Magnetic Resonance in Medicine最新文献

Purpose: To reduce the upfront cost of small, low-field MRI systems, while expanding the capabilities of their gradient systems.

Methods: A gradient power amplifier was designed to leverage the lowering cost of Gallium Nitride (GaN) power transistors and high speed logic, to achieve high efficiency and responsiveness for driving gradient coils. The switching H-bridge design was realized as a prototype and tested to determine power output capabilities. With a digital control system, the prototype was further tested using a load which simulates a small gradient, such as those used in head and extremity low-field MRI systems. Additionally in this test, the noise spectra produced in operation are analyzed.

Results: The amplifier combined with an example control system to drive 15 A into a $225\mu H$ , $0.3\Omega$ load simulating an effective strength over 15 mT/m and slew over 32 T/m/s, has a total build cost of under US$300 and an amplifier size under $6\times 6\times 2\text{cm}$ . High efficiency allows for this performance with no active cooling at full duty cycle, and high frequency switching produces controllable interference when imaging frequencies lay in the same range.

Conclusion: Using GaN transistors, a low-cost gradient amplifier can be implemented that will reduce the cost and size of low-field MRI systems, improving accessibility.

Purpose: Paramagnetic ions are distributed throughout the human brain. The increased accumulation of these metals, such as iron and copper, can induce cellular death and the development of neurological diseases. Electron Paramagnetic Resonance (EPR) is a spectroscopic technique capable of detecting these ions in a given biological sample.

Methods: Samples from 17 human brain structures of 8 ex vivo subjects were extracted, lyophilized, and triturated for EPR measurements at variable temperatures ranging from 193 to 293 K. Simulations were performed using the EasySpin toolbox to calculate qualitative parameters and the EPR absorption of high-spin iron (Fe(III)), copper ion (Cu(II)), and ferritin (Ft) signals in all obtained EPR spectra.

Results: The simulated parameters showed a considerable percentage variation relative to the input values, which resulted in spectral visual changes of each paramagnetic ion signal. The simulated EPR brain spectra demonstrated temperature dependence, with an increase in the amplitude of Fe(III), Cu(II), and Ft signals as the temperature decreased.

Conclusions: The magnetic behavior of these paramagnetic species exhibited linearity with the inverse of temperature for the Cu(II) EPR absorption across all brain structures, while Fe(III) and Ft signals showed a nonlinear pattern in the EPR absorption, with heterogeneity among all brain regions and subjects.

Purpose: To develop and validate a vendor-agnostic, motion-insensitive proton-density fat-fraction (PDFF) quantification method.

Methods: Flip-angle-modulated (FAM) 2D chemical-shift-encoded (CSE) MRI for PDFF quantification was implemented in both the vendor-agnostic platform Pulseq ("Pulseq-FAM") and one vendor-specific platform ("GE-specific FAM"). These implementations were distributed to four sites with twelve MR systems of three vendors (Siemens/GE/Philips) and field strengths (0.55T/1.5T/3T). A sequentially-shipped 16-vial phantom (PDFF = 0%-30%/T1_water = 200-1400 ms) underwent confounder-corrected PDFF mapping with commercial 3D-CSE methods and GE-specific FAM as available on each system, and Pulseq-FAM on every system. To assess bias, phantom PDFF measurements were compared to reference. Between-system variance was evaluated with linear mixed-effects modeling. Different volunteers were also imaged at each site to assess free-breathing PDFF mapping feasibility. A prospective single-site volunteer study was also conducted. Adult patients and children were imaged with breath-held 3D-CSE and free-breathing GE-specific and Pulseq-FAM. Radiologists evaluated images for overall quality and motion artifacts. To assess bias, Pulseq-FAM PDFF measurements were compared to 3D-CSE and GE-specific FAM. Test-retest repeatability was assessed by re-imaging after repositioning. Between-field-strength reproducibility was assessed at 1.5T and 3.0T.

