PubMed Health⌕ Search

Biomedical subjects

Mathias Nittka

Publications and source records attributed to Mathias Nittka.

3 recordsLinked to original sources

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↗

Renal MR angiography: current debates and developments in imaging of renal artery stenosis.

Because of its safety and robustness with reproducible image quality, three-dimensional gadolinium-enhanced magnetic resonance angiography (3D-Gd-MRA) has been widely established as a diagnostic tool for screening and grading of renal artery stenosis. Accuracy and superiority over other noninvasive imaging procedures was again demonstrated in two recent meta-analyses. However, ambiguous results on the accuracy of this technique have been reported recently, again questioning the sole role of this modality for diagnostic assessment of the renal arteries. The main deficiencies of the technique are limited spatial resolution, high interobserver variability, limited anatomic coverage, as well as inability to assess the stenosis site after stent placement. In addition, a high level of competition has been introduced by techniques such as 16 detector multislice computed tomography, which generates superb image quality, with broad anatomic coverage and high spatial resolution, with minimal technical complexity. Lastly, aggressive search for renal artery stenosis by angiographic techniques in patients with hypertension is of debate, since only a limited percentage of these patients benefit from interventions. In this article, a comprehensive approach to high-resolution 3D-Gd-MRA, using parallel imaging in combination with cardiac-gated, phase-contrast flow measurements, is reviewed. This review is based on various studies and articles that address many of the problems of 3D-Gd-MRA. By making use of maximum spatial resolution and additional functional data, MRI permits accurate detection and grading of renal artery stenosis in most cases, with acceptable interobserver variability.

Contrast Media↗

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↗