Faculty Bibliography

The task of imaging is to gather spatiotemporal information which can be organized into a coherent map. Tomographic imaging in particular involves the use of multiple projections, or other interactions of a probe (light, sound, etc.) with a body, in order to determine cross-sectional information. Though the probes and the corresponding imaging modalities may vary, and though the methodology of particular imaging approaches is in constant ferment, the conceptual underpinnings of tomographic imaging have in many ways remained fixed for many decades. Recent advances in applied mathematics, however, have begun to roil this intellectual landscape. The advent of compressed sensing, anticipated in various algorithms dating back many years but unleashed in full theoretical force in the last decade, has changed the way imagers have begun to think about data acquisition and image reconstruction. The power of incoherent sampling and sparsity-enforcing reconstruction has been demonstrated in various contexts and, when combined with other modern fast imaging techniques, has enabled unprecedented increases in imaging efficiency. Perhaps more importantly, however, such approaches have spurred a shift in perspective, prompting us to focus less on nominal data sufficiency than on information content. Beginning with examples from MRI, then proceeding through selected other modalities such as CT and PET, as well as multimodality combinations, this paper explores the potential of newly evolving acquisition and reconstruction paradigms to change the way we do imaging in the lab and in the clinic.

Multi-contrast magnetic resonance imaging (MRI) is a useful technique to aid clinical diagnosis. This paper proposes an efficient algorithm to jointly reconstruct multiple T1/T2-weighted images of the same anatomical cross section from partially sampled k-space data. The joint reconstruction problem is formulated as minimizing a linear combination of three terms, corresponding to a least squares data fitting, joint total variation (TV) and group wavelet-sparsity regularization. It is rooted in two observations: 1) the variance of image gradients should be similar for the same spatial position across multiple contrasts; 2) the wavelet coefficients of all images from the same anatomical cross section should have similar sparse modes. To efficiently solve this problem, we decompose it into joint TV regularization and group sparsity subproblems, respectively. Finally, the reconstructed image is obtained from the weighted average of solutions from the two subproblems, in an iterative framework. Experiments demonstrate the efficiency and effectiveness of the proposed method compared to existing multi-contrast MRI methods.

This article is an invited editorial comment on the paper entitled "In vivo cardiovascular magnetic resonance diffusion tensor imaging shows evidence of abnormal myocardial laminar orientations and mobility in hypertrophic cardiomyopathy" by Ferreira et al., and published as Journal of Cardiovascular Magnetic Resonance 2014; 16:87.

BACKGROUND: Measurement of mitral annulus (MA) dynamics is an important component of the evaluation of left ventricular (LV) diastolic function; MA velocities are commonly measured using tissue Doppler imaging (TDI). This study aimed to examine the clinical potential of a semi-automated cardiovascular magnetic resonance (CMR) technique for quantifying global LV diastolic function, using 3D volume tracking of the MA with conventional cine-CMR images. METHODS: 124 consecutive patients with normal ejection fraction underwent both clinically indicated transthoracic echocardiography (TTE) and CMR within 2 months. Interpolated 3D reconstruction of the MA over time was performed with semi-automated atrioventricular junction (AVJ) tracking in long-axis cine-CMR images, producing an MA sweep volume over the cardiac cycle. CMR-based diastolic function was evaluated, using the following parameters: peak volume sweep rates in early diastole (PSRE) and atrial systole (PSRA), PSRE/PSRA ratio, deceleration time of sweep volume (DTSV), and 50% diastolic sweep volume recovery time (DSVRT50); these were compared with TTE diastolic measurements. RESULTS: Patients with TTE-based diastolic dysfunction (n = 62) showed significantly different normalized MA sweep volume profiles compared to those with TTE-based normal diastolic function (n = 62), including a lower PSRE (5.25 +/- 1.38 s-1 vs. 7.72 +/- 1.7 s-1), a higher PSRA (6.56 +/- 1.99 s-1 vs. 4.67 +/- 1.38 s-1), a lower PSRE/PSRA ratio (0.9 +/- 0.44 vs. 1.82 +/- 0.69), a longer DTSV (144 +/- 55 ms vs. 96 +/- 37 ms), and a longer DSVRT50 (25.0 +/- 11.0% vs. 15.6 +/- 4.0%) (all p < 0.05). CMR diastolic parameters were independent predictors of TTE-based diastolic dysfunction after adjusting for left ventricular hypertrophy, hypertension, and coronary artery disease. Good correlations were observed between CMR PSRE/PSRA and early-to-late diastolic annular velocity ratios (e'/a') measured by TDI (r = 0.756 to 0.828, p < 0.001). CONCLUSIONS: 3D MA sweep volumes generated by semi-automated AVJ tracking in routinely acquired CMR images yielded diastolic parameters that were effective in identifying patients with diastolic dysfunction when correlated with TTE-based variables.

