Fast myocardial T1ρ mapping in mice using k-space weighted image contrast and a Bloch simulation-optimized radial sampling pattern

Purpose T1ρ dispersion quantification can potentially be used as a cardiac magnetic resonance index for sensitive detection of myocardial fibrosis without the need of contrast agents. However, dispersion quantification is still a major challenge, because T1ρ mapping for different spin lock amplitudes is a very time consuming process. This study aims to develop a fast and accurate T1ρ mapping sequence, which paves the way to cardiac T1ρ dispersion quantification within the limited measurement time of an in vivo study in small animals. Methods A radial spin lock sequence was developed using a Bloch simulation-optimized sampling pattern and a view-sharing method for image reconstruction. For validation, phantom measurements with a conventional sampling pattern and a gold standard sequence were compared to examine T1ρ quantification accuracy. The in vivo validation of T1ρ mapping was performed in N = 10 mice and in a reproduction study in a single animal, in which ten maps were acquired in direct succession. Finally, the feasibility of myocardial dispersion quantification was tested in one animal. Results The Bloch simulation-based sampling shows considerably higher image quality as well as improved T1ρ quantification accuracy (+ 56%) and precision (+ 49%) compared to conventional sampling. Compared to the gold standard sequence, a mean deviation of − 0.46 ± 1.84% was observed. The in vivo measurements proved high reproducibility of myocardial T1ρ mapping. The mean T1ρ in the left ventricle was 39.5 ± 1.2 ms for different animals and the maximum deviation was 2.1% in the successive measurements. The myocardial T1ρ dispersion slope, which was measured for the first time in one animal, could be determined to be 4.76 ± 0.23 ms/kHz. Conclusion This new and fast T1ρ quantification technique enables high-resolution myocardial T1ρ mapping and even dispersion quantification within the limited time of an in vivo study and could, therefore, be a reliable tool for improved tissue characterization.

Assessment of Agricultural Land Use Systems for Soil Fertility Maintenance

Land is the most important endowment in nature, providing livelihood in both the agricultural and non-agricultural sectors. However, most areas of land previously developed from tropical rainforest have been degraded as a result of land misuse with nutrient mining and soil degradation presently considered as problems in arable farms. Hence, the extent to which land for crop production influences soil properties need to be studied to greater details due to variations in soils by location. The objective of the study is to investigate the effect of agricultural land use systems on the soil physical and chemical properties. Three representative fields with three replicates each which have been in active use for last 5 years were selected from each agricultural land use types: Cultivated (07.31° N 05.12° E 360.0 M), Agroforestry (07.31° N 05.21° E 373.5 M) and Grazing land (07.29° N 05.35° E 355.0 M). Five soil subsamples were collected from the depths of 0-20 and 20 - 40 cm each in a radial sampling. The data was subjected to analysis of variance (ANOVA) using Statistical Analytical System (SAS) and the means were separated using Duncan’s Multiple Range Test (DMRT) at P<0.05 significant level. The mean values of soil chemical properties are highest in the agroforestry land followed by cultivated and then in the grazing land. Grazing land shows the highest bulk density of (1.87 g/cm3), cultivated (1.30 g/cm3) and then agroforestry (1.24 g/cm3) with same trends recorded in particle density across the land use. The soils significantly responded to changes in land use systems through salient soil features which constitute soil properties governing soil fertility and productivity. Such human-induced change is not limited to surface soils but also the subsurface soils and has remarkable implication for ecosystem quality and productivity of the traditional low-external-input agriculture in the study area.

Radial Undersampling-Based Interpolation Scheme for Multislice CSMRI Reconstruction Techniques

Magnetic Resonance Imaging (MRI) is an important yet slow medical imaging modality. Compressed sensing (CS) theory has enabled to accelerate the MRI acquisition process using some nonlinear reconstruction techniques from even 10% of the Nyquist samples. In recent years, interpolated compressed sensing (iCS) has further reduced the scan time, as compared to CS, by exploiting the strong interslice correlation of multislice MRI. In this paper, an improved efficient interpolated compressed sensing (EiCS) technique is proposed using radial undersampling schemes. The proposed efficient interpolation technique uses three consecutive slices to estimate the missing samples of the central target slice from its two neighboring slices. Seven different evaluation metrics are used to analyze the performance of the proposed technique such as structural similarity index measurement (SSIM), feature similarity index measurement (FSIM), mean square error (MSE), peak signal to noise ratio (PSNR), correlation (CORR), sharpness index (SI), and perceptual image quality evaluator (PIQE) and compared with the latest interpolation techniques. The simulation results show that the proposed EiCS technique has improved image quality and performance using both golden angle and uniform angle radial sampling patterns, with an even lower sampling ratio and maximum information content and using a more practical sampling scheme.

