Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks.

Hippocampal atrophy (tissue loss) has become a fundamental outcome parameter in clinical trials on Alzheimer's disease. To accurately estimate hippocampus volume and track its volume loss, a robust and reliable segmentation is essential. Manual hippocampus segmentation is considered the gold standard but is extensive, time-consuming, and prone to rater bias. Therefore, it is often replaced by automated programs like FreeSurfer, one of the most commonly used tools in clinical research. Recently, deep learning-based methods have also been successfully applied to hippocampus segmentation. The basis of all approaches are clinically used T1-weighted whole-brain MR images with approximately 1 mm isotropic resolution. However, such T1 images show low contrast-to-noise ratios (CNRs), particularly for many hippocampal substructures, limiting delineation reliability. To overcome these limitations, high-resolution T2-weighted scans are suggested for better visualization and delineation, as they show higher CNRs and usually allow for higher resolutions. Unfortunately, such time-consuming T2-weighted sequences are not feasible in a clinical routine. We propose an automated hippocampus segmentation pipeline leveraging deep learning with T2-weighted MR images for enhanced hippocampus segmentation of clinical T1-weighted images based on a series of 3D convolutional neural networks and a specifically acquired multi-contrast dataset. This dataset consists of corresponding pairs of T1- and high-resolution T2-weighted images, with the T2 images only used to create more accurate manual ground truth annotations and to train the segmentation network. The T2-based ground truth labels were also used to evaluate all experiments by comparing the masks visually and by various quantitative measures. We compared our approach with four established state-of-the-art hippocampus segmentation algorithms (FreeSurfer, ASHS, HippoDeep, HippMapp3r) and demonstrated a superior segmentation performance. Moreover, we found that the automated segmentation of T1-weighted images benefits from the T2-based ground truth data. In conclusion, this work showed the beneficial use of high-resolution, T2-based ground truth data for training an automated, deep learning-based hippocampus segmentation and provides the basis for a reliable estimation of hippocampal atrophy in clinical studies.

Real-time fMRI neurofeedback of the anterior insula using arterial spin labelling.

Arterial spin labelling (ASL) is the only non-invasive technique that allows absolute quantification of perfusion and is increasingly used in brain activation studies. Contrary to the blood oxygen level-dependent (BOLD) effect ASL measures the cerebral blood flow (CBF) directly. However, the ASL signal has a lower signal-to-noise ratio (SNR), than the BOLD signal, which constrains its utilization in neurofeedback studies. If successful, ASL neurofeedback can be used to aid in the rehabilitation of health conditions with impaired blood flow, for example, stroke. We provide the first ASL-based neurofeedback study incorporating a double-blind, sham-controlled design. A pseudo-continuous ASL (pCASL) approach with background suppression and 3D GRASE readout was combined with a real-time post-processing pipeline. The real-time pipeline allows to monitor the ASL signal and provides real-time feedback on the neural activity to the subject. In total 41 healthy adults (19-56 years) divided into three groups underwent a neurofeedback-based emotion imagery training of the left anterior insula. Two groups differing only in the explicitness level of instruction received real training and a third group received sham feedback. Only those participants receiving real feedback with explicit instruction showed significantly higher absolute CBF values in the trained region during neurofeedback than participants receiving sham feedback. However, responder analyses of percent signal change values show no differences in activation between the three groups. Persisting limitations, such as the lower SNR, confounding effects of arterial transit time and partial volume effects still impact negatively the implementation of ASL neurofeedback.

Enhanced and robust contrast in CEST MRI: Saturation pulse shape design via optimal control.

