Applicability and efficiency of near-optimal spatial encoding for dynamically adaptive MRI

Adaptive near-optimal MRI spatial encoding entails, for the acquisition of each image update in a dynamic series, the computation of encodes in the form of a linear algebra-derived orthogonal basis set determined from an image estimate. The origins of adaptive encoding relevant to MRI are reviewed. Sources of error of this approach are identified from the linear algebraic perspective where MRI data acquisition is viewed as the projection of information from the field-of-view onto the encoding basis set. The definitions of ideal and non-ideal encoding follow, with nonideal encoding characterized by the principal angles between two vector spaces. An analysis of the distribution of principal angles is introduced and applied in several example cases to quantitatively describe the suitability of a basis set derived from a specific image estimate for the spatial encoding of a given field-of-view. The robustness of adaptive near-optimal spatial encoding for dynamic MRI is favorably shown by results computed using singular value decomposition encoding that simulates specific instances of worst case data acquisition when all objects have changed or new objects have appeared in the field-of-view. The mathematical analysis and simulations presented clarify the applicability and efficiency of adaptively determined near-optimal spatial encoding throughout a range of circumstances as may typically occur during use of dynamic MRI.     

Dynamic magnetic resonance inverse imaging of human brain function.

MRI is widely used for noninvasive hemodynamic-based functional brain imaging. In traditional spatial encoding, however, gradient switching limits the temporal resolution, which makes it difficult to unambiguously identify possible fast nonhemodynamic changes. In this paper we propose a novel reconstruction approach, called dynamic inverse imaging (InI), that is capable of providing millisecond temporal resolution when highly parallel detection is used. To achieve an order-of-magnitude speedup in generating time-resolved contrast estimates and dynamic statistical parametric maps (dSPMs), the spatial information is derived from an array of detectors rather than by time-consuming gradient-encoding methods. The InI approach was inspired by electroencephalography (EEG) and magnetoencephalography (MEG) source localization techniques. Dynamic MR InI was evaluated by means of numerical simulations. InI was also applied to measure BOLD hemodynamic time curves at 20-ms temporal resolution in a visual stimulation experiment using a 90-channel head array. InI is expected to improve the time resolution of MRI and provide increased flexibility in the trade-off between spatial and temporal resolution for studies of dynamic activation patterns in the human brain.     

Multidimensionally encoded magnetic resonance imaging

Magnetic resonance imaging (MRI) typically achieves spatial encoding by measuring the projection of a q‐dimensional object over q‐dimensional spatial bases created by linear spatial encoding magnetic fields (SEMs). Recently, imaging strategies using nonlinear SEMs have demonstrated potential advantages for reconstructing images with higher spatiotemporal resolution and reducing peripheral nerve stimulation. In practice, nonlinear SEMs and linear SEMs can be used jointly to further improve the image reconstruction performance. Here, we propose the multidimensionally encoded (MDE) MRI to map a q‐dimensional object onto a p‐dimensional encoding space where p > q. MDE MRI is a theoretical framework linking imaging strategies using linear and nonlinear SEMs. Using a system of eight surface SEM coils with an eight‐channel radiofrequency coil array, we demonstrate the five‐dimensional MDE MRI for a two‐dimensional object as a further generalization of PatLoc imaging and O‐space imaging. We also present a method of optimizing spatial bases in MDE MRI. Results show that MDE MRI with a higher dimensional encoding space can reconstruct images more efficiently and with a smaller reconstruction error when the k‐space sampling distribution and the number of samples are controlled. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.     

