Keith Heberlein

The Human Connectome Project and beyond: initial applications of 300 mT/m gradients.

The engineering of a 3 T human MRI scanner equipped with 300 mT/m gradients - the strongest gradients ever built for an in vivo human MRI scanner - was a major component of the NIH Blueprint Human Connectome Project (HCP). This effort was motivated by the HCPs goal of mapping, as completely as possible, the macroscopic structural connections of the in vivo healthy, adult human brain using diffusion tractography. Yet, the 300 mT/m gradient system is well suited to many additional types of diffusion measurements. Here, we present three initial applications of the 300 mT/m gradients that fall outside the immediate scope of the HCP. These include: 1) diffusion tractography to study the anatomy of consciousness and the mechanisms of brain recovery following traumatic coma; 2) q-space measurements of axon diameter distributions in the in vivo human brain and 3) postmortem diffusion tractography as an adjunct to standard histopathological analysis. We show that the improved sensitivity and diffusion-resolution provided by the gradients are rapidly enabling human applications of techniques that were previously possible only for in vitro and animal models on small-bore scanners, thereby creating novel opportunities to map the microstructure of the human brain in health and disease.

Diffusion imaging in humans at 7T using readout-segmented EPI and GRAPPA.

Anatomical MRI studies at 7T have demonstrated the ability to provide high‐quality images of human tissue in vivo. However, diffusion‐weighted imaging at 7T is limited by the increased level of artifact associated with standard, single‐shot, echo‐planar imaging, even when parallel imaging techniques such as generalized autocalibrating partially parallel acquisitions (GRAPPA) are used to reduce the effective echo spacing. Readout‐segmented echo‐planar imaging in conjunction with parallel imaging has the potential to reduce these artifacts by allowing a further reduction in effective echo spacing during the echo‐planar imaging readout. This study demonstrates that this approach does indeed provide a substantial improvement in image quality by reducing image blurring and susceptibility‐based distortions, as well as by allowing the acquisition of diffusion‐weighted images with a high spatial resolution. A preliminary application of the technique to high‐resolution diffusion tensor imaging provided a high level of neuroanatomical detail, which should prove valuable in a wide range of applications. Magn Reson Med 64:9–14, 2010.

Evaluation of optimized inversion-recovery fat-suppression techniques for T2-weighted abdominal MR imaging.

To test the theoretical benefits of a spectral attenuated inversion‐recovery (SPAIR) fat‐suppression (FS) technique in clinical abdominal MRI by comparison to conventional inversion‐recovery (IR) FS combined with T2‐weighted (T2W) partial Fourier single shot fast spin echo (SSFSE).

Reducing sensitivity losses due to respiration and motion in accelerated echo planar imaging by reordering the autocalibration data acquisition.

To reduce the sensitivity of echo‐planar imaging (EPI) auto‐calibration signal (ACS) data to patient respiration and motion to improve the image quality and temporal signal‐to‐noise ratio (tSNR) of accelerated EPI time‐series data.

Cross-validation-based kernel support selection for improved GRAPPA reconstruction.

The extended version of the generalized autocalibrating partially parallel acquisition (GRAPPA) technique incorporates multiple lines and multiple columns of measured k‐space data to estimate missing data. For a given accelerated dataset, the selection of the measured data points for fitting a missing datum (i.e., the kernel support) that provides optimal reconstruction depends on coil array configuration, noise level in the acquired data, imaging configuration, and number and position of autocalibrating signal lines. In this work, cross‐validation is used to select the kernel support that best balances the conflicting demands of fit accuracy and stability in GRAPPA reconstruction. The result is an optimized tradeoff between artifacts and noise. As demonstrated with experimental data, the method improves image reconstruction with GRAPPA. Because the method is simple and applied in postprocessing, it can be used with GRAPPA routinely. Magn Reson Med 59:819–825, 2008.

