Faculty Bibliography

Fast, 3D radio-frequency transmit field (B(1) ) mapping is important for parallel transmission, spatially selective pulse design and quantitative MRI applications. It has been shown that actual flip angle imaging-two interleaved spoiled gradient recalled echo images acquired in steady state with two very short time delays (TR(1) , TR(2) )-is an attractive method of B(1) mapping. Herein, we describe the TROMBONE method that efficiently integrates actual flip angle imaging with EPI imaging, alleviates very short TR requirement of actual flip angle imaging and through their synergy yields up to 16 times higher precision in B(1) estimation in the same experimental time. High precision of TROMBONE can be traded for faster scans. The map of B(1) reconstructed from the ratio of intensities of two images is insensitive to longitudinal relaxation time (T(1) ) in the physiologically relevant range. A table of the optimal acquisition protocol parameters for various target experimental conditions is provided. Magn Reson Med, 2011. (c) 2011 Wiley-Liss, Inc

Cardiac T(2) mapping is a promising method for quantitative assessment of myocardial edema and iron overload. We have developed a new multiecho fast spin echo (ME-FSE) pulse sequence for breath-hold T(2) mapping with acceptable spatial resolution. We propose to further accelerate this new ME-FSE pulse sequence using k-t focal underdetermined system solver adapted with a framework that uses both compressed sensing and parallel imaging (e.g., sensitivity encoding) to achieve higher spatial resolution. We imaged 12 control subjects in midventricular short-axis planes and compared the accuracy of T(2) measurements obtained using ME-FSE with generalized autocalibrating partially parallel acquisitions and ME-FSE with k-t focal underdetermined system solver. For image reconstruction, we used a bootstrapping two-step approach, where in the first step fast Fourier transform was used as the sparsifying transform and in the final step principal component analysis was used as the sparsifying transform. When compared with T(2) measurements obtained using generalized autocalibrating partially parallel acquisitions, T(2) measurements obtained using k-t focal underdetermined system solver were in excellent agreement (mean difference = 0.04 msec; upper/lower 95% limits of agreement were 2.26/-2.19 msec, respectively). The proposed accelerated ME-FSE pulse sequence with k-t focal underdetermined system solver is a promising investigational method for rapid T(2) measurement of the heart with relatively high spatial resolution (1.7 x 1.7 mm(2) ). Magn Reson Med, 2011. (c) 2011 Wiley-Liss, Inc

Diffusion-weighted imaging plays important roles in cancer diagnosis, monitoring, and treatment. Although most applications measure restricted diffusion by tumor cellularity, diffusion-weighted imaging is also sensitive to vascularity through the intravoxel incoherent motion effect. Hypervascularity can confound apparent diffusion coefficient measurements in breast cancer. We acquired multiple b-value diffusion-weighted imaging at 3 T in a cohort of breast cancer patients and performed biexponential intravoxel incoherent motion analysis to extract tissue diffusivity (D(t) ), perfusion fraction (f(p) ), and pseudodiffusivity (D(p) ). Results indicated significant differences between normal fibroglandular tissue and malignant lesions in apparent diffusion coefficient mean (+/-standard deviation) values (2.44 +/- 0.30 vs. 1.34 +/- 0.39 mum(2) /msec, P < 0.01) and D(t) (2.36 +/- 0.38 vs. 1.15 +/- 0.35 mum(2) /msec, P < 0.01). Lesion diffusion-weighted imaging signals demonstrated biexponential character in comparison to monoexponential normal tissue. There is some differentiation of lesion subtypes (invasive ductal carcinoma vs. other malignant lesions) with f(p) (10.5 +/- 5.0% vs. 6.9 +/- 2.9%, P = 0.06), but less so with D(t) (1.14 +/- 0.32 mum(2) /msec vs. 1.18 +/- 0.52 mum(2) /msec, P = 0.88) and D(p) (14.9 +/- 11.4 mum(2) /msec vs. 16.1 +/- 5.7 mum(2) /msec, P = 0.75). Comparison of intravoxel incoherent motion biomarkers with contrast enhancement suggests moderate correlations. These results suggest the potential of intravoxel incoherent motion vascular and cellular biomarkers for initial grading, progression monitoring, or treatment assessment of breast tumors. Magn Reson Med, 2011. (c) 2011 Wiley-Liss, Inc

A system that provides a sustained hyperpolarized (1)H NMR signal in an aqueous medium is reported. The enhanced signal lasts much longer than typical (1)H T(1) values, uncovering new possibilities for implementing hyperpolarized (1)H NMR/MRI experiments or performing kinetics studies that would not otherwise be detectable

