Biomedical subjects

Robin M Heidemann

Publications and source records attributed to Robin M Heidemann.

12 recordsLinked to original sources

PubMed2006

Accelerated volumetric MRI with a SENSE/GRAPPA combination.

PURPOSE: To combine the specific advantages of the generalized autocalibrating partially parallel acquisitions (GRAPPA) technique and sensitivity encoding (SENSE) with two-dimensional (2D) undersampling. MATERIALS AND METHODS: By splitting the 2D reconstruction process into multiple one-dimensional (1D) reconstructions, the normal 1D GRAPPA method can be used for image reconstruction. Due to this data-handling process, a GRAPPA reconstruction is performed along the phase-encoding (PE) direction and effectively a SENSE reconstruction is performed along the partition-encoding (PAE) direction. RESULTS: In vivo experiments demonstrate the successful implementation of the SENSE/GRAPPA combination. Experimental results with up to 9.6-fold acceleration using a prototype 32-channel receiver head coil array are presented. CONCLUSION: The proposed SENSE/GRAPPA combination for 3D imaging allows the GRAPPA method to be applied in combination with 2D undersampling. Because the SENSE/GRAPPA combination is not based on knowledge of spatial coil sensitivities, it should be the method of choice whenever it is difficult to extract the sensitivity information.

Algorithms↗

PubMed2006

Controlled aliasing in volumetric parallel imaging (2D CAIPIRINHA).

The CAIPIRINHA (Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration) concept in parallel imaging has recently been introduced, which modifies the appearance of aliasing artifacts during data acquisition in order to improve the subsequent parallel imaging reconstruction procedure. This concept has been successfully applied to simultaneous multi-slice imaging (MS CAIPIRINHA). In this work, we demonstrate that the concept of CAIPIRINHA can also be transferred to 3D imaging, where data reduction can be performed in two spatial dimensions simultaneously. In MS CAIPIRINHA, aliasing is controlled by providing individual slices with different phase cycles by means of alternating multi-band radio frequency (RF) pulses. In contrast to MS CAIPIRINHA, 2D CAIPIRINHA does not require special RF pulses. Instead, aliasing in 2D parallel imaging can be controlled by modifying the phase encoding sampling strategy. This is done by shifting sampling positions from their normal positions in the under-sampled 2D phase encoding scheme. Using this modified sampling strategy, coil sensitivity variations can be exploited more efficiently in multiple dimensions, resulting in a more robust parallel imaging reconstruction.

Humans↗

PubMed2006

Direct parallel image reconstructions for spiral trajectories using GRAPPA.

The use of spiral trajectories is an efficient way to cover a desired k-space partition in magnetic resonance imaging (MRI). Compared to conventional Cartesian k-space sampling, it allows faster acquisitions and results in a slight reduction of the high gradient demand in fast dynamic scans, such as in functional MRI (fMRI). However, spiral images are more susceptible to off-resonance effects that cause blurring artifacts and distortions of the point-spread function (PSF), and thereby degrade the image quality. Since off-resonance effects scale with the readout duration, the respective artifacts can be reduced by shortening the readout trajectory. Multishot experiments represent one approach to reduce these artifacts in spiral imaging, but result in longer scan times and potentially increased flow and motion artifacts. Parallel imaging methods are another promising approach to improve image quality through an increase in the acquisition speed. However, non-Cartesian parallel image reconstructions are known to be computationally time-consuming, which is prohibitive for clinical applications. In this study a new and fast approach for parallel image reconstructions for spiral imaging based on the generalized autocalibrating partially parallel acquisitions (GRAPPA) methodology is presented. With this approach the computational burden is reduced such that it becomes comparable to that needed in accelerated Cartesian procedures. The respective spiral images with two- to eightfold acceleration clearly benefit from the advantages of parallel imaging, such as enabling parallel MRI single-shot spiral imaging with the off-resonance behavior of multishot acquisitions.

Algorithms↗

PubMed2006

2D-GRAPPA-operator for faster 3D parallel MRI.

