Michael Erb

Für die präoperative Planung werden neben den strukturellen Bildern aus der Computertomographie (CT) und Magnetresonanztomographie (MRT) auch funktionelle Daten über die Lokalisation der an verschiedenen Aufgaben beteiligten Hirngebiete immer wichtiger. Es können vor allem primäre sensorische und motorische Areale dargestellt werden, aber auch die an höheren kognitiven Funktionen, wie Sprache und Gedächtnis, beteiligten Hirnstrukturen. Um diese Information richtig einschätzen zu können, muss man sich der Variabilität der Aktivierungsmuster abhängig von der gewählten statistischen Schwelle bewusst sein. Insbesondere bedeutet das Verfehlen des Signifikanzniveaus an einer Stelle nicht automatisch, dass dieser Bereich nicht die untersuchte Funktion hat. Die Zuverlässigkeit der Messungen hängt von der Effizienz des experimentellen Designs und der Kooperation des Patienten ab. Daher sind kurze, einfache Aufgaben, die im Blockdesign durchgeführt werden können, zu bevorzugen. Die so gewonnenen Informationen über die Lokalisation von Funktionen können zur Operationsplanung herangezogen werden. Die intraoperative Verwendung im Neuronavigationssystem ist vor allem durch die Gehirnverschiebung auf Grund des Öffnens des Schädels (Brain-Shift) problematisch. Intraoperative Bildgebung mit dynamischer Anpassung der präoperativ akquirierten Daten durch nichtlineare Deformationsalgorithmen kann hier den Wert dieser Informationen in Zukunft deutlich steigern.Beside structural images from CT and MR, functional data about localization of brain activations with different tasks becomes more and more important for presurgical planning. With this method, it's possible to depict mainly primary sensory and motoric areas, but also higher functions like speech and memory. To judge this information adequately, one has to be aware of the variability of activation pattern dependent on chosen threshold. Especially, the absence of such activation at a given location does not necessary mean that this area has no function. The reliability of a measurement strongly depends on efficiency of experimental design and cooperation of the patient. Therefore, short and easy tasks which can be performed in a block design should be preferred. Information about localization of functions determined by fMRI can mainly be used for presurgical planning. Intraoperative usage in the navigation system is problematic due to the brain shift. Therefore, intraoperative imaging together with dynamic adaptation using nonlinear deformation algorithms may improve the value of fMRI in the future.

To systematically evaluate image characteristics of simultaneous-multislice (SMS)-accelerated diffusion-weighted imaging (DWI) of the liver using different breathing schemes in comparison to standard sequences. DWI of the liver was performed in 10 healthy volunteers and 12 patients at 1.5T using an SMS-accelerated echo planar imaging sequence performed with respiratory-triggering and free breathing (SMS-RT, SMS-FB). Standard DWI sequences served as reference (STD-RT, STD-FB). Reduction of scan time by SMS-acceleration was measured. Image characteristics of SMS-DWI and STD-DWI with both breathing schemes were analyzed quantitatively (apparent diffusion coefficient [ADC], signal-to-noise ratio [SNR]) and qualitatively (5-point Likert scale, 5 = excellent). Qualitative and quantitative parameters were compared using Friedman test and Dunn-Bonferroni post-hoc method with P-values < 0.05 considered statistically significant. SMS-DWI provided diagnostic image quality in volunteers and ...

In localized in vivo proton NMR spectroscopy (1H MRS) of the human brain, it often cannot be avoided that the selected volume of interest (voxel) includes both gray matter (GM) and white matter (WM). Since the spectra of GM and WM differ, in general, the acquired spectrum represents a mixed spectrum that depends on the tissue composition inside the voxel. This study describes a method that enables the determination of pure GM spectra and pure WM spectra from mixed spectra. The pure tissue spectra are calculated from measured spectra acquired from several voxels with different mixed tissue compositions. For this purpose, the tissue composition in the voxels must be known. It is determined by segmentation of an additionally acquired 3D image data set with higher spatial resolution. In volunteer examinations, measurements were performed in different regions of the cerebrum, cerebellum, and thalamus. In all examined brain regions, particularly in the cerebellum, clear differences were found between the spectra of WM and GM. The detected differences in the spectra of WM and GM indicate that the tissue composition in the voxel has to be considered in patient studies, in order to distinguish pathological alterations in the spectra from the effects of tissue composition.

