Simultaneous use of Individual and Joint Regularization Terms in Compressive Sensing: Joint Reconstruction of Multi-Channel Multi-Contrast MRI Acquisitions

Purpose: A time-efficient strategy to acquire high-quality multi-contrast images is to reconstruct undersampled data with joint regularization terms that leverage common information across contrasts. However, these terms can cause leakage of uncommon features among contrasts, compromising diagnostic utility. The goal of this study is to develop a compressive sensing method for multi-channel multi-contrast magnetic resonance imaging (MRI) that optimally utilizes shared information while preventing feature leakage. Theory: Joint regularization terms group sparsity and colour total variation are used to exploit common features across images while individual sparsity and total variation are also used to prevent leakage of distinct features across contrasts. The multi-channel multi-contrast reconstruction problem is solved via a fast algorithm based on Alternating Direction Method of Multipliers. Methods: The proposed method is compared against using only individual and only joint regularization terms in reconstruction. Comparisons were performed on single-channel simulated and multi-channel in-vivo datasets in terms of reconstruction quality and neuroradiologist reader scores. Results: The proposed method demonstrates rapid convergence and improved image quality for both simulated and in-vivo datasets. Furthermore, while reconstructions that solely use joint regularization terms are prone to leakage-of-features, the proposed method reliably avoids leakage via simultaneous use of joint and individual terms. Conclusion: The proposed compressive sensing method performs fast reconstruction of multi-channel multi-contrast MRI data with improved image quality. It offers reliability against feature leakage in joint reconstructions, thereby holding great promise for clinical use.Comment: 13 pages, 13 figures. Submitted for possible publicatio

Research gaps in diet and nutrition in inflammatory bowel disease. A topical review by D-ECCO Working Group (Dietitians of ECCO)

Although the current doctrine of IBD pathogenesis proposes an interaction between environmental factors with gut microbiota in genetically-susceptible individuals, dietary exposures have attracted recent interest and are, at least in part, likely to explain the rapid rise in disease incidence and prevalence. The D-ECCO working group along with other ECCO experts with expertise in nutrition, microbiology, physiology and medicine reviewed the evidence investigating the role of diet and nutritional therapy in the onset, perpetuation and management of IBD. A narrative topical review is presented where evidence pertinent to the topic is summarized collectively under three main thematic domains: i) the role of diet as an environmental factor in IBD aetiology; ii) the role of diet as induction and maintenance therapy in IBD; and iii) assessment of nutritional status and supportive nutritional therapy in IBD. A summary of research gaps for each of these thematic domains is proposed which is anticipated to be agenda setting for future research in the area of diet and nutrition in IBD

A SPAK Isoform Switch Modulates Renal Salt Transport and Blood Pressure

SummaryThe renal thick ascending limb (TAL) and distal convoluted tubule (DCT) play central roles in salt homeostasis and blood pressure regulation. An emerging model suggests that bumetanide- and thiazide-sensitive NaCl transporters (NKCC2 and NCC) along these segments are phosphorylated and activated by WNK kinases, via SPAK and OSR1. Here, we show that a kidney-specific SPAK isoform, which lacks the kinase domain, inhibits phosphorylation of NCC and NKCC2 by full-length SPAK in vitro. Kidney-specific SPAK is highly expressed along the TAL, whereas full-length SPAK is more highly expressed along the DCT. As predicted from the differential expression, SPAK knockout in animals has divergent effects along TAL and DCT, with increased phosphorylated NKCC2 along TAL and decreased phosphorylated NCC along DCT. In mice, extracellular fluid volume depletion shifts SPAK isoform abundance to favor NaCl retention along both segments, indicating that a SPAK isoform switch modulates sodium avidity along the distal nephron

Low drive field amplitude for improved image resolution in magnetic particle imaging

Purpose: Magnetic particle imaging (MPI) is a new imaging technology that directly detects superparamagnetic iron oxide nanoparticles. The technique has potential medical applications in angiography, cell tracking, and cancer detection. In this paper, the authors explore how nanoparticle relaxation affects image resolution. Historically, researchers have analyzed nanoparticle behavior by studying the time constant of the nanoparticle physical rotation. In contrast, in this paper, the authors focus instead on how the time constant of nanoparticle rotation affects the final image resolution, and this reveals nonobvious conclusions for tailoring MPI imaging parameters for optimal spatial resolution. Methods: The authors first extend x-space systems theory to include nanoparticle relaxation. The authors then measure the spatial resolution and relative signal levels in an MPI relaxometer and a 3D MPI imager at multiple drive field amplitudes and frequencies. Finally, these image measurements are used to estimate relaxation times and nanoparticle phase lags. Results: The authors demonstrate that spatial resolution, as measured by full-width at half-maximum, improves at lower drive field amplitudes. The authors further determine that relaxation in MPI can be approximated as a frequency-independent phase lag. These results enable the authors to accurately predict MPI resolution and sensitivity across a wide range of drive field amplitudes and frequencies. Conclusions: To balance resolution, signal-to-noise ratio, specific absorption rate, and magnetostimulation requirements, the drive field can be a low amplitude and high frequency. Continued research into how the MPI drive field affects relaxation and its adverse effects will be crucial for developing new nanoparticles tailored to the unique physics of MPI. Moreover, this theory informs researchers how to design scanning sequences to minimize relaxation-induced blurring for better spatial resolution or to exploit relaxation-induced blurring for MPI with molecular contrast. © 2016 American Association of Physicists in Medicine

Joint reconstruction of multi-contrast images: compressive sensing reconstruction using both joint and individual regularization functions

In many clinical settings, multi-contrast images of a patient are acquired to maximize complementary information. With the underlying anatomy being the same, the mutual information in multi-contrast data can be exploited to improve image reconstruction, especially in accelerated acquisition schemes such as Compressive Sensing (CS). This study proposes a CS-reconstruction algorithm that uses four regularization functions; joint L1-sparsity and TV-regularization terms to exploit the mutual information, and individual L1-sparsity and TV-regularization terms to recover unique features in each image. The proposed method is shown to be robust against leakage-of-features across contrasts, and is demonstrated using simulations and in-vivo experiments

Statistically segregated k-space sampling for accelerating multiple-acquisition MRI

A central limitation of multiple-acquisition magnetic resonance imaging (MRI) is the degradation in scan efficiency as the number of distinct datasets grows. Sparse recovery techniques can alleviate this limitation via randomly undersampled acquisitions. A frequent sampling strategy is to prescribe for each acquisition a different random pattern drawn from a common sampling density. However, naive random patterns often contain gaps or clusters across the acquisition dimension that in turn can degrade reconstruction quality or reduce scan efficiency. To address this problem, a statistically-segregated sampling method is proposed for multiple-acquisition MRI. This method generates multiple patterns sequentially, while adaptively modifying the sampling density to minimize k-space overlap across patterns. As a result, it improves incoherence across acquisitions while still maintaining similar sampling density across the radial dimension of k-space. Comprehensive simulations and in vivo results are presented for phase-cycled balanced steady-state free precession and multi-echo T2-weighted imaging. Segregated sampling achieves significantly improved quality in both Fourier and compressedsensing reconstructions of multiple-acquisition datasets