Magnetic Resonance in Medicine最新文献

Purpose: To apply the Magnetization Transfer Indirect Spin Labeling (MISL) MRI technique for quantifying tissue-CSF water exchange in the human brain, and to investigate its utility in (1) evaluating tissue-CSF water exchange within perivascular spaces (PVS), and (2) characterizing altered water exchange dynamics in pathologic conditions.

Methods: MISL was implemented on a 3 T MRI using off-resonance magnetization transfer to label parenchymal water. The resulting exchange with CSF was captured via long-TE 3D-TSE readout to suppress parenchymal signals. CSF-region-specific quantification was achieved by atlas-based segmentation. Studies were conducted in healthy subjects across age groups and in patient with metastatic brain tumor.

Results: MISL revealed widespread and regionally heterogeneous tissue-CSF exchange, with the strongest signals observed in the PVS and areas adjacent to the choroid plexus. MISL signals were typically 2%-3% in the ventricles and subarachnoid space, and reached 3% in the cerebellar regions, suggesting tissue-to-CSF flow (TCF) in the range of 100-300 mL/100 mL/min. The high MISL signals observed in the PVS (∼8.4%) indicated active tissue-CSF water exchange, providing functional information of the PVS that conventional T2w imaging cannot capture. Significant age-dependent declines in TCF were observed across most brain regions, except for the third and fourth ventricles. In the tumor patient, MISL revealed elevated water exchange, even where no overt FLAIR hyperintensity was present.

Conclusion: MISL enables robust, non-invasive mapping of tissue-CSF exchange with high sensitivity and spatial resolution. MISL provides a unique window into tissue-CSF exchange within PVS, which may reflect glymphatic function.

Purpose: Quantitative mapping of cardiac tissue properties is used clinically in diagnosis and monitoring of a wide variety of cardiac pathologies. Cardiac Magnetic Resonance Fingerprinting (cMRF) enables rapid and simultaneous quantification of multiple parameters in the myocardium from a single scan. In this work, a multi-echo cMRF acquisition is combined with a deep image prior framework to reconstruct cardiac T₁, T₂, $T_2^{*}$ , and fat fraction maps.

Methods: A 2D, single-breathhold, ECG-gated rosette trajectory cMRF sequence was deployed to sensitize the signal to T₁, T₂, $T_2^{*}$ , and fat off-resonance effects. Data were processed using a deep image prior reconstruction trained with the cMRF encoding model to generate images consistent with the acquired k-space data. These images were used in curve fitting and pattern matching algorithms to generate T₁, T₂, $T_2^{*}$ and fat fraction maps. The technique was validated using numerical simulations, standard phantoms, and 28 healthy subjects.

Results: In phantoms, good agreement was observed between the proposed technique and gold-standard reference measurements. In healthy subjects, measurements made with the deep image prior (DIP) reconstruction agreed with clinical cardiac measurements and demonstrated smaller voxel-level variance in a healthy population compared to iterative low-rank and direct matching reconstructions.

Conclusion: The multi-echo cMRF acquisition coupled with a DIP reconstruction enables the simultaneous quantification of T₁, T₂, $T_2^{*}$ , and fat in the heart and demonstrates good agreement with conventional mapping approaches in phantom and in vivo experiments. Additionally, the DIP reconstruction provides accurate measurements with a lower voxel-level variance compared with direct gridding and iterative low-rank reconstruction methods.

Purpose: To investigate dipole antennas with electronically switchable transmit field patterns to improve flip angle homogeneity in ultra-high field MRI.

Methods: Reconfigurable dipole elements that could produce two distinct electronically switchable $B_1^{+}$ field profiles were conceptualized and constructed. Eight such elements were combined into an array. Alteration of the field profiles was accomplished by modulating the currents along the dipoles using a combination of PIN diodes and lumped inductors. The behavior of these reconfigurable elements was studied in numerical electromagnetic simulations and 9.4T MRI measurements, investigating rapid switching of transmit sensitivities during excitation pulses in both single-channel and pTx mode operation.

Results: For the simulated dipole elements, modulating the current densities along the dipole's axis causes a $\sim$ 30% change of the $B_1^{+}$ field between superior and inferior regions of the brain. When rapidly switched during excitation pulses, this degree of freedom can improve flip angle homogeneity, e.g., by a factor of $\sim$ 2.2 for a two kT points pTx pulse. For the constructed prototype array, the switching effect was observable but weaker, causing $\sim$ 10% superior-inferior $B_1^{+}$ variation.

