281 research outputs found

    Segmentation of Myocardial Boundaries in Tagged Cardiac MRI Using Active Contours: A Gradient-Based Approach Integrating Texture Analysis

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    The noninvasive assessment of cardiac function is of first importance for the diagnosis of cardiovascular diseases. Among all medical scanners only a few enables radiologists to evaluate the local cardiac motion. Tagged cardiac MRI is one of them. This protocol generates on Short-Axis (SA) sequences a dark grid which is deformed in accordance with the cardiac motion. Tracking the grid allows specialists a local estimation of cardiac geometrical parameters within myocardium. The work described in this paper aims to automate the myocardial contours detection in order to optimize the detection and the tracking of the grid of tags within myocardium. The method we have developed for endocardial and epicardial contours detection is based on the use of texture analysis and active contours models. Texture analysis allows us to define energy maps more efficient than those usually used in active contours methods where attractor is often based on gradient and which were useless in our case of study, for quality of tagged cardiac MRI is very poor

    Three-Dimensional Motion Reconstruction and Analysis of the Right Ventricle Using Tagged MRI

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    Right ventricular (RV) dysfunction can serve as an indicator of heart and lung disease and can adversely affect the left ventricle (LV). However, normal RV function must be characterized before abnormal states can be detected. We can describe a method for reconstructing the 3D motion of the RV images by fitting of a deformable model to extracted tag and contour data from multiview tagged magnetic resonance images(MRI). The deformable model is a biventricular finite element mesh built directly from the contours. Our approach accommodates the geometrically complex RV by using the entire lengths of the tags, localized degrees of freedom (DOFs), and finite elements for geometric modeling. We convert the results of the reconstruction into potentially useful motion variables, such as strains and displacements. The fitting technique is applied to synthetic data, two normal hearts, and a heart with right ventricular hypertrophy (RVH). The results in this paper are limited to the RV free wall and septum. We find noticeable differences between the motion variables calculated for the normal volunteers and the RVH patient

    Analysis of myocardial motion using generalized spline models and tagged magnetic resonance images

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    Heart wall motion abnormalities are the very sensitive indicators of common heart diseases, such as myocardial infarction and ischemia. Regional strain analysis is especially important in diagnosing local abnormalities and mechanical changes in the myocardium. In this work, we present a complete method for the analysis of cardiac motion and the evaluation of regional strain in the left ventricular wall. The method is based on the generalized spline models and tagged magnetic resonance images (MRI) of the left ventricle. The whole method combines dynamical tracking of tag deformation, simulating cardiac movement and accurately computing the regional strain distribution. More specifically, the analysis of cardiac motion is performed in three stages. Firstly, material points within the myocardium are tracked over time using a semi-automated snake-based tag tracking algorithm developed for this purpose. This procedure is repeated in three orthogonal axes so as to generate a set of one-dimensional sample measurements of the displacement field. The 3D-displacement field is then reconstructed from this sample set by using a generalized vector spline model. The spline reconstruction of the displacement field is explicitly expressed as a linear combination of a spline kernel function associated with each sample point and a polynomial term. Finally, the strain tensor (linear or nonlinear) with three direct components and three shear components is calculated by applying a differential operator directly to the displacement function. The proposed method is computationally effective and easy to perform on tagged MR images. The preliminary study has shown potential advantages of using this method for the analysis of myocardial motion and the quantification of regional strain

