Correction of gradient-induced phase errors in radial MRI

Radial compressed sensing imaging improves the velocity detection limit of single cell tracking time-lapse MRI

PURPOSE

Time-lapse MRI enables tracking of single iron-labeled cells. Yet, due to temporal blurring, only slowly moving cells can be resolved. To study faster cells for example during inflammatory processes, accelerated acquisition is needed.

METHODS

A rotating phantom system was developed to quantitatively measure the current maximum detectable speed of cells in time-lapse MRI. For accelerated cell tracking, an interleaved radial acquisition scheme was applied to phantom and murine brain in vivo time-lapse MRI experiments at 9.4 T. Detection of iron-labeled cells was evaluated in fully sampled and undersampled reconstructions with and without compressed sensing.

RESULTS

The rotating phantom system enabled ultra-slow rotation of phantoms and a velocity detection limit of full-brain Cartesian time-lapse MRI of up to 172 μm/min was determined. Both phantom and in vivo measurements showed that single cells can be followed dynamically using radial time-lapse MRI. Higher temporal resolution of undersampled reconstructions reduced geometric distortion, the velocity detection limit was increased to 1.1 mm/min in vitro, and previously hidden fast-moving cells were recovered. In the mouse brain after in vivo labeling, a total of 42 ± 4 cells were counted in fully sampled, but only 7 ± 1 in undersampled images due to streaking artifacts. Using compressed sensing 33 ± 4 cells were detected.

CONCLUSION

Interleaved radial time-lapse MRI permits retrospective reconstruction of both fully sampled and accelerated images, enables single cell tracking at higher temporal resolution and recovers cells hidden before due to blurring. The velocity detection limit as determined with the rotating phantom system increased two- to three-fold compared to previous results.

Self-gated cine phase-contrast balanced SSFP flow quantification at 0.55 T

PURPOSE

To implement cine phase-contrast balanced SSFP (PC-bSSFP) for low-field 0.55T cardiac MRI by exploiting the intrinsic flow sensitivity of the bSSFP slice-select gradient and the in-plane phase-cancelation properties of radial trajectories, enabling self-gated and referenceless PC-bSSFP flow quantification at 0.55 T.

METHODS

A free-running, tiny golden-angle radial PC-bSSFP approach was implemented on 0.55T and 1.5T systems. Cardiac and respiratory self-gating was incorporated to enable electrocardiogram-free scanning during breath-hold and free-breathing. By exploiting the intrinsic in-plane phase-cancelation properties of radial acquisitions and background phase fitting, referenceless single-point PC-bSSFP was realized. In vivo data were acquired in the ascending aorta of healthy subjects at 0.55 T and 1.5 T during breath-hold and free-breathing. Flow data, SNR, and velocity-to-noise ratio were compared relative to data obtained with phase-contrast spoiled gradient-echo variants.

RESULTS

Velocities acquired with PC-bSSFP compared well with data from phase-contrast spoiled gradient-echo (RMSEv  = 5.8 cm/s). PC-bSSFP at 0.55 T resulted in high-quality cine magnitude images and phase maps with sufficient SNR and velocity-to-noise ratio. Breath-hold and free-breathing PC-bSSFP performed very similarly, with comparable flow quantification (RMSEv  = 5.7 cm/s). Referenceless single-point PC-bSSFP results agreed well with two-point PC-bSSFP (-1.8 ± 5.2 cm/s) while reducing scan times 2-fold.

CONCLUSION

PC-bSSFP is feasible on low-field 0.55T systems, producing high-quality cine images while permitting simultaneous aortic flow measurements during breath-hold and free-breathing and without the need for electrocardiogram gating.

Joint radial trajectory correction for accelerated T2 * mapping on an MR-Linac

BACKGROUND

T2 * mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T2 * maps during MR-guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub-volumes.

PURPOSE

The purpose of this work is to demonstrate the feasibility of the accelerated T2 * mapping technique using model-based image reconstruction with integrated trajectory auto-correction (TrACR) for MR-guided radiotherapy on an MR-Linear accelerator (MR-Linac).

MATERIALS AND METHODS

The proposed method was validated in a numerical phantom, where two T2 * mapping approaches (sequential and joint) were compared for different noise levels (0,0.1,0.5,1) and gradient delays ([1, -1] and [1, -2] in units of dwell time for x- and y-axis, respectively). Fully sampled k-space was retrospectively undersampled using two different undersampling patterns. Root mean square errors (RMSEs) were calculated between reconstructed T2 * maps and ground truth. In vivo data was acquired twice weekly in one prostate and one head and neck cancer patient undergoing treatment on a 1.5 T MR-Linac. Data were retrospectively undersampled and T2 * maps reconstructed, with and without trajectory corrections were compared.

RESULTS

Numerical simulations demonstrated that, for all noise levels, T2 * maps reconstructed with a joint approach demonstrated less error compared to an uncorrected and sequential approach. For a noise level of 0.1, uniform undersampling and gradient delay [1, -1] (in units of dwell time for x- and y-axis, respectively), RMSEs for sequential and joint approaches were 13.01 and 9.32 ms, respectively, which reduced to 10.92 and 5.89 ms for a gradient delay of [1, 2]. Similarly, for alternate undersampling and gradient delay [1, -1], RMSEs for sequential and joint approaches were 9.80 and 8.90 ms, respectively, which reduced to 9.10 and 5.40 ms for gradient delay [1, 2]. For in vivo data, T2 * maps reconstructed with our proposed approach resulted in less artifacts and improved visual appearance compared to the uncorrected approach. For both prostate and head and neck cancer patients, T2 * maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV).

CONCLUSION

Using the proposed approach, a retrospective data-driven gradient delay correction can be performed, which is particularly relevant for hybrid devices, where full information on the machine configuration is not available for image reconstruction. T2 * maps were acquired in under 5 min and can be integrated into MR-guided radiotherapy treatment workflows, which minimizes patient burden and leaves time for additional imaging for online adaptive radiotherapy on an MR-Linac.

GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging

The purpose of the current study was to develop a deep learning technique called Golden-angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast-enhanced 4D MRI acquired with golden-angle radial k-space trajectories. GRASPnet operates in the image-time space and does not use explicit data consistency to minimize the reconstruction time. Three different network architectures were developed: (1) GRASPnet-2D: 2D convolutional kernels (x,y) and coil and contrast dimensions collapsed into a single combined dimension; (2) GRASPnet-3D: 3D kernels (x,y,t); and (3) GRASPnet-2D + time: two 3D kernels to first exploit spatial correlations (x,y,1) followed by temporal correlations (1,1,t). The networks were trained using iterative GRASP reconstruction as the reference. Free-breathing 3D abdominal imaging with contrast injection was performed on 33 patients with liver lesions using a T1-weighted golden-angle stack-of-stars pulse sequence. Ten datasets were used for testing. The three GRASPnet architectures were compared with iterative GRASP results using quantitative and qualitative analysis, including impressions from two body radiologists. The three GRASPnet techniques reduced the reconstruction time to about 13 s with similar results with respect to iterative GRASP. Among the GRASPnet techniques, GRASPnet-2D + time compared favorably in the quantitative analysis. Spatiotemporal deep learning enables reconstruction of dynamic 4D contrast-enhanced images in a few seconds, which would facilitate translation to clinical practice of compressed sensing methods that are currently limited by long reconstruction times.

MR image reconstruction from undersampled data for image-guided radiation therapy using a patient-specific deep manifold image prior

Introduction

Recent advancements in radiotherapy (RT) have allowed for the integration of a Magnetic Resonance (MR) imaging scanner with a medical linear accelerator to use MR images for image guidance to position tumors against the treatment beam. Undersampling in MR acquisition is desired to accelerate the imaging process, but unavoidably deteriorates the reconstructed image quality. In RT, a high-quality MR image of a patient is available for treatment planning. In light of this unique clinical scenario, we proposed to exploit the patient-specific image prior to facilitate high-quality MR image reconstruction.

Methods

Utilizing the planning MR image, we established a deep auto-encoder to form a manifold of image patches of the patient. The trained manifold was then incorporated as a regularization to restore MR images of the same patient from undersampled data. We performed a simulation study using a patient case, a real patient study with three liver cancer patient cases, and a phantom experimental study using data acquired on an in-house small animal MR scanner. We compared the performance of the proposed method with those of the Fourier transform method, a tight-frame based Compressive Sensing method, and a deep learning method with a patient-generic manifold as the image prior.

Results

In the simulation study with 12.5% radial undersampling and 15% increase in noise, our method improved peak-signal-to-noise ratio by 4.46dB and structural similarity index measure by 28% compared to the patient-generic manifold method. In the experimental study, our method outperformed others by producing reconstructions of visually improved image quality.

CSR-PERT: Joint framework for MRI and HARDI data reconstruction using perturbed radial trajectory estimated from compressively sensed measurements

Radial sampling pattern is an important signal acquisition strategy in magnetic resonance imaging (MRI) owing to better immunity to motion-induced artifacts and less pronounced aliasing due to undersampling compared to the Cartesian sampling. These advantages of radial sampling can be exploited in acquisition of multidimensional signals such as High Angular Resolution Diffusion Imaging (HARDI), with tremendous scope of acceleration. Despite such benefits, gradient delays lead to samples being acquired from unknown miscentered radial trajectories, severely degrading the image reconstruction quality. In the present work, we propose Csr-Pert that is a joint framework, wherein these perturbed radial trajectories are estimated and utilized for image reconstruction from the compressively sensed measurements of (i) MRI data and (ii) HARDI data. The proposed Csr-Pert method is tested on one real MRI dataset with trajectory deviations and is observed to perform better than the existing state-of-the-art method at high acceleration factors up to 8. To the best of our knowledge, this is the first work to address the problem of estimating perturbed trajectories using the compressively sensed MRI and HARDI data. The method is also tested for varying combinations of trajectory deviations and sampling proportions. It is observed to yield very good quality HARDI reconstruction for a wide variety of scenarios. We have also demonstrated the robustness of the proposed method on real datasets in clinical settings assuming perturbed as well as noisy trajectories.

Real-time B0 compensation during gantry rotation in a 0.35 T MRI-Linac

BACKGROUND

Rotation of the ferromagnetic gantry of a low magnetic field MRI-Linac was previously demonstrated to cause large center frequency offsets of ±400 Hz. The B₀ off-resonances cause image artifacts and imaging isocenter shifts that would preclude MRI-guided arc therapy.

PURPOSE

The purpose of this study was to measure and compensate for center frequency offsets in real-time during gantry rotation on a 0.35 T MRI-Linac using a free induction decay (FID) navigator.

METHODS

A nonselective FID navigator was added before each 2D balanced steady-state free precession (bSSFP) cine image acquisition on a 0.35 T MRI-Linac. Images were acquired at 7.3 frames per second. Phase data from the initial FID navigator (while the gantry was stationary) was used as a reference. The phase data from each subsequent FID navigator was used to calculate the real-time B₀ off-resonance. The transmitter/receiver phase and the phase accrual over the adjacent image acquisition were adjusted to correct for the center frequency offset. Measurements were performed using a MRI-Linac dynamic phantom prior to and while the gantry rotated clockwise and counterclockwise. Image quality and signal-to-noise ratio were compared between uncorrected and B₀ corrected MRIs using a reference image acquired while the gantry was stationary. Four targets in the phantom were manually contoured on the first image frame and an active contouring algorithm was used retrospectively on each subsequent frame to assess image variations and calculate Dice coefficients. Additionally, three healthy volunteers were imaged using the same pulse sequences with and without real-time B₀ compensation during gantry rotation. Normalized root mean square errors (nRMSEs) were calculated for the phantom and in vivo to assess the efficacy of the B₀ compensation on image quality. The measured center frequency offsets from the volunteer and MRI dynamic phantom navigator data were also compared. The sinusoidal behavior of the center frequency offsets was modeled based on the gantry layout and long time constant eddy currents resulting from gantry rotation.