OBJECTIVE: To consider potential clinical needs, technical solutions and research promises of ultrahigh-field strength cardiovascular MR (CMR). METHODS: A literature review is given, surveying advantages and disadvantages of CMR at ultrahigh fields (UHF). Key concepts, emerging technologies, practical considerations and applications of UHF CMR are provided. Examples of UHF CMR imaging strategies and their added value are demonstrated, including the numerous unsolved problems. A concluding section explores future directions in UHF CMR. RESULTS: UHF CMR can be regarded as one of the most challenging MRI applications. Image quality achievable at UHF is not always exclusively defined by signal-to-noise considerations. Some of the inherent advantages of UHF MRI are offset by practical challenges. But UHF CMR can boast advantages over its kindred lower field counterparts by trading the traits of high magnetic fields for increased temporal and/or spatial resolution. CONCLUSIONS: CMR at ultrahigh-field strengths is a powerful motivator, since speed and signal may be invested to overcome the fundamental constraints that continue to hamper traditional CMR. If practical challenges can be overcome, UHF CMR will help to open the door to new approaches for basic science and clinical research

First-pass cardiac perfusion MRI is a natural candidate for compressed sensing acceleration since its representation in the combined temporal Fourier and spatial domain is sparse and the required incoherence can be effectively accomplished by k-t random undersampling. However, the required number of samples in practice (three to five times the number of sparse coefficients) limits the acceleration for compressed sensing alone. Parallel imaging may also be used to accelerate cardiac perfusion MRI, with acceleration factors ultimately limited by noise amplification. In this work, compressed sensing and parallel imaging are combined by merging the k-t SPARSE technique with sensitivity encoding (SENSE) reconstruction to substantially increase the acceleration rate for perfusion imaging. We also present a new theoretical framework for understanding the combination of k-t SPARSE with SENSE based on distributed compressed sensing theory. This framework, which identifies parallel imaging as a distributed multisensor implementation of compressed sensing, enables an estimate of feasible acceleration for the combined approach. We demonstrate feasibility of 8-fold acceleration in vivo with whole-heart coverage and high spatial and temporal resolution using standard coil arrays. The method is relatively insensitive to respiratory motion artifacts and presents similar temporal fidelity and image quality when compared to Generalized autocalibrating partially parallel acquisitions (GRAPPA) with 2-fold acceleration

The quality of an RF detector coil design is commonly judged on how it compares with other coil configurations. The aim of this article is to develop a tool for evaluating the absolute performance of RF coil arrays. An algorithm to calculate the ultimate intrinsic signal-to-noise ratio (SNR) was implemented for a spherical geometry. The same imaging tasks modeled in the calculations were reproduced experimentally using a 32-element head array. Coil performance maps were then generated based on the ratio of experimentally measured SNR to the ultimate intrinsic SNR, for different acceleration factors associated with different degrees of parallel imaging. The relative performance in all cases was highest near the center of the samples (where the absolute SNR was lowest). The highest performance was found in the unaccelerated case and a maximum of 85% was observed with a phantom whose electrical properties are consistent with values in the human brain. The performance remained almost constant for 2-fold acceleration, but deteriorated at higher acceleration factors, suggesting that larger arrays are needed for effective highly-accelerated parallel imaging. The method proposed here can serve as a tool for the evaluation of coil designs, as well as a tool to guide the development of original designs which may begin to approach the optimal performance.

Imaging of cardiac perfusion with MR is a challenging area of research especially due to the motion of the heart and limited time of data acquisition. Compressed sensing is a popular signal estimation method recently adopted by researchers in MRI which can improve the spatial and/or temporal resolution of the acquired images by reducing the number of necessary samples for image reconstruction. This paper focuses on performance of temporal regularization with total variation and wavelets in compressed sensing. The impact of the choice of regularization parameters on the image quality and the temporal variation of intensity in region of interests (ROIs) are discussed. It is found that selecting the regularization parameter so as to optimize the quality of the reconstructed image sequence as a whole, leads to erroneous reconstruction of certain regions due to over regularization.