    Model-Based Shape and Motion Analysis: Left Ventricle of a Heart

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    The accurate and clinically useful estimation of the shape, motion, and deformation of the left ventricle of a heart (LV) is an important yet open research problem. Recently, computer vision techniques for reconstructing the 3-D shape and motion of the LV have been developed. The main drawback of these techniques, however, is that their models are formulated in terms of either too many local parameters that require non-trivial processing to be useful for close to real time diagnosis, or too few parameters to offer an adequate approximation to the LV motion. To address the problem, we present a new class of volumetric primitives for a compact and accurate LV shape representation in which model parameters are functions. Lagrangian dynamics are employed to convert geometric models into dynamic models that can deform according to the forces manifested in the data points. It is thus possible to make a precise estimation of the deformation of the LV shape endocardial, epicardial and anywhere in between with a small number of intuitive parameter functions. We believe that the proposed technique has a wide range of potential applications. In this thesis, we demonstrate the possibility by applying it to the 3-D LV shape and motion characterization from magnetic tagging data (MRI-SPAMM). We show that the results of our experiments with normal and abnormal heart data enable us to quantitatively verify the physicians\u27 qualitative conception of the left ventricular wall motion

    Magnetic resonance imaging detects significant sex differences in human myocardial strain

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    <p>Abstract</p> <p>Background</p> <p>The pathophysiology responsible for the significant outcome disparities between men and women with cardiac disease is largely unknown. Further investigation into basic cardiac physiological differences between the sexes is needed. This study utilized magnetic resonance imaging (MRI)-based multiparametric strain analysis to search for sex-based differences in regional myocardial contractile function.</p> <p>Methods</p> <p>End-systolic strain (circumferential, longitudinal, and radial) was interpolated from MRI-based radiofrequency tissue tagging grid point displacements in each of 60 normal adult volunteers (32 females).</p> <p>Results</p> <p>The average global left ventricular (LV) strain among normal female volunteers (n = 32) was significantly larger in absolute value (functionally better) than in normal male volunteers (n = 28) in both the circumferential direction (Male/Female = -0.19 ± 0.02 vs. -0.21 ± 0.02; p = 0.025) and longitudinal direction (Male/Female = -0.14 ± 0.03 vs. -0.16 ± 0.02; p = 0.007).</p> <p>Conclusions</p> <p>The finding of significantly larger circumferential and longitudinal LV strain among normal female volunteers suggests that baseline contractile differences between the sexes may contribute to the well-recognized divergence in cardiovascular disease outcomes. Further work is needed in order to determine the pathologic changes that occur in LV strain between women and men with the onset of cardiovascular disease.</p

    VALIDATION, OPTIMIZATION, AND IMAGE PROCESSING OF SPIRAL CINE DENSE MAGNETIC RESONANCE IMAGING FOR THE QUANTIFICATION OF LEFT AND RIGHT VENTRICULAR MECHANICS

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    Recent evidence suggests that cardiac mechanics (e.g. cardiac strains) are better measures of heart function compared to common clinical metrics like ejection fraction. However, commonly-used parameters of cardiac mechanics remain limited to just a few measurements averaged over the whole left ventricle. We hypothesized that recent advances in cardiac magnetic resonance imaging (MRI) could be extended to provide measures of cardiac mechanics throughout the left and right ventricles (LV and RV, respectively). Displacement Encoding with Stimulated Echoes (DENSE) is a cardiac MRI technique that has been validated for measuring LV mechanics at a magnetic field strength of 1.5 T but not at higher field strengths such as 3.0 T. However, it is desirable to perform DENSE at 3.0 T, which would yield a better signal to noise ratio for imaging the thin RV wall. Results in Chapter 2 support the hypothesis that DENSE has similar accuracy at 1.5 and 3.0 T. Compared to standard, clinical cardiac MRI, DENSE requires more expertise to perform and is not as widely used. If accurate mechanics could be measured from standard MRI, the need for DENSE would be reduced. However, results from Chapter 3 support the hypothesis that measured cardiac mechanics from standard MRI do not agree with, and thus cannot be used in place of, measurements from DENSE. Imaging the thin RV wall with its complex contraction pattern requires both three-dimensional (3D) measures of myocardial motion and higher resolution imaging. Results from Chapter 4 support the hypothesis that a lower displacement-encoding frequency can be used to allow for easier processing of 3D DENSE images. Results from Chapter 5 support the hypothesis that images with higher resolution (decreased blurring) can be achieved by using more spiral interleaves during the DENSE image acquisition. Finally, processing DENSE images to yield measures of cardiac mechanics in the LV is relatively simple due to the LV’s mostly cylindrical geometry. Results from Chapter 6 support the hypothesis that a local coordinate system can be adapted to the geometry of the RV to quantify mechanics in an equivalent manner as the LV. In summary, cardiac mechanics can now be quantified throughout the left and right ventricles using DENSE cardiac MRI

    MR imaging of left-ventricular function : novel image acquisition and analysis techniques.