RESULTS

The duration of the FID navigator and processing was 4.5 ms. The FID navigator resulted in a ≤11% drop in signal-to-noise ratio (SNR) in the phantom and in vivo (liver). Dice coefficients from the MR-IGRT phantom contour measurements remained above 0.8 with B₀ compensation. Without B₀ compensation, the Dice coefficients dropped below 0.8 for up to 21% of the time depending on the contour. Real-time B₀ compensation resulted in mean reductions in nRMSE of 51% and 16% for the MR-IGRT phantom and in vivo, respectively. Peak-to-peak center frequency offsets ranged from 757 to 773 Hz in the phantom and 670 to 871 Hz in vivo.

CONCLUSION

Dynamic real-time B₀ compensation significantly improved image quality and reduced artifacts during gantry rotation in the phantom and in vivo. However, the FID navigator resulted in a small drop in the imaging duty cycle and SNR. This article is protected by copyright. All rights reserved.

MRI evaluation of cerebral metabolic rate of oxygen (CMRO2) in obstructive sleep apnea

Patients with obstructive sleep apnea (OSA) are at elevated risk of developing systemic vascular disease and cognitive dysfunction. Here, cerebral oxygen metabolism was assessed in patients with OSA by means of a magnetic resonance-based method involving simultaneous measurements of cerebral blood flow rate and venous oxygen saturation in the superior sagittal sinus for a period of 10 minutes at an effective temporal resolution of 1.3 seconds before, during, and after repeated 24-second breath-holds mimicking spontaneous apneas, yielding, along with pulse oximetry-derived arterial saturation, whole-brain CMRO2 via Fick's Principle. Enrolled subjects were classified based on their apnea-hypopnea indices into OSA (N = 31) and non-sleep apnea reference subjects (NSA = 21), and further compared with young healthy subjects (YH, N = 10). OSA and NSA subjects were matched for age and body mass index. CMRO2 was lower in OSA than in the YH group during normal breathing (105.6 ± 14.1 versus 123.7 ± 22.8 μmol O2/min/100g, P = 0.01). Further, the fractional change in CMRO2 in response to a breath-hold challenge was larger in OSA than in the YH group (15.2 ± 9.2 versus 8.5 ± 3.4%, P = 0.04). However, there was no significant difference in CMRO2 between OSA and NSA subjects. The data suggest altered brain oxygen metabolism in OSA and possibly in NSA as well.

Real-time radial tagging for quantification of left ventricular torsion

PURPOSE

To develop a real-time radial tagging MRI for accurate measurement of rotational motion and twist of the left ventricle (LV).

METHODS

A FLASH-based radial tagging sequence with an undersampled radial reading scheme was developed for both single and double-slice imaging in real-time. The Polar Fourier Transform was used for reconstruction to push the undersampling artifacts out of a reduced FOV. The developed technique was used to image five normal subjects during rest, plus one during both exercise and rest conditions. LV rotational motions were estimated for five consecutive cardiac cycles in all cases. The process was validated using a numerical phantom. The real-time measurement of global rotational motion was compared with those measured from a non-real-time exam using linear regression analysis and the Bland-Altman plot.

RESULTS

The real-time acquisition was performed successfully with a temporal resolution of 46.2 ms. Image quality was sufficient for the reproducible calculation of rotation at rest and exercise. The feasibility of double-slice acquisition on human was further studied and a real-time twist of the left ventricle was demonstrated. The difference between LV global rotations from real-time and non-real-time approaches was 0.27 degrees. A significant reverse recoiling, induced by exercise, was reproducibly measured by the technique.

CONCLUSION

A real-time radial tagging MRI technique was developed based on the undersampled radial acquisition and Polar Fourier Transform reconstruction, for accurate measuring of the heart rotational motion and twist. The technique was able to extract a meaningful change of diastolic recoiling under stress test conditions during physical activities (cycling).

Technical Note: Effects of rotating gantry on magnetic field and eddy currents in 0.35 T MRI-guided radiotherapy (MR-IGRT) system

PURPOSE

The purpose of this study was to identify the cause of severe image artifacts that occurred during gantry rotation in a 0.35 T MRI-Linac by comparing measurements of eddy currents, center frequency, and field inhomogeneities made with the gantry in motion and stationary.

METHODS

Gradient and B₀ eddy currents were calculated from the free induction decays (FIDs) resulting from selective excitation at a temporal resolution of 200 ms/measurement. B₀ eddy currents were also calculated from FIDs acquired with nonselective excitation at a temporal resolution of 100 ms/measurement. Center frequencies and B₀ inhomogeneities were measured by acquiring FIDs with a repetition time (TR) of 290 ms. Cartesian and radial 2D true fast imaging with steady-state precession (TrueFISP) pulse sequences used in real-time MRI-guided radiation therapy (MR-IGRT) were acquired. To assess artifact severity, the normalized root mean square error (nRMSE) was calculated between a reference MRI (static gantry) and MRIs acquired during gantry rotation for each serial acquisition. Image artifacts were qualitatively graded as nominal, minor, or severe. Measurements were conducted while the gantry was rotated through its entire range for both clockwise and counterclockwise. Measurements during gantry rotation were compared to measurements with a stationary gantry (every 30°).

RESULTS

Severe image artifacts were observed 22-35% of the time while the gantry was rotating. Short time constant eddy currents were not affected by gantry rotation. The peak to peak center frequency and FWHM rose by factors of 13.2-14.5 and 1.1-1.6, respectively, for the rotating versus stationary gantry. The magnitude of the center frequency offset and field inhomogeneities depended on the direction of the gantry rotation.

CONCLUSIONS

Image artifacts during gantry rotation were primarily caused by center frequency variations and field inhomogeneities. Therefore, dynamic B₀ compensation techniques should be able to reduce artifacts during gantry rotation.

