Body MRI artifacts in clinical practice: a physicist\u27s and radiologist\u27s perspective.

The high information content of MRI exams brings with it unintended effects, which we call artifacts. The purpose of this review is to promote understanding of these artifacts, so they can be prevented or properly interpreted to optimize diagnostic effectiveness. We begin by addressing static magnetic field uniformity, which is essential for many techniques, such as fat saturation. Eddy currents, resulting from imperfect gradient pulses, are especially problematic for new techniques that depend on high performance gradient switching. Nonuniformity of the transmit radiofrequency system constitutes another source of artifacts, which are increasingly important as magnetic field strength increases. Defects in the receive portion of the radiofrequency system have become a more complex source of problems as the number of radiofrequency coils, and the sophistication of the analysis of their received signals, has increased. Unwanted signals and noise spikes have many causes, often manifesting as zipper or banding artifacts. These image alterations become particularly severe and complex when they are combined with aliasing effects. Aliasing is one of several phenomena addressed in our final section, on artifacts that derive from encoding the MR signals to produce images, also including those related to parallel imaging, chemical shift, motion, and image subtraction

Introduction to quantitative susceptibility mapping and susceptibility weighted imaging.

Quantitative Susceptibility Mapping (QSM) and Susceptibility Weighted Imaging (SWI) are magnetic resonance imaging techniques that measure and display differences in the magnetisation that is induced in tissues, i.e. their magnetic susceptibility, when placed in the strong external magnetic field of an MRI system. SWI produces images in which the contrast is heavily weighted by the intrinsic tissue magnetic susceptibility. It has been applied in a wide range of clinical applications. QSM is a further advancement of this technique that requires sophisticated post-processing in order to provide quantitative maps of tissue susceptibility. This review explains the steps involved in both SWI and QSM as well as describing some of their uses in both clinical and research applications.Mr Ruetten is funded by a Medical Research Council/Sackler Stipend. The project was supported by the Addenbrooke’s Charitable Trust and the National Institute for Health Research [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust]

Subtractive NCE-MRA: Improved background suppression using robust regression-based weighted subtraction.

PURPOSE: To correct the intensity difference of static background signal between bright blood images and dark blood images in subtractive non-contrast-enhanced MR angiography using robust regression, thereby improving static background signal suppression on subtracted angiograms. METHODS: Robust regression (RR), using iteratively reweighted least squares, is used to calculate the regression coefficient of background tissues from a scatter plot showing the voxel intensity of bright blood images versus dark blood images. The weighting function is based on either the Euclidean distance from the estimated regression line or the deviation angle. Results from RR using the deviation angle (RRDA), conventional RR using the Euclidean distance, and ordinary leastsquares regression were compared with reference values determined manually by two observers. Performance was evaluated over studies using different sequences, including 36 thoracic flow-sensitive dephasing data sets, 13 iliac flow-sensitive dephasing data sets, and 26 femoral fresh blood imaging data sets. RESULTS: RR deviation angle achieved robust and accurate performance in all types of images, with small bias, small mean absolute error, and high-correlation coefficients with reference values. Background tissues, such as muscle, veins, and bladder, were suppressed while the vascular signal was preserved. Euclidean distance gave good performance for thoracic and iliac flow-sensitive dephasing, but could not suppress background tissues in femoral fresh blood imaging. Ordinary least squares regression was sensitive to outliers and overestimated regression coefficients in thoracic flow-sensitive dephasing. CONCLUSION: Weighted subtraction using RR was able to acquire the regression coefficients of background signal and improve background suppression of subtractive non-contrast-enhanced MR angiography techniques. RR deviation angle has the most robust and accurate overall performance among three regression methods

In vivo MRI-based simulation of fatigue process: a possible trigger for human carotid atherosclerotic plaque rupture.

