DeepEMC-T2 mapping: Deep learning-enabled T2 mapping based on echo modulation curve modeling.

PURPOSE: Echo modulation curve (EMC) modeling enables accurate quantification of T2 relaxation times in multi-echo spin-echo (MESE) imaging. The standard EMC-T2 mapping framework, however, requires sufficient echoes and cumbersome pixel-wise dictionary-matching steps. This work proposes a deep learning version of EMC-T2 mapping, called DeepEMC-T2 mapping, to efficiently estimate accurate T2 maps from fewer echoes. METHODS: DeepEMC-T2 mapping was developed using a modified U-Net to estimate both T2 and proton density (PD) maps directly from MESE images. The network implements several new features to improve the accuracy of T2/PD estimation. A total of 67 MESE datasets acquired in axial orientation were used for network training and evaluation. An additional 57 datasets acquired in coronal orientation with different scan parameters were used to evaluate the generalizability of the framework. The performance of DeepEMC-T2 mapping was evaluated in seven experiments. RESULTS: Compared to the reference, DeepEMC-T2 mapping achieved T2 estimation errors from 1% to 11% and PD estimation errors from 0.4% to 1.5% with ten/seven/five/three echoes, which are more accurate than standard EMC-T2 mapping. By incorporating datasets acquired with different scan parameters and orientations for joint training, DeepEMC-T2 exhibits robust generalizability across varying imaging protocols. Increasing the echo spacing and including longer echoes improve the accuracy of parameter estimation. The new features proposed in DeepEMC-T2 mapping all enabled more accurate T2 estimation. CONCLUSIONS: DeepEMC-T2 mapping enables simplified, efficient, and accurate T2 quantification directly from MESE images without dictionary matching. Accurate T2 estimation from fewer echoes allows for increased volumetric coverage and/or higher slice resolution without prolonging total scan times.

Fast and High-Resolution T2 Mapping Based on Echo Merging Plus k-t Undersampling with Reduced Refocusing Flip Angles (TEMPURA) as Methods for Human Renal MRI.

PURPOSE: To develop a highly accelerated multi-echo spin-echo method, TEMPURA, for reducing the acquisition time and/or increasing spatial resolution for kidney T2 mapping. METHODS: TEMPURA merges several adjacent echoes into one k-space by either combining independent echoes or sharing one echo between k-spaces. The combined k-space is reconstructed based on compressed sensing theory. Reduced flip angles are used for the refocusing pulses, and the extended phase graph algorithm is used to correct the effects of indirect echoes. Two sequences were developed: a fast breath-hold sequence; and a high-resolution sequence. The performance was evaluated prospectively on a phantom, 16 healthy subjects, and two patients with different types of renal tumors. RESULTS: The fast TEMPURA method reduced the acquisition time from 3-5 min to one breath-hold (18 s). Phantom measurements showed that fast TEMPURA had a mean absolute percentage error (MAPE) of 8.2%, which was comparable to a standardized respiratory-triggered sequence (7.4%), but much lower than a sequence accelerated by purely k-t undersampling (21.8%). High-resolution TEMPURA reduced the in-plane voxel size from 3 × 3 to 1 × 1 mm2, resulting in improved visualization of the detailed anatomical structure. In vivo T2 measurements demonstrated good agreement (fast: MAPE = 1.3%-2.5%; high-resolution: MAPE = 2.8%-3.3%) and high correlation coefficients (fast: R = 0.85-0.98; high-resolution: 0.82-0.96) with the standardized method, outperforming k-t undersampling alone (MAPE = 3.3-4.5%, R = 0.57-0.59). CONCLUSION: TEMPURA provides fast and high-resolution renal T2 measurements. It has the potential to improve clinical throughput and delineate intratumoral heterogeneity and tissue habitats at unprecedented spatial resolution.

Accelerated 3D multi-echo spin-echo sequence with a subspace constrained reconstruction for whole mouse brain T 2 mapping.