Efficient gradient waveform measurements with variable-prephasing

Accurate measurement of gradient waveform errors can often improve image quality in sequences with time varying readout and excitation waveforms. Self-encoding or offset-slice sequences are commonly used to measure gradient waveforms. However, the self-encoding method requires a long scan time, while the offset-slice method is often low precision, requiring the thickness of the excited slice to be small compared to the maximal k-space encoded by the test waveform. This work introduces a hybrid these methods, called variable-prephasing. Using a straightforward algebraic model, we demonstrate that variable-prephasing improves the precision of the waveform measurement by allowing acquisition of larger slice thicknesses. Experiments in a phantom were used to validate the theoretical predictions, showing that the precision of variable-prephasing gradient waveform measurements improves with increasing slice thickness.

Preclinical MRI to Quantify Pulmonary Disease Severity and Trajectories in Poorly Characterized Mouse Models: A Pedagogical Example Using Data from Novel Transgenic Models of Lung Fibrosis

Structural remodeling in lung disease is progressive and heterogeneous, making temporally and spatially explicit information necessary to understand disease initiation and progression. While mouse models are essential to elucidate mechanistic pathways underlying disease, the experimental tools commonly available to quantify lung disease burden are typically invasive (e.g., histology). This necessitates large cross-sectional studies with terminal endpoints, which increases experimental complexity and expense. Alternatively, magnetic resonance imaging (MRI) provides information noninvasively, thus permitting robust, repeated-measures statistics. Although lung MRI is challenging due to low tissue density and rapid apparent transverse relaxation (T₂* <1 ms), various imaging methods have been proposed to quantify disease burden. However, there are no widely accepted strategies for preclinical lung MRI. As such, it can be difficult for researchers who lack lung imaging expertise to design experimental protocols-particularly for novel mouse models. Here, we build upon prior work from several research groups to describe a widely applicable acquisition and analysis pipeline that can be implemented without prior preclinical pulmonary MRI experience. Our approach utilizes 3D radial ultrashort echo time (UTE) MRI with retrospective gating and lung segmentation is facilitated with a deep-learning algorithm. This pipeline was deployed to assess disease dynamics over 255 days in novel, transgenic mouse models of lung fibrosis based on disease-associated, loss-of-function mutations in Surfactant Protein-C. Previously identified imaging biomarkers (tidal volume, signal coefficient of variation, etc.) were calculated semi-automatically from these data, with an objectively-defined high signal volume identified as the most robust metric. Beyond quantifying disease dynamics, we discuss common pitfalls encountered in preclinical lung MRI and present systematic approaches to identify and mitigate these challenges. While the experimental results and specific pedagogical examples are confined to lung fibrosis, the tools and approaches presented should be broadly useful to quantify structural lung disease in a wide range of mouse models.

Effects of B0 eddy currents on imaging isocenter shifts in 0.35-T MRI-guided radiotherapy (MR-IGRT) system

PURPOSE

The purpose of this study was to measure gantry angle-related eddy currents in a 0.35-T MRI-Linac and determine if B₀ (zeroth order) eddy currents are the primary cause of gantry angle-dependent imaging isocenter shifts vs other potential causes like B₀ inhomogeneities and gradient (first order) eddy currents. For conventional Cartesian acquisitions, B₀ eddy currents can cause imaging isocenter shifts along both phase encode and readout directions. Gradient eddy currents can cause spatial distortion along both the phase encode and readout directions. Center frequency offsets can cause imaging isocenter shifts along the readout direction that vary with readout gradient polarity.

METHODS

MRI-related eddy currents and imaging isocenter shifts were measured on a 0.35-T MRI-Linac at gantry angles from 0° to 330° in increments of 30^° . All measurements were made after gradient shimming and center frequency tuning at each planned gantry angle. Eddy current and field homogeneity measurements were conducted using a 24-cm diameter spherical phantom. Gradient and B₀ eddy currents were calculated from the free induction decays (FIDs) resulting from selective excitation of slices located ±5 cm from isocenter. B₀ eddy currents were also calculated from FIDs acquired with nonselective excitation and compared with B₀ eddy current values derived using selective excitation. B₀ inhomogeneities and center frequency offsets were measured by acquiring FIDs with nonselective excitation. Imaging isocenter shifts were measured using a 33x33x10.5 cm³ uniformity linearity (grid) phantom and a 3D true fast imaging with steady-state precession (TrueFISP) sequence used in MRI-guided radiation therapy. Eddy currents were compared to vendor specifications and correlated with the imaging isocenter shifts. Measurements were conducted before and after the MRI-Linac's waveguide was replaced with an updated design to reduce eddy currents.

RESULTS

B₀ eddy currents were highly correlated (r = 0.986, P << 0.001) for measurements made with vs without selective excitation. Transverse (X and Y) axis B₀ eddy currents before and after the waveguide upgrade were out of specification (specification: ≤0.1 μT m/mT for delays < 10 ms) for most of the measured gantry angles. Gradient eddy currents before and after the upgrade were within specifications for the measured gantry angles (≤0.1% for delays < 10 ms). B₀ eddy currents and imaging isocenter shifts were highly correlated (r = 0.965, P << 0.001). After the Linac waveguide upgrade, root mean square (RMS) peak B₀ and gradient eddy currents dropped 45% and 11%, respectively, for delays <10 ms, while imaging isocenter shifts dropped 53%. Isocenter shifts were observed in both phase encode and readout directions. Center frequency offsets were <26 Hz while B₀ inhomogeneities were <33 Hz full width at half maximum (FWHM).

CONCLUSIONS

Imaging isocenter shifts measured in a 0.35-T MRI-Linac were highly correlated with B₀ eddy currents. The eddy currents and imaging isocenter shifts decreased after the MRI-Linac's waveguide was replaced.

