Faculty Bibliography

A new technique was developed to increase the signal-to-noise ratio (SNR) in displacement encoding with stimulated echoes (DENSE) MRI. This signal-averaged DENSE (sav-DENSE) technique is based on the SNR advantage of extracting a pair of DENSE images with uncorrelated noise from the complex complementary spatial modulation of the magnetization image, and combining them during image reconstruction. Eleven healthy volunteers were imaged at three short-axis locations with the use of sav-DENSE, cine DENSE, and myocardial tagging pulse sequences. In this study, sav-DENSE increased the SNR by 15-34% as compared to cine DENSE. Circumferential strain values measured by sav-DENSE and myocardial tagging were strongly correlated (slope = 0.95, intercept = -0.02, R = 0.92) and within the 95% limits of agreement. The breath-hold sav-DENSE technique yielded relatively accurate and precise quantification of 2D intramyocardial function, with a 40.2-ms temporal resolution and a 3.5 x 3.5 mm2 spatial resolution

The interventricular septum (IVS) occupies a unique position within the heart, lying between the left (LV) and right (RV) ventricular cavities. Changes in its normal geometry may signify not only abnormalities of the septal myocardium, but also abnormal pressure differences between the LV and RV. Flattening of the IVS has been noted with cross-sectional imaging in association with pulmonary hypertension, but the septal curvature and shape have not previously been measured in three dimensions. This paper describes a method to model the RV surface of the IVS from spatially registered cross-sectional images for measurements of curvature. A smoothing 2D spline surface is constructed through the RV septal surface at regular times during the cardiac cycle, and the principal curvatures, as well as the Gaussian and mean curvatures, shape index, and curvedness, are calculated. Vector and color surface maps and graphs of average curvature and shape indices are constructed. Consistent curvature patterns were observed in four normal subjects. This method of measuring septal geometry can provide potentially useful new information on the effects of RV disease. We examine the problem of describing septal motion, and describe a simple measure of septal curvature that may be of clinical value

BACKGROUND: The papillary muscles (PMs) play an important role in normal cardiac function, helping to prevent leakage through the AV valves during systole. The nature of their attachment to the heart wall can affect the understanding of their function. This attachment is conventionally portrayed as a direct connection of their bases to the solid portion of the heart wall. X-ray multidetector CT provides a new, noninvasive way to investigate this connection in vivo. METHODS AND RESULTS: With the use of x-ray multidetector CT with interactive 3D reconstruction, the bases of the PMs are seen to attach to the trabeculae carneae lining the ventricular wall rather than directly to the solid portion of the wall, as has been conventionally believed. This is true for both the left and right ventricular PMs. CONCLUSIONS: This new picture of the geometry of the attachment of the PMs to the heart wall may have important implications for the understanding of their function, including the nature of the transmission of the forces between the PMs and the heart wall

Pericardial disease and its consequences can be well shown with magnetic resonance imaging (MRI) and computed tomography (CT). Here I review the normal and pathologic anatomy and physiology of the pericardium, approaches to MRI and CT imaging of the pericardium, and some specific considerations in common conditions affecting the pericardium

This paper presents a new approach for accurate extraction of tissue deformation imaged with tagged MR. Our method, based on banks of Gabor filters, adjusts (1) the aspect and (2) orientation of the filter's envelope and adjusts (3) the radial frequency and (4) angle of the filter's sinusoidal grating to extract information about the deformation of tissue. The method accurately extracts tag line spacing, orientation, displacement and effective contrast. Existing, non-adaptive methods often fail to recover useful displacement information in the proximity of tissue boundaries while our method works in the proximity of the boundaries. We also present an interpolation method to recover all tag information at a finer resolution than the filter bank parameters. Results are shown on simulated images of translating and contracting tissue.

Mechanical properties of the myocardium have been investigated intensively in the last four decades. Many complex strain energy functions have been used to estimate the stress-strain relationship of myocardium because the heart muscle is an inhomogeneous, anisotropic, and nearly incompressible material, which undergoes large deformations. These functions can be effective for fitting in vitro experimental data from myocardial stretch testing. However, it is difficult to model in vivo myocardium using these strain energy functions. Moreover, such estimates have so far been carried out almost exclusively on the left ventricle, because of the relative thinness and complex geometry of the right ventricle. Previous work from our research group has successful estimated the motion and deformation of both the left and the right ventricles, using data from noninvasive tagged magnetic resonance imaging. In this paper, we present a novel statistical model to estimate the in vivo material properties and strain and stress distribution in both ventricles, using such data. Two normal hearts and two hearts with right-ventricular hypertrophy (RVH) were studied and noticeable differences were found between the strain and stress distributions for normal volunteers and RVH patients. Compared to the strain energy function approach, our model is more intuitively understandable

Tagged MRI provides a potentially powerful new way to non-invasively assess the regional function of the heart. Although its potential has not yet been fully realized, due to remaining technical limitations in image acquisition and analysis, good progress is being made to overcome these limitations. Current research focuses on improving imaging methods to obtain high resolution 3D spatially registered tagged images, designing more efficient methods to extract the heart wall contours and tag positions within the wall from the tagged images, and implementing efficient ways to reconstruct the 3D motion of the heart from this data. In addition to the new regional motion and deformation data that tagged MRI can provide on normal and abnormal cardiac function, we can potentially use this motion data to model the corresponding forces within the heart wall

Mechanical properties of the myocardium. have been investigated intensively in the last four decades. Due to the nonlinearity and history dependence of the myocardial deformation, many complex strain energy functions have been used to describe the stress-strain relationship of myocardium. These functions are good at fitting in-vitro experimental data from myocardial stretch testing. However it is difficult to model in-vivo myocardium by using the strain energy functions. In a previous paper [24], we have implemented transversely anisotropic material model to estimate in-vivo strain-stress analysis in the myocardium. In this work, the fiber orientation is updated at each time step from the end of diastole to the end of systole, and the stiffness matrix is recalculated using the current fiber orientation. We also extended our model to include residual ventricular stresses and time dependent blood pressure in the left ventricle cavity

While cardiovascular disease is the leading cause of death in most developed countries, SPAMM-MRI can reduce morbidity by facilitating patient diagnosis. An image analysis method with a high degree of automation is essential for clinical adoption of SPAMM-MRI. The degree of this automation is dependent on the amount of thermal noise and surface coil-induced intensity inhomogeneity that can be removed from the images. An ideal noise suppression algorithm removes thermal noise yet retains or enhances the strength of the edges of salient structures. In this paper, we quantitatively compare and rank several noise suppression algorithms in images from both normal and diseased subjects using measures of the residual noise and edge strength and the statistical significance levels and confidence intervals of these measures. We also investigate the interrelationship between inhomogeneity correction and noise suppression algorithms and compare the effect of the ordering of these algorithms. The variance of thermal noise does not tend to change with position; however, inhomogeneity correction increases noise variance in deep thoracic regions. We quantify the degree to which an inhomogeneity estimate can improve noise suppression and whether noise suppression can facilitate the identification of homogeneous tissue regions, and thereby, assist in inhomogeneity correction.