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PURPOSE: To improve image quality and resolution of dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) by developing acquisition and reconstruction methods exploiting the temporal regularity property of DSC-PWI signal. THEORY AND METHODS: A novel regularized reconstruction is proposed that recovers DSC-PWI series from interleaved segmented spiral k-space acquisition using higher order temporal smoothness (HOTS) properties of the DSC-PWI signal. The HOTS regularization is designed to tackle representational insufficiency of the standard first-order temporal regularizations for supporting higher accelerations. The higher accelerations allow for k-space coverage with shorter spiral interleaves resulting in improved acquisition point spread function, and acquisition of images at multiple TEs for more accurate DSC-PWI analysis. RESULTS: The methods were evaluated in simulated and in-vivo studies. HOTS regularization provided increasingly more accurate models for DSC-PWI than the standard first-order methods with either quadratic or robust norms at the expense of increased noise. HOTS DSC-PWI optimized for noise and accuracy demonstrated significant advantages over both spiral DSC-PWI without temporal regularization and traditional echo-planar DSC-PWI, improving resolution and mitigating image artifacts associated with long readout, including blurring and geometric distortions. In context of multi-echo DSC-PWI, the novel methods allowed ∼4.3× decrease of voxel volume, providing 2× number of TEs compared to the previously published results. CONCLUSIONS: Proposed HOTS reconstruction combined with dynamic spiral sampling represents a valid mechanism for improving image quality and resolution of DSC-PWI significantly beyond those available with established fast imaging techniques.

Purpose: To investigate the effect of incomplete fat spoiling on the accuracy of B1 mapping with actual flip angle imaging (AFI) and to propose a method to minimize the errors using the chemical shift properties of fat. Theory and Methods: Diffusion-based dephasing is the main spoiling mechanism exploited in AFI. However, a very low diffusion in fat may make the spoiling insufficient, leading to ghosts in the B1 maps. As the errors retain the chemical-shift signature of fat, their impact can be minimized using chemical-shift-based fat signal removal from AFI acquisition modified to includemulti-echo readout. The source of the errors and the proposed correction were studied in simulations and phantom and in-vivo imaging experiments. Results: Our results support that AFI artifacts are caused by the incomplete fat spoiling present in clinically attractive short TR acquisition regimes. The correction eliminated the ghosting and significantly improved the B1 mapping accuracy as well as the accuracy of R1 mapping performed with AFI-derived B1 maps. Conclusions: The incomplete fat signal spoiling may be a source of AFI B1 mapping errors, especially in subjects with high fat content. Achieving complete fat spoiling requires longer TR, which is undesirable in clinical applications. The proposed approach based on fat signal removal can reduce errors without significant prolongation of the AFI pulse sequence. We propose that, when attaining complete fat spoiling is not feasible, AFI mapping should be performed in a multi-echo regime with appropriate fat separation or suppression to minimize these errors. [ABSTRACT FROM AUTHOR]

Purpose: To introduce a method of inducing Bloch‐Siegert shift and magnetization Transfer Simultaneously (BTS) and demonstrate its utilization for measuring binary spin‐bath model parameters free pool spin–lattice relaxation (T1F$$ {T}_1^{\mathrm{F}} $$), macromolecular fraction (f$$ f $$), magnetization exchange rate (kF$$ {k}_{\mathrm{F}} $$) and local transmit field (B1+$$ {B}_1^{+} $$). Theory and Methods: Bloch‐Siegert shift and magnetization transfer is simultaneously induced through the application of off‐resonance irradiation in between excitation and acquisition of an RF‐spoiled gradient‐echo scheme. Applying the binary spin‐bath model, an analytical signal equation is derived and verified through Bloch simulations. Monte Carlo simulations were performed to analyze the method's performance. The estimation of the binary spin‐bath parameters with B1+$$ {B}_1^{+} $$ compensation was further investigated through experiments, both ex vivo and in vivo. Results: Comparing BTS with existing methods, simulations showed that existing methods can significantly bias T1$$ {T}_1 $$ estimation when not accounting for transmit B1$$ {B}_1 $$ heterogeneity and MT effects that are present. Phantom experiments further showed that the degree of this bias increases with increasing macromolecular proton fraction. Multi‐parameter fit results from an in vivo brain study generated values in agreement with previous literature. Based on these studies, we confirmed that BTS is a robust method for estimating the binary spin‐bath parameters in macromolecule‐rich environments, even in the presence of B1+$$ {B}_1^{+} $$ inhomogeneity. Conclusion: A method of estimating Bloch‐Siegert shift and magnetization transfer effect has been developed and validated. Both simulations and experiments confirmed that BTS can estimate spin‐bath parameters (T1F$$ {T}_1^{\mathrm{F}} $$, f$$ f $$, kF$$ {k}_{\mathrm{F}} $$) that are free from B1+$$ {B}_1^{+} $$ bias. [ABSTRACT FROM AUTHOR]

