Tony Stöcker

Multimodal MEMPRAGE, FLAIR, and R2* Segmentation to Resolve Dura and Vessels from Cortical Gray Matter

While widely in use in automated segmentation approaches for the detection of group differences or of changes associated with continuous predictors in gray matter volume, T1-weighted images are known to represent dura and cortical vessels with signal intensities similar to those of gray matter. By considering multiple signal sources at once, multimodal segmentation approaches may be able to resolve these different tissue classes and address this potential confound. We explored here the simultaneous use of FLAIR and apparent transverse relaxation rates (a signal related to T2* relaxation maps and having similar contrast) with T1-weighted images. Relative to T1-weighted images alone, multimodal segmentation had marked positive effects on 1. the separation of gray matter from dura, 2. the exclusion of vessels from the gray matter compartment, and 3. the contrast with extracerebral connective tissue. While obtainable together with the T1-weighted images without increasing scanning times, apparent transverse relaxation rates were less effective than added FLAIR images in providing the above mentioned advantages. FLAIR images also improved the detection of cortical matter in areas prone to susceptibility artifacts in standard MPRAGE T1-weighted images, while the addition of transverse relaxation maps exacerbated the effect of these artifacts on segmentation. Our results confirm that standard MPRAGE segmentation may overestimate gray matter volume by wrongly assigning vessels and dura to this compartment and show that multimodal approaches may greatly improve the specificity of cortical segmentation. Since multimodal segmentation is easily implemented, these benefits are immediately available to studies focusing on translational applications of structural imaging.

Comparative analysis of isotropic diffusion weighted imaging sequences.

Visualisation of living tissue structure and function is a challenging problem of modern imaging techniques. Diffusion MRI allows one to probe in vivo structures on a micrometer scale. However, conventional diffusion measurements are time-consuming procedures, because they require several measurements with different gradient directions. Considerable time savings are therefore possible by measurement schemes that generate an isotropic diffusion weighting in a single shot. Multiple approaches for generating isotropic diffusion weighting are known and have become very popular as useful tools in clinical research. Thus, there is a strong need for a comprehensive comparison of different isotropic weighting approaches. In the present work we introduce two new sequences based on simple (co)sine modulations and compare their performance to established q-space magic-angle spinning sequences and conventional DTI, using a diffusion phantom assembled from microcapillaries and in vivo experiments at 7T. The advantages and disadvantages of all compared schemes are demonstrated and discussed.

Rapid fat suppression for three-dimensional echo planar imaging with minimized specific absorption rate.

To investigate a method for rapid water excitation with minimal radiofrequency power deposition for efficient functional MRI at ultrahigh fields.

Multimodal FLAIR/MPRAGE segmentation of cerebral cortex and cortical myelin

ABSTRACT The MR signal from gray matter has been long known to present small differences in intensity that have been attributed to variations in cortical myelin content. Previous studies have shown that the T1‐, T2‐weighted signal and their ratio are sensitive to these variations. Here, we investigated different combinations of signal from MPRAGE and FLAIR images in multimodal segmentation with parametric models of signal intensity to identify a procedure for the identification of contrast in cortical gray matter and the segmentation of different cortical components at 3T. We show that a three‐modal combination of these signals delivers a stable segmentation of the cortical mantle in which two distinct components are reliably identified. The resulting intensity maps correspond well to known regional myeloarchitectural differences between cortical regions. These results confirm that widely available MR sequences contain signal that may be used to reliably detect subtle differences in the composition of gray matter with a segmentation approach. Graphical abstract Figure. No Caption available.

Application of the limited-memory quasi-Newton algorithm for multi-dimensional, large flip-angle RF pulses at 7T

ObjectiveUltrahigh field MRI provides great opportunities for medical diagnostics and research. However, ultrahigh field MRI also brings challenges, such as larger magnetic susceptibility induced field changes. Parallel-transmit radio-frequency pulses can ameliorate these complications while performing advanced tasks in routine applications. To address one class of such pulses, we propose an optimal-control algorithm as a tool for designing advanced multi-dimensional, large flip-angle, radio-frequency pulses. We contrast initial conditions, constraints, and field correction abilities against increasing pulse trajectory acceleration factors.Materials and methodsOn an 8-channel 7T system, we demonstrate the quasi-Newton algorithm with pulse designs for reduced field-of-view imaging with an oil phantom and in vivo with scans of the human brain stem. We used echo-planar imaging with 2D spatial-selective pulses. Pulses are computed sufficiently rapid for routine applications.ResultsOur dataset was quantitatively analyzed with the conventional mean-square-error metric and the structural-similarity index from image processing. Analysis of both full and reduced field-of-view scans benefit from utilizing both complementary measures.ConclusionWe obtained excellent outer-volume suppression with our proposed method, thus enabling reduced field-of-view imaging using pulse trajectory acceleration factors up to 4.

Accelerated 3D-GRASE imaging improves quantitative multiple post labeling delay arterial spin labeling

To investigate the impact of accelerated, single‐shot 3D‐GRASE acquisition on quantitative arterial spin labeling (ASL) with multiple and single post‐labeling delay (PLD) in terms of perfusion‐weighted SNR per unit scan time (TSNRPW) and quantification accuracy.

SAR and scan-time optimized 3D whole-brain double inversion recovery imaging at 7T

The aim of this project was to implement an ultra‐high field (UHF) optimized double inversion recovery (DIR) sequence for gray matter (GM) imaging, enabling whole brain coverage in short acquisition times ( ≈ 5 min, image resolution 1 mm3).

GRAPPA reconstructed wave-CAIPI MP-RAGE at 7 Tesla

The aim of this project was to develop a GRAPPA‐based reconstruction for wave‐CAIPI data. Wave‐CAIPI fully exploits the 3D coil sensitivity variations by combining corkscrew k‐space trajectories with CAIPIRINHA sampling. It reduces artifacts and limits reconstruction induced spatially varying noise enhancement. The GRAPPA‐based wave‐CAIPI method is robust and does not depend on the accuracy of coil sensitivity estimations.

Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging

Mapping non-invasively the complex microstructural architecture of the living human brain, diffusion magnetic resonance imaging (dMRI) is one of the core imaging modalities in current population studies. For the application in longitudinal population imaging, the dMRI protocol should deliver reliable data with maximum potential for future analysis. With the recent introduction of novel MRI hardware, advanced dMRI acquisition strategies can be applied within reasonable scan time. In this work we conducted a pilot study based on the requirements for high resolution dMRI in a long-term and high throughput population study. The key question was: can diffusion spectrum imaging accelerated by compressed sensing theory (CS-DSI) be used as an advanced imaging protocol for microstructure dMRI in a long-term population imaging study? As a minimum requirement we expected a high level of agreement of several diffusion metrics derived from both CS-DSI and a 3-shell high angular resolution diffusion imaging (HARDI) acquisition, an established imaging strategy used in other population studies. A wide spectrum of state-of-the-art diffusion processing and analysis techniques was applied to the pilot study data including quantitative diffusion and microstructural parameter mapping, fiber orientation estimation and white matter fiber tracking. When considering diffusion weighted images up to the same maximum diffusion weighting for both protocols, group analysis across 20 subjects indicates that CS-DSI performs comparable to 3-shell HARDI in the estimation of diffusion and microstructural parameters. Further, both protocols provide similar results in the estimation of fiber orientations and for local fiber tracking. CS-DSI provides high radial resolution while maintaining high angular resolution and it is well-suited for analysis strategies that require high b-value acquisitions, such as CHARMED modeling and biomarkers from the diffusion propagator.