High-resolution real-time spiral MRI for guiding vascular interventions in a rabbit model at 1.5 T

PURPOSE: To study the feasibility of a combined high spatial and temporal resolution real-time spiral MRI sequence for guiding coronary-sized vascular interventions. MATERIALS AND METHODS: Eight New Zealand White rabbits (four normal and four with a surgically-created stenosis in the abdominal aorta) were studied. A real-time interactive spiral MRI sequence combining 1.1 x 1.1 mm(2) in-plane resolution and 189-msec total image acquisition time was used to image all phases of an interventional procedure (i.e., guidewire placement, balloon angioplasty, and stenting) in the rabbit aorta using coronary-sized devices on a 1.5 T MRI system. RESULTS: Real-time spiral MRI identified all rabbit aortic stenoses and provided high-temporal-resolution visualization of guide-wires crossing the stenoses in all animals. Angioplasty balloon dilatation and deployment of coronary-sized copper stents in the rabbit aorta were also successfully imaged by real-time spiral MRI. CONCLUSION: Combining high spatial and temporal resolution with spiral MRI allows real-time MR-guided vascular intervention using coronary-sized devices in a rabbit model. This is a promising approach for guiding coronary interventions.     

Spatially encoded phase‐contrast MRI—3D MRI movies of 1D and 2D structures at millisecond resolution

This work demonstrates that the principles underlying phase‐contrast MRI may be used to encode spatial rather than flow information along a perpendicular dimension, if this dimension contains an MRI‐visible object at only one spatial location. In particular, the situation applies to 3D mapping of curved 2D structures which requires only two projection images with different spatial phase‐encoding gradients. These phase‐contrast gradients define the field of view and mean spin‐density positions of the object in the perpendicular dimension by respective phase differences. When combined with highly undersampled radial fast low angle shot (FLASH) and image reconstruction by regularized nonlinear inversion, spatial phase‐contrast MRI allows for dynamic 3D mapping of 2D structures in real time. First examples include 3D MRI movies of the acting human hand at a temporal resolution of 50 ms. With an even simpler technique, 3D maps of curved 1D structures may be obtained from only three acquisitions of a frequency‐encoded MRI signal with two perpendicular phase encodings. Here, 3D MRI movies of a rapidly rotating banana were obtained at 5 ms resolution or 200 frames per second. In conclusion, spatial phase‐contrast 3D MRI of 2D or 1D structures is respective two or four orders of magnitude faster than conventional 3D MRI. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

Reconstruction of MRI data encoded by multiple nonbijective curvilinear magnetic fields

Parallel imaging technique using localized gradients (PatLoc) uses the combination of surface gradient coils generating nonbijective curvilinear magnetic fields for spatial encoding. PatLoc imaging using one pair of multipolar spatial encoding magnetic fields (SEMs) has two major caveats: (1) The direct inversion of the encoding matrix requires exact determination of multiple locations which are ambiguously encoded by the SEMs. (2) Reconstructed images have a prominent loss of spatial resolution at the center of field‐of‐view using a symmetric coil array for signal detection. This study shows that a PatLoc system actually has a higher degree of freedom in spatial encoding to mitigate the two challenges mentioned above. Specifically, a PatLoc system can generate not only multipolar but also linear SEMs, which can be used to reduce the loss of spatial resolution at the field‐of‐view center. Here, we present an efficient and generalized image reconstruction method for PatLoc imaging using multiple SEMs without explicitly identifying the locations where SEM encoding is not unique. Reconstructions using simulations and empirical experimental data are compared with those using conventional linear gradients to demonstrate that the general combination of SEMs can improve image reconstructions. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.     

Phase contrast MRI of myocardial 3D strain by encoding contiguous slices in a single shot.

Quantitative measurements of inherently three-dimensional (3D) cardiac strain and strain rate require 3D data; MRI provides uniquely high sensitivity to material strain by combining phase contrast with single-shot acquisition methods, such as echo-planar imaging (EPI). Previous MRI methods applied to 3D strain used multiple two-dimensional (2D) acquisitions and suffered loss of sensitivity due to magnification within the strain calculation of physiologic noise related to cardiac beat-to-beat variability. In the present work, each single-shot acquisition generates 3D image data by acquiring two contiguous 2D Fourier transform (FT) images in a single echo train of an EPI readout. Although strain encoding divides across multiple EPI shots, each strain component is computed only within single-shot data, avoiding noise magnification. Strain tensor maps are displayed using iconic 3D graphics or a simple color code of tensor shape. In a deforming gel phantom, gradient-recalled echo (GRE) MRI movies of 3D strain rates match expected strain fields. In normal human subjects, 3D strain rate tensor movies of heart and brain comprising seven slices in each of seven cardiac phases were completed in 56 heartbeats. Stimulated echo (STE) MRI of net systolic 3D strain was also demonstrated. Two-slices-in-one-shot spatial encoding permits a complete quantitative survey of ventricular 3D strain in under a minute, with routine patient supervision and turnkey image processing.     

