Cornelius Eichner

Slice accelerated diffusion‐weighted imaging at ultra‐high field strength

Diffusion magnetic resonance imaging (dMRI) data with very high isotropic resolution can be obtained at 7T. However, for extensive brain coverage, a large number of slices is required, resulting in long acquisition times (TAs). Recording multiple slices simultaneously (SMS) promises to reduce the TA.

A low power radiofrequency pulse for simultaneous multislice excitation and refocusing

Simultaneous multislice (SMS) acquisition enables increased temporal efficiency of MRI. Nonetheless, MultiBand (MB) radiofrequency (RF) pulses used for SMS can cause large energy deposition. Power independent of number of slices (PINS) pulses reduce RF power at cost of reduced bandwidth and increased off‐resonance dependency. This work improves PINS design to further reduce energy deposition, off‐resonance dependency and peak power.

RARE/turbo spin echo imaging with simultaneous multislice Wave-CAIPI

To enable highly accelerated RARE/Turbo Spin Echo (TSE) imaging using Simultaneous MultiSlice (SMS) Wave‐CAIPI acquisition with reduced g‐factor penalty.

Real diffusion-weighted MRI enabling true signal averaging and increased diffusion contrast.

This project aims to characterize the impact of underlying noise distributions on diffusion-weighted imaging. The noise floor is a well-known problem for traditional magnitude-based diffusion-weighted MRI (dMRI) data, leading to biased diffusion model fits and inaccurate signal averaging. Here, we introduce a total-variation-based algorithm to eliminate shot-to-shot phase variations of complex-valued diffusion data with the intention to extract real-valued dMRI datasets. The obtained real-valued diffusion data are no longer superimposed by a noise floor but instead by a zero-mean Gaussian noise distribution, yielding dMRI data without signal bias. We acquired high-resolution dMRI data with strong diffusion weighting and, thus, low signal-to-noise ratio. Both the extracted real-valued and traditional magnitude data were compared regarding signal averaging, diffusion model fitting and accuracy in resolving crossing fibers. Our results clearly indicate that real-valued diffusion data enables idealized conditions for signal averaging. Furthermore, the proposed method enables unbiased use of widely employed linear least squares estimators for model fitting and demonstrates an increased sensitivity to detect secondary fiber directions with reduced angular error. The use of phase-corrected, real-valued data for dMRI will therefore help to clear the way for more detailed and accurate studies of white matter microstructure and structural connectivity on a fine scale.

Slice accelerated gradient-echo spin-echo dynamic susceptibility contrast imaging with blipped CAIPI for increased slice coverage

To improve slice coverage of gradient echo spin echo (GESE) sequences for dynamic susceptibility contrast (DSC) MRI using a simultaneous‐multiple‐slice (SMS) method.

Toward an In Vivo Neuroimaging Template of Human Brainstem Nuclei of the Ascending Arousal, Autonomic, and Motor Systems

Brainstem nuclei (Bn) in humans play a crucial role in vital functions, such as arousal, autonomic homeostasis, sensory and motor relay, nociception, sleep, and cranial nerve function, and they have been implicated in a vast array of brain pathologies. However, an in vivo delineation of most human Bn has been elusive because of limited sensitivity and contrast for detecting these small regions using standard neuroimaging methods. To precisely identify several human Bn in vivo, we employed a 7 Tesla scanner equipped with multi-channel receive-coil array, which provided high magnetic resonance imaging sensitivity, and a multi-contrast (diffusion fractional anisotropy and T2-weighted) echo-planar-imaging approach, which provided complementary contrasts for Bn anatomy with matched geometric distortions and resolution. Through a combined examination of 1.3 mm(3) multi-contrast anatomical images acquired in healthy human adults, we semi-automatically generated in vivo probabilistic Bn labels of the ascending arousal (median and dorsal raphe), autonomic (raphe magnus, periaqueductal gray), and motor (inferior olivary nuclei, two subregions of the substantia nigra compatible with pars compacta and pars reticulata, two subregions of the red nucleus, and, in the diencephalon, two subregions of the subthalamic nucleus) systems. These labels constitute a first step toward the development of an in vivo neuroimaging template of Bn in standard space to facilitate future clinical and research investigations of human brainstem function and pathology. Proof-of-concept clinical use of this template is demonstrated in a minimally conscious patient with traumatic brainstem hemorrhages precisely localized to the raphe Bn involved in arousal.

Rapid high spatial resolution diffusion MRI at 7 Tesla using simultaneous multislice acquisition

Diffusion weighted MRI (dMRI) data with very high spatial resolution can be obtained using ultra high magnetic field strength MRI such as 7 Tesla(T). However, for extensive brain coverage a large number of imaging slices are required, which can result in long acquisition times (TA). Simultaneous Multi-Slice (SMS) acquisition technology enables increased temporal efficiency of MRI to permit rapid acquisition of dMRI. However, Multiband (MB) RF-pulses used for SMS acquisition can cause large energy deposition into the subject and limit the rate at which data can be acquired. Power Independent of Number of Slices (PINS) pulses can be used instead of MB pulse to reduce RF-power. However, this comes at a cost of reduced bandwidth and increased off-resonance dependency, which degrades image quality. We proposed a new RF pulse design, MultiPINS, by combining MB with PINS RF pulses to further decrease RF energy and/or shorten pulse lengths. Employing SMS technology and PINS/MultiPINS pulses, in-vivo dMRI results were recorded at high spatial resolutions at 7 T. The data shows that this method enables a 3-fold scan time reduction while preserving image quality.