PET/MR Imaging in the Presence of Metal Implants: Completion of the Attenuation Map from PET Emission Data

We present a novel technique for accurate whole-body attenuation correction in the presence of metallic endoprosthesis, on integrated non–time-of-flight (non-TOF) PET/MRI scanners. The proposed implant PET-based attenuation map completion (IPAC) method performs a joint reconstruction of radioactivity and attenuation from the emission data to determine the position, shape, and linear attenuation coefficient (LAC) of metallic implants. Methods: The initial estimate of the attenuation map was obtained using the MR Dixon method currently available on the Siemens Biograph mMR scanner. The attenuation coefficients in the area of the MR image subjected to metal susceptibility artifacts are then reconstructed from the PET emission data using the IPAC algorithm. The method was tested on 11 subjects presenting 13 different metallic implants, who underwent CT and PET/MR scans. Relative mean LACs and Dice similarity coefficients were calculated to determine the accuracy of the reconstructed attenuation values and the shape of the metal implant, respectively. The reconstructed PET images were compared with those obtained using the reference CT-based approach and the Dixon-based method. Absolute relative change (aRC) images were generated in each case, and voxel-based analyses were performed. Results: The error in implant LAC estimation, using the proposed IPAC algorithm, was 15.7% ± 7.8%, which was significantly smaller than the Dixon- (100%) and CT- (39%) derived values. A mean Dice similarity coefficient of 73% ± 9% was obtained when comparing the IPAC- with the CT-derived implant shape. The voxel-based analysis of the reconstructed PET images revealed quantification errors (aRC) of 13.2% ± 22.1% for the IPAC- with respect to CT-corrected images. The Dixon-based method performed substantially worse, with a mean aRC of 23.1% ± 38.4%. Conclusion: We have presented a non-TOF emission-based approach for estimating the attenuation map in the presence of metallic implants, to be used for whole-body attenuation correction in integrated PET/MR scanners. The Graphics Processing Unit implementation of the algorithm will be included in the open-source reconstruction toolbox Occiput.io.

Progressive magnetic resonance image reconstruction based on iterative solution of a sparse linear system

Image reconstruction from nonuniformly sampled spatial frequency domain data is an important problem that arises in computed imaging. Current reconstruction techniques suffer from limitations in their model and implementation. In this paper, we present a new reconstruction method that is based on solving a system of linear equations using an efficient iterative approach. Image pixel intensities are related to the measured frequency domain data through a set of linear equations. Although the system matrix is too dense and large to solve by direct inversion in practice, a simple orthogonal transformation to the rows of this matrix is applied to convert the matrix into a sparse one up to a certain chosen level of energy preservation. The transformed system is subsequently solved using the conjugate gradient method. This method is applied to reconstruct images of a numerical phantom as well as magnetic resonance images from experimental spiral imaging data. The results support the theory and demonstrate that the computational load of this method is similar to that of standard gridding, illustrating its practical utility.

Combined intra- and inter-slice motion artifact suppression in magnetic resonance imaging

We propose a technique for suppression of both intra-slice and inter-slice types of motion artifacts simultaneously. Starting from the general assumption of rigid body motion, we consider the case when the acquisition of the k-space is in the form of bands of finite number of lines arranged in a rectilinear fashion to cover the k-space area of interest. We also assume that an averaging factor of at least 2 is desired. Instead of acquiring a full k-space of each image and then average the result, we propose a new acquisition strategy based on acquiring the k-space in consecutive bands having 50% overlap going from one end of the phase encoding direction to the other end. In case of no motion, this overlap can be used as the second acquisition (NEX=2). When motion is encountered, both types motion are reduced to the same form under this acquisition strategy. In particular, detection and correction of motion between consecutive bands result in suppression of both motion types. In this work, this is achieved by utilizing the overlap area to estimate the motion, which is then taken into consideration in further reconstruction (or even acquisition if real-time control is available on the MR system). We demonstrate the accuracy and computational efficiency of this motion estimation approach. Once the motion is estimated, we propose a simple strategy to reconstruct artifact-free images from the acquired data that take into account the possible voids in the acquired k-space as a result of rotational motion between blades.

Ultrafast Brain MRI: Clinical Deployment and Comparison to Conventional Brain MRI at 3T

To compare an ultrafast brain magnetic resonance imaging (MRI) protocol to the conventional protocol in motion‐prone inpatient clinical settings.

Simultaneous Multislice–Based 5-Minute Lumbar Spine MRI Protocol: Initial Experience in a Clinical Setting

Previous studies have used parallel imaging (PI) techniques to decrease spine magnetic resonance imaging (MRI) protocol acquisition times. Recently developed MRI sequences allow even faster acquisitions. Our purpose was to develop a lumbar spine MRI protocol using PI with GRAPPA (generalized autocalibrating partially parallel acquisition) and a simultaneous multislice (SMS)–based sequence and to evaluate its diagnostic performance compared to a standard lumbar spine MRI protocol.