PURPOSE: To employ optimal control for the numerical design of Chemical Exchange Saturation Transfer (CEST) saturation pulses to maximize contrast and stability against B 0 $$ {\mathrm{B}}_0 $$ inhomogeneities. THEORY AND METHODS: We applied an optimal control framework for the design pulse shapes for CEST saturation pulse trains. The cost functional minimized both the pulse energy and the discrepancy between the corresponding CEST spectrum and the target spectrum based on a continuous radiofrequency (RF) pulse. The optimization is subject to hardware limitations. In measurements on a 7 T preclinical scanner, the optimal control pulses were compared to continuous-wave and Gaussian saturation methods. We conducted a comparison of the optimal control pulses with Gaussian, block pulse trains, and adiabatic spin-lock pulses. RESULTS: The optimal control pulse train demonstrated saturation levels comparable to continuous-wave saturation and surpassed Gaussian saturation by up to 50 % in phantom measurements. In phantom measurements at 3 T the optimized pulses not only showcased the highest CEST contrast, but also the highest stability against field inhomogeneities. In contrast, block pulse saturation resulted in severe artifacts. Dynamic Bloch-McConnell simulations were employed to identify the source of these artifacts, and underscore the B 0 $$ {\mathrm{B}}_0 $$ robustness of the optimized pulses. CONCLUSION: In this work, it was shown that a substantial improvement in pulsed saturation CEST imaging can be achieved by using Optimal Control design principles. It is possible to overcome the sensitivity of saturation to B0 inhomogeneities while achieving CEST contrast close to continuous wave saturation.

Improved quantification in CEST-MRI by joint spatial total generalized variation.

PURPOSE: In this work, the use of joint Total Generalized Variation (TGV) regularization to improve Multipool-Lorentzian fitting of chemical exchange saturation transfer (CEST) Spectra in terms of stability and parameter signal-to-noise ratio (SNR) was investigated. THEORY AND METHODS: The joint TGV term was integrated into the nonlinear parameter fitting problem. To increase convergence and weight the gradients, preconditioning using a voxel-wise singular value decomposition was applied to the problem, which was then solved using the iteratively regularized Gauss-Newton method combined with a Primal-Dual splitting algorithm. The TGV method was evaluated on simulated numerical phantoms, 3T phantom data and 7T in vivo data with respect to systematic errors and robustness. Three reference methods were also implemented: The standard nonlinear fitting, a method using a nonlocal-means filter for denoising and the pyramid scheme, which uses downsampled images to acquire accurate start values. RESULTS: The proposed regularized fitting method showed significantly improved robustness (compared to the reference methods). In testing, over a range of SNR values the TGV fit outperformed the other methods and showed accurate results even for large amounts of added noise. Parameter values found were closer or comparable to the ground truth. For in vivo datasets, the added regularization increased the parameter map SNR and prevented instabilities. CONCLUSION: The proposed fitting method using TGV regularization leads to improved results over a range of different data-sets and noise levels. Furthermore, it can be applied to all Z-spectrum data, with different amounts of pools, where the improved SNR and stability can increase diagnostic confidence.

Robust dual-angle T 1 measurement in magnetization transfer spectroscopy by time-optimal control.

Magnetization transfer spectroscopy relies heavily on the robust determination of T 1 relaxation times of nuclei participating in metabolic exchange. Challenges arise due to the use of surface RF coils for transmission (high B 1 + variation) and the broad resonance band of most X nuclei. These challenges are particularly pronounced when fast T 1 mapping methods, such as the dual-angle method, are employed. Consequently, in this work, we develop resonance offset and B 1 + robust excitation RF pulses for 31P magnetization transfer spectroscopy at 7T through ensemble-based time-optimal control. In our approach, we introduce a cost functional for designing robust pulses, incorporating the full Bloch equations as constraints, which are solved using symmetric operator splitting techniques. The optimal control design of the RF pulses developed demonstrates improved accuracy, desired phase properties, and reduced RF power when applied to dual-angle T 1 mapping, thereby improving the precision of exchange-rate measurements, as demonstrated in a preclinical in vivo study quantifying brain creatine kinase activity.

Whole-Cerebrum distortion-free three-dimensional pseudo-continuous arterial spin labeling at 7T.