BACKGROUND: Atherosclerotic plaque is subjected to a repetitive deformation due to arterial pulsatility during each cardiac cycle and damage may be accumulated over a time period causing fibrous cap (FC) fatigue, which may ultimately lead to rupture. In this study, we investigate the fatigue process in human carotid plaques using in vivo carotid magnetic resonance (MR) imaging. METHOD: Twenty seven patients with atherosclerotic carotid artery disease were included in this study. Multi-sequence, high-resolution MR imaging was performed to depict the plaque structure. Twenty patients were found with ruptured FC or ulceration and 7 without. Modified Paris law was used to govern crack propagation and the propagation direction was perpendicular to the maximum principal stress at the element node located at the vulnerable site. RESULTS: The predicted crack initiations from 20 patients with FC defect all matched with the locations of the in vivo observed FC defect. Crack length increased rapidly with numerical steps. The natural logarithm of fatigue life decreased linearly with the local FC thickness (R(2) = 0.67). Plaques (n=7) without FC defect had a longer fatigue life compared with those with FC defect (p = 0.03). CONCLUSION: Fatigue process seems to explain the development of cracks in FC, which ultimately lead to plaque rupture.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Well-to-wheel analysis of direct and indirect use of natural gas in passenger vehicles

AbstractThe abundance of natural gas in the United States because of the number of existing natural gas reserves and the recent advances in extracting unconventional reserves has been one of the main drivers for low natural gas prices. A question arises of what is the optimal use of natural gas as a transportation fuel. Is it more efficient to use natural gas in a stationary power application to generate electricity to charge electric vehicles, compress natural gas for onboard combustion in vehicles, or re-form natural gas into a denser transportation fuel? This study investigates the well-to-wheels energy use and greenhouse gas emissions from various natural gas to transportation fuel pathways and compares the results to conventional gasoline vehicles and electric vehicles using the US electrical generation mix. Specifically, natural gas vehicles running on compressed natural gas are compared against electric vehicles charged with electricity produced solely from natural gas combustion in stationary power plants. The results of the study show that the dependency on the combustion efficiency of natural gas in stationary power can outweigh the inherent efficiency of electric vehicles, thus highlighting the importance of examining energy use on a well-to-wheels basis

Quantitative BOLD imaging at 3T: Temporal changes in hepatocellular carcinoma and fibrosis following oxygen challenge.

PURPOSE: To evaluate the utility of oxygen challenge and report on temporal changes in blood oxygenation level-dependent (BOLD) contrast in normal liver, hepatocellular carcinoma (HCC) and background fibrosis. MATERIALS AND METHODS: Eleven volunteers (nine male and two female, mean age 33.5, range 27-41 years) and 10 patients (nine male and one female, mean age 68.9, range 56-87 years) with hepatocellular carcinoma on a background of diffuse liver disease were recruited. Imaging was performed on a 3T system using a multiphase, multiecho, fast gradient echo sequence. Oxygen was administered via a Hudson mask after 2 minutes of free-breathing. Paired t-tests were performed to determine if the mean pre- and post-O2 differences were statistically significant. RESULTS: In patients with liver fibrosis (n = 8) the change in T2* following O2 administration was elevated (0.88 ± 0.582 msec, range 0.03-1.69 msec) and the difference was significant (P = 0.004). The magnitude of the BOLD response in patients with HCC (n = 10) was larger, however the response was more variable (1.07 ± 1.458 msec, range -0.93-3.26 msec), and the difference was borderline significant (P = 0.046). The BOLD response in the volunteer cohort was not significant (P = 0.121, 0.59 ± 1.162 msec, range -0.81-2.44 msec). CONCLUSION: This work demonstrates that the BOLD response following oxygen challenge within cirrhotic liver is consistent with a breakdown in vascular autoregulatory mechanisms. Similarly, the elevated BOLD response within HCC is consistent with the abnormal capillary vasculature within tumors and the arterialization of the blood supply. Our results suggest that oxygen challenge may prove a viable BOLD contrast mechanism in the liver. J. Magn. Reson. Imaging 2016;44:739-744.This study was supported by the Addenbrooke’s Charitable Trust, Cambridge’s Experimental Cancer Medicine Centre and a NIHR comprehensive Biomedical Research Centre award to Cambridge University Hospitals NHS Foundation Trust in partnership with the University of Cambridge.This is the final version of the article. It first appeared from Wiley via https://doi.org/10.1002/jmri.2518

Learning the Sampling Pattern for MRI.