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    Many cardiac diseases, such as myocardial ischemia, secondary to coronary artery disease, may be identified and localized through the analysis of cardiac deformations. Early efforts for quantifying ventricular wall motion used surgical implantation and tracking of radiopaque markers with X-ray imaging in canine hearts [1]. Such techniques are invasive and affect the regional motion pattern of the ventricular wall during the marker tracking process and, clearly are not feasible clinically. Noninvasive imaging techniques are vital and have been widely applied to the clinic. MRI is a noninvasive imaging technique with the capability to monitor and assess the progression of cardiovascular diseases (CVD) so that effective procedures for the care and treatment of patients can be developed by physicians and researchers. It is capable of providing 3D analysis of global and regional cardiac function with great accuracy and reproducibility. In the past few years, numerous efforts have been devoted to cardiac motion recovery and deformation analysis from MR imaging sequences. In order to assess cardiac function, there are two categories of indices that are used: global and regional indices. Global indices include ejection fraction, cavity volume, and myocardial mass [2]. They are important indices for cardiac disease diagnosis. However, these global indices are not specific for regional analysis. A quantitative assessment of regional parameters may prove beneficial for the diagnosis of disease and evaluation of severity and the quantification of treatment [3]. Local measures, such as wall deformation and strain in all regions of the heart, can provide objective regional quantification of ventricular wall function and relate to the location and extent of ischemic injury. This dissertation is concerned with the development of novel MR imaging techniques and image postprocessing algorithms to analyze left ventricular deformations. A novel pulse sequence, termed Orthogonal CSPAMM (OCSPAMM), has been proposed which results in the same acquisition time as SPAMM for 2D deformation estimation while keeping the main advantages of CSPAMM [4,5]: i.e., maintaining tag contrast through-out the ECG cycle. Different from CSPAMM, in OCSPAMM the second tagging pulse orientation is rotated 90 degrees relative to the first one so that motion information can be obtained simultaneously in two directions. This reduces the acquisition time by a factor of two as compared to the traditional CSPAMM, in which two separate imaging sequences are applied per acquisition. With the application of OCSPAMM, the effect of tag fading encountered in SPAMM tagging due to Tl relaxation is mitigated and tag deformations can be visualized for the entire cardiac cycle, including diastolic phases. A multilevel B-spline fitting method (MBS) has been proposed which incorporates phase-based displacement information for accurate calculation of 2D motion and strain from tagged MRI [6, 7]. The proposed method combines the advantages of continuity and smoothness of MBS, and makes use of phase information derived from tagged MR images. Compared to previous 2D B-spline-based deformation analysis methods, MBS has the following advantages: 1) It can simultaneously achieve a smooth deformation while accurately approximating the given data set; 2) Computationally, it is very fast; and 3) It can produce more accurate deformation results. Since the tag intersections (intersections between two tag lines) can be extracted accurately and are more or less distributed evenly over the myocardium, MBS has proven effective for 2D cardiac motion tracking. To derive phase-based displacements, 2D HARP and SinMod analysis techniques [8,9] were employed. By producing virtual tags from HARP /SinMod and calculating intersections of virtual tag lines, more data points are obtained. In the reference frame, virtual tag lines are the isoparametric curves of an undeformed 2D B-spline model. In subsequent frames, the locations of intersections of virtual tag lines over the myocardium are updated with phase-based displacement. The advantage of the technique is that in acquiring denser myocardial displacements, it uses both real and virtual tag line intersections. It is fast and more accurate than 2D HARP and SinMod tracking. A novel 3D sine wave modeling (3D SinMod) approach for automatic analysis of 3D cardiac deformations has been proposed [10]. An accelerated 3D complementary spatial modulation of magnetization (CSPAMM) tagging technique [11] was used to acquire complete 3D+t tagged MR data sets of the whole heart (3 dynamic CSPAMM tagged MRI volume with tags in different orientations), in-vivo, in 54 heart beats and within 3 breath-holds. In 3D SinMod, the intensity distribution around each pixel is modeled as a cosine wave front. The principle behind 3D SinMod tracking is that both phase and frequency for each voxel are determined directly from the frequency analysis and the displacement is calculated from the quotient of phase difference and local frequency. The deformation fields clearly demonstrate longitudinal shortening during systole. The contraction of the LV base towards the apex as well as the torsional motion between basal and apical slices is clearly observable from the displacements. 3D SinMod can automatically process the image data to derive measures of motion, deformations, and strains between consecutive pair of tagged volumes in 17 seconds. Therefore, comprehensive 4D imaging and postprocessing for determination of ventricular function is now possible in under 10 minutes. For validation of 3D SinMod, 7 3D+t CSPAMM data sets of healthy subjects have been processed. Comparison of mid-wall contour deformations and circumferential shortening results by 3D SinMod showed good agreement with those by 3D HARP. Tag lines tracked by the proposed technique were also compared with manually delineated ones. The average errors calculated for the systolic phase of the cardiac cycles were in the sub-pixel range

