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Purpose Tissue microstructure can influence quantitative magnetic resonance imaging such as relaxation rate measurements. Consequently, relaxation rate mapping can provide useful information on tissue microstructure. PCNA-I1 solubility dmso In this work, the theory on relaxation mechanisms of the change of the relaxation rate ∆R2⁎ in the presence of spherical susceptibility sources in a spin bearing medium is validated in simulations and phantom experiments for the coexistence of two species of susceptibility sources. Methods The influence of coexisting spherical perturbers with magnetic susceptibilitys of different signs was evaluated in Monte Carlo simulations including diffusion effects in the surrounding medium. Simulations were compared with relaxometry measurements at 1.5 Tesla and at 3 Tesla. The phantoms used to validate the simulations were built from agarose gel containing calcium carbonate and tungsten carbide particles of different size and concentration. Results The Monte Carlo simulations showed, that the change in relaxation rate only depends on the overall amount of susceptibility producing structures in the simulation volume and no difference was found, if mixtures of positive and negative particles were simulated. Phantom measurements within the static dephasing regime showed linear additivity of the effects from positive and negative susceptibility sources that were present within the same voxel. Conclusions In summary, both the simulations and the phantom measurements showed that changes in the relaxation rate ΔR2⁎ add up linearly for spherical particles with different susceptibilities within the same voxel if the conditions for the static dephasing regime are fulfilled. If particles with different susceptibilities have both different sizes and violate the conditions of the static dephasing regime, effects on relaxation rates might no longer be linear.Purpose The gradient system transfer function (GSTF) can be used to describe the dynamic gradient system and applied for trajectory correction in non-Cartesian MRI. This study compares the field camera and the phantom-based methods to measure the GSTF and implements a compensation for the difference in measurement dwell time. Methods The self-term GSTFs of a MR system were determined with two approaches 1) using a dynamic field camera and 2) using a spherical phantom-based measurement with standard MR hardware. The phantom-based GSTF was convolved with a box function to compensate for the dwell time dependence of the measurement. The field camera and phantom-based GSTFs were used for trajectory prediction during retrospective image reconstruction of 3D wave-CAIPI phantom images. Results Differences in the GSTF magnitude response were observed between the two measurement methods. For the wave-CAIPI sequence, this led to deviations in the GSTF predicted trajectories of 4% compared to measured trajectories, and residual distortions in the reconstructed phantom images generated with the phantom-based GSTF. Following dwell-time compensation, deviations in the GSTF magnitudes, GSTF-predicted trajectories, and resulting image artifacts were eliminated ( less then 0.5% deviation in trajectories). Conclusion With dwell time compensation, both the field camera and the phantom-based GSTF self-terms show negligible deviations and lead to strong artifact reduction when they are used for trajectory correction in image reconstruction.Purpose To investigate characteristics of intra- and extracranial arterial culprit plaques between patients with single infarct and multiple-infarcts by a head-neck combined high resolution magnetic resonance vessel wall imaging (HR-MRVWI). Materials and methods Forty-three patients with recent ischemic stroke due to large artery atherosclerosis were enrolled. The head-neck combined HR-MRVWI was performed in all patients both pre- and post-contrast administration. Based on diffusion weighted imaging findings, patients were divided into single-infarction and multiple-infarction groups. For patients with anterior circulation ischemic stroke, they were also divided into perforating artery infarction (PAI) and non-PAI groups. Patient demographics, number and location of culprit plaques, artery stenosis percentage, intraplaque hemorrhage, and plaque enhancement were evaluated and compared between single-infarction and multiple-infarction groups, as well as between PAI and non-PAI groups. Results A total of 83 culprit plaques were identified. The artery stenosis degree was more severe and plaque enhancement more prominent in multiple-infarction group than in single-infarction group. Patients with multiple infarcts also had more culprit plaques per patient than those with single infarct, which contributed to the occurrence of multiple infarcts. For comparison of PAI and non-PAI groups, a higher artery stenosis percentage was observed in non-PAI group, and patients with non-PAI had more culprit plaques per patient, which contributed to a variety of infarct manifestations. Conclusion A higher stenosis grade and higher number of culprit plaques seem to be associated with a higher number of cerebral infarcts in patients with large artery atherosclerosis.Plant phytochromes enable vital adaptations to red and far-red light. At the molecular level, these responses are mediated by light-regulated interactions between phytochromes and partner proteins, foremost the phytochrome-interacting factors (PIF). Although known for decades, quantitative analyses of these interactions have long been sparse. To address this deficit, we here studied by an integrated fluorescence-spectroscopic approach the equilibrium and kinetics of Arabidopsis thaliana phytochrome B binding to a tetramerized PIF6 variant. Several readouts consistently showed the stringently light-regulated interaction to be little affected by PIF tetramerization. Analysis of the binding kinetics allowed the determination of bimolecular association and unimolecular dissociation rate constants as a function of light. Unexpectedly, the stronger affinity of A. thaliana phytochrome B under red light relative to far-red light is entirely due to accelerated association rather than decelerated dissociation. The association reaction under red light is highly efficient and only 3-fold slower than the diffusion limit.
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