Magnetic Resonance in Medicine最新文献

Preclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high SNR images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a three-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing, and comparisons with microscopy. In each section, we attempt to provide guidelines and recommendations but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing and point toward open-source software and databases specific to small animal and ex vivo imaging.

Small-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the resultant data. This work aims to present selected considerations and recommendations from the diffusion community on best practices for preclinical dMRI of in vivo animals. We describe the general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss why some may be more or less appropriate for different studies. We, then, give recommendations for in vivo acquisition protocols, including decisions on hardware, animal preparation, and imaging sequences, followed by advice for data processing including preprocessing, model-fitting, and tractography. Finally, we provide an online resource that lists publicly available preclinical dMRI datasets and software packages to promote responsible and reproducible research. In each section, we attempt to provide guides and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should focus. Although we mainly cover the central nervous system (on which most preclinical dMRI studies are focused), we also provide, where possible and applicable, recommendations for other organs of interest. An overarching goal is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.

Purpose: Patients undergoing craniofacial surgery for skull reconstruction may have titanium mesh implants. The safety risks related to 7 T MRI with these patients are not well understood. This study investigates the RF heating of titanium mesh head implants at 7 T.

Methods: A simulation model for a 7 T birdcage head coil was developed and validated against $\left(B_1^{+}\right)$ , 1 g-averaged specific absorption rate (SAR), and temperature measurements in the presence of a titanium mesh. Various mesh sizes and shapes at different angular positions were simulated to determine the worst-case scenario in a spherical phantom in addition to the effect of rounding the mesh edges. Full-wave electromagnetic and bioheat thermal simulations were conducted on anatomical human models.

Results: Preliminary results indicate an increase in the local SAR near the meshes depending on the shape, size, and location. The maximum absolute temperatures in the head were, on average, around 38.2°C after 15 min of RF power exposure, corresponding to 3.2 W/kg whole-head SAR without a titanium mesh implant. The maximum absolute temperatures did not significantly change after introducing the titanium mesh implants, and the highest temperature was 38.4°C, observed near the cerebellum and the facial muscles. The maximum local increase in temperature was observed at the vicinity of the mesh as 2.8°C. Finally, it was shown that large mesh implants can negatively impact $\left(B_1^{+}\right)$ field.

Conclusions: Small rounded titanium mesh head implants can be generally safe for 7 T MRI scans under the standard guidelines. Avoiding sharp corners and edges may reduce the chances of RF safety risks.

Purpose: In comparison to dipole antennas, the coax monopole antenna (CMA) diminishes the possibility of cable-coil coupling. This greatly facilitates cable routing in spatially restricted environments, such as head coil arrays. With the outlook of a 14T MRI system being installed at the Donders Center in Nijmegen, the Netherlands, this study aims to optimize the CMA for an eight-channel head array at 14 T and compare its performance with an array of fractionated dipole antennas.

Methods: Both antenna designs were optimized for head imaging at 14 T using single-channel finite-difference time-domain (FDTD) simulations at 596 MHz. Eight-channel simulations were then used on a human model to evaluate $B_1^{+}$ and specific absorption rate (SAR) distributions. For both antenna types, prototype arrays were built by placing eight elements on a 26-cm-diameter cylindrical holder. These prototype arrays were used for S₁₁ and S₁₂ evaluation.

Results: The optimal dimensions of the CMA were a length of 20 cm and a gap position of 4 cm. The fractionated dipole was optimal for a length of 25 cm. Evaluation of 100 000 random shims revealed that the CMA performs with lower SAR efficiency, although the SAR efficiencies are similar in CP mode. Measured S₁₁ and S₁₂ levels were both lower for the CMA.

Conclusion: The coax monopole would be an excellent candidate for head coil arrays at 14T MRI. Although the CMA is expected to perform with lower SAR efficiency than the fractionated dipole, its single-ended design will facilitate elements placement and cable-routing, especially in a spatially restricted environment.

Purpose: Diagnosis and treatment monitoring of iron overload increasingly relies on non-invasive MRI-based measurement of liver iron concentration (LIC). Liver R₂ mapping is known to correlate well with LIC. However, traditional spin-echo based R₂ mapping methods have drawbacks such as long acquisition times and limited volumetric coverage. In this work, we present an optimized phase-based R₂ mapping method to quantify whole-liver R₂ in iron overload patients within a single breathhold.

Theory and methods: A recently developed phase-based R₂ mapping method is optimized in this study to improve estimation of high R₂ values using reduced TR, spatial averaging, and R₁ correction. Using Bloch equation simulations, the proposed optimization method was evaluated. Furthermore, the impact of fat on R₂ bias was investigated through simulations. The feasibility of the optimized phase-based R₂ method was assessed in healthy volunteers and patients with iron overload and compared to reference STEAM-MRS R₂ measurements.

Results: Simulations demonstrate that a shorter TR extends the dynamic range of R₂ estimation to higher values and that averaging of signal phase before R₂ estimation is necessary when R₂ is high. Phantom experiments also demonstrate reduced phase-based R₂ bias using R₁ correction. Good agreement (1.5 T: r² = 0.76, 3.0 T: r² = 0.70) between the modified phase-based R₂ method and reference STEAM R₂ was found in healthy volunteers and iron overload patients over a wide range of LIC values.

Conclusion: This study demonstrates the feasibility of the proposed phase-based R₂ method to accurately measure whole-liver R₂ mapping in severe iron overloaded patients during a single breathhold.

Purpose: Four-pool Voigt (FPV) machine learning (ML)-based fitting for Z-spectra was developed to reduce fitting times for clinical feasibility in terms of on-scanner analysis and to promote larger cohort studies. The approach was compared to four-pool Lorentzian (FPL)-ML-based modeling to empirically verify the advantage of Voigt models for Z-spectra.