Closed-loop control of k-space sampling via physiologic feedback for cine MRI

Background Segmented cine cardiac MRI combines data from multiple heartbeats to achieve high spatiotemporal resolution cardiac images, yet predefined k-space segmentation trajectories can lead to suboptimal k-space sampling. In this work, we developed and evaluated an autonomous and closed-loop control system for radial k-space sampling (ARKS) to increase sampling uniformity. Methods The closed-loop system autonomously selects radial k-space sampling trajectory during live segmented cine MRI and attempts to optimize angular sampling uniformity by selecting views in regions of k-space that were not previously well-sampled. Sampling uniformity and the ability to detect cardiac phase in vivo was assessed using ECG data acquired from 10 normal subjects in an MRI scanner. The approach was then implemented with a fast gradient echo sequence on a whole-body clinical MRI scanner and imaging was performed in 4 healthy volunteers. The closed-loop k-space trajectory was compared to random, uniformly distributed and golden angle view trajectories via measurement of k-space uniformity and the point spread function. Lastly, an arrhythmic dataset was used to evaluate a potential application of the approach. Results The autonomous trajectory increased k-space sampling uniformity by 15±7%, main lobe point spread function (PSF) signal intensity by 6±4%, and reduced ringing relative to golden angle sampling. When implemented, the autonomous pulse sequence prescribed radial view angles faster than the scan TR (0.98 ± 0.01 ms, maximum = 1.38 ms) and increased k-space sampling mean uniformity by 10±11%, decreased uniformity variability by 44±12%, and increased PSF signal ratio by 6±6% relative to golden angle sampling. Conclusion The closed-loop approach enables near-uniform radial sampling in a segmented acquisition approach which was higher than predetermined golden-angle radial sampling. This can be utilized to increase the sampling or decrease the temporal footprint of an acquisition and the closed-loop framework has the potential to be applied to patients with complex heart rhythms.

Identifying and Characterizing Local Gaps in Saturn’s Rings from Skewness of Cassini UVIS Stellar Occultation Data

&lt;p&gt;The Ultraviolet Imaging Spectrograph (UVIS) high-speed photometer (HSP) aboard the Cassini spacecraft collected stellar occultation data for stars of various brightness and viewing geometries as they were occulted by Saturn&amp;#8217;s rings. We calculate the variance and skewness of the occultation light curves, and we analyze these statistical moments as functions of both optical depth and ring plane radius. Typical radial resolution of the occultations is 10-20 meters allowing for statistical moments to be calculated from 1000 points at 10 km radial sampling in the rings. We derived an analytic expression for skewness (S) as a function of optical depth assuming a ring composed of identical spherical particles, analogous to the normalized excess variance (E) relationship to optical depth used by Showalter and Nicholson (1990) and Colwell et al. (2018) to determine an effective particle size across the rings. We compared the results for effective particle size derived from S and E. Some regions, such as the inner B ring, return similar R-effective values, while others, such as the C ring plateaus, show distinctly different values. Skewness is a measure of the asymmetry of the distribution of photon counts in a measurement sample, while the variance is related to the spread of the distribution. Thus, agreement in the derived values of R-effective from S and E indicates an absence of clumps or local holes (nicknamed &amp;#8220;ghosts&amp;#8221;) in the rings that would lead to unusually small or large values of S, respectively. Regions of the rings where the values of R-effective from skewness (R_S) disagree with those derived from E (R_E) thus indicate the presence of ghosts or clumps that skew the distribution of photon counts in those regions. We use Monte-Carlo simulations of a simplified ring system composed of identical spherical particles interspersed with clumps and ghosts to determine the effects of these phenomena on S and compare to data. We also use simulated occultations through N-body simulations of the rings to calculate E and S where ghosts due to small moonlets or boulders are prevalent. We find variations in the suggested number of ghosts, presumed to be openings due to the same phenomena that create propeller structures in the A ring, across the rings, including in regions where there are no obvious optical depth signatures.&amp;#160;&lt;/p&gt;

The Set Increment with Limited Views Encoding Ratio (SILVER) Method for Optimizing Radial Sampling of Dynamic MRI

PurposeTo present and assess a method for choosing the increment between spokes in radially sampled MRI that can produce higher SNR than golden ratio derived methods.Theory and MethodsSampling uniformity determines image SNR when reconstructed using linear methods. Thus, for a radial trajectory, uniformly spaced sampling is ideal. However, uniform sampling lacks post-acquisition reconstruction flexibility, which is often needed in dynamic imaging. Golden ratio-based methods are often used for this purpose. The method presented here, Set Increment with Limited Views Encoding Ratio (SILVER), optimizes sampling uniformity when the number of spokes per frame is approximately known a-priori. With SILVER, an optimization algorithm finds the angular increment that provides the highest uniformity for a pre-defined set of reconstruction window sizes. The optimization cost function was based on an electrostatic model of uniformity. SILVER was tested over multiple sets and assessed in terms of uniformity, analytical g-factor, and SNR both in simulation and applied to dynamic arterial spin labeling angiograms in three healthy volunteers.ResultsAll SILVER optimizations produced higher or equal uniformity than the golden ratio within the predefined sets. The SILVER method converged to the golden ratio for broad optimization sets. As hypothesized, the g-factors for SILVER were higher than for uniform sampling, but, on average, 26% lower than golden ratio. Image SNR followed the same trend both in simulation and in vivo.ConclusionSILVER is a simple addition to any sequence currently using golden ratio sampling and it has a small but measurable effect on sampling efficiency.