PURPOSE: To accelerate whole-brain quantitative T 2 $$ {\mathrm{T}}_2 $$ mapping in preclinical imaging setting. METHODS: A three-dimensional (3D) multi-echo spin echo sequence was highly undersampled with a variable density Poisson distribution to reduce the acquisition time. Advanced iterative reconstruction based on linear subspace constraints was employed to recover high-quality raw images. Different subspaces, generated using exponential or extended-phase graph (EPG) simulations or from low-resolution calibration images, were compared. The subspace dimension was investigated in terms of T 2 $$ {\mathrm{T}}_2 $$ precision. The method was validated on a phantom containing a wide range of T 2 $$ {\mathrm{T}}_2 $$ and was then applied to monitor metastasis growth in the mouse brain at 4.7T. Image quality and T 2 $$ {\mathrm{T}}_2 $$ estimation were assessed for 3 acceleration factors (6/8/10). RESULTS: The EPG-based dictionary gave robust estimations of a large range of T 2 $$ {\mathrm{T}}_2 $$ . A subspace dimension of 6 was the best compromise between T 2 $$ {\mathrm{T}}_2 $$ precision and image quality. Combining the subspace constrained reconstruction with a highly undersampled dataset enabled the acquisition of whole-brain T 2 $$ {\mathrm{T}}_2 $$ maps, the detection and the monitoring of metastasis growth of less than 500 µ m 3 $$ \mu {\mathrm{m}}^3 $$ . CONCLUSION: Subspace-based reconstruction is suitable for 3D T 2 $$ {\mathrm{T}}_2 $$ mapping. This method can be used to reach an acceleration factor up to 8, corresponding to an acquisition time of 25 min for an isotropic 3D acquisition of 156 µ $$ \mu $$ m on the mouse brain, used here for monitoring metastases growth.

Lung parenchyma transverse relaxation rates at 0.55 T.

PURPOSE: To determine R2 and R 2 ' $$ {R}_2^{\prime } $$ transverse relaxation rates in healthy lung parenchyma at 0.55 T. This is important in that it informs the design and optimization of new imaging methods for 0.55T lung MRI. METHODS: Experiments were performed in 3 healthy adult volunteers on a prototype whole-body 0.55T MRI, using a custom free-breathing electrocardiogram-triggered, single-slice echo-shifted multi-echo spin echo (ES-MCSE) pulse sequence with respiratory navigation. Transverse relaxation rates R2 and R 2 ' $$ {R}_2^{\prime } $$ and off-resonance ∆f were jointly estimated using nonlinear least-squares estimation. These measurements were compared against R2 estimates from T2 -prepared balanced SSFP (T2 -Prep bSSFP) and R 2 * $$ {R}_2^{\ast } $$ estimates from multi-echo gradient echo, which are used widely but prone to error due to different subvoxel weighting. RESULTS: The mean R2 and R 2 ' $$ {R}_2^{\prime } $$ values of lung parenchyma obtained from ES-MCSE were 17.3 ± 0.7 Hz and 127.5 ± 16.4 Hz (T2  = 61.6 ± 1.7 ms; T 2 ' $$ {\mathrm{T}}_2^{\prime } $$  = 9.5 ms ± 1.6 ms), respectively. The off-resonance estimates ranged from -60 to 30 Hz. The R2 from T2 -Prep bSSFP was 15.7 ± 1.7 Hz (T2  = 68.6 ± 8.6 ms) and R 2 * $$ {R}_2^{\ast } $$ from multi-echo gradient echo was 131.2 ± 30.4 Hz ( T 2 * $$ {\mathrm{T}}_2^{\ast } $$  = 8.0 ± 2.5 ms). Paired t-test indicated that there is a significant difference between the proposed and reference methods (p < 0.05). The mean R2 estimate from T2 -Prep bSSFP was slightly smaller than that from ES-MCSE, whereas the mean R 2 ' $$ {R}_2^{\prime } $$ and R 2 * $$ {R}_2^{\ast } $$ estimates from ES-MCSE and multi-echo gradient echo were similar to each other across all subjects. CONCLUSIONS: Joint estimation of transverse relaxation rates and off-resonance is feasible at 0.55 T with a free-breathing electrocardiogram-gated and navigator-gated ES-MCSE sequence. At 0.55 T, the mean R2 of 17.3 Hz is similar to the reported mean R2 of 16.7 Hz at 1.5 T, but the mean R 2 ' $$ {R}_2^{\prime } $$ of 127.5 Hz is about 5-10 times smaller than that reported at 1.5 T.

T2 relaxation-time mapping in healthy and diseased skeletal muscle using extended phase graph algorithms.