Fulfilling potentials of ultrahigh field for pseudo-Continuous Arterial Spin Labeling (pCASL) has been hampered by B1/B0 inhomogeneities that affect pCASL labeling, background suppression (BS), and the readout sequence. This study aimed to present a whole-cerebrum distortion-free three-dimensional (3D) pCASL sequence at 7T by optimizing pCASL labeling parameters, BS pulses, and an accelerated Turbo-FLASH (TFL) readout. A new set of pCASL labeling parameters (Gave = 0.4 mT/m, Gratio = 14.67) was proposed to avoid interferences in bottom slices while achieving robust labeling efficiency (LE). An OPTIM BS pulse was designed based on the range of B1/B0 inhomogeneities at 7T. A 3D TFL readout with 2D-CAIPIRINHA undersampling (R = 2 × 2) and centric ordering was developed, and the number of segments (Nseg) and flip angle (FA) were varied in simulation to achieve the optimal trade-off between SNR and spatial blurring. In-vivo experiments were performed on 19 subjects. The results showed that the new set of labeling parameters effectively achieved whole-cerebrum coverage by eliminating interferences in bottom slices while maintaining a high LE. The OPTIM BS pulse achieved 33.3% higher perfusion signal in gray matter (GM) than the original BS pulse with a cost of 4.8-fold SAR. Incorporating a moderate FA (8°) and Nseg (2), whole-cerebrum 3D TFL-pCASL imaging was achieved with a 2 × 2 × 4 mm3 resolution without distortion and susceptibility artifacts compared to 3D GRASE-pCASL. In addition, 3D TFL-pCASL showed a good to excellent test-retest repeatability and potential of higher resolution (2 mm isotropic). The proposed technique also significantly improved SNR when compared to the same sequence at 3T and simultaneous multislice TFL-pCASL at 7T. By combining a new set of labeling parameters, OPTIM BS pulse, and accelerated 3D TFL readout, we achieved high resolution pCASL at 7T with whole-cerebrum coverage, detailed perfusion and anatomical information without distortion, and sufficient SNR.

Model-based reconstructions for intravoxel incoherent motion and diffusion tensor imaging parameter map estimations.

Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.

Advanced design of MRI inversion pulses for inhomogeneous field conditions by optimal control.

Non-selective inversion pulses find widespread use in MRI applications, where requirements on them are increasingly demanding. With the use of high and ultra-high field strength systems, robustness to Δ B 0 and B 1 + inhomogeneities, while tackling SAR and hardware limitations, has rapidly become important. In this work, we propose a time-optimal control framework for the optimization of Δ B 0 - and B 1 + -robust inversion pulses. Robustness is addressed by means of ensemble formulations, while allowing inclusion of hardware and energy limitations. The framework is flexible and performs excellently for various optimization goals. The optimization results are analyzed extensively in numerical experiments. Furthermore, they are validated, and compared with adiabatic RF pulses, in various phantom and in vivo measurements on a 3 T MRI system.

Adaptive slice-specific z-shimming for 2D spoiled gradient-echo sequences.

PURPOSE: To reduce the misbalance between compensation gradients and macroscopic field gradients, we introduce an adaptive slice-specific z-shimming approach for 2D spoiled multi-echo gradient-echoe sequences in combination with modeling of the signal decay. METHODS: Macroscopic field gradients were estimated for each slice from a fast prescan (15 seconds) and then used to calculate slice-specific compensation moments along the echo train. The coverage of the compensated field gradients was increased by applying three positive and three negative moments. With a forward model, which considered the effect of the slice profile, the z-shim moment, and the field gradient, R2∗ maps were estimated. The method was evaluated in phantom and in vivo measurements at 3 T and compared with a spoiled multi-echo gradient-echo and a global z-shimming approach without slice-specific compensation. RESULTS: The proposed method yielded higher SNR in R2∗ maps due to a broader range of compensated macroscopic field gradients compared with global z-shimming. In global white matter, the mean interquartile range, proxy for SNR, could be decreased to 3.06 s-1 with the proposed approach, compared with 3.37 s-1 for global z-shimming and 3.52 s-1 for uncompensated multi-echo gradient-echo. CONCLUSION: Adaptive slice-specific compensation gradients between echoes substantially improved the SNR of R2∗ maps, and the signal could also be rephased in anatomical areas, where it has already been completely dephased.