Results: In the multi-center study, Pulseq-FAM showed reduced T1-bias and between-system variability versus 3D-CSE in phantom PDFF measurements, and free-breathing feasibility in volunteers. In the single-site volunteer study (N = 57), Pulseq-FAM improved image quality and motion artifacts versus 3D-CSE (p < 0.01). Pulseq-FAM showed excellent agreement with 3D-CSE (95% limits-of-agreement (LoA) = 3.4% PDFF) and GE-specific FAM (LoA = 2.0%). Pulseq-FAM showed excellent repeatability (repeatability coefficient (RC) = 1.6% PDFF) and between-field-strength reproducibility (reproducibility coefficient (RDC) = 2.4%) versus 3D-CSE (RC = 2.7%/RDC = 3.4%; differences p < 0.05).

Conclusion: Pulseq-FAM enables accurate, reproducible, vendor-agnostic, and motion-insensitive PDFF quantification in adults and children.

Purpose: The goal of this article is to introduce a technique to measure the velocity distribution of water inside each voxel of an MR image. The method is based on the use of motion sensitizing gradients with changing first moment to encode velocity. As such, it is completely non-invasive and requires no contrast injections.

Methods: The technique consists of acquiring a series of images preceded by preparatory RF pulses that encode velocity information, analogously to k-space encoding. The velocity distribution can be decoded via the Fourier transform. We demonstrate its use on a simple flow phantom with known flow characteristics. We demonstrate the technique on the brains of five human participants from whom we collected the velocity distribution along each of the three laboratory axes.

Results: Velocity distribution measurements on simple phantoms yielded velocity distributions consistent with theory. Human velocity spectra identified specific anatomical features at different velocity bins. The largest fraction of spins was in the lowest velocity bands. Movement in the CSF spaces could be clearly identified at different velocity bands.

Conclusion: Velocity Spectrum Imaging has great potential as a tool to study the movement of fluids in the human body without contrast agents. In addition to a useful tool for validating computational fluid dynamic models in vivo, it can be used to study the complex movement of water in the glymphatic system and its involvement in neurodegenerative disorders. However, further development is needed to probe the velocity spectrum in the ultra-low velocity regime of the perivascular spaces.

Purpose: PCr/ATP ratio is determined at 7 T typically using Fourier-transform based magnetic resonance spectroscopic imaging sequences (FT-MRSI). These sequences require acquisition times longer than desirable for inclusion in cardiac clinical trials. Concentric ring trajectory (CRT-MRSI) has been described as an accelerated alternative k-space sampling method. In this work we aim to establish the inter- and intra-session repeatability of three different CRT protocols and compare their voxel-based PCr/ATP ratios to compartment-based PCr/ATP values extracted with spectroscopy using a linear algebraic model (SLAM) method.

Methods: Seven healthy volunteers were scanned twice on two different days. Each time a 6.5-min 3D FT-MRSI acquisition with 10 × 10 × 10 resolution was followed by a 2.5-min CRT-MRSI with matched resolution, a 1.5-min CRT-MRSI with matched resolution, and a 6.9-min CRT-MRSI with 12 × 12 × 12 resolution. Spectra from a mid-septal voxel and the cardiac compartment were fitted with the OXSA toolbox. PCr/ATP ratio was quantified for inter- and intra-session repeatability analysis.

Results: Paired repeated measurements were not significantly different within subjects. Good inter- and intra-session agreement was observed between FT-MRSI and each CRT-MRSI protocol. CRT-MRSI protocols all had larger coefficients of repeatability (CoR) than FT-MRSI. CRT-SLAM-based PCr/ATP values had lower CoR than voxel-based data except for 2.5-min CRT-SLAM, and high-resolution CRT-SLAM had lower inter-session CoR compared to FT-MRSI (1.42 vs. 2.21).

Conclusion: We established the repeatability of CRT-MRSI-based PCr/ATP values and showed higher SNR and lower CoR for CRT-SLAM. Our findings allow shorter ³¹P MRS acquisition times and the use of more advanced energetics-probing techniques in clinical studies.

Purpose: To achieve the simultaneous acquisition of gamma-aminobutyric acid (GABA) and glycine (Gly) using a MEGA-PRESS sequence with an optimized TE at 3T.