Conclusions: The proposed coaxial dipole array with switchable transmit sensitivities offers a novel degree of freedom for designing excitation pulses. The approach has the potential to improve flip angle homogeneity without necessitating an expensive increase in the number of independent transmit channels.

Purpose: First-pass perfusion cardiovascular MR (FPP-CMR) enables the non-invasive diagnosis of microcirculation and coronary artery disease. In free-breathing FPP-CMR, motion correction is usually performed in the image domain, requiring an initial reconstruction. This fact hinders its use in model-based and deep learning reconstructions, which present remarkable performance in obtaining high-quality images from highly accelerated acquisitions. We address this challenge by estimating and correcting respiratory motion in free-breathing FPP-CMR directly in k-space.

Methods: We propose K-CC-MoCo, an inter-frame rigid motion correction approach formulated exclusively in k-space that handles dynamic contrast through a specifically targeted design of the normalized cross-correlation (CC) objective function to deal with the dynamic contrast. In addition, an ROI-based coil-compression approach was employed to focus the optimization on the heart region. The proposed method was compared to state-of-the-art image-based registration using a digital phantom and real free-breathing acquisitions with different accelerations.

Results: The proposed k-space-based method is approximately 2× faster and can correct respiratory motion even at high acceleration factors (up to 50×), where the image-based method fails due to severe undersampling artifacts. Notably, after K-CC-MoCo, the time-averaged images are visibly less blurred. Quantitative metrics (SSIM, etc.) support this conclusion.

Conclusion: K-CC-MoCo outperforms image-based correction in free-breathing FPP-CMR acquisitions accelerated up to 50×. Respiratory motion is estimated and corrected in k-space, enabling its use for model-based and/or deep learning reconstructions from highly accelerated scans.

Purpose: Provide the theoretical foundation and the first practical demonstration of spatiotemporal encoding (SPEN) using additional nonlinear gradient hardware.

Methods: The quadratic phase profile can be generated either by a chirped-RF pulse combined with a constant gradient or, directly, by a quadratic gradient pulse. Both a conventional chirped-RF and a novel SPEN method using a custom-built matrix gradient coil for quadratic phase generation were implemented and integrated into a spin-echo echo-planar-imaging (SE-EPI) sequence using Pulseq. The methods were compared through phantom imaging experiments performed on a 3T MRI system.

Results: The required quadratic phase profile for SPEN was successfully generated using the nonlinear gradient coil, resulting in images of comparable quality. This quadratic gradient-based approach was achieved while exploiting the advantages of SPEN and overcoming current SAR and minimal TE limitations arising from the use of chirped-RF pulses.

Conclusion: The generation of the SPEN-defining quadratic phase using nonlinear gradients is an advantageous alternative to conventional methods. This approach enables improved clinical applicability of SPEN, particularly for 3D and high-field MRI, by mitigating critical safety and timing limitations. Additionally, an implementation of the conventional method is provided open-source to support further research.

Purpose: To develop a new method for free-running three-dimensional (3D) extracellular volume mapping of the heart in a single scan with mid-scan contrast injection.

Methods: 3D cardiac MR imaging was performed with a single scan that acquired k-space data continuously using an inversion recovery (IR) sequence with a spoiled gradient-echo readout. Contrast agent was injected in the middle of the scan. Dynamic images were reconstructed utilizing a linear tangent space alignment (LTSA) model. The pre- and postcontrast T₁* was estimated by finding the best fit between the measured signal and the MR signal model, which assumes a linearly time-varying R₁* that accounts for T₁* changes after the contrast agent injection. Cardiac cine images were synthesized by fitting with the signal model. The 3D ECV mapping was performed using the 3D pre- and postcontrast T₁* maps and the measured hematocrit level from blood sampling.

Results: The feasibility of the proposed method was demonstrated through in vivo studies conducted on three healthy subjects using a 3T MR scanner. The ECV maps from the proposed method showed good agreement with those from the MOLLI method. The estimated average myocardial ECV from the proposed and MOLLI methods was 29.82% ± 2.45% and 29.28% ± 2.15%, respectively. The cine images from the proposed method successfully captured the heart's motion. The estimated ejection fraction was 63.3% ± 8%, which was in good agreement with literature values.

Conclusion: We developed a novel approach that allows 3D cardiac ECV mapping in a single, free-running, continuous 15-min scan with mid-scan contrast injection.

Purpose: Using artificial intelligence neural networks to generate a representation that maps the input directly to neurochemical concentrations and metabolite-level average transverse relaxation times (T₂).

