Acquisition and Reconstruction Techniques for Fat Quantification Using Magnetic Resonance Imaging

Quantifying the tissue fat concentration is important for several diseases in various organs including liver, heart, skeletal muscle and kidney. Uniquely, MRI can separate the signal from water and fat in-vivo, rendering it the most suitable imaging modality for non-invasive fat quantification. Chemical-shift-encoded MRI is commonly used for quantitative fat measurement due to its unique ability to generate a separate image for water and fat. The tissue fat concentration can be consequently estimated from the two images. However, several confounding factors can hinder the water/fat separation process, leading to incorrect estimation of fat concentration. The inhomogeneities of the main magnetic field represent the main obstacle to water/fat separation. Most existing techniques rely mainly on imposing spatial smoothness constraints to address this problem; however, these often fail to resolve large and abrupt variations in the magnetic field. A novel convex relaxation approach to water/fat separation is proposed. The technique is compared to existing methods, demonstrating its robustness to resolve abrupt magnetic field inhomogeneities. Water/fat separation requires the acquisition of multiple images with different echo-times, which prolongs the acquisition time. Bipolar acquisitions can efficiently acquire the required data in shorter time. However, they induce phase errors that significantly distort the fat measurements. A new bipolar acquisition strategy that overcomes the phase errors and provides accurate fat measurements is proposed. The technique is compared to the current clinical sequence, demonstrating its efficiency in phantoms and in-vivo experiments. The proposed acquisition technique is also applied on animal models to achieve higher spatial resolution than the current sequence. In conclusion, this dissertation describes a complete framework for accurate and precise MRI fat quantification. Novel acquisitions and reconstruction techniques that address the current challenges for fat quantification are proposed

Intra-thoracic fat volume is associated with myocardial infarction in patients with metabolic syndrome

Background: Visceral adiposity is increased in those with Metabolic Syndrome (MetS) and atherosclerotic disease burden. In this study we evaluate for associations between intra-thoracic fat volume (ITFV) and myocardial infarction (MI) in patients with MetS. Methods. Ninety-four patients with MetS, MI or both were identified from a cardiovascular CMR clinical registry. MetS was defined in accordance to published guidelines; where-as MI was defined as the presence of subendocardial-based injury on late gadolinium enhancement imaging in a coronary vascular distribution. A healthy control group was also obtained from the same registry. Patients were selected into the following groups: MetS+/MI- (N = 32), MetS-/MI + (N = 30), MetS+/MI + (N = 32), MetS-/MI- (N = 16). ITFV quantification was performed using signal threshold analysis of sequential sagittal CMR datasets (HASTE) and indexed to body mass index. Results: The mean age of the population was 59.8 ± 12.5 years. MetS+ patients (N=64) demonstrated a significantly higher indexed ITFV compared to MetS- patients (p = 0.05). Patients in respective MetS-/MI-, MetS+/MI-, MetS-/MI+, and MetS+/MI + study groups demonstrated a progressive elevation in the indexed ITFV (22.3 ± 10.6, 28.6 ± 12.6, 30.6 ± 12.3, and 35.2 ± 11.4 ml/kg/m2, (p = 0.002)). Among MetS+ patients those with MI showed a significantly higher indexed ITFV compared to those without MI (p = 0.02). Conclusions: ITFV is elevated in patients with MetS and incrementally elevated among those with evidence of prior ischemic myocardial injury. Accordingly, the quantification of ITFV may be a valuable marker of myocardial infarction risk among patients with MetS and warrants further investigation. © 2013 Jolly et al.; licensee BioMed Central Ltd

A convex relaxation approach to fat/water separation with minimum label description

While Magnetic Resonance Imaging is capable of separating water and fat components in the body, mapping of magnetic field inhomogeneities is essential for the successful application of this process. In this study, we address the problem of field map estimation using a convex-relaxed max-flow method. We propose a novel two-stage approach that leads to the global optimum of the proposed problem. The first stage minimizes the signal residuals via a convexrelaxed minimum description length (MDL)-based approach. The MDL-based labeling model penalizes the total number of appearing labels, which helps to avoid field map errors when abrupt changes in field homogeneity exist. By exploring the whole range of possible frequency offsets, this stage ensures limiting the estimated field offset within certain boundaries where the global minimum resides. The second stage employs the output of the labeling model in a commonly used gradient-descent based method (known as IDEAL) to converge to the exact global minimum, i.e. the required value of the field offset. Experimental results for cardiac imaging, where challenging field inhomogeneities exist, showed that our method significantly outperforms over a widely-used technique for fat/water separation in terms of robustness and efficiency