Cerebral metabolic rate of oxygen during transition from wakefulness to sleep measured with high temporal resolution OxFlow MRI with concurrent EEG

During slow-wave sleep, synaptic transmissions are reduced with a concomitant reduction in brain energy consumption. We used 3 Tesla MRI to noninvasively quantify changes in the cerebral metabolic rate of O2 (CMRO2) during wakefulness and sleep, leveraging the 'OxFlow' method, which provides venous O2 saturation (SvO2) along with cerebral blood flow (CBF). Twelve healthy subjects (31.3 ± 5.6 years, eight males) underwent 45-60 min of continuous scanning during wakefulness and sleep, yielding one image set every 3.4 s. Concurrent electroencephalography (EEG) data were available in eight subjects. Mean values of the metabolic parameters measured during wakefulness were stable, with coefficients of variation below 7% (average values: CMRO2 = 118 ± 12 µmol O2/min/100 g, SvO2 = 67.0 ± 3.7% HbO2, CBF = 50.6 ±4.3 ml/min/100 g). During sleep, on average, CMRO2 decreased 21% (range: 14%-32%; average nadir = 98 ± 16 µmol O2/min/100 g), while EEG slow-wave activity, expressed in terms of δ -power, increased commensurately. Following sleep onset, CMRO2 was found to correlate negatively with relative δ -power (r = -0.6 to -0.8, P < 0.005), and positively with heart rate (r = 0.5 to 0.8, P < 0.0005). The data demonstrate that OxFlow MRI can noninvasively measure dynamic changes in cerebral metabolism associated with sleep, which should open new opportunities to study sleep physiology in health and disease.

Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T

Magnetic resonance fingerprinting (MRF) is highly promising as a quantitative MRI technique due to its accuracy, robustness, and efficiency. Previous studies have found high repeatability and reproducibility of 2D MRF acquisitions in the brain. Here, we have extended our investigations to 3D MRF acquisitions covering the whole brain using spiral projection k-space trajectories. Our travelling head study acquired test/retest data from the brains of 12 healthy volunteers and 8 MRI systems (3 systems at 3 T and 5 at 1.5 T, all from a single vendor), using a study design not requiring all subjects to be scanned at all sites. The pulse sequence and reconstruction algorithm were the same for all acquisitions. After registration of the MRF-derived PD T1 and T2 maps to an anatomical atlas, coefficients of variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site. Our analysis demonstrated a high repeatability (CVs 0.7-1.3% for T1, 2.0-7.8% for T2, 1.4-2.5% for normalized PD) and reproducibility (CVs of 2.0-5.8% for T1, 7.4-10.2% for T2, 5.2-9.2% for normalized PD) in gray and white matter. Both repeatability and reproducibility improved when compared to similar experiments using 2D acquisitions. Three-dimensional MRF obtains highly repeatable and reproducible estimations of T1 and T2, supporting the translation of MRF-based fast quantitative imaging into clinical applications.

Simple compensation method for improved half-pulse excitation profile with rephasing gradient

PURPOSE

To improve the slice profile quality obtained by RF half-pulse excitation for 2D-UTE applications.

METHODS

The overall first-order and zero-order phase errors along the slice-selection direction were obtained with the help of an optimization task to minimize the out-of-slice signal contamination from the calibration 1-dimenisonal (1D) profile data. The time-phase-error evolution was approximated from the k-space readout data, which were acquired primarily for correction of the readout trajectories during data regridding to the rectilinear grids. The correction of the slice profile was achieved by rephasing gradient pulses applied immediately after the end of excitation. The total prescan calibration typically took less than 2 minutes.

RESULTS

The improved image quality using the proposed calibration method was demonstrated both on phantoms and on ankle images obtained from healthy volunteers. It was demonstrated that calibration can be performed either as a separate water phantom measurement or directly as a prescan procedure.

CONCLUSION

The slice-profile distortion from the half-pulse excitation could substantially affect the overall fidelity of 2D-UTE images. The presented experiments proved that the image quality could be substantially increased by application of the proposed slice-correction method.

The noise navigator: a surrogate for respiratory-correlated 4D-MRI for motion characterization in radiotherapy

Respiratory-correlated 4D-MRI can characterize respiratory-induced motion of tumors and organs-at-risk for radiotherapy treatment planning and is a necessity for image guidance of moving tumors treated on an MRI-linac. Essential for 4D-MRI generation is a robust respiratory surrogate signal. We investigated the feasibility of the noise navigator as respiratory surrogate signal for 4D-MRI generation. The noise navigator is based on the respiratory-induced modulation of the thermal noise variance measured by the receive coils during MR acquisition and thus is inherently present and synchronized with MRI data acquisition. Additionally, the noise navigator can be combined with any rectilinear readout strategy (e.g. radial and cartesian) and is independent of MR image contrast and imaging orientation. For radiotherapy applications, the noise navigator provides a robust respiratory signal for patients scanned with an elevated coil setup. This is particularly attractive for widely used cartesian sequences where currently a non-interfering self-navigation means is lacking for MRI-based simulation and MRI-guided radiotherapy. The feasibility of 4D-MRI generation with the noise navigator as respiratory surrogate signal was demonstrated for both cartesian and radial readout strategies in radiotherapy setup on four healthy volunteers and two radiotherapy patients on a dedicated 1.5 T MRI scanner and two radiotherapy patients on a 1.5 T MRI-linac system. Moreover, the respiratory-correlated 4D-MR images showed liver motion comparable to a reference 2D cine MRI series for the volunteers. For 2D cartesian cine MRI acquisitions, both the noise navigator and respiratory bellows were benchmarked against an image navigator. Respiratory phase detection based on the noise navigator agreed 1.4 times better with the image navigator than the respiratory bellows did. For a 3D Stack-of-Stars acquisitions, the noise navigator was compared to radial self-navigation and a 1.7 times higher respiratory phase detection agreement was observed than for the respiratory bellows compared to radial self-navigation.