Joint multi-field T1 quantification for fast field-cycling MRI.

PURPOSE: Recent developments in hardware design enable the use of fast field-cycling (FFC) techniques in MRI to exploit the different relaxation rates at very low field strength, achieving novel contrast. The method opens new avenues for in vivo characterizations of pathologies but at the expense of longer acquisition times. To mitigate this, we propose a model-based reconstruction method that fully exploits the high information redundancy offered by FFC methods. METHODS: The proposed model-based approach uses joint spatial information from all fields by means of a Frobenius - total generalized variation regularization. The algorithm was tested on brain stroke images, both simulated and acquired from FFC patients scans using an FFC spin echo sequences. The results are compared to three non-linear least squares fits with progressively increasing complexity. RESULTS: The proposed method shows excellent abilities to remove noise while maintaining sharp image features with large signal-to-noise ratio gains at low-field images, clearly outperforming the reference approach. Especially patient data show huge improvements in visual appearance over all fields. CONCLUSION: The proposed reconstruction technique largely improves FFC image quality, further pushing this new technology toward clinical standards.

Impact of the Choice of Native T1 in Pixelwise Myocardial Blood Flow Quantification.

BACKGROUND: Quantification of myocardial blood flow (MBF) from dynamic contrast-enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T1 values of blood and myocardium. PURPOSE: To assess the impact of T1 values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population-averaged vs. subject-specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T1 values. STUDY TYPE: Prospective. SUBJECTS: Fifteen patients with chronic coronary heart disease. FIELD STRENGTH/SEQUENCE: 3T; modified Look-Locker inversion recovery for T1 mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid-ventricular short-axis slice in systole and diastole. ASSESSMENT: MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T1 values: study population-averaged blood and myocardial, subject-specific systolic and diastolic, and segmental T1 values. Myocardial segments with perfusion deficits were identified visually from DCE series. STATISTICAL TESTS: The relationships between MBF parameters derived by different methods were analyzed by Bland-Altman analysis; corresponding mean values were compared by t-test. RESULTS: Using subject-specific diastolic T1 values, global diastolic MBF was 0.61 ± 0.13 mL/(min·g). It did not differ from global MBF derived from the study population-averaged T1 (P = 0.88), but the standard deviation of differences was large (0.07 mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ (P = 0.12), whereas global diastolic MBF using systolic (0.62 ± 0.13 mL/(min·g)) and diastolic T1 values differed (P < 0.05). If regional instead of global T1 values were used, segmental MBF was lower in segments with perfusion deficits (bias = -0.03 mL/(min·g), -7% of mean MBF, P < 0.05) but higher in segments without perfusion deficits (bias = 0.01 mL/(min·g), 1% of mean MBF, P < 0.05). DATA CONCLUSION: Whereas cardiac phase-specific T1 values have a minor impact on MBF estimates, subject-specific and myocardial segment-specific T1 values substantially affect MBF quantification. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

Robust single-shot acquisition of high resolution whole brain ASL images by combining time-dependent 2D CAPIRINHA sampling with spatio-temporal TGV reconstruction.

For ASL perfusion imaging in clinical settings the current guidelines recommends pseudo-continuous arterial spin labeling with segmented 3D readout. This combination achieves the best signal to noise ratio with reasonable resolution but is prone to motion artifacts due to the segmented readout. Motion robust single-shot 3D acquisitions suffer from image blurring due to the T2 decay of the sampled signals during the long readout. To tackle this problem, we propose an accelerated 3D-GRASE sequence with a time-dependent 2D-CAIPIRINHA sampling pattern. This has several advantages: First, the single-shot echo trains are shortened by the acceleration factor; Second, the temporal incoherence between measurements is increased; And third, the coil sensitivity maps can be estimated directly from the averaged k-space data. To obtain improved perfusion images from the undersampled time series, we developed a variational image reconstruction approach employing spatio-temporal total-generalized-variation (TGV) regularization. The proposed ASL-TGV method reduced the total acquisition time, improved the motion robustness of 3D ASL data, and the image quality of the cerebral blood flow (CBF) maps compared to those by a standard segmented approach. An evaluation was performed on 5 healthy subjects including intentional movement for 2 subjects. Single-shot whole brain CBF-maps with high resolution 3.1 × 3.1 × 3 mm and image quality can be acquired in 1min 46sec. Additionally high quality CBF- and arterial transit time (ATT) -maps from single-shot multi-post-labeling delay (PLD) data can be gained with the proposed method. This method may improve the robustness of 3D ASL in clinical settings, and may be applied for perfusion fMRI.

