Fully refocused multi-shot spatiotemporally encoded MRI: robust imaging in the presence of metallic implants

Object

An approach has been recently introduced for acquiring arbitrary 2D NMR spectra or images in a single scan, based on the use of frequency-swept RF pulses for the sequential excitation and acquisition of the spins response. This spatiotemporal-encoding (SPEN) approach enables a unique, voxel-by-voxel refocusing of all frequency shifts in the sample, for all instants throughout the data acquisition. The present study investigates the use of this full-refocusing aspect of SPEN-based imaging in the multi-shot MRI of objects, subject to sizable field inhomogeneities that complicate conventional imaging approaches.

Materials and methods

2D MRI experiments were performed at 7 T on phantoms and on mice in vivo, focusing on imaging in proximity to metallic objects. Fully refocused SPEN-based spin echo imaging sequences were implemented, using both Cartesian and back-projection trajectories, and compared with k-space encoded spin echo imaging schemes collected on identical samples under equal bandwidths and acquisition timing conditions.

Results

In all cases assayed, the fully refocused spatiotemporally encoded experiments evidenced a ca. 50?% reduction in signal dephasing in the proximity of the metal, as compared to analogous results stemming from the k-space encoded spin echo counterparts.

Conclusion

The results in this study suggest that SPEN-based acquisition schemes carry the potential to overcome strong field inhomogeneities, of the kind that currently preclude high-field, high-resolution tissue characterizations in the neighborhood of metallic implants.     

Incorporating Machine Learning into Established Bioinformatics Frameworks

The exponential growth of biomedical data in recent years has urged the application of numerous machine learning techniques to address emerging problems in biology and clinical research. By enabling the automatic feature extraction, selection, and generation of predictive models, these methods can be used to efficiently study complex biological systems. Machine learning techniques are frequently integrated with bioinformatic methods, as well as curated databases and biological networks, to enhance training and validation, identify the best interpretable features, and enable feature and model investigation. Here, we review recently developed methods that incorporate machine learning within the same framework with techniques from molecular evolution, protein structure analysis, systems biology, and disease genomics. We outline the challenges posed for machine learning, and, in particular, deep learning in biomedicine, and suggest unique opportunities for machine learning techniques integrated with established bioinformatics approaches to overcome some of these challenges.     

Synthesis,structure and stability of fac-[FeII(CO)3X3]1− (X = Br,I)

fac-[Fe^II(CO)₃X₃]^1? (X = Br, I) are synthesized and their structures have been determined. They are the first crystallographically characterized iron tricarbonyl trihalide complexes. fac-[Fe^II(CO)₃X₃]^1? (X = Br, I) are fairly thermally stable and therefore lead themselves as excellent starting materials for the preparation of various iron carbonyl complexes since both the halide and carbonyl ligands are substitutionally labile.     

Hydrogen effects on the spall strength and fracture characteristics of amorphous Fe-Si-B alloy at very high strain rates

A novel approach is suggested, using laser-induced shock wave measurements to estimate the effects of cathodic hydrogen charging on the mechanical properties and fracture characteristics of materials. This approach is applied to (1) determine the dominant mechanism of hydrogen embrittlement (HE) in an amorphous Fe₈₀B₁₁Si₉ alloy; and (2) estimate the effects of the high pressures involved in cathodic charging. The dynamic spall strength of an amorphous Fe₈₀B₁₁Si₉ alloy shocked before and after hydrogenation by a high-power laser to very high pressures (tens of giga Pascals) is measured. The dynamic spall strength of crystalline iron is measured as well for comparison. An optically recording velocity interferometer system (ORVIS) is used to measure the profile of the free surface velocity in time. The spall strength and the strain rate are calculated from the measurement of the free surface velocity as a function of time. Fracture characteristics are studied by scanning electron microscopy (SEM). The main conclusions are (1) the most reasonable mechanism of HE in the amorphous Fe-Si-B alloy is the high-pressure bubble formation; (2) the high pressures involved in cathodic hydrogen charging or laser-induced shock waves measurements may have similar effects on fracture characteristics; and (3) at very high strain rates, the spall strength is determined mainly by the interatomic bonds.     