ENLIVE: An Efficient Nonlinear Method for Calibrationless and Robust Parallel Imaging

Robustness against data inconsistencies, imaging artifacts and acquisition speed are crucial factors limiting the possible range of applications for magnetic resonance imaging (MRI). Therefore, we report a novel calibrationless parallel imaging technique which simultaneously estimates coil profiles and image content in a relaxed forward model. Our method is robust against a wide class of data inconsistencies, minimizes imaging artifacts and is comparably fast, combining important advantages of many conceptually different state-of-the-art parallel imaging approaches. Depending on the experimental setting, data can be undersampled well below the Nyquist limit. Here, even high acceleration factors yield excellent imaging results while being robust to noise and the occurrence of phase singularities in the image domain, as we show on different data. Moreover, our method successfully reconstructs acquisitions with insufficient field-of-view. We further compare our approach to ESPIRiT and SAKE using spin-echo and gradient echo MRI data from the human head and knee. In addition, we show its applicability to non-Cartesian imaging on radial FLASH cardiac MRI data. Using theoretical considerations, we show that ENLIVE can be related to a low-rank formulation of blind multi-channel deconvolution, explaining why it inherently promotes low-rank solutions.

Multiresolution radial MRI to reduce IDLE time in pre-beam imaging on an MR-Linac (MR-RIDDLE)

Online adaptive MR-guided radiation therapy improves treatment quality at the expense of considerable longer treatment time. The treatment lengthening partially originates from the preparatory (pre-beam) MR imaging required to encode all the information needed for contour propagation, contour adaptation and replanning. MRI requires several minutes of scan time before the encoded information is converted to usable images, which results in long idle times before the first clinical tasks are performed. In this study we propose a novel imaging sequence, called MR-RIDDLE, that reduces the idle time and therefore speeds-up the workflow in online MR-guided radiation therapy. MR-RIDDLE enables multiresolution image reconstruction to commence during data acquisition where low resolution images are available within one minute, after which the data collection continuous for subsequent high-resolution image updates. We demonstrate that the low resolution images can be used to accurately propagate contours from the pre-treatment scan. For abdominothoracic tumours MR-RIDDLE inherently captures a motion-blurred representation of the mid-position, which we were able to deblur using a combination of an internal motion surrogate and auto-adaptive soft-gating filters. Our results demonstrate that MR-RIDDLE provides a robust, flexible and time-efficient strategy for pre-beam imaging, even for cases with large respiratory movements or baseline shifts within the acquisition. We anticipate that this novel concept of parallelising the MR imaging and the clinical tasks has the potential to considerably speed-up and streamline the online MR-guided radiation therapy workflow.

Ultra-short echo time imaging with multiple echo refocusing for porous media T2 mapping

T₂ relaxation time measurement is a powerful tool to distinguish signal components in porous media. As T₂ weighting is generally achieved by spin-echo based methods, it is very challenging to capture very short T₂ relaxation time components, approximately 1 ms, with high resolution spatial encoding. It is especially challenging when T₂ relaxation times of the other signal components are not known a priori. We propose a method, combining ultrashort echo time (UTE) imaging with multiple spin echo refocusing, to generate a series of images with T₂ weighting. The T₂ decay curves for each image voxel were extracted, and multiple T₂ relaxation components were quantitatively evaluated. The method has been applied to a fast relaxation system, namely, moisture content in wood samples to differentiate cell wall (bound) water and cell cavity (lumen) water.

Imperfect magnetic field gradients in radial k-space encoding-Quantification, correction, and parameter dependency

PURPOSE

Sensitivity to imperfections of image-encoding gradient fields may significantly impair widespread use of radial MR data acquisition. Such imperfections can cause individual echo shifts for each spoke acquired in the k-space and may produce severe image artifacts. Therefore, fast and robust methods to quantify and correct for those echo shifts are required.

THEORY AND METHODS

Echo shifts can be induced by inhomogeneities of the static magnetic field (δn_B ) and by imbalances of the imaging gradients (δn_G ) mainly caused by eddy currents. However, mismatch between data acquisition and gradient switching may additionally play a role. From the position of the echo maxima of 2 opposing spokes, δn_G and δn_B can be determined and corrected by adapting the read-dephasing gradient accordantly. This approach was implemented on MR-systems of different field strengths, gradient systems, and vendors, and the dependencies of echo shift and acquisition parameters were analyzed. Data sets of phantoms and of mice under in vivo conditions were obtained using RF-spoiled 2D radial-FLASH.

RESULTS

The presented method allowed for echo-shift detection and correction of < 1 data point, significantly improving the image quality in vitro and in vivo. Moreover, the method separated the effect of imbalanced gradients from those of magnetic inhomogeneities. The observed echo shifts were MR system-specifically dependent on acquisition parameters such as gradient strengths and dwell time.

CONCLUSIONS

By acquiring 12 spokes for a certain set of acquisition parameters, the proposed method successfully corrects echo shift-related image artifacts independently of the MR system.

CAPTURE: Consistently Acquired Projections for Tuned and Robust Estimation: A Self-Navigated Respiratory Motion Correction Approach

OBJECTIVES

In this study, we present a fully automated and robust self-navigated approach to obtain 4-dimensional (4-D) motion-resolved images during free breathing.

MATERIALS AND METHODS

The proposed method, Consistently Acquired Projections for Tuned and Robust Estimation (CAPTURE), is a variant of the stack-of-stars gradient-echo sequence. A 1-D navigator was consistently acquired at a fixed azimuthal angle for all stacks of spokes to reduce nonphysiological signal contamination due to system imperfections. The resulting projections were then "tuned" using complex phase rotation to adapt to scan-to-scan variations, followed by the detection of the respiratory curve. Four-dimensional motion-corrected and uncorrected images were then reconstructed via respiratory and temporal binning, respectively.This Health Insurance Portability and Accountability Act-compliant study was performed with Institutional Review Board approval. A phantom experiment was performed using a custom-made deformable motion phantom with an adjustable frequency and amplitude. For in vivo experiments, 10 healthy participants and 12 liver tumor patients provided informed consent and were imaged with the CAPTURE sequence.Two radiologists, blinded to which images were motion-corrected and which were not, independently reviewed the images and scored the image quality using a 5-point Likert scale.