Assessment and correction of macroscopic field variations in 2D spoiled gradient-echo sequences.

PURPOSE: To model and correct the dephasing effects in the gradient-echo signal for arbitrary RF excitation pulses with large flip angles in the presence of macroscopic field variations. METHODS: The dephasing of the spoiled 2D gradient-echo signal was modeled using a numerical solution of the Bloch equations to calculate the magnitude and phase of the transverse magnetization across the slice profile. Additionally, regional variations of the transmit RF field and slice profile scaling due to macroscopic field gradients were included. Simulations, phantom, and in vivo measurements at 3 T were conducted for R2∗ and myelin water fraction (MWF) mapping. RESULTS: The influence of macroscopic field gradients on R2∗ and myelin water fraction estimation can be substantially reduced by applying the proposed model. Moreover, it was shown that the dephasing over time for flip angles of 60° or greater also depends on the polarity of the slice-selection gradient because of phase variation along the slice profile. CONCLUSION: Substantial improvements in R2∗ accuracy and myelin water fraction mapping coverage can be achieved using the proposed model if higher flip angles are required. In this context, we demonstrated that the phase along the slice profile and the polarity of the slice-selection gradient are essential for proper modeling of the gradient-echo signal in the presence of macroscopic field variations.

Time optimal control-based RF pulse design under gradient imperfections.

PURPOSE: This study incorporates a gradient system imperfection model into an optimal control framework for radio frequency (RF) pulse design. THEORY AND METHODS: The joint design of minimum-time RF and slice selective gradient shapes is posed as an optimal control problem. Hardware limitations such as maximal amplitudes for RF and slice selective gradient or its slew rate are included as hard constraints to assure practical applicability of the optimized waveforms. In order to guarantee the performance of the optimized waveform with possible gradient system disturbances such as limited system bandwidth and eddy currents, a measured gradient impulse response function (GIRF) for a specific system is integrated into the optimization. RESULTS: The method generates optimized RF and pre-distorted slice selective gradient shapes for refocusing that are able to fully compensate the modeled imperfections of the gradient system under investigation. The results nearly regenerate the optimal results of an idealized gradient system. The numerical Bloch simulations are validated by phantom and in-vivo experiments on 2 3T scanners. CONCLUSIONS: The presented design approach demonstrates the successful correction of gradient system imperfections within an optimal control framework for RF pulse design.

Automated mitral valve vortex ring extraction from 4D-flow MRI.

PURPOSE: To present and validate a method for automated extraction and analysis of the temporal evolution of the mitral valve (MV) vortex ring from MR 4D-flow data. METHODS: The proposed algorithm uses the divergence-free part of the velocity vector field for Q criterion-based identification and tracking of MV vortex ring core and region within the left ventricle (LV). The 4D-flow data of 20 subjects (10 healthy controls, 10 patients with ischemic heart disease) were used to validate the algorithm against visual analysis as well as to assess the method's sensitivity to manual LV segmentation. Quantitative MV vortex ring parameters were analyzed with respect to both their differences between healthy subjects and patients and their correlation with transmitral peak velocities. RESULTS: The algorithm successfully extracted MV vortex rings throughout the entire cardiac cycle, which agreed substantially with visual analysis (Cohen's kappa = 0.77). Furthermore, vortex cores and regions were robustly detected even if a static end-diastolic LV segmentation mask was applied to all frames (Dice coefficients 0.82 ± 0.08 and 0.94 ± 0.02 for core and region, respectively). Early diastolic MV vortex ring vorticity, kinetic energy and circularity index differed significantly between healthy controls and patients. In contrast to vortex shape parameters, vorticity and kinetic energy correlated strongly with transmitral peak velocities. CONCLUSION: An automated method for temporal MV vortex ring extraction demonstrating robustness with respect to LV segmentation strategies is introduced. Quantitative vortex parameter analysis indicates importance of the MV vortex ring for LV diastolic (dys)function.

