for clinical CMR were consecutively approached to undergo the supplementary CMR 4D flow acquisition. Fifty four patients(median age 39 years, 32 males) were included. Detection and grading of the aortic valve regurgitation using CMR4D flow imaging were evaluated against transthoracic echocardiography. The agreement between 4D flow CMR and transthoracic echocardiography for grading of aortic valve regurgitation was good (j = 0.73). To identify relevant,more than mild aortic valve regurgitation, CMR 4D flow imaging had a sensitivity of 100 % and specificity of 98 %. Aortic regurgitation can be well visualized, in a similar manner as transthoracic echocardiography, when using CMR 4D flow imaging
Three-dimensional echocardiography for the assessment of congenital and acquired heart disease
Although conventional two-dimensional and Doppler blood-flow
echocardiography are the standard imaging approaches in the assessment of heart
disease they do not provide anatomic reconstructions in a form that resembles the
cardiac morphology as visualized by the surgeon.The work presented in this thesis has explored the hypotheses that threedimensional echocardiography facilitates spatial recognition of intracardiac
structures and therefore enhances the diagnostic confidence of echocardiography in
congenital and acquired heart disease. The accuracy of three-dimensional
reconstructions has been validated in vitro using two different phantoms and in vivo
comparing the results with other established diagnostic techniques or surgical
findings. Additionally, as the main limitation of transthoracic three-dimensional
echocardiography is poor image quality in a substantial proportion of adult patients,
Doppler myocardial imaging has been tested as a potentially superior method to
conventional grey-scale imaging for transthoracic three-dimensional image
acquisition.In vitro, using a virtual computer-generated phantom and a dynamic tissuemimicking phantom, the accuracy of both linear measurements and volume
computation obtained from three-dimensional images was established. For both
grey-scale and Doppler myocardial imaging, a detail of 1.0 mm dimension and two
details separated from each other by a distance of 1.0 mm were the smallest
structures and distances identified from a three-dimensional image. When testing the
accuracy of volume measurements it appeared that both techniques marginally
underestimated the true phantom volume (by approximately 1.0 ml for Doppler
myocardial imaging and 4.0 ml for grey-scale imaging), but the systematic error was
smaller and more constant in the case of Doppler myocardial imaging over the range
of different true volumes.In vivo, the study was designed to compare the accuracy of grey-scale and
Doppler myocardial imaging three-dimensional left ventricular volume
measurements and cineventriculography. The differences were significantly smaller
for the Doppler technique during both end-diastole and end-systole. A series of
congenital heart lesions has also been studied. It has been shown that dynamic
surgical reconstruction of the secundum atrial septal defect is feasible from the
transthoracic approach in all patients. However, in adults, Doppler myocardial
imaging proved more effective than grey-scale imaging in the accuracy of threedimensional defect reconstruction. In patients with sinus venosus atrial septal defect,
transthoracic three-dimensional echocardiography was more accurate than standard
echocardiography in diagnosing the defect including a detailed description of the
abnormal pulmonary venous drainage. Finally, in children with atrio-ventricular
septal defects, the 'unroofed' atrial reconstruction of the common valve accurately
displayed dynamic valve morphology en face and the mechanism of valve reflux
Assessment of hemodynamic conditions in the aorta following root replacement with composite valve-conduit graft
This paper presents the analysis of detailed hemodynamics in the aortas of four patients following replacement with a composite bio-prosthetic valve-conduit. Magnetic resonance image-based computational models were set up for each patient with boundary conditions comprising subject-specific three-dimensional inflow velocity profiles at the aortic root and central pressure waveform at the model outlet. Two normal subjects were also included for comparison. The purpose of the study was to investigate the effects of the valve-conduit on flow in the proximal and distal aorta. The results suggested that following the composite valve-conduit implantation, the vortical flow structure and hemodynamic parameters in the aorta were altered, with slightly reduced helical flow index, elevated wall shear stress and higher non-uniformity in wall shear compared to normal aortas. Inter-individual analysis revealed different hemodynamic conditions among the patients depending on the conduit configuration in the ascending aorta, which is a key factor in determining post-operative aortic flow. Introducing a natural curvature in the conduit to create a smooth transition between the conduit and native aorta may help prevent the occurrence of retrograde and recirculating flow in the aortic arch, which is particularly important when a large portion or the entire ascending aorta needs to be replaced