Relation between macroscopic and microscopic dielectric relaxation times in water dynamics

A simplified derivation for the ratio of macroscopic to microscopic relaxation times of polar liquids is based on the Mori-Zwanzig projection-operator technique, with added statistical assumptions. We obtain several useful forms for the lifetime ratio, which we apply to the dynamics of liquid water. Our theoretical single-molecule relaxation times agree with the second Debye relaxation times as measured by frequency-domain dielectric spectroscopy of water and alcohols. From the theory, fast relaxation modes couple to the Debye relaxation time, τ_d, through very large water clusters, and their temperature dependence is similar to that of τ_d. Slower modes are localized to smaller water clusters and exhibit weaker temperature dependence. This is exemplified by the lifetime ratios measured by time-domain dielectric spectroscopy and optical Kerr effect spectroscopy, respectively.     

The Kinetic Inversion Problem in Ligand-Binding Heme Proteins

For a two-dimensional potential of intersecting parabolic bowls, we obtain an analytical approximation for the survival probability in the limit that the reactive mode is diffusive and the perpendicular protein mode frozen. The approximation is used in an automated computer algorithm for determining the parameters of the potential. Using this program, we are able to obtain a reasonably good fit to the low- temperature data of CO binding to horse myoglobin. We find, however, that features of the potential such as the saddle-point energy and the effective barrier, expected to dictate the high-temperature kinetics, are not uniquely determined for this potential from fitting the low-temperature data.     

The effect of surface treatments on the adhesion of electrochemically deposited hydroxyapatite coating to titanium and on its interaction with cells and bacteria

The effect of different mechanical and chemical pre-treatments on the adhesion strength of hydroxyapatite (HAp) coating on a commercially pure titanium (CP-Ti) substrate was studied by means of a standard tensile test followed by microscopic and chemical analysis to determine the locus of fracture. In addition, the effects of either these pre-treatments or post-treatment by low-energy electron irradiation, which allowed tuning the wettability of the surface, on both osteoblast progenitor attachment and S. aureus bacteria attachment were investigated. A dedicated program was developed for unambiguous identification and count of stained cells. A single-phase HAp coating was formed by electrodeposition. A series of surface pre-treatments consisted of grinding down to P1000, etching in HNO₃/HF solution, grit blast, soaking in NaOH and subsequent heat treatment provided the highest adhesion strength to the HAp coating. Osteoblast progenitors derived from rats may be attached preferentially to a hydrophilic surface (post-treatment to θ = 30°), while the bacteria seemed to be less attached to hydrophobic surfaces (post-treatment to θ = 105°). However, the results were not statistically different. The bacteria seemed to be less attached to the smoother, uncoated surfaces.     

Atomistic features of the amorphous–crystal interface in silicon

We simulate the amorphous–crystal interface in silicon using a combination of interatomic potential molecular-dynamics and tight- binding conjugate-gradient relaxation. The samples we create have high quality crystalline and amorphous portions. We develop some localized measures of order to characterize the interface, including a missing neighbor vector and the bond angle deviation. We find that the measures of order interpolate smoothly from a bulk crystal value to a bulk amorphous value across a 7 Å thick interface region. The interface structures exhibit a number of interesting features. The crystal planes near the interface are nearly perfect, with a few dimer defects similar to the Si(100) 2×1 reconstruction. Interfaces produced with one constant temperature simulation method are rough, with several layers of atoms forming <110> chains and (111) facets. A different simulation method produces more planar interfaces with only a few <110> chains.     

Effects of practice, age, and task demands, on interference from a phone task while driving

Experimental research on the effects of cellular phone conversations on driving indicates that the phone task interferes with many driving-related functions, especially with older drivers. Unfortunately in past research (1) the dual task conditions were not repeated in order to test for learning, (2) the 'phone tasks' were not representative of real conversations, and (3) most often both the driving and the phone tasks were experimenter-paced. In real driving drivers learn to time-share various tasks, they can pace their driving to accommodate the demands of a phone conversation, and they can even partially pace the phone conversation to accommodate the driving demands. The present study was designed to better simulate real driving conditions by providing a simulated driving environment with repeated experiences of driving while carrying two different hands-free 'phone' tasks with different proximities to real conversations. In the course of five sessions of driving and using the phone, there was a learning effect on most of the driving measures. In addition, the interference from the phone task on many of the driving tasks diminished over time as expected. Finally, the interference effects were greater when the phone task was the often-used artificial math operations task than when it was an emotionally involving conversation, when the driving demands were greater, and when the drivers were older. Thus, the deleterious effects of conversing on the phone are very real initially, but may not be as severe with continued practice at the dual task, especially for drivers who are not old.