T2 and T2∗ mapping in ex situ porcine myocardium: myocardial intravariability, temporal stability and the effects of complete coronary occlusion.

Diagnosis of ischaemia-related sudden cardiac death in the absence of microscopic and macroscopic ischaemic lesions remains a challenge for medical examiners. Medical imaging techniques increasingly provide support in post-mortem examinations by detecting and documenting internal findings prior to autopsy. Previous studies have characterised MR relaxation times to investigate post-mortem signs of myocardial infarction in forensic cohorts. In this prospective study based on an ex situ porcine heart model, we report fundamental findings related to intramyocardial variability and temporal stability of T2 as well as the effects of permanent coronary occlusion on T2 and T2∗ relaxation in post-mortem myocardium. The ex situ porcine hearts included in this study (n= 19) were examined in two groups (Ss, n= 11 and Si, n= 8). All magnetic resonance imaging (MRI) examinations were performed ex situ, at room temperature and at 3 T. In the Ss group, T2 mapping was performed on slaughterhouse porcine hearts at different post-mortem intervals (PMI) between 7 and 26 h. Regarding the intramyocardial variability, no statistically significant differences in T2 were observed between myocardial segments (p= 0.167). Assessment of temporal stability indicated a weak negative correlation (r=- 0.21) between myocardial T2 and PMI. In the Si group, animals underwent ethanol-induced complete occlusion of the left anterior descending artery. T2 and T2∗ mapping were performed within 3 h of death. Differences between the expected ischaemic and remote regions were statistically significant for T2 (p= 0.007), however not for T2∗ (p= 0.062). Our results provide important information for future assessment of the diagnostic potential of quantitative MRI in the post-mortem detection of early acute myocardial infarction.

The four-minute approach revisited: accelerating MRI-based multi-factorial age estimation.

OBJECTIVES: This feasibility study aimed to investigate the reliability of multi-factorial age estimation based on MR data of the hand, wisdom teeth and the clavicles with reduced acquisition time. METHODS: The raw MR data of 34 volunteers-acquired on a 3T system and using acquisition times (TA) of 3:46 min (hand), 5:29 min (clavicles) and 10:46 min (teeth)-were retrospectively undersampled applying the commercially available CAIPIRINHA technique. Automatic and radiological age estimation methods were applied to the original image data as well as undersampled data to investigate the reliability of age estimates with decreasing acquisition time. Reliability was investigated determining standard deviation (SSD) and mean (MSD) of signed differences, intra-class correlation (ICC) and by performing Bland-Altman analysis. RESULTS: Automatic age estimation generally showed very high reliability (SSD < 0.90 years) even for very short acquisition times (SSD ≈ 0.20 years for a total TA of 4 min). Radiological age estimation provided highly reliable results for images of the hand (ICC ≥ 0.96) and the teeth (ICC ≥ 0.79) for short acquisition times (TA = 16 s for the hand, TA = 2:21 min for the teeth), imaging data of the clavicles allowed for moderate acceleration (TA = 1:25 min, ICC ≥ 0.71). CONCLUSIONS: The results demonstrate that reliable multi-factorial age estimation based on MRI of the hand, wisdom teeth and the clavicles can be performed using images acquired with a total acquisition time of 4 min.

Magnetic resonance elastography of the human brain using a multiphase DENSE acquisition.