    Meshless deformable models for LV motion analysis

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    We propose a novel meshless deformable model for in vivo cardiac left ventricle (LV) 3D motion estimation. As a relatively new technology, tagged MRI (tMRI) provides a direct and noninvasive way to reveal local deformation of the myocardium, which creates a large amount of heart motion data which requiring quantitative analysis. In our study, we sample the heart motion sparsely at intersections of three sets of orthogonal tagging planes and then use a new meshless deformable model to recover the dense 3D motion of the myocardium temporally during the cardiac cycle. We compute external forces at tag intersections based on tracked local motion and redistribute the force to meshless particles throughout the myocardium. Internal constraint forces at particles are derived from local strain energy using a Moving Least Squares (MLS) method. The dense 3D motion field is then computed and updated using the Lagrange equation. The new model avoids the singularity problem of mesh-based models and is capable of tracking large deformation with high efficiency and accuracy. In particular, the model performs well even when the control points (tag intersections) are relatively sparse. We tested the performance of the meshless model on a numerical phantom, as well as in vivo heart data of healthy subjects and patients. The experimental results show that the meshless deformable model can fully recover the myocardium motion in 3D. 1

    Deformable models with parameter functions for cardiac motion analysis from tagged MRI data

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    Motion tracking tMRI datasets to quantify abnormal left ventricle motion using finite element modelling

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    According to `The Atlas of Heart Disease and Stroke'[MMMG04] published by the World Health Organization, heart disease accounts for nearly half the deaths in both the developed and developing countries and is the world's single biggest killer. However, early detection of a diseased heart condition can prevent many of these fatalities. Regional wall motion abnormalities of the heart precede both ECG abnormalities and chest pain as an indicator of myocardial ischaemia and are an excellent indicator of coronary stenosis [GZM97]. These motion abnormalities of the heart muscle are difficult to observe and track, because the heart is a relatively smooth organ with few landmarks and non-rigid motion with a twisting motion or tangential component. The MRI tissue-tagging technique gives researchers the first glimpse into how the heart actually beats. This research uses the tagged MRI images of the heart to create a three dimensional model of a beating heart indicating the stress of a region. Tagged MRI techniques are still developing and vary vastly, meaning that there needs to be a methodology that can adapt to these changes rapidly and effectively, to meet the needs of the evolving technology. The focus of this research is to develop and test such a methodology by the means of a Strain Estimation Pipeline along with an effective way of validating any changes made to the individual processes that it comprises of
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