PURPOSE: To develop a fast and flexible free-breathing dynamic volumetric MRI technique, iterative Golden-angle RAdial Sparse Parallel MRI (iGRASP), that combines compressed sensing, parallel imaging, and golden-angle radial sampling. METHODS: Radial k-space data are acquired continuously using the golden-angle scheme and sorted into time series by grouping an arbitrary number of consecutive spokes into temporal frames. An iterative reconstruction procedure is then performed on the undersampled time series where joint multicoil sparsity is enforced by applying a total-variation constraint along the temporal dimension. Required coil-sensitivity profiles are obtained from the time-averaged data. RESULTS: iGRASP achieved higher acceleration capability than either parallel imaging or coil-by-coil compressed sensing alone. It enabled dynamic volumetric imaging with high spatial and temporal resolution for various clinical applications, including free-breathing dynamic contrast-enhanced imaging in the abdomen of both adult and pediatric patients, and in the breast and neck of adult patients. CONCLUSION: The high performance and flexibility provided by iGRASP can improve clinical studies that require robustness to motion and simultaneous high spatial and temporal resolution. Magn Reson Med, 2013. (c) 2013 Wiley Periodicals, Inc.

Deformable models integrate bottom-up information derived from image appearance cues and top-down priori knowledge of the shape. They have been widely used with success in medical image analysis. One limitation of traditional deformable models is that the information extracted from the image data may contain gross errors, which adversely affect the deformation accuracy. To alleviate this issue, we introduce a new family of deformable models that are inspired from the compressed sensing, a technique for accurate signal reconstruction by harnessing some sparseness priors. In this paper, we employ sparsity constraints to handle the outliers or gross errors, and integrate them seamlessly with deformable models. The proposed new formulation is applied to the analysis of cardiac motion using tagged magnetic resonance imaging (tMRI), where the automated tagging line tracking results are very noisy due to the poor image quality. Our new deformable models track the heart motion robustly, and the resulting strains are consistent with those calculated from manual labels.

Primary tumors of the aorta are rare entities. We report the unusual manifestation of an aortic intimal sarcoma that presented as a brain metastasis in a 56-year-old, otherwise healthy woman. After the brain mass had been resected, multiple imaging methods revealed pseudocoarctation and the primary tumor in the aortic arch. To our knowledge, this is the first report of the diagnosis of an aortic intimal sarcoma with use of real-time, 3-dimensional transesophageal echocardiography.

BACKGROUND: We have developed a novel and practical cardiovascular magnetic resonance (CMR) technique to evaluate left ventricular (LV) mitral annular motion by tracking the atrioventricular junction (AVJ). To test AVJ motion analysis as a metric for LV function, we compared AVJ motion variables between patients with hypertrophic cardiomyopathy (HCM), a group with recognized systolic and diastolic dysfunction, and healthy volunteers. METHODS: We retrospectively evaluated 24 HCM patients with normal ejection fractions (EF) and 14 healthy volunteers. Using the 4-chamber view cine images, we tracked the longitudinal motion of the lateral and septal AVJ at 25 time points during the cardiac cycle. Based on AVJ displacement versus time, we calculated maximum AVJ displacement (MD) and velocity in early diastole (MVED), velocity in diastasis (VDS) and the composite index VDS/MVED. RESULTS: Patients with HCM showed significantly slower median lateral and septal AVJ recoil velocities during early diastole, but faster velocities in diastasis. We observed a 16-fold difference in VDS/MVED at the lateral AVJ [median 0.141, interquartile range (IQR) 0.073, 0.166 versus 0.009 IQR -0.006, 0.037, P < 0.001]. Patients with HCM also demonstrated significantly less mitral annular excursion at both the septal and lateral AVJ. Performed offline, AVJ motion analysis took approximately 10 minutes per subject. CONCLUSIONS: Atrioventricular junction motion analysis provides a practical and novel CMR method to assess mitral annular motion. In this proof of concept study we found highly statistically significant differences in mitral annular excursion and recoil between HCM patients and healthy volunteers.