Introduction: Robust implementation of first-pass cardiac perfusion MRI for clinical use can be particularly challenging due to competing constraints of spatial and temporal resolution, and spatial coverage [1]. k-t SENSE [2] can be used to achieve high accelerations, but dynamic training data are required which reduces the effective acceleration rate. An alternative acceleration technique is compressed sensing (CS) [3], where spatial and temporal correlations result in sparsity of image series content, which may in turn be exploited to achieve high levels of undersampling without losing image information. We have recently presented the combination of compressed sensing and parallel imaging (JOCS: JOint-CS [4]) to increase the acceleration rate of CS alone. In this work, we demonstrate first-pass cardiac perfusion MRI with whole-heart coverage and high spatial and temporal resolution using the JOCS technique. Purpose: Evaluate the feasibility of highly-accelerated first-pass cardiac perfusion MRI with whole-heart coverage per heartbeat using JOCS. Methods: First-pass cardiac perfusion MRI with 0.1 mmol/kg of Gd-DTPA (Magnevist) was performed in two healthy volunteers and one patient with coronary artery disease. A modified multislice TurboFLASH sequence was employed on a whole-body 3 T scanner (Siemens;Tim-Trio) using the 12-element body matrix coil array. The relevant imaging parameters include: FOV = 320 mm x 320 mm, image-resolution = 1.7 mm x 1.7 mm, slice-thickness = 8 mm, TE/TR = 1.3 ms/2.5 ms, repetitions = 40. Acceleration was accomplished using ky-t random undersampling to produce the required incoherence. Breath-hold measurements with acceleration factor of R = 8 (allowing 10 (Figure presented) (Figure presented) acquired slices per heartbeat, temporal-resolution = 60 ms/slice) were performed. In the patient, delayed-enhancement images were obtained using a phase-sensitive inversion recovery (PSIR) [6] pulse sequence, 15 minutes after the administration of the contrast agent. Image reconstruction was performed using the JOCS algorithm [5]. A Fourier transform along the time dimension and finite differences along the spatial dimensions were used as sparsifying transforms. Results: Fig. 1 shows the reconstructed images (10 slices) for the peak blood and peak myocardial wall enhancement phases for one volunteer study. The reconstructed images covered most of the heart with adequate blood and myocardial wall enhancement and good image quality. Fig. 2 shows perfusion images at peak myocardial wall enhancement in three short-axis views (mid-to-apical) with perfusion defects for the patient study. The corresponding PSIR delayed-enhancement images show myocardial scarring regions that correlate well with the perfusion defect regions. Conclusion: JOCS enables first-pass cardiac perfusion MRI studies with whole-heart coverage and high spatial (<2 mm) and temporal (60 ms/slice) resolution. Future work will explore 3D imaging and the use of larger numbers of coils

Introduction: Imaging of the carotid artery with black-blood MRI can be used to identify plaques that are vulnerable for rupture [1, 2]. 3D imaging is particularly interesting to overcome the SNR and volumetric coverage limitations of 2D multi-slice techniques. However, 3D scans are more susceptible to motion artifacts, particularly swallowing-related artifacts, due to the longer acquisition times [3]. Parallel imaging can be used to accelerate the acquisition, but acceleration is limited by noise amplification. An alternative acceleration technique is compressed sensing (CS) [4], where image compressibility can be exploited to undersample k-space without losing image information. 3D imaging is a natural candidate for CS, since higher dimensional data sets increase sparsity. We propose to combine CS and parallel imaging to increase the acceleration rate for 3D carotid imaging. Purpose: Evaluate the feasibility of highly-accelerated 3D carotid MRI using CS and parallel imaging. Methods: 3D carotid MRI was performed in a healthy volunteer on a 3 T scanner (Siemens; Tim-Trio) using a custom 8-channel carotid coil array. Fully-sampled 3D fast spin echo data were acquired with T1-weighting. The relevant imaging parameters include: TE = 12 ms, TR = 800 ms, scan-time = 15 min, FOV = 190 mm x143 mm x 44 mm, image-resolution = 0.3 mm x 0.3 mm x 2 mm. Acceleration was simulated by decimating the fully-sampled data along the phase-encoding (ky) and partition-encoding (kz) dimensions by factors R = 4, 6 and 8, using a random undersampling pattern to generate the required incoherence for CS. Combination of CS and parallel imaging was performed using a single joint reconstruction algorithm (JOCS: joint CS [5]) by enforcing joint sparsity on the multicoil images in order to exploit k-space redundancy and incoherence along the coil dimension. Finite differences along x, y and z were employed to sparsify the 3D data set. A standard GRAPPA reconstruction with simulated acceleration R = 4(2 x 2) was also performed for comparison purposes. Results: Fig. 1 shows reconstructed images in an axial view and Table 1 shows the corresponding root-mean-square-error (RMSE) values. JOCS presented improved image quality over GRAPPA, which yielded more noise. Compared with R = 4, acceleration factors R = 6 and R = 8 presented more blurring and change of contrast in regions with low-value finitedifferences, which are challenging for JOCS reconstruction. Fig. 2 shows intensity profiles through a carotid vessel. JOCS with (Figure Presented) (Figure Presented) R = 4 and R = 6 presented adequate profiles, whereas for R = 8 the epithelium-tissue border was considerably blurred. Conclusion: JOCS enables higher accelerations than GRAPPA for 3D carotid imaging, which may markedly reduce sensitivity to motion. Future work will explore the use of geometricallyoriented wavelets to further improve image sparsity