RESULTS

In the respiratory motion phantom experiment, CAPTURE reversed the effects of motion blurring and restored edge sharpness from 36% to 78% of that observed in the images from the static scan.Despite large intra- and intersubject variability in respiration patterns, CAPTURE successfully detected the respiratory motion signal in all participants and significantly improved the image quality according to the subjective radiological assessments of 2 raters (P < 0.05 for both raters) with a 1 to 2-point improvement in the median Likert scores across the whole set of participants. Small lesions (<1 cm in size) which might otherwise be missed on uncorrected images because of motion blurring were more clearly depicted on the CAPTURE images.

CONCLUSIONS

CAPTURE provides a robust and fully automated solution for obtaining 4-D motion-resolved images in a free-breathing setting. With its unique tuning feature, CAPTURE can adapt to large intersubject and interscan variations. CAPTURE also enables better lesion delineation because of improved image sharpness, thereby increasing the visibility of small lesions.

Accelerated 4D self-gated MRI of tibiofemoral kinematics

Anatomical (static) magnetic resonance imaging (MRI) is the most useful imaging technique for the evaluation and assessment of internal derangement of the knee, but does not provide dynamic information and does not allow the study of the interaction of the different tissues during motion. As knee pain is often only experienced during dynamic tasks, the ability to obtain four-dimensional (4D) images of the knee during motion could improve the diagnosis and provide a deeper understanding of the knee joint. In this work, we present a novel approach for dynamic, high-resolution, 4D imaging of the freely moving knee without the need for external triggering. The dominant knee of five healthy volunteers was scanned during a flexion/extension task. To evaluate the effects of non-uniform motion and poor coordination skills on the quality of the reconstructed images, we performed a comparison between fully free movement and movement instructed by a visual cue. The trigger signal for self-gating was extracted using principal component analysis (PCA), and the images were reconstructed using a parallel imaging and compressed sensing reconstruction pipeline. The reconstructed 4D movies were scored for image quality and used to derive bone kinematics through image registration. Using our method, we were able to obtain 4D high-resolution movies of the knee without the need for external triggering hardware. The movies obtained with and without instruction did not differ significantly in terms of image scoring and quantitative values for tibiofemoral kinematics. Our method showed to be robust for the extraction of the self-gating signal even for uninstructed motion. This can make the technique suitable for patients who, as a result of pain, may find it difficult to comply exactly with instructions. Furthermore, bone kinematics can be derived from accelerated MRI without the need for additional hardware for triggering.

Free-breathing liver fat quantification using a multiecho 3D stack-of-radial technique

PURPOSE

The diagnostic gold standard for nonalcoholic fatty liver disease is an invasive biopsy. Noninvasive Cartesian MRI fat quantification remains limited to a breath-hold (BH). In this work, a novel free-breathing 3D stack-of-radial (FB radial) liver fat quantification technique is developed and evaluated in a preliminary study.

METHODS

Phantoms and healthy subjects (n = 11) were imaged at 3 Tesla. The proton-density fat fraction (PDFF) determined using FB radial (with and without scan acceleration) was compared to BH single-voxel MR spectroscopy (SVS) and BH 3D Cartesian MRI using linear regression (correlation coefficient ρ and concordance coefficient ρ_c ) and Bland-Altman analysis.

RESULTS

In phantoms, PDFF showed significant correlation (ρ > 0.998, ρ_c  > 0.995) and absolute mean differences < 2.2% between FB radial and BH SVS, as well as significant correlation (ρ > 0.999, ρ_c  > 0.998) and absolute mean differences < 0.6% between FB radial and BH Cartesian. In the liver and abdomen, PDFF showed significant correlation (ρ > 0.986, ρ_c  > 0.985) and absolute mean differences < 1% between FB radial and BH SVS, as well as significant correlation (ρ > 0.996, ρ_c  > 0.995) and absolute mean differences < 0.9% between FB radial and BH Cartesian.

CONCLUSION

Accurate 3D liver fat quantification can be performed in 1 to 2 min using a novel FB radial technique. Magn Reson Med 79:370-382, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

High-speed whole-brain oximetry by golden-angle radial MRI

PURPOSE

To determine whole-brain cerebral metabolic rate of oxygen (CMRO₂ ), an improved imaging approach, based on radial encoding, termed radial OxFlow (rOxFlow), was developed to simultaneously quantify draining vein venous oxygen saturation (SvO₂ ) and total cerebral blood flow (tCBF).

METHODS

To evaluate the efficiency and precision of the rOxFlow sequence, 10 subjects were studied during a paradigm of repeated breath-holds with both rOxFlow and Cartesian OxFlow (cOxFlow) sequences. CMRO₂ was calculated at baseline from OxFlow-measured data assuming an arterial O₂ saturation of 97%, and the SvO₂ and tCBF breath-hold responses were quantified.

RESULTS

Average neurometabolic-vascular parameters across the 10 subjects for cOxFlow and rOxFlow were, respectively: SvO₂ (%) baseline: 64.6 ± 8.0 versus 64.2 ± 6.6; SvO₂ peak: 70.5 ± 8.5 versus 72.6 ± 5.4; tCBF (mL/min/100 g) baseline: 39.2 ± 3.8 versus 40.6 ± 8.0; tCBF peak: 53.2 ± 5.1 versus 56.1 ± 11.7; CMRO₂ (µmol O₂ /min/100 g) baseline: 111.5 ± 26.8 versus 120.1 ± 19.6. The above measures were not significantly different between sequences (P > 0.05).

CONCLUSION

There was good agreement between the two methods in terms of the physiological responses measured. Comparing the two, rOxFlow provided higher temporal resolution and greater flexibility for reconstruction while maintaining high SNR. Magn Reson Med 79:217-223, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 Tesla

PURPOSE

Hepatic iron content (HIC) quantification via transverse relaxation rate (R2*)-MRI using multi-gradient echo (mGRE) imaging is compromised toward high HIC or at higher fields due to the rapid signal decay. Our study aims at presenting an optimized 2D ultrashort echo time (UTE) sequence for R2* quantification to overcome these limitations.