When using parallel MRI (pMRI) methods in combination with three-dimensional (3D) imaging, it is beneficial to subsample the k-space along both phase-encoding directions because one can then take advantage of coil sensitivity variations along two spatial dimensions. This results in an improved reconstruction quality and therefore allows greater scan time reductions as compared to subsampling along one dimension. In this work we present a new approach based on the generalized autocalibrating partially parallel acquisitions (GRAPPA) technique that allows Fourier-domain reconstructions of data sets that are subsampled along two dimensions. The method works by splitting the 2D reconstruction process into two separate 1D reconstructions. This approach is compared with an extension of the conventional GRAPPA method that directly regenerates missing data points of a 2D subsampled k-space by performing a linear combination of acquired data points. In this paper we describe the theoretical background and present computer simulations and in vivo experiments.

Adult↗

PubMed2006

Autocalibrated coil sensitivity estimation for parallel imaging.

Parallel imaging has proven to be a robust solution to the problem of acquisition speed in MRI. These methods are based on extracting spatial information from an array of multiple surface coils in order to speed up image acquisition. One of the most essential elements of any parallel imaging method is the information describing the coil sensitivity distribution throughout the sample. This paper covers some of the advanced methods to obtain coil sensitivity-related information, focusing particularly on the class of methods referred to as autocalibrating. These methods all acquire the data for coil sensitivity estimation directly before, during or directly after the reduced data acquisition. After a review of standard methods for coil sensitivity estimation, some of the basic and advanced autocalibrating methods are reviewed, and some example applications shown.

Algorithms↗

PubMed2006

Perspectives and limitations of parallel MR imaging at high field strengths.

In medical magnetic resonance imaging (MRI) imaging, it is standard practice to use MR scanners with a field strength of 1.5 Tesla. Recently, an ongoing trend towards higher field strengths can be observed, with a new potential clinical standard of 3.0 Tesla. High-field MR imaging, with its intrinsic higher signal-to-noise ratio (SNR), can enable new applications for MRI in medical diagnosis, or can serve to improve existing methods. The use of high field MRI is not without its limitations, however. Besides SNR, other unwanted effects increase with a higher field strength. Without correction, these high field problems can cause a serious loss in image quality. An elegant way to address these problems is the use of parallel imaging. In many clinical applications, parallel MRI (pMRI) is part of the standard protocol, as pMRI can enhance virtually every MRI application without necessarily affecting the contrast behavior of the underlying imaging sequence. In addition to the speed advantages offered by pMRI, the capability of parallel imaging to reduce significant high field-specific problems, thereby improving image quality, will be of major importance.

Brain↗

PubMed2005

Controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) for multi-slice imaging.

In all current parallel imaging techniques, aliasing artifacts resulting from an undersampled acquisition are removed by means of a specialized image reconstruction algorithm. In this study a new approach termed "controlled aliasing in parallel imaging results in higher acceleration" (CAIPIRINHA) is presented. This technique modifies the appearance of aliasing artifacts during the acquisition to improve the subsequent parallel image reconstruction procedure. This new parallel multi-slice technique is more efficient compared to other multi-slice parallel imaging concepts that use only a pure postprocessing approach. In this new approach, multiple slices of arbitrary thickness and distance are excited simultaneously with the use of multi-band radiofrequency (RF) pulses similar to Hadamard pulses. These data are then undersampled, yielding superimposed slices that appear shifted with respect to each other. The shift of the aliased slices is controlled by modulating the phase of the individual slices in the multi-band excitation pulse from echo to echo. We show that the reconstruction quality of the aliased slices is better using this shift. This may potentially allow one to use higher acceleration factors than are used in techniques without this excitation scheme. Additionally, slices that have essentially the same coil sensitivity profiles can be separated with this technique.

Abdomen↗

PubMed2005

Parallel magnetic resonance imaging using the GRAPPA operator formalism.

In this article it is shown that GRAPPA reconstruction can be reformulated as a matrix operator, similar to ladder or propagator operators used in quantum mechanics, that shifts data in k-space. Using this formalism, it is shown that there exists an infinitesimal GRAPPA operator that shifts data in k-space by arbitrarily small amounts. Other desired k-space shifts can then be accomplished through repeated applications of this infinitesimal GRAPPA operator. Implications of these ideas are described.

Algorithms↗

PubMed2004

Field-of-view limitations in parallel imaging.