Methods: MEGA-PRESS simulations were performed at TEs 60-88 ms to determine the optimal TE for Gly detection with minimal myo-Inositol (mI) overlap and maximal GABA detection sensitivity. MEGA-PRESS data were acquired in the occipital lobe of 6 healthy subjects at TEs of 64 and 68 ms. GABA+ levels, between-acquisition (SUM (edit-ON+edit-OFF) and edit-OFF) and inter-subject coefficient-of-variation (CVs) and mI, Gly, and glucose CRLBs were evaluated to assess fit reliability. The residuals of the edit-OFF and SUM fits were compared with and without Gly in the basis set to examine the effect of Gly on fit accuracy and metabolite quantification.

Results: Simulations indicated that optimal Gly detection with minimal overlap from mI is observed at a TE of 64 ms. Simulations and in vivo experiments indicate that this TE resulted in no reduction in GABA+ sensitivity relative to the commonly used TE of 68 ms. Gly between-acquisition and inter-subject CVs and CRLBs were substantially lower at a TE of 64 ms than at a TE 68 ms. Spectral fits with Gly excluded from the basis set resulted in a significant increase in CRLBs and fit residuals for mI and glucose at a TE of 64 ms, but not at a TE of 68 ms.

Conclusion: The simultaneous detection of GABA+ from the difference spectrum and Gly from the edit-OFF/SUM spectra is possible using a MEGA-PRESS sequence at a TE of 64 ms.

Purpose: To develop accelerated 3D phase contrast (PC) MRI using jointly learned wave encoding and reconstruction.

Methods: Pseudo-fully sampled neurovascular 4D flow data (N = 40) and a simulation framework were used to learn phase encoding locations, wave readout parameters, and model-based reconstruction network (MoDL) for a rapid 3D PC scan (2.25 min). Parameters were also learned for an otherwise identical scan without wave encoding. Prospective scans with and without wave sampling, time-matched 3D radial, and reference 3D radial (5.65 min) were conducted in a flow phantom and 12 healthy participants. Flow rate, pixel-wise velocity, and variability of maximum velocity ( ${\sigma }_{v_{\max }}$ ) were compared.

Results: In the phantom, learned wave scans provided accurate flow rates compared to flow probe values (0.170 ± 0.002 vs. 0.17, 0.152 ± 0.003 vs. 0.15, 1.838 ± 0.044 vs. 1.83 L/min) and showed high correlation with reference scan (slope = 0.97, R² = 0.99). In vivo, learned wave scans demonstrated reduced aliasing and blurring, and better small vessel conspicuity compared to scans without wave sampling and time-matched 3D radial scans. The internal carotid artery (ICA) flow rate coefficient of variation (CV) and intraclass correlation coefficient (ICC) for learned wave scans were similar to reference 3D radial scans (CV = 6.569, ICC = 0.927; reference CV = 6.553, ICC = 0.910). Learned wave sampling demonstrated similar or lower ${\sigma }_{v_{\max }}$ in middle cerebral artery (MCA), basilar artery (BA), superior sagittal sinus (SSS), and most ICA segments than the longer reference scan.

Conclusion: This work demonstrates feasibility, improved image quality and accurate flow measurements of learned wave sampling and MoDL reconstruction for 3D PC MRI.

Magnetic resonance fingerprinting (MRF) enables quantitative MRI by allowing the simultaneous mapping of multiple tissue properties through innovative acquisition and computational methods. This review focuses on the application of MRF techniques to cerebral physiology, emphasizing advancements in vascular imaging and the integration of biophysical modeling. We discuss the principles of MRF, its adaptation to quantify hemodynamic and vascular parameters, and its potential to overcome challenges in mapping vascular-related parameters. The review categorizes MRF-based imaging approaches, including MRF-arterial spin labeling (MRF-ASL), MR vascular fingerprinting (MRvF), and vascular fluid dynamics-MRF (VFD-MRF), highlighting their technical implementations, accuracy, and clinical applications in conditions such as stroke, brain tumors, and cerebrovascular diseases. We also explore the role of machine learning in enhancing dictionary matching and reducing computational time for more accurate and reliable real-time parameter estimation. The challenges such as low signal-to-noise ratios and computational demands are addressed through tailored sequence designs, noise-resilient dictionaries, and deep learning approaches. This comprehensive review provides a detailed technical framework for advancing the role of MRF in assessing cerebral physiology and its clinical translation.