METHODS

Two-dimensional UTE imaging was realized via half-pulse excitation and radial center-out sampling. The sequence includes chemically selective saturation pulses to reduce streaking artifacts from subcutaneous fat, and spatial saturation (sSAT) bands to suppress out-of-slice signals. The sequence employs interleaved multi-echo readout trains to achieve dense temporal sampling of rapid signal decays. Evaluation was done at 1.5 Tesla (T) and 3T in phantoms, and clinical applicability was demonstrated in five patients with biopsy-confirmed massively high HIC levels (>25 mg Fe/g dry weight liver tissue).

RESULTS

In phantoms, the sSAT pulses were found to remove out-of-slice contamination, and R2* results were in excellent agreement to reference mGRE R2* results (slope of linear regression: 1.02/1.00 for 1.5/3T). UTE-based R2* quantification in patients with massive iron overload proved successful at both field strengths and was consistent with biopsy HIC values.

CONCLUSION

The UTE sequence provides a means to measure R2* in patients with massive iron overload, both at 1.5T and 3T. Magn Reson Med 78:1839-1851, 2017. © 2017 Wiley Periodicals, Inc.

Non-invasive pressure difference estimation from PC-MRI using the work-energy equation

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A novel semi-automatic method for the estimation of pressure differences in cardiovascular compartments from dense velocity fields (4D flow MRI data).

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The approach relies on the work-energy principle, and removes the need for second order spatial derivatives.

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Pressure differences are evaluated directly from the 4D flow data, without the need of any computational mesh.

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The method shows good accuracy, robustness to noise and robustness to segmentation compared to existing methods.

Pressure difference is an accepted clinical biomarker for cardiovascular disease conditions such as aortic coarctation. Currently, measurements of pressure differences in the clinic rely on invasive techniques (catheterization), prompting development of non-invasive estimates based on blood flow. In this work, we propose a non-invasive estimation procedure deriving pressure difference from the work-energy equation for a Newtonian fluid. Spatial and temporal convergence is demonstrated on in silico Phase Contrast Magnetic Resonance Image (PC-MRI) phantoms with steady and transient flow fields. The method is also tested on an image dataset generated in silico from a 3D patient-specific Computational Fluid Dynamics (CFD) simulation and finally evaluated on a cohort of 9 subjects. The performance is compared to existing approaches based on steady and unsteady Bernoulli formulations as well as the pressure Poisson equation. The new technique shows good accuracy, robustness to noise, and robustness to the image segmentation process, illustrating the potential of this approach for non-invasive pressure difference estimation.

Strategies for optimizing the phase correction algorithms in Nuclear Magnetic Resonance spectroscopy

Nuclear Magnetic Resonance (NMR) spectroscopy is a popular medical diagnostic technique. NMR is also the favourite tool of chemists/biochemists to elucidate the molecular structure of small or big molecules; it is also a widely used tool in material science, in food science etc. In the case of medical diagnosis it allows for determining a metabolic composition of analysed tissue which may support the identification of tumour cells. Precession signal, that is a crucial part of MR phenomenon, contains distortions that must be filtered out before signal analysis. One of such distortions is phase error.

Five popular algorithms: Automics, Shanon's entropy minimization, Ernst's method, Dispa and eDispa are presented and discussed. A novel adaptive tuning algorithm for Automics method was developed and numerically optimal solutions to automatic tuning of the other four algorithms were proposed. To validate the performance of the proposed techniques, two experiments were performed - the first one was done with the use of in silico generated data. For all presented methods, the fine tuning strategies significantly increased the correction accuracy. The highest improvement was observed for Automics algorithm, independently of noise level, with relative phase error dropping by average from 10.25% to 2.40% for low noise level and from 12.45% to 2.66% for high noise level. The second validation experiment, done with the use of phantom data, confirmed the in silico results. The obtained accuracy of the estimation of metabolite concentration was at 99.5%.

Self-calibrated trajectory estimation and signal correction method for robust radial imaging using GRAPPA operator gridding

PURPOSE

In radial imaging, projections may become "miscentered" due to gradient errors such as delays and eddy currents. These errors may result in image artifacts and can disrupt the reliability of direct current (DC) navigation. The proposed parallel imaging-based technique retrospectively estimates trajectory error from miscentered radial data without extra acquisitions, hardware, or sequence modification.

THEORY AND METHODS

After phase correction, self-calibrated GRAPPA operator gridding (GROG) weights are iteratively applied to shift-miscentered projections toward the center of k-space. A search algorithm identifies the shift that aligns the peak k-space signals by maximizing the sum-of-squares DC signal estimate of each projection. The algorithm returns a trajectory estimate and a corrected radial k-space signal.

RESULTS

Data from a spherical phantom, the head, and the heart demonstrate that image reconstruction with the estimated trajectory restores image quality and reduces artifacts such as streaks and signal voids. The DC signal level is increased and variability is reduced.

CONCLUSION

Retrospective phase correction and iterative application of GROG can be used to successfully estimate the trajectory error in two-dimensional radial acquisitions for improved image reconstruction without requiring extra data acquisition or sequence modification.

Functional assessment of the mouse heart by MRI with a 1-min acquisition

In vivo assessment of heart function in mice is important for basic and translational research in cardiology. MRI is an accurate tool for the investigation of the anatomy and function in the preclinical setting; however, the long scan duration limits its usage. We aimed to reduce the acquisition time of cine MRI to 1 min. We employed spatiotemporal compressed sensing and parallel imaging to accelerate retrospectively gated cine MRI. We compared the functional parameters derived from full and undersampled data in Cartesian and radial MRI by means of Bland-Altman plots. We found that the scan time for the whole heart could be reduced to 2 min with Cartesian sampling and to 1 min with radial sampling. Despite a reduction in the signal-to-noise ratio, the accuracy in the estimation of left and right ventricular volumes was preserved for all tested subjects. This method can be used to perform accurate functional MRI examinations in mice for high-throughput phenotyping or translational studies.