Frequency-dependent diffusion kurtosis imaging in the human brain using an oscillating gradient spin echo sequence and a high-performance head-only gradient.

Measuring the time/frequency dependence of diffusion MRI is a promising approach to distinguish between the effects of different tissue microenvironments, such as membrane restriction, tissue heterogeneity, and compartmental water exchange. In this study, we measure the frequency dependence of diffusivity (D) and kurtosis (K) with oscillating gradient diffusion encoding waveforms and a diffusion kurtosis imaging (DKI) model in human brains using a high-performance, head-only MAGNUS gradient system, with a combination of b-values, oscillating frequencies (f), and echo time that has not been achieved in human studies before. Frequency dependence of diffusivity and kurtosis are observed in both global and local white matter (WM) and gray matter (GM) regions and characterized with a power-law model ∼Λ*fθ. The frequency dependences of diffusivity and kurtosis (including changes between fmin and fmax, Λ, and θ) vary over different WM and GM regions, indicating potential microstructural differences between regions. A trend of decreasing kurtosis over frequency in the short-time limit is successfully captured for in vivo human brains. The effects of gradient nonlinearity (GNL) on frequency-dependent diffusivity and kurtosis measurements are investigated and corrected. Our results show that the GNL has prominent scaling effects on the measured diffusivity values (3.5∼5.5% difference in the global WM and 6∼8% difference in the global cortex) and subsequently affects the corresponding power-law parameters (Λ, θ) while having a marginal influence on the measured kurtosis values (<0.05% difference) and power-law parameters (Λ, θ). This study expands previous OGSE studies and further demonstrates the translatability of frequency-dependent diffusivity and kurtosis measurements to human brains, which may provide new opportunities to probe human brain microstructure in health and disease.

Improving in situ acoustic intensity estimates using MR acoustic radiation force imaging in combination with multifrequency MR elastography.

PURPOSE: Magnetic resonance acoustic radiation force imaging (MR-ARFI) enables focal spot localization during nonablative transcranial ultrasound therapies. As the acoustic radiation force is proportional to the applied acoustic intensity, measured MR-ARFI displacements could potentially be used to estimate the acoustic intensity at the target. However, variable brain stiffness is an obstacle. The goal of this study was to develop and assess a method to accurately estimate the acoustic intensity at the focus using MR-ARFI displacements in combination with viscoelastic properties obtained with multifrequency MR elastography (MRE). METHODS: Phantoms with a range of viscoelastic properties were fabricated, and MR-ARFI displacements were acquired within each phantom using multiple acoustic intensities. Voigt model parameters were estimated for each phantom based on storage and loss moduli measured using multifrequency MRE, and these were used to predict the relationship between acoustic intensity and measured displacement. RESULTS: Using assumed viscoelastic properties, MR-ARFI displacements alone could not accurately estimate acoustic intensity across phantoms. For example, acoustic intensities were underestimated in phantoms stiffer than the assumed stiffness and overestimated in phantoms softer than the assumed stiffness. This error was greatly reduced using individualized viscoelasticity measurements obtained from MRE. CONCLUSION: We demonstrated that viscoelasticity information from MRE could be used in combination with MR-ARFI displacements to obtain more accurate estimates of acoustic intensity. Additionally, Voigt model viscosity parameters were found to be predictive of the relaxation rate of each phantom's time-varying displacement response, which could be used to optimize patient-specific MR-ARFI pulse sequences.

Simultaneous multislice MRI thermometry with a single coil using incoherent blipped-controlled aliasing.

PURPOSE: To increase volume coverage in real-time MR thermometry for transcranial MR-guided focused ultrasound (tcMRgFUS) ablation, without multiple receive coils. THEORY AND METHODS: Multiband excitation and incoherent blipped-controlled aliasing were implemented in a 2DFT pulse sequence used clinically for tcMRgFUS, and an extended k-space hybrid reconstruction was developed that recovers slice-separated temperature maps assuming that heating is focal, given slice-separated pretreatment images. Simulations were performed to characterize slice leakage, the number of slices that can be simultaneously imaged with low-temperature error, and robustness across random slice-phase k-space permutations. In vivo experiments were performed using a single receive coil without heating to measure temperature precision, and gel phantom FUS experiments were performed to test the method with heating and with a water bath. RESULTS: Simulations showed that with large hot spots and identical magnitude images on each slice, up to three slices can be simultaneously imaged with less than 1∘ C temperature root-mean-square error. They also showed that hot spots do not alias coherently between slices, and that an average 86% of random slice-phase k-space permutations yielded less than 1∘ C temperature error. Temperature precision was not degraded compared to single-slice imaging in the in vivo SMS scans, and the gel phantom SMS temperature maps closely tracked single-slice temperature in the hot spot, with no coherent aliasing to other slices. CONCLUSIONS: Incoherent controlled aliasing SMS enables accurate reconstruction of focal heating maps from two or three slices simultaneously, using a single receive coil and a sparsity-promoting temperature reconstruction.