PURPOSE: In magnetic resonance elastography (MRE), a series of time-shifted images is acquired at specific phase offsets in relation to an induced mechanical excitation. To efficiently gather the set of phase offset images and to overcome limitations due to prolonged TEs and related susceptibility artifacts at low-frequency MRE, we developed an improved displacement encoding with a stimulated echoes (DENSE) method. METHODS: The proposed multiphase DENSE-MRE acquisition scheme allows full sampling of the wave propagation in 1 encoding direction during each TR using multiple readouts at specific phase offsets. With this approach, all phase offsets can be imaged in 1 TR without the need for whole sequence repetitions at time-shifted offsets relative to the excitation motion. We tested this technique in phantom experiments with 60 Hz and in the brain of 4 volunteers using 20-Hz harmonic excitation. RESULTS: Three-dimensional wave propagation could be acquired in 7 minutes 30 seconds. Following background phase elimination, clear wave images were obtained, showing the propagation of the waves over time. Calculated shear modulus maps of the phantom matched well to the maps obtained by conventional gradient-echo MRE. In the brain, low-frequency DENSE-MRE images were free of susceptibility-induced artifacts and the calculated maps showed a median global complex shear modulus magnitude of 0.72 kPa and phase angle of 1.03 rad across volunteers. CONCLUSION: The proposed multiphase DENSE approach allows efficient low-frequency MRE with short TEs and is well-suited for low-frequency MRE of the human brain.

Ultrafast 3D Bloch-Siegert B 1 + -mapping using variational modeling.

PURPOSE: Highly accelerated B 1 + -mapping based on the Bloch-Siegert shift to allow 3D acquisitions even within a brief period of a single breath-hold. THEORY AND METHODS: The B 1 + dependent Bloch-Siegert phase shift is measured within a highly subsampled 3D-volume and reconstructed using a two-step variational approach, exploiting the different spatial distribution of morphology and B 1 + -field. By appropriate variable substitution the basic non-convex optimization problem is transformed in a sequential solution of two convex optimization problems with a total generalized variation (TGV) regularization for the morphology part and a smoothness constraint for the B 1 + -field. The method is evaluated on 3D in vivo data with retro- and prospective subsampling. The reconstructed B 1 + -maps are compared to a zero-padded low resolution reconstruction and a fully sampled reference. RESULTS: The reconstructed B 1 + -field maps are in high accordance to the reference for all measurements with a mean error below 1% and a maximum of about 4% for acceleration factors up to 100. The minimal error for different sampling patterns was achieved by sampling a dense region in k-space center with acquisition times of around 10-12 s for 3D-acquistions. CONCLUSIONS: The proposed variational approach enables highly accelerated 3D acquisitions of Bloch-Siegert data and thus full liver coverage in a single breath hold.

Rapid T1 quantification from high resolution 3D data with model-based reconstruction.

PURPOSE: Magnetic resonance imaging protocols for the assessment of quantitative information suffer from long acquisition times since multiple measurements in a parametric dimension are required. To facilitate the clinical applicability, accelerating the acquisition is of high importance. To this end, we propose a model-based optimization framework in conjunction with undersampling 3D radial stack-of-stars data. THEORY AND METHODS: High resolution 3D T1 maps are generated from subsampled data by employing model-based reconstruction combined with a regularization functional, coupling information from the spatial and parametric dimension, to exploit redundancies in the acquired parameter encodings and across parameter maps. To cope with the resulting non-linear, non-differentiable optimization problem, we propose a solution strategy based on the iteratively regularized Gauss-Newton method. The importance of 3D-spectral regularization is demonstrated by a comparison to 2D-spectral regularized results. The algorithm is validated for the variable flip angle (VFA) and inversion recovery Look-Locker (IRLL) method on numerical simulated data, MRI phantoms, and in vivo data. RESULTS: Evaluation of the proposed method using numerical simulations and phantom scans shows excellent quantitative agreement and image quality. T1 maps from accelerated 3D in vivo measurements, e.g. 1.8 s/slice with the VFA method, are in high accordance with fully sampled reference reconstructions. CONCLUSIONS: The proposed algorithm is able to recover T1 maps with an isotropic resolution of 1 mm3 from highly undersampled radial data by exploiting structural similarities in the imaging volume and across parameter maps.