PURPOSE: Multi-echo spin-echo (MSE) transverse relaxometry mapping using multi-component models is used to study disease activity in neuromuscular disease by assessing the T2 of the myocytic component (T2water ). Current extended phase graph algorithms are not optimized for fat fractions above 50% and the effects of inaccuracies in the T2fat calibration remain unexplored. Hence, we aimed to improve the performance of extended phase graph fitting methods over a large range of fat fractions, by including the slice-selection flip angle profile, a through-plane chemical-shift displacement correction, and optimized calibration of T2fat . METHODS: Simulation experiments were used to study the influence of the slice flip-angle profile with chemical-shift and T2fat estimations. Next, in vivo data from four neuromuscular disease cohorts were studied for different T2fat calibration methods and T2water estimations. RESULTS: Excluding slice flip-angle profiles or chemical-shift displacement resulted in a bias in T2water up to 10 ms. Furthermore, a wrongly calibrated T2fat caused a bias of up to 4 ms in T2water . For the in vivo data, one-component calibration led to a lower T2fat compared with a two-component method, and T2water decreased with increasing fat fractions. CONCLUSION: In vivo data showed a decline in T2water for increasing fat fractions, which has important implications for clinical studies, especially in multicenter settings. We recommend using an extended phase graph-based model for fitting T2water from MSE sequences with two-component T2fat calibration. Moreover, we recommend including the slice flip-angle profile in the model with correction for through-plane chemical-shift displacements.

Human in-vivo brain magnetic resonance current density imaging (MRCDI).

Magnetic resonance current density imaging (MRCDI) and MR electrical impedance tomography (MREIT) are two emerging modalities, which combine weak time-varying currents injected via surface electrodes with magnetic resonance imaging (MRI) to acquire information about the current flow and ohmic conductivity distribution at high spatial resolution. The injected current flow creates a magnetic field in the head, and the component of the induced magnetic field ΔBz,c parallel to the main scanner field causes small shifts in the precession frequency of the magnetization. The measured MRI signal is modulated by these shifts, allowing to determine ΔBz,c for the reconstruction of the current flow and ohmic conductivity. Here, we demonstrate reliable ΔBz,c measurements in-vivo in the human brain based on multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. In a series of experiments, we optimize their robustness for in-vivo measurements while maintaining a good sensitivity to the current-induced fields. We validate both methods by assessing the linearity of the measured ΔBz,c with respect to the current strength. For the more efficient SSFP-FID measurements, we demonstrate a strong influence of magnetic stray fields on the ΔBz,c images, caused by non-ideal paths of the electrode cables, and validate a correction method. Finally, we perform measurements with two different current injection profiles in five subjects. We demonstrate reliable recordings of ΔBz,c fields as weak as 1 nT, caused by currents of 1 mA strength. Comparison of the ΔBz,c measurements with simulated ΔBz,c images based on FEM calculations and individualized head models reveals significant linear correlations in all subjects, but only for the stray field-corrected data. As final step, we reconstruct current density distributions from the measured and simulated ΔBz,c data. Reconstructions from non-corrected ΔBz,c measurements systematically overestimate the current densities. Comparing the current densities reconstructed from corrected ΔBz,c measurements and from simulated ΔBz,c images reveals an average coefficient of determination R2 of 71%. In addition, it shows that the simulations underestimated the current strength on average by 24%. Our results open up the possibility of using MRI to systematically validate and optimize numerical field simulations that play an important role in several neuroscience applications, such as transcranial brain stimulation, and electro- and magnetoencephalography.

Sensitivity analysis of magnetic field measurements for magnetic resonance electrical impedance tomography (MREIT).

