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Register a new userExploring the physical limits of saturation contrast in Magnetic Resonance Imagign
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Magnetic Resonance Imaging has become nowadays an indispensable tool with applications ranging from medicine to material science. However, so far the physical limits of the maximum achievable experimental contrast were unknown. We introduce an approach based on principles of optimal control theory to explore these physical limits, providing a benchmark for numerically optimized robust pulse sequences which can take into account experimental imperfections. This approach is demonstrated experimentally using a model system of two spatially separated liquids corresponding to blood in its oxygenated and deoxygenated forms.
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Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify perfusion and vascular permeability. In most cases a bolus arrival time (BAT) delay exists between the arterial input function (AIF) and the contrast agent arrival in the tissue of interest which needs to be estimated. Existing methods for BAT estimation are tailored to tissue concentration curves which have a fast upslope to the peak as frequently observed in patient data. However, they may give poor results for curves that do not have this characteristic shape such as tissue concentration curves of small animals. In this paper, we propose a novel method for BAT estimation of signals that do not have a fast upslope to their peak. The model is based on splines which are able to adapt to a large variety of concentration curves. Furthermore, the method estimates BATs on a continuous time scale. All relevant model parameters are automatically determined by generalized cross validation. We use simulated concentration curves of small animal and patient settings to assess the accuracy and robustness of our approach. The proposed method outperforms a state-of-the-art method for small animal data and it gives competitive results for patient data. Finally, it is tested on in vivo acquired rat data where accuracy of BAT estimation was also improved upon the state-of-the-art method. The results indicate that the proposed method is suitable for accurate BAT estimation of DCE-MRI data, especially for small animals.
In this paper, it is shown that the experimental values of the nonextensive scattering entropies $S_L (p)$ and $S_theta (q)$ for the pion-nucleus ($pi^0 He, pi^0 C, pi^0 O, pi^0 Ca$) scatterings, in the energy region corresponding to $Delta (1236)$ resonance in the elementary pion-nucleon interaction, are well described by the entropic optimal resonance predictions $S_L^o1 (p)$ and $S_theta^o1 (q)$ and when the nonextensivities indices are correlated by a Riesz-Thorin-like relation: 1/2p+1/2q=1.
Magnetic Resonance Fingerprinting (MRF) is a method to extract quantitative tissue properties such as T1 and T2 relaxation rates from arbitrary pulse sequences using conventional magnetic resonance imaging hardware. MRF pulse sequences have thousands of tunable parameters which can be chosen to maximize precision and minimize scan time. Here we perform de novo automated design of MRF pulse sequences by applying physics-inspired optimization heuristics. Our experimental data suggests systematic errors dominate over random errors in MRF scans under clinically-relevant conditions of high undersampling. Thus, in contrast to prior optimization efforts, which focused on statistical error models, we use a cost function based on explicit first-principles simulation of systematic errors arising from Fourier undersampling and phase variation. The resulting pulse sequences display features qualitatively different from previously used MRF pulse sequences and achieve fourfold shorter scan time than prior human-designed sequences of equivalent precision in T1 and T2. Furthermore, the optimization algorithm has discovered the existence of MRF pulse sequences with intrinsic robustness against shading artifacts due to phase variation.
Purpose: To develop a fast magnetic resonance fingerprinting (MRF) method for quantitative chemical exchange saturation transfer (CEST) imaging. Methods: We implemented a CEST-MRF method to quantify the chemical exchange rate and volume fraction of the N${alpha}$-amine protons of L-arginine (L-Arg) phantoms and the amide and semi-solid exchangeable protons of in vivo rat brain tissue. L-Arg phantoms were made with different concentrations (25-100 mM) and pH (pH 4-6). The MRF acquisition schedule varied the saturation power randomly for 30 iterations (phantom: 0-6 ${mu}$T; in vivo: 0-4 ${mu}$T) with a total acquisition time of <=2 minutes. The signal trajectories were pattern-matched to a large dictionary of signal trajectories simulated using the Bloch-McConnell equations for different combinations of exchange rate, exchangeable proton volume fraction, and water T1 and T2* relaxation times. Results: The chemical exchange rates of the N${alpha}$-amine protons of L-Arg were significantly (p<0.0001) correlated with the rates measured with the Quantitation of Exchange using Saturation Power method. Similarly, the L-Arg concentrations determined using MRF were significantly (p<0.0001) correlated with the known concentrations. The pH dependence of the exchange rate was well fit (R2=0.9186) by a base catalyzed exchange model. The amide proton exchange rate measured in rat brain cortex (36.3+-12.9 Hz) was in good agreement with that measured previously with the Water Exchange spectroscopy method (28.6+-7.4 Hz). The semi-solid proton volume fraction was elevated in white (11.2+-1.7%) compared to gray (7.6+-1.8%) matter brain regions in agreement with previous magnetization transfer studies. Conclusion: CEST-MRF provides a method for fast, quantitative CEST imaging.
Magnetic resonance plays an important role in todays science, engineering, and medical diagnostics. Learning and teaching magnetic resonance is challenging since it requires advanced knowledge of condensed matter physics and quantum mechanics. Driven by the need to popularize this technologically impactful phenomenon, we develop an inexpensive table-top demonstration experiment. It unveils the magnetic resonance of a hand-held compass in the magnetic fields of a permanent magnet. The setup provides an immediate visualization of the underlying physical concepts and allows for their translation to broad student audiences.
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