The discovery of the theory of compressed sensing brought the realisation that many inverse problems can be solved even when measurements are "incomplete". This is particularly interesting in magnetic resonance imaging (MRI), where long acquisition times can limit its use. In this work, we consider the problem of learning a sparse sampling pattern that can be used to optimally balance acquisition time versus quality of the reconstructed image. We use a supervised learning approach, making the assumption that our training data is representative enough of new data acquisitions. We demonstrate that this is indeed the case, even if the training data consists of just 7 training pairs of measurements and ground-truth images; with a training set of brain images of size 192 by 192, for instance, one of the learned patterns samples only 35% of k-space, however results in reconstructions with mean SSIM 0.914 on a test set of similar images. The proposed framework is general enough to learn arbitrary sampling patterns, including common patterns such as Cartesian, spiral and radial sampling

From Galaxy Clusters to Ultra-Faint Dwarf Spheroidals: A Fundamental Curve Connecting Dispersion-supported Galaxies to Their Dark Matter Halos

We examine scaling relations of dispersion-supported galaxies over more than eight orders of magnitude in luminosity by transforming standard fundamental plane parameters into a space of mass (M1/2), radius (r1/2), and luminosity (L1/2). We find that from ultra-faint dwarf spheroidals to giant cluster spheroids, dispersion-supported galaxies scatter about a one-dimensional "fundamental curve" through this MRL space. The weakness of the M1/2-L1/2 slope on the faint end may imply that potential well depth limits galaxy formation in small galaxies, while the stronger dependence on L1/2 on the bright end suggests that baryonic physics limits galaxy formation in massive galaxies. The mass-radius projection of this curve can be compared to median dark matter halo mass profiles of LCDM halos in order to construct a virial mass-luminosity relationship (Mvir-L) for galaxies that spans seven orders of magnitude in Mvir. Independent of any global abundance or clustering information, we find that (spheroidal) galaxy formation needs to be most efficient in halos of Mvir ~ 10^12 Msun and to become inefficient above and below this scale. Moreover, this profile matching technique is most accurate at the high and low luminosity extremes (where dark matter fractions are highest) and is therefore quite complementary to statistical approaches that rely on having a well-sampled luminosity function. We also consider the significance and utility of the scatter about this relation, and find that in the dSph regime observational errors are almost at the point where we can explore the intrinsic scatter in the luminosity-virial mass relation. Finally, we note that purely stellar systems like Globular Clusters and Ultra Compact Dwarfs do not follow the fundamental curve relation. This allows them to be easily distinguished from dark-matter dominated dSph galaxies in MRL space. (abridged)Comment: 27 pages, 18 figures, ApJ accepted. High-res movies of 3D figures are available at http://www.physics.uci.edu/~bullock/fcurve/movies.htm

A higher order perfectly matched layer formulation for finite-difference time-domain seismic wave modeling

We have developed a higher order perfectly matched layer (PML) formulation to improve the absorption performance for finite-difference time-domain seismic modeling. First, we outlined a new unsplit “correction” approach, which allowed for traditional, first-order PMLs to be added directly to existing codes in a straightforward manner. Then, using this framework, we constructed a PML formulation that can be used to construct higher order PMLs of arbitrary order. The greater number of degrees of freedom associated with the higher order PML allow for enhanced flexibility of the PML stretching functions, thus potentially facilitating enhanced absorption performance. We found that the new approach can offer increased elastodynamic absorption, particularly for evanescent waves. We also discovered that the extra degrees of freedom associated with the higher order PML required careful optimization if enhanced absorption was to be achieved. Furthermore, these extra degrees of freedom increased the computational requirements in comparison with first-order schemes. We reached our formulations using one compact equation thus increasing the ease of implementation. Additionally, the formulations are based on a recursive integration approach that reduce PML memory requirements, and do not require special consideration for corner regions. We tested the new formulations to determine their ability to absorb body waves and surface waves. We also tested standard staggered grid stencils and rotated staggered grid stencils

Likely Impacts of Future Agricultural Change on Upland Farming and Biodiversity

Recent decades have witnessed substantial losses of biodiversity in Europe, partly driven by the ecological changes associated with intensification of agricultural production. These changes have particularly affected avian (bird) diversity in marginal areas such as the uplands of the UK. We developed integrated ecological-economic models, using eight different indicators of biodiversity based on avian species richness and individual bird densities. The models represent six different types of farms which are typical for the UK uplands, and were used to assess the outcomes of different agricultural futures. Our results show that the impacts of these future agricultural scenarios on farm incomes, land use and biodiversity are very diverse across policy scenarios and farm types. Moreover, each policy scenario produces un-equal distributions of farm income changes, and gains and losses in alternative biodiversity indicators. This shows that generalisations of the effects of land use change on biodiversity can be misleading. Our results also suggest that a focus on umbrella species or indicators (such as total richness) can miss important compositional effects