Parallel imaging reconstruction using automatic regularization.

Increased spatiotemporal resolution in MRI can be achieved by the use of parallel acquisition strategies, which simultaneously sample reduced k-space data using the information from multiple receivers to reconstruct full-FOV images. The price for the increased spatiotemporal resolution in parallel MRI is the degradation of the signal-to-noise ratio (SNR) in the final reconstructed images. Part of the SNR reduction results when the spatially correlated nature of the information from the multiple receivers destabilizes the matrix inversion used in the reconstruction of the full-FOV image. In this work, a reconstruction algorithm based on Tikhonov regularization is presented that reduces the SNR loss due to geometric correlations in the spatial information from the array coil elements. Reference scans are utilized as a priori information about the final reconstructed image to provide regularized estimates for the reconstruction using the L-curve technique. This automatic regularization method reduces the average g-factors in phantom images from a two-channel array from 1.47 to 0.80 in twofold sensitivity encoding (SENSE) acceleration. In vivo anatomical images from an eight-channel system show an averaged g-factor reduction of 1.22 to 0.84 in 2.67-fold acceleration.     

Prospective comparison of high- and low-spatial-resolution dynamic MR imaging with sensitivity encoding (SENSE) for hypervascular hepatocellular carcinoma

The purpose of this study was to prospectively evaluate the efficacy of high-spatial-resolution dynamic MRI using sensitivity encoding (SENSE) in detection of hypervascular hepatocellular carcinoma (HCC). Thirty-five patients were included in this prospectively planned study, and 25 patients with 31 HCCs were assigned into three groups and underwent the following sequences: group A (n = 11): three-dimensional fast-gradient-echo (3D-FGE) high-spatial-resolution dynamic MRI (HR-MRI) with SENSE; group B (n = 10): 3D-FGE low-spatial-resolution dynamic MRI (LR-MRI) with SENSE; and group C (n = 14): 3D-FGE/LR-MRI without SENSE. For the quantitative analysis, the lesion-to-liver contrast-to-noise ratio (CNR) between the liver and HCCs was measured. For the qualitative analysis, overall image quality for each group was evaluated with a five-point scale analysis. The sensitivities for detection of HCCs were evaluated. The overall image quality in group A was significantly greater than both groups B and C (P < 0.01). The sensitivity of lesion detection on HAP was not significantly higher in group A (100%) than group C (69.2%; P > 0.05). In our pilot study on a small number of patients, image quality in HR-MRI with SENSE was superior to LR-MRI. A high detection rate was seen with HR-MRI with SENSE in the patients with hypervascular HCCs.     

Method for rapid MRI needle tracking.

A new method for MRI needle tracking within a given two-dimensional (2D) image slice is presented. The method is based on k-space investigation of the difference image between the current dynamic frame and a reference frame. Using only a few central k-lines of the difference image and a nonlinear optimization procedure, one can resolve the parameters that define the 2D sinc function that best characterizes the needle in k-space. The spatial location and orientation of the needle are determined from these parameters. Rapid needle tracking is obtained by repeated acquisitions of the same set of several central k-lines (as in a "keyhole" protocol) and repeated computation of these parameters. The calculated needle tip is depicted on the reference image by means of a graphic overlay. The procedure was tested in computer simulations and in actual MRI scans (the computations were done offline). It was demonstrated that six k-lines out of 128 usually suffice to locate the needle. The refresh rate of the needle location depends on the time required to sample the subset of k-lines, calculate the current needle location, and refresh the reference image.     

Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real‐time reconstruction enables immediate visualization during the scan. Commonly used view‐sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time‐consuming, or both. A Kalman filter model capable of real‐time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non‐Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal‐to‐noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view‐sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real‐time reconstruction. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.     

Noquist: reduced field-of-view imaging by direct Fourier inversion.

A novel technique called "Noquist" is introduced for the acceleration of dynamic cardiac magnetic resonance imaging (CMRI). With the use of this technique, a more sparsely sampled dynamic image sequence is reconstructed correctly, without Nyquist foldover artifact. Unlike most other reduced field-of-view (rFOV) methods, Noquist does not rely on data substitution or temporal interpolation to reconstruct the dynamic image sequence. The proposed method reduces acquisition time in dynamic MRI scans by eliminating the data redundancy associated with static regions in the dynamic scene. A reduction of imaging time is achieved by a fraction asymptotically equal to the static fraction of the FOV, by omitting acquisition of an appropriate subset of phase-encoding views from a conventional equidistant Cartesian acquisition grid. The theory behind this method is presented along with sample reconstructions from real and simulated data. Noquist is compared with conventional cine imaging by retrospective selection of a reduced data set from a full-grid conventional image sequence. In addition, a comparison is presented, using real and simulated data, of our technique with an existing rFOV technique that uses temporal interpolation. The experimental results confirm the theory, and demonstrate that Noquist reduces scan time for cine MRI while fully preserving both spatial and temporal resolution, but at the cost of a reduced signal-to-noise ratio (SNR).     

Rapid full-brain fMRI with an accelerated multi shot 3D EPI sequence using both UNFOLD and GRAPPA

The desire to understand complex mental processes using functional MRI drives development of imaging techniques that scan the whole human brain at a high spatial and temporal resolution. In this work, an accelerated multishot three-dimensional echo-planar imaging sequence is proposed to increase the temporal resolution of these studies. A combination of two modern acceleration techniques, UNFOLD and GRAPPA is used in the secondary phase encoding direction to reduce the scan time effectively. The sequence (repetition time of 1.02 s) was compared with standard two-dimensional echo-planar imaging (3 s) and multishot three-dimensional echo-planar imaging (3 s) sequences with both block design and event-related functional MRI paradigms. With the same experimental setup and imaging time, the temporal resolution improvement with our sequence yields similar activation regions in the block design functional MRI paradigm with slightly increased t-scores. Moreover, additional information on the timing of rapid dynamic changes was extracted from accelerated images for the case of the event related complex mental paradigm.     

Super‐resolved spatially encoded single‐scan 2D MRI

Single‐scan MRI underlies a wide variety of clinical and research activities, including functional and diffusion studies. Most common among these “ultrafast” MRI approaches is echo‐planar imaging. Notwithstanding its proven success, echo‐planar imaging still faces a number of limitations, particularly as a result of susceptibility heterogeneities and of chemical shift effects that can become acute at high fields. The present study explores a new approach for acquiring multidimensional MR images in a single scan, which possesses a higher built‐in immunity to this kind of heterogeneity while retaining echo‐planar imaging's temporal and spatial performances. This new protocol combines a novel approach to multidimensional spectroscopy, based on the spatial encoding of the spin interactions, with image reconstruction algorithms based on super‐resolution principles. Single‐scan two‐dimensional MRI examples of the performance improvements provided by the resulting imaging protocol are illustrated using phantom‐based and in vivo experiments. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.     

Accelerated bilateral dynamic contrast‐enhanced 3D spiral breast MRI using TSENSE

Purpose

To assess the ability of adaptive sensitivity encoding incorporating temporal filtering (TSENSE) to accelerate bilateral dynamic contrast‐enhanced (DCE) 3D breast MRI.

Materials and Methods

Bilateral DCE breast magnetic resonance imaging (MRI) exams were performed using a dual‐band water‐only excitation and a “stack‐of‐spirals” imaging trajectory. TSENSE was applied in the slab direction with an acceleration factor of 2. Four different techniques for sensitivity map calculation were compared by analyzing resultant contrast uptake curves qualitatively and quantitatively for 10 patient datasets. In addition, image quality and temporal resolution were compared between unaccelerated and TSENSE images.

