Golden-angle Radial MRI Research Articles

Real Time Volumetric MRI for MR-Guided 3D Motion Tracking via Sparse Prior-Augmented Neural Representation Learning

To reconstruct volumetric MRI from orthogonal cine acquisition aided by sparse priors of 2 static 3D MRI through implicit neural representation (NeRP) learning, with the goal of eliminating large-scale training datasets for data-driven sparse MRI reconstruction and supporting clinical workflow of real time 3D motion tracking during MR-guided radiotherapy. A multi-layer perceptron network was trained to learn the NeRP of a patient-specific MRI dataset, where the network takes 4D data coordinates of voxel locations and motion states as inputs and outputs corresponding voxel intensities. By first learning the NeRP of 2 static 3D MRI with different breathing motion states, prior knowledge of patient breathing motion was embedded into network weights through optimization. The prior knowledge was then augmented from 2 to 31 motion states by querying the optimized network at interpolated/extrapolated motion state coordinates. Starting from the prior-augmented network as an initialization point, the network was further trained using sparse samples of 2 orthogonal cine slices. The final volumetric reconstruction was obtained by querying the trained network at desired 3D spatial locations. We evaluated the proposed method using 5-minute volumetric MRI time series with 340 ms temporal resolution collected from 7 liver carcinoma patients. The time series was acquired using golden-angle radial MRI sequence and reconstructed through retrospective sorting. Two MRI with inhale and exhale states respectively were selected from the first 30 sec of the time series for prior embedding and augmentation. The remaining 4.5-min time series was used for volumetric reconstruction evaluation, where we retrospectively subsampled each MRI to 2 orthogonal slices and compared network-reconstructed images to ground truth images in terms of image quality and the capability of supporting 3D target motion tracking. Across the 7 patients evaluated, the peak signal to noise ratio between model reconstruction and ground truth was 54.66 ± 6.16 dB and the structural similarity index measure was 0.99 ± 0.01. Gross tumor volume (GTV) contours estimated by deforming a reference state MRI to model-reconstructed and ground truth MRI showed good consistency. The 95-percentile Hausdorff distance between GTV contours was 1.89 ± 1.13 mm, which is less than the voxel dimension. The mean GTV centroid position difference between ground truth and model estimation was less than 1 mm in all 3 orthogonal directions. Volumetric MRI from orthogonal cine acquisition with sparse priors is feasible by modeling prior knowledge through implicit neural representation learning. The model-reconstructed images showed sufficient accuracy in supporting 3D motion tracking of abdominal targets. By eliminating the need for large scale training datasets, the method promises to enable clinical implementation of 3D motion tracking for precision radiation therapy.

High-resolution CINE imaging of active guided knee motion using continuously acquired golden-angle radial MRI and rotary sensor information

To explore and extend on dynamic imaging of joint motion, an MRI-safe device guiding knee motion with an attached rotary encoder was used in MRI measurements of multiple knee flexion-extension cycles using radial gradient echo imaging with the golden-angle as azimuthal angle increment. Reproducibility of knee motion was investigated. Real-time and CINE mode anatomical images were reconstructed for different knee flexion angles by synchronizing the encoder information with the MRI data, and performing flexion angle selective gating across multiple motion cycles. When investigating the influence of the rotation angle window width on reconstructed CINE images, it was found that angle windows between 0.5° and 3° exhibited acceptable image sharpness without suffering from significant motion-induced blurring. Furthermore, due to flexible retrospective image reconstruction afforded by the radial golden-angle imaging, the number of motion cycles included in the reconstruction could be retrospectively reduced to investigate the corresponding influence of acquisition time on image quality. Finally, motion reproducibility between motion cycles and accuracy of the flexion angle selective gating were sufficient to acquire whole-knee 3D dynamic imaging with a retrospectively gated 3D cone UTE sequence.

Respiratory motion compensation using data binning in dynamic contrast enhanced golden-angle radial MRI

GRASP (Golden-Angle Radial Sparse Parallel MRI) is a data acquisition and reconstruction technique that combines parallel imaging and golden-angle radial sampling. The continuously acquired free breathing Dynamic Contrast Enhanced (DCE) golden-angle radial MRI data of liver and abdomen has artifacts due to respiratory motion, resulting in low vessel-tissue contrast that makes GRASP reconstructed images less suitable for diagnosis. In this paper, DCE golden-angle radial MRI data of abdomen and liver perfusion is sorted into different motion states using the self-gating property of radial acquisition and then reconstructed using GRASP. Three methods of amplitude-based data binning namely uniform binning, adaptive binning and optimal binning are applied on the DCE golden-angle radial data to extract different motion states and a comparison is performed with the conventional GRASP reconstruction. Also, a comparison among the amplitude-based data binning techniques is performed and benefits of each of these binning techniques are discussed from a clinical perspective. The image quality assessment in terms of hepatic vessel clarity, liver edge sharpness, contrast enhancement clarity and streaking artifacts is performed by a certified radiologist. The results show that DCE golden-angle radial trajectories benefit from all the three types of amplitude-based data binning methods providing improved reconstruction results. The choice of binning technique depends upon the clinical application e.g. uniform and adaptive binning are helpful for a detailed analysis of lesion characteristic and contrast enhancement in different motion states while optimal binning can be used when clinical analysis requires a single image per contrast enhancement phase with no motion blurring artifacts.