Real-time three-dimensional ultrasound : a valuable new tool in preoperative assessment of complex congenital cardiac disease
Evaluating complex cardiac defects in small children preoperatively requires multiple diagnostic procedures including echocardiography, and also invasive methods such as cardiac catheterisation, computer-tomography and magnetic resonance imaging. This article assesses the complex anatomy of the atrioventricular valves in atrioventricular septal defect using bedside real-time three-dimensional echocardiography and comparing these results to the anatomic findings at the time of operative intervention.peer-reviewe
Intracardiac 4D flow MRI in congenital heart disease : recommendations on behalf of the ISMRM flow & motion study group
Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.Cardiovascular Aspects of Radiolog
MR image reconstruction using deep density priors
Algorithms for Magnetic Resonance (MR) image reconstruction from undersampled
measurements exploit prior information to compensate for missing k-space data.
Deep learning (DL) provides a powerful framework for extracting such
information from existing image datasets, through learning, and then using it
for reconstruction. Leveraging this, recent methods employed DL to learn
mappings from undersampled to fully sampled images using paired datasets,
including undersampled and corresponding fully sampled images, integrating
prior knowledge implicitly. In this article, we propose an alternative approach
that learns the probability distribution of fully sampled MR images using
unsupervised DL, specifically Variational Autoencoders (VAE), and use this as
an explicit prior term in reconstruction, completely decoupling the encoding
operation from the prior. The resulting reconstruction algorithm enjoys a
powerful image prior to compensate for missing k-space data without requiring
paired datasets for training nor being prone to associated sensitivities, such
as deviations in undersampling patterns used in training and test time or coil
settings. We evaluated the proposed method with T1 weighted images from a
publicly available dataset, multi-coil complex images acquired from healthy
volunteers (N=8) and images with white matter lesions. The proposed algorithm,
using the VAE prior, produced visually high quality reconstructions and
achieved low RMSE values, outperforming most of the alternative methods on the
same dataset. On multi-coil complex data, the algorithm yielded accurate
magnitude and phase reconstruction results. In the experiments on images with
white matter lesions, the method faithfully reconstructed the lesions.
Keywords: Reconstruction, MRI, prior probability, machine learning, deep
learning, unsupervised learning, density estimationComment: Published in IEEE TMI. Main text and supplementary material, 19 pages
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Structure-based finite strain modelling of the human left ventricle in diastole
Finite strain analyses of the left ventricle provide important information on heart function and have the potential to provide insights into the biomechanics of myocardial contractility in health and disease. Systolic dysfunction is the most common cause of heart failure; however, abnormalities of diastolic function also contribute to heart failure, and are associated with conditions including left ventricular hypertrophy and diabetes. The clinical significance of diastolic abnormalities is less well understood than systolic dysfunction, and specific treatments are presently lacking. To obtain qualitative and quantitative information on heart function in diastole, we develop a three-dimensional computational model of the human left ventricle that is derived from noninvasive imaging data. This anatomically realistic model has a rule-based fibre structure and a structure-based constitutive model. We investigate the sensitivity of this comprehensive model to small changes in the constitutive parameters and to changes in the fibre distribution. We make extensive comparisons between this model and similar models that employ different constitutive models, and we demonstrate qualitative and quantitative differences in stress and strain distributions for the different constitutive models. We also provide an initial validation of our model through comparisons to experimental data on stress and strain distributions in the left ventricle
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