Results

TSENSE can increase temporal resolution by a factor of 2 in DCE imaging, providing better depiction of contrast uptake curves and good image quality. Of the different methods tested, calculation of static sensitivity maps by averaging late postcontrast frames yields the lowest aliasing artifact level based on ROI analysis.

Conclusion

TSENSE acceleration combined with 3D spiral imaging is very time‐efficient, providing 11‐second temporal resolution and 1.1 × 1.1 × 3 mm³ spatial resolution over a 20 × 20 × 10 cm³ field of view for each breast. J. Magn. Reson. Imaging 2008;28:1425–1434. © 2008 Wiley‐Liss, Inc.     

Large field-of-view real-time MRI with a 32-channel system.

The emergence of parallel MRI techniques and new applications for real-time interactive MRI underscores the need to evaluate performance gained by increasing the capability of MRI phased-array systems beyond the standard four to eight high-bandwidth channels. Therefore, to explore the advantages of highly parallel MRI a 32-channel 1.5 T MRI system and 32-element torso phased arrays were designed and constructed for real-time interactive MRI. The system was assembled from multiple synchronized scanner-receiver subsystems. Software was developed to coordinate across subsystems the real-time acquisition, reconstruction, and display of 32-channel images. Real-time, large field-of-view (FOV) body-survey imaging was performed using interleaved echo-planar and single-shot fast-spin-echo pulse sequences. A new method is demonstrated for augmenting parallel image acquisition by independently offsetting the frequency of different array elements (FASSET) to variably shift their FOV. When combined with conventional parallel imaging techniques, image acceleration factors of up to 4 were investigated. The use of a large number of coils allowed the FOV to be doubled in two dimensions during rapid imaging, with no degradation of imaging time or spatial resolution. The system provides a platform for evaluating the applications of many-channel real-time MRI, and for understanding the factors that optimize the choice of array size.     

k-t ISD: dynamic cardiac MR imaging using compressed sensing with iterative support detection

Compressed sensing (CS) has been used in dynamic cardiac MRI to reduce the data acquisition time. The sparseness of the dynamic image series in the spatial‐ and temporal‐frequency (x‐f) domain has been exploited in existing works. In this article, we propose a new k‐t iterative support detection (k‐t ISD) method to improve the CS reconstruction for dynamic cardiac MRI by incorporating additional information on the support of the dynamic image in x‐f space based on the theory of CS with partially known support. The proposed method uses an iterative procedure for alternating between image reconstruction and support detection in x‐f space. At each iteration, a truncated ?₁ minimization is applied to obtain the reconstructed image in x‐f space using the support information from the previous iteration. Subsequently, by thresholding the reconstruction, we update the support information to be used in the next iteration. Experimental results demonstrate that the proposed k‐t ISD method improves the reconstruction quality of dynamic cardiac MRI over the basic CS method in which support information is not exploited. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.     

2D partially parallel imaging with k-space surrounding neighbors-based data reconstruction.

Partially parallel imaging (PPI) achieves imaging acceleration by replacing partial phase encoding (PE) with the spatially localized sensitivity encoding of a receiver surface coil array. Further accelerations can be achieved through 2D PPI along two PE directions in 3D MRI. This paper is to explore the k-space-based PPI acquisition and reconstruction strategies for 3D MRI. A surrounding neighbors-based autocalibrating PPI (SNAPPI) was first presented by generalizing the 2D multicolumn multiline interpolation method. Several 2D PPI reconstruction methods were then provided by applying SNAPPI to recover the partially skipped k-space data along two PE directions separately or nonseparately, in k-space or in the hybrid k and image space. An optimal 2D PPI sampling-based reconstruction approach was also presented for applying PPI along certain spatial direction along which the array coil has not sufficient sensitivity variation for a valid PPI reconstruction. Both simulated and in vivo 2D PPI data were used to evaluate the proposed methods.