Methods: The proposed model used time-domain JPRESS data as input and was trained to be invariant to phase shifts, frequency offsets, and lineshape variations, using computer-synthesized data without prior knowledge of in vivo metabolite concentration distributions. TE-specific representations were generated using a combination of WaveNet and gated recurrent units (GRUs) and integrated into a unified JPRESS representation.

Results: By focusing solely on target metabolite signals, the model effectively filtered out background signals, including spectral artifacts and unregistered metabolites. The predicted concentrations and metabolite-level average T₂ values were consistent with those reported in the literature. The model demonstrated robustness to phase shifts, frequency offsets, and line broadening. Additionally, it was capable of detecting low-concentration neurochemicals, such as gamma-aminobutyric acid (GABA), without spectral editing.

Conclusion: This study demonstrates that deep learning can be used for automatically quantifying both metabolite concentrations and transverse relaxation times with high practical viability.

Purpose: Blood T₁ is a key parameter for hemodynamic quantification in both non-contrast- and contrast-enhanced imaging. Individual vessel T₁ has been measured using a modified Look-Locker scheme with multi-shot EPI or FLASH in high spatial resolution, requiring ∼1 min. Here, by exploiting the temporal sparsity from the excessive number of inversion delays, we apply Golden Angle rotated Spiral k-t Sparse Parallel imaging (GASSP) to enable blood T₁ measurement in a single shot of 10 s.

Methods: The pulse sequence with single-shot GASSP reconstruction was developed for T₁ measurement from the internal jugular vein (IJV) with 1 × 1 mm² in-plane resolution. On nine healthy volunteers, the single-shot GASSP was compared to the segmented EPI readout and was repeated to assess its intra-scan reproducibility. Another experiment was performed on three patients, during which the 10 s GASSP was obtained at different time points prior to and following the Gadolinium (Gd) administration to assess dynamic changes in blood T₁.

Results: The blood T₁ values measured with the highly undersampled GASSP method were strongly correlated (r = 0.83) with those using the multi-shot EPI readout and exhibited high reproducibility (r = 0.88) within the session. The baseline IJV T₁ values measured were 1700-2000 ms. Following the Gd injection, the T₁ values of IJVs gradually recovered from ∼300-400 to ∼500 ms within 10-15 min.

Conclusion: The feasibility of an ultrafast blood T₁ measurement was demonstrated with high spatial resolution in a single shot of 10 s, applicable to both pre- and post-contrast conditions.

Purpose: To improve cardiac motion representation and reduce artifacts for cardiac- and respiratory-resolved imaging through a synergistic combination of retrospective cardiac phased array RF focusing and rigid respiratory motion compensation (MoCo).

Methods: We incorporated cardiac receive focusing using region-optimized virtual coils (ROVir) and MoCo into cardiac- and respiratory-resolved low-rank tensor (LRT) reconstruction, hypothesizing that the combination of MoCo + ROVir would prioritize the LRT representation of cardiac motion over respiratory motion. We compared LRT, MoCo-LRT, ROVir-LRT, and the proposed MoCo + ROVir-LRT reconstructions of retrospective data from N = 24 pediatric patients with congenital heart disease (CHD) scanned at 3.0 T using ROCK-MUSIC. Technical evaluation metrics included the proportion of cardiac-to-respiratory motion energy in self-gating lines, cardiac motion priority in the temporal basis, flickering energy, and edge sharpness in end-expiratory cardiac cine. Reconstructed cardiac cines were scored by two expert image readers.

Results: MoCo + ROVir significantly increased the proportion of cardiac-to-respiratory motion energy in self-gating lines (p < 0.001) and prioritized cardiac motion in the temporal basis (p < 0.001). MoCo + ROVir reduced flickering energy in cardiac cine images (p < 0.001), sharpened the liver-lung interface (p < 0.001), and improved flickering-specific scores (p = 0.001). Myocardium-blood pool interface sharpness (p = 0.831), cardiac-specific image scores (p = 0.188), and vascular-specific scores (p = 0.901) were not significantly different. Together, these two techniques allowed 3.7-5.2× faster reconstruction times versus LRT-only.

Conclusion: The synergy of MoCo + ROVir successfully prioritized cardiac motion, suppressed respiratory motion, and reduced flickering artifacts, with an added benefit of accelerating reconstruction times. The improved respiratory motion handling may provide an avenue for free-breathing cardiac scans in pediatric patients with CHD.