Parallel imaging is one of the most promising developments in recent years for the acceleration of MR acquisitions. One area of practical importance where different parallel imaging methods perform differently is the manner in which they deal with aliasing in the full-FOV reconstructed image. It has been reported that sensitivity encoding (SENSE) reconstruction fails whenever the reconstructed FOV is smaller than the object being imaged. On the other hand, generalized autocalibrating partially parallel acquisition (GRAPPA) has been used successfully to reconstruct images with aliasing in the reconstructed FOV, as in conventional imaging. The disparate behavior of these methods can be easily demonstrated by a few simple illustrative examples. Additional in vivo examples using GRAPPA and modified SENSE (mSENSE) make this distinction clear. These experiments demonstrate that SENSE fails to reconstruct correct images when coil sensitivity maps are used that do not automatically account for the object size and therefore the aliasing in the reconstructed images. However, with the use of aliased high-resolution coil sensitivity maps, accurate SENSE reconstructions can be generated. On the other hand, GRAPPA produces images with an aliasing appearance that is exactly as would be expected from normal nonaccelerated acquisitions. An understanding of these effects could potentially lead to fewer operator-dependent errors, as well as a better understanding of the differences between the underlying reconstruction processes.

Computer Simulation↗

PubMed2004

SMASH, SENSE, PILS, GRAPPA: how to choose the optimal method.

Fast imaging methods and the availability of required hardware for magnetic resonance tomography (MRT) have significantly reduced acquisition times from about an hour down to several minutes or seconds. With this development over the last 20 years, magnetic resonance imaging (MRI) has become one of the most important instruments in clinical diagnosis. In recent years, the greatest progress in further increasing imaging speed has been the development of parallel MRI (pMRI). Within the last 3 years, parallel imaging methods have become commercially available, and therefore are now available for a broad clinical use. The basic feature of pMRI is a scan time reduction, applicable to nearly any available MRI method, while maintaining the contrast behavior without requiring higher gradient system performance. Because of its faster image acquisition, pMRI can in some cases even significantly improve image quality. In the last 10 years of pMRI development, several different pMRI reconstruction methods have been set up which partially differ in their philosophy, in the mode of reconstruction as well in their advantages and drawbacks with regard to a successful image reconstruction. In this review, a brief overview is given on the advantages and disadvantages of present pMRI methods in clinical applications, and examples from different daily clinical applications are shown.

Artifacts↗

PubMed2003

A brief review of parallel magnetic resonance imaging.

Since the 1980s, the implementation of fast imaging methods and dedicated hardware for MRI scanners has reduced the image acquisition time from nearly an hour down to several seconds and has therefore enabled a widespread use of MRI in clinical diagnosis. Since this development, the greatest incremental gain in imaging speed has been provided by the development of parallel MRI (pMRI) techniques in late 1990s. Within the past 2 years, parallel imaging methods have become commercially available, which means that pMRI is now available for broad clinical use. In the clinical routine, virtually any MRI method can be enhanced by pMRI, allowing faster image acquisitions without any increased gradient system performance. In some cases pMRI can even result in a significant gain in image quality due to this faster acquisition. In this review article, the advantages and the disadvantages of pMRI in clinical applications are discussed and examples from many different daily applications are given.

Brain Neoplasms↗

PubMed2002

Generalized autocalibrating partially parallel acquisitions (GRAPPA).

In this study, a novel partially parallel acquisition (PPA) method is presented which can be used to accelerate image acquisition using an RF coil array for spatial encoding. This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD-AUTO-SMASH reconstruction techniques. As in those previous methods, a detailed, highly accurate RF field map is not needed prior to reconstruction in GRAPPA. This information is obtained from several k-space lines which are acquired in addition to the normal image acquisition. As in PILS, the GRAPPA reconstruction algorithm provides unaliased images from each component coil prior to image combination. This results in even higher SNR and better image quality since the steps of image reconstruction and image combination are performed in separate steps. After introducing the GRAPPA technique, primary focus is given to issues related to the practical implementation of GRAPPA, including the reconstruction algorithm as well as analysis of SNR in the resulting images. Finally, in vivo GRAPPA images are shown which demonstrate the utility of the technique.

Algorithms↗