Methods: Voigt and Lorentzian models were fitted to human 3 T Z-spectral data using least squares (LS) to generate training data for the corresponding ML versions. Gradient boosting decision trees were trained, resulting in one Voigt and one Lorentzian ML model. Modeling accuracy was tested, and the fitting times of the ML models and LS versions were evaluated. The goodness of fits of Voigt and Lorentzian ML models were compared.

Results: The training time for each ML model (Voigt and Lorentzian) was less than 1 min, and the modeling accuracy compared to the corresponding LS versions was excellent, as indicated by a nonsignificant difference between the parameters obtained by LS and corresponding ML versions. The average fitting time was 20 μs/spectrum for both ML models compared to 0.27 and 0.82 s/spectrum for LS with FPL and FPV, respectively. The goodness of fits of FPV-ML and FPL-ML differed significantly (p < 0.005), with FPV-ML showing an improvement for all tested data.

Conclusion: Gradient boosting decision trees fitting of multi-pool Z-spectra significantly reduces fitting times compared to traditional LS approaches, allowing fast data processing while upholding fitting quality. Along with the short training times, this makes the method suitable for clinical settings and for large cohort research applications. The FPV-ML approach provides a significant improvement of goodness of fit compared to FPL-ML.

Purpose: This study investigates the impact of orthopedic plates on peripheral nerve stimulation (PNS) during MRI, focusing on how the presence of implants affects PNS thresholds.

Methods: A combination of anatomical electromagnetic and neurophysiological modeling was utilized. Electromagnetic fields in human body models were simulated, both with and without orthopedic plates. Simulations were performed under x-, y-, and z-axis gradient coils, with plates implanted at two clinically relevant locations. Nerve responses were modeled using an established neurophysiological model.

Results: The presence of orthopedic implants significantly influenced nerve stimulation, leading to reductions in stimulation thresholds of up to 80%. Some of the reduced thresholds were close to the PNS limits outlined in International Electrotechnical Commission (IEC) 60601-2-33, suggesting a considerably reduced safety margin compared to cases without implants.

Conclusion: Orthopedic implants can substantially lower the activation thresholds of nearby nerves, with some thresholds approaching the PNS limits defined in IEC 60601-2-33 for MRI gradient field. This finding indicates a reduced safety margin for patients with implants, highlighting the need for more comprehensive safety assessments.

Purpose: Accurate quantification of metabolism in hyperpolarized (HP) ¹³C MRI is essential for clinical applications. However, kinetic model parameters are often confounded by uncertainties in radiofrequency flip angles and other model parameters.

Methods: A data-driven kinetic fitting approach for HP ¹³C-pyruvate MRI was proposed that compensates for uncertainties in the B₁ ⁺ field. We hypothesized that introducing a scaling factor to the flip angle to minimize fit residuals would allow more accurate determination of the pyruvate-to-lactate conversion rate (k_PL). Numerical simulations were performed under different conditions (flip angle, k_PL, and T₁ relaxation), with further testing using HP ¹³C-pyruvate MRI of rat liver and kidneys.

Results: Simulations showed that the proposed method reduced k_PL error from 60% to 1% when the prescribed and actual flip angles differed by 60%. The method also showed robustness to T₁ uncertainties, achieving median k_PL errors within ±3% even when the assumed T₁ was incorrect by up to a factor of 2. In rat studies, better-quality fitting for lactate signals (a 1.4-fold decrease in root mean square error [RMSE] for lactate fit) and tighter k_PL distributions (an average of 3.1-fold decrease in k_PL standard deviation) were achieved using the proposed method compared with when no correction was applied.

Conclusion: The proposed data-driven kinetic fitting approach provided a method to accurately quantify HP ¹³C-pyruvate metabolism in the presence of B₁ ⁺ inhomogeneity. This model may also be used to correct for other error sources, such as T₁ relaxation and flow, and may prove to be clinically valuable in improving tumor staging or assessing treatment response.

Purpose: Blood oxygen-level dependent (BOLD) functional MRI signals depend on changes in deoxyhemoglobin content, which is associated with baseline cerebral blood volume (CBV) and blood oxygen saturation change. To accurately interpret activation-induced BOLD responses and quantify perfusion values by BOLD dynamic susceptibility contrast (BOLD-DSC) with transient hypoxia, it is critical to assess Δ $R_2^{*}$ values in tissue and blood across varying levels of hypoxia and magnetic field strengths (B₀).

Methods: Whole-brain BOLD responses were examined using 5-s graded hypoxic challenges with 10%, 5%, and 0% O₂ at ultrahigh field strengths of 7 T, 9.4 T, and 15.2 T. Both tissue and blood responses were analyzed for BOLD-DSC quantification.

Results: Substantial heterogeneity in hypoxia-induced Δ $R_2^{*}$ was observed among regions under different hypoxic doses and B₀. Nonlinear Δ $R_2^{*}$ responses with increasing field strength were observed, depending on hypoxic levels: 10% O₂ condition exhibited pronounced supralinear trends, whereas 0% and 5% O₂ conditions showed nearly linear dependencies. Blood arterial and venous ${∆R}_2^{*}$ responses showed a similar dependence as tissue. However, at 15.2 T, the venous signal saturated under 5% and 0% O₂ conditions. Quantitative CBV values obtained from BOLD-DSC data showed dependency on susceptibility effects, and higher B₀ and hypoxic severity resulted in slightly higher CBV, indicating that caution is needed when comparing quantitative CBV values derived from different experimental protocols. Normalizing regional CBV values to those of white matter effectively reduced the impact of varying susceptibility contrasts.

Conclusions: Our investigations provide biophysical insights into the BOLD contrast mechanism at ultrahigh fields, and address quantification issues in susceptibility-based CBV measurements.