PURPOSE: Clinical use of magnetic resonance electrical impedance tomography (MREIT) still requires significant sensitivity improvements. Here, the measurement of the current-induced magnetic field (ΔBz,c ) is improved using systematic efficiency analyses and optimization of multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. THEORY AND METHODS: Considering T1 , T2 , and T2* relaxation in the signal-to-noise ratios (SNRs) of the MR magnitude images, the efficiency of MESE and SSFP-FID MREIT experiments, and its dependence on the sequence parameters, are analytically analyzed and simulated. The theoretical results are experimentally validated in a saline-filled homogenous spherical phantom with relaxation parameters similar to brain tissue. Measurement of ΔBz,c is also performed in a cylindrical phantom with saline and chicken meat. RESULTS: The efficiency simulations and experimental results are in good agreement. When using optimal parameters, ΔBz,c can be reliably measured in the phantom even at injected current strengths of 1 mA or lower for both sequence types. The importance of using proper crusher gradient selection on the phase evolution in a MESE experiment is also demonstrated. CONCLUSION: The efficiencies observed with the optimized sequence parameters will likely render in-vivo human brain MREIT feasible. Magn Reson Med 79:748-760, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Spatiotemporal Analysis of Hydration Mechanism in Sodium Alginate Matrix Tablets.

Methods of spatiotemporal characterization of nonequilibrated polymer based matrices are still immature and imperfect. The purpose of the study was to develop the methodology for the spatiotemporal characterization of water transport and properties in alginate tablets under hydration. The regions of low water content were spatially and temporally sampled using Karl Fisher and Differential Scanning Callorimetry (spatial distribution of freezing/nonfreezing water) with spatial resolution of 1 mm. In the regions of high water content, where sampling was infeasible due to gel/sol consistency, magnetic resonance imaging (MRI) enabled characterization with an order of magnitude higher spatial resolution. The minimally hydrated layer (MHL), infiltration layer (IL) and fully hydrated layer (FHL) were identified in the unilaterally hydrated matrices. The MHL gained water from the first hour of incubation (5-10% w/w) and at 4 h total water content was 29-39% with nonfreezing pool of 28-29%. The water content in the IL was 45-47% and at 4 h it reached ~50% with the nonfreezing pool of 28% and T2 relaxation time < 10 ms. The FHL consisted of gel and sol layer with water content of 85-86% with a nonfreezing pool of 11% at 4 h and T2 in the range 20-200 ms. Hybrid destructive/nondestructive analysis of alginate matrices under hydration was proposed. It allowed assessing the temporal changes of water distribution, its mobility and interaction with matrices in identified layers.

A time domain signal equation for multi-echo spin-echo sequences with arbitrary excitation and refocusing angle and phase.

Accurate T2 mapping using multi-echo spin-echo is usually impaired by non-ideal refocusing due to B1+ inhomogeneities and slice profile effects. Incomplete refocusing gives rise to stimulated echo and so called "T1-mixing" and consequently a non-exponential signal decay. Here we present a time domain formula that incorporates all relaxation and pulse parameters and enables accurate and realistic modelling of the magnetization decay curve. By pulse parameters here we specifically mean the actual refocusing angle and axis, and phase angle of both the excitation and refocusing pulse. The method used for derivation comprises the so called Generating functions approach with subsequent back-transformation to the time domain. The proposed approach was validated by simulations using realistic RF pulse shapes as well as by comparison to phantom measurements. Excellent agreement between simulations and measurements underpin the validity of the presented approach. Conclusively, we here present a complete time domain formula ready to use for accurate T2 mapping with multi-echo spin-echo sequences.

Accelerating the estimation of 3D spatially resolved T2 distributions.

Obtaining quantitative, 3D spatially-resolved T2 distributions (T2 maps) from magnetic resonance data is of importance in both medical and porous media applications. Due to the long acquisition time, there is considerable interest in accelerating the experiments by applying undersampling schemes during the acquisition and developing reconstruction techniques for obtaining the 3D T2 maps from the undersampled data. A multi-echo spin echo pulse sequence is used in this work to acquire the undersampled data according to two different sampling patterns: a conventional coherent sampling pattern where the same set of lines in k-space is sampled for all equally-spaced echoes in the echo train, and a proposed incoherent sampling pattern where an independent set of k-space lines is sampled for each echo. The conventional reconstruction technique of total variation regularization is compared to the more recent techniques of nuclear norm regularization and Nuclear Total Generalized Variation (NTGV) regularization. It is shown that best reconstructions are obtained when the data acquired using an incoherent sampling scheme are processed using NTGV regularization. Using an incoherent sampling pattern and NTGV regularization as the reconstruction technique, quantitative results are obtained at sampling percentages as low as 3.1% of k-space, corresponding to a 32-fold decrease in the acquisition time, compared to a fully sampled dataset.