Simultaneous Measurement of Perfusion and T2* in Calf Muscle at 7T with Submaximal Exercise using Radial Acquisition

Impairments in oxygen delivery and consumption can lead to reduced muscle endurance and physical disability. Perfusion, a measure of microvascular blood flow, provides information on nutrient delivery. T2* provides information about relative tissue oxygenation. Changes in these parameters following stress, such as exercise, can yield important information about imbalance between delivery and consumption. In this study, we implemented novel golden angle radial MRI acquisition technique to simultaneously quantify muscle perfusion and T2* at 7T with improved temporal resolution, and demonstrated assessment of spatial and temporal changes in these parameters within calf muscles during recovery from plantar flexion exercise. Nine healthy subjects participated the studies. At rest, perfusion and T2* in gastrocnemius muscle group within calf muscle were 5 ± 2 mL/100 g/min and 21.1 ± 3 ms respectively. Then the subjects performed plantar flexion exercise producing a torque of ~8ft-lb. Immediately after the exercise, perfusion was elevated to 79.3 ± 9 mL/100 g/min and T2* was decreased by 6 ± 3%. The time constants for 50% perfusion and T2* recovery were 54.1 ± 10 s and 68.5 ± 7 s respectively. These results demonstrate successful simultaneous quantification of perfusion and T2* in skeletal muscle using the developed technique.

Trajectory optimized NUFFT: Faster non-Cartesian MRI reconstruction through prior knowledge and parallel architectures.

PurposeThe non‐uniform fast Fourier transform (NUFFT) involves interpolation of non‐uniformly sampled Fourier data onto a Cartesian grid, an interpolation that is slowed by complex, non‐local data access patterns. A faster NUFFT would increase the clinical relevance of the plethora of advanced non‐Cartesian acquisition methods.MethodsHere we customize the NUFFT procedure for a radial trajectory and GPU architecture to eliminate the bottlenecks encountered when allowing for arbitrary trajectories and hardware. We call the result TRON, for TRajectory Optimized NUFFT. We benchmark the speed and accuracy TRON on a Shepp‐Logan phantom and on whole‐body continuous golden‐angle radial MRI.ResultsTRON was 6–30× faster than the closest competitor, depending on test data set, and was the most accurate code tested.ConclusionsSpecialization of the NUFFT algorithm for a particular trajectory yielded significant speed gains. TRON can be easily extended to other trajectories, such as spiral and PROPELLER. TRON can be downloaded at http://github.com/davidssmith/TRON.

Pulmonary artery imaging under free-breathing using golden-angle radial bSSFP MRI: a proof of concept.

To evaluate the feasibility of an improved motion and flow robust methodology for imaging the pulmonary vasculature using non-contrast-enhanced, free-breathing, golden-angle radial MRI. Healthy volunteers (n = 10, age 46 ± 11 years, 50% female) and patients (n = 2, ages 27 and 84, both female) were imaged at 1.5 T using a Cartesian and golden-angle radial 2D balanced SSFP pulse sequence. The acquisitions were made under free breathing without contrast agent enhancement. The radial acquisitions were reconstructed at 3 temporal footprints. All series were scored from 1 to 5 for perceived diagnostic quality, artifact level, and vessel sharpness in multiple anatomical locations. In addition, vessel sharpness and blood-to-blood clot contrast were measured. Quantitative measurements showed higher vessel sharpness for golden-angle radial (n = 76, 0.79 ± 0.11 versus 0.71 ± 0.16, p < .05). Blood-to-blood clot contrast was found to be 23% higher in golden-angle radial in the 2 patients. At comparable temporal footprints, golden-angle radial was scored higher for diagnostic quality (mean ± SD, 2.3 ± 0.7 versus 2.2 ± 0.6, p < .01) and vessel sharpness (2.2 ± 0.8 versus 2.1 ± 0.5, p < .01), whereas the artifact level did not differ (3.0 ± 0.9 versus 3.0 ± 1.0, p = .80). The ability to retrospectively choose a temporal resolution and perform sliding-window reconstructions was demonstrated in patients. In pulmonary artery imaging, the motion and flow robustness of a radial trajectory does both improve image quality over Cartesian trajectory in healthy volunteers, and allows for flexible selection of temporal footprints and the ability to perform real-time sliding window reconstructions, which could potentially provide further diagnostic insight.

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

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). 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. 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). 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.

XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.

To develop a novel framework for free-breathing MRI called XD-GRASP, which sorts dynamic data into extra motion-state dimensions using the self-navigation properties of radial imaging and reconstructs the multidimensional dataset using compressed sensing. Radial k-space data are continuously acquired using the golden-angle sampling scheme and sorted into multiple motion-states based on respiratory and/or cardiac motion signals derived directly from the data. The resulting undersampled multidimensional dataset is reconstructed using a compressed sensing approach that exploits sparsity along the new dynamic dimensions. The performance of XD-GRASP is demonstrated for free-breathing three-dimensional (3D) abdominal imaging, two-dimensional (2D) cardiac cine imaging and 3D dynamic contrast-enhanced (DCE) MRI of the liver, comparing against reconstructions without motion sorting in both healthy volunteers and patients. XD-GRASP separates respiratory motion from cardiac motion in cardiac imaging, and respiratory motion from contrast enhancement in liver DCE-MRI, which improves image quality and reduces motion-blurring artifacts. XD-GRASP represents a new use of sparsity for motion compensation and a novel way to handle motions in the context of a continuous acquisition paradigm. Instead of removing or correcting motion, extra motion-state dimensions are reconstructed, which improves image quality and also offers new physiological information of potential clinical value.