In this study, we utilized a handheld LIBS (laser-induced breakdown spectroscopy) analyzer (Z-300, SciAps) to quantitatively determine cerium and lanthanum in ores enriched with rare earth elements (REEs). Due to the complex electronic structure of REEs and their presence in laser plasma in multiple ionization stages (neutral, singly- and doubly-ionized species), determining their concentrations using a handheld instrument with relatively low spectral resolution is a challenging task for on-field quantitative analysis. Another issue is the rich emission spectrum of matrix elements of ores, which can cause strong overlapping between lines of analytes and matrixes, preventing quantitative analysis of ores. To address this issue, we employed Design of Experiment based on Latin Hypercube Sampling to construct an artificial calibration set of samples with varying REEs content. We compared univariate calibration and projection to latent structures (PLS) regression for atomic and ionic lines of REEs, as well as for molecular bands of LaO (740.5 nm). We observed a worsening of calibration due to matrix effects for LaO molecules. To validate our method, we used certified reference material of OREAS natural ore samples to simulate the real in-field application of the handheld analyzer. Our study revealed that Ce can be quantified regardless of concentration in niobium REE-rich ores with a relative error of about ±10% if the Ce II line at 462.82 nm is used, which is close to the level of quantitative accuracy. However, predicted concentrations of La in OREAS 460–465 appear to be biased by matrix effects. We conclude that the accuracy achieved in our study is mostly sufficient for qualitative analysis of uranium ores (OREAS 100a–102a). Furthermore, considering the possible matrix effects in La determination, we suggest that it is possible to use OREAS samples as a calibration set instead of artificial samples to build linear univariate regression models, as the lines employed in this study do not overlap. Our results are expected to optimize the procedure of online in-field monitoring of the mining process and provide rapid preliminary analysis for decision-making, with further, more time-consuming, and accurate analysis (e.g., using ICP-OES/MS) required as necessary. [ABSTRACT FROM AUTHOR]

The use of brain hemodynamics is important in the assessment of numerous pathophysiologic conditions. The measurement of perfusion or delivery of blood to tissues by MR imaging is essential for neuroradiologists to understand and appropriately apply to clinical practice. Several different approaches are used. DSC and dynamic contrast-enhanced MR imaging study the signal change (according to T2* and T1, respectively) induced by an exogenous contrast agent, allowing the measurement of CBF, CBV, and time-related parameters. Blood oxygen level--dependent (BOLD) MR imaging measures the T2* signal changes induced by the paramagnetic molecule deoxyhemoglobin. BOLD MR imaging provides complex measurements because the signal varies not only with changes in CBF but also with several other parameters such as tissular oxygen uptake and brain activation. Arterial spin-labeling MR imaging is a technique relying on labeled endogenous water as a tracer. By measuring the signal difference between 2 sets of acquisitions (labeling and control), arterial spin-labeling MR imaging calculates cerebral perfusion in a quantitative manner. This article aims to review the fundamentals of perfusion MR imaging techniques essential to any neuroradiology practice along with their advantages, disadvantages, and applications to research and clinical care. [ABSTRACT FROM AUTHOR]

Background: Characterization of cognitive impairment (CI) in multiple sclerosis into distinct phenotypes holds promise for individualized treatments and biomarker exploration. Objective: Apply a previously validated, neuropsychologically driven diagnostic algorithm to identify a taxonomy of the type of cognitive phenotypes in multiple sclerosis. Methods: An algorithm developed and validated in other neurological diseases was applied to a cohort of 1281 people with multiple sclerosis who underwent clinical neuropsychological evaluation across three multiple sclerosis centers. A domain was marked impaired if scores on two tests within the domain fell below one of the two thresholds of interest (compared to controls; −1.0 SD and −1.5 SD below the mean). Results were then tabulated for each participant to determine the type of impairments across the sample. Results: At −1 SD threshold, 48.7% were intact, 21.6% had single-domain, 14.3% bi-domain, and 15.4% multi-domain impairment. At −1.5 SD threshold, 72.9% were intact, 14.0% had single-domain, 8.2% bi-domain, and 5.0% multi-domain impairment. Processing speed was the most frequent single-domain impairment, followed by executive function and memory. Conclusions: These findings advance the taxonomy of cognitive phenotypes in multiple sclerosis and clarify the type and distribution of possible cognitive diagnoses, pave the way for further investigation of associated biomarkers, and provide clinically meaningful information to guide individualized treatment and rehabilitation. [ABSTRACT FROM AUTHOR]