The present study combines functional magnetic resonance imaging (fMRI) and reaction time (RT) measurements to further elucidate the influence of syllable frequency and complexity on speech motor control processes, i.e., overt reading of pseudowords. Tying in with a recent fMRI-study of our group we focused on the concept of a mental syllabary housing syllable sized ready-made motor plans for high- (HF), but not low-frequency (LF) syllables. The RT-analysis disclosed a frequency effect weakened by a simultaneous complexity effect for HF-syllables. In contrast, the fMRI data revealed no effect of syllable frequency, but point to an impact of syllable structure: Compared with CV-items, syllables with a complex onset (CCV) yielded higher hemodynamic activation in motor "execution" areas (left sensorimotor cortex, right inferior cerebellum), which is at least partially compatible with our previous study. We discuss the role of the syllable in speech motor control.

Synopsis: In proton MR spectroscopy of the human brain, it is often difficult to select voxels that contain only one tissue type, such as gray matter (GM) or white matter (WM), due to relatively large voxel sizes. In this study, metabolite concentrations in pure GM and pure WM were calculated from the values obtained from short TE spectra of voxels with mixed tissue components. The tissue composition was determined by image segmentation. Significant differences between GM and WM were found for most of the major metabolites in the parietal region and the cerebellum. Methods: Examinations were performed on a 1.5 T whole-body imager (Magnetom Sonata, Siemens). Short-TE PRESS spectra (TE 30 ms, TR 3,000 ms, 64 acquisitions) were measured in the parietal region and in the cerebellum of nine healthy volunteers. In each of these brain regions, two volumes of interest (VOIs or voxels) of (2 cm) 3 were used, one of them containing mainly gray matter, the other mainly white matter (see Fig. 1...

ABSTRACT MR diffusion tensor imaging (DTI) allows the visualization of location and course of brain fiber bundles. To obtain these results, however, special evaluation techniques are necessary in addition to image acquisition and reconstruction. These include first the calculation of a preferential diffusional direction of water molecules in each voxel, and then the tracking of brain fibers or segmentation of regions with similar fiber directions. In both cases, the procedures available thus far require the interactive definition of seed points. In this paper, we propose a method to segment voxel groups of connected data points without the need of setting seed points. This method is based first on the identification of all voxels of a brain volume with a sufficiently unique preferential diffusional direction and with interconnection. For each selected voxel, neighboring voxels are then identified that have a small deviation from the chosen preferential direction and can therefore be grouped with this point. Finally, the largest partial volumes determined in this way are marked and color-coded to present them as three-dimensional structures. The present method was applied to a DTI data set of a healthy female volunteer, resulting in a largely automatic subdivision of the white matter in the brain in a number of bilateral partial volumes.

To assess the impact of colored noise on statistics in event-related functional MRI (fMRI) (visual stimulation using checkerboards) acquired by simultaneous multislice imaging enabling repetition times (TRs) between 2.64 to 0.26 s. T-values within the visual cortex obtained with analysis tools that assume a first-order autoregressive plus white noise process (AR(1)+w) with a fixed AR coefficient versus higher-order AR models with spatially varying AR coefficients were compared. In addition, dependency of T-values on correction of physiological noise (respiration, heart rate) was evaluated. Optimal statistical power was obtained for a TR of 0.33 s, but T-values as obtained by AR(1)+w models were strongly dependent on the predefined AR coefficients in fMRI with short TRs which required higher-order AR models to achieve stable statistics. Direct estimation of AR coefficients revealed the highest values within the default mode network while physiological noise had little influence on statistics in cortical structures. Colored noise in event-related fMRI obtained at short TRs originates mainly from neural sources and calls for more sophisticated correction of serial autocorrelations which cannot be achieved with standard methods relying on AR(1)+w models with globally fixed AR coefficients. Magn Reson Med, 2016. © 2016 Wiley Periodicals, Inc.

The purpose of the study was to develop a measuring technique, which allows the investigation of brainstem and auditory cortex activation after application of auditory stimuli by functional magnetic resonance imaging (fMRI). In addition to the conventional t-test analysis, a correlation analysis using, the signal in the acoustical cortex was applied. Eight healthy volunteers were examined on 3T scanner (Trio Tim, Siemens, Erlangen, Germany) with pure tones and music stimulation. Cortical and subcortical auditory structures were successfully visualized. Such investigation showed similar behavior comparing the both kind of created maps T and correlation. Maps of correlation demonstrated additional localization of brainstem structures which were not able to obtain after statistical analysis. These results demonstrate a tight functional relation between subcortical and cortical areas in the human brain.

Dynamic causal modeling (DCM) is a method to non-invasively assess effective connectivity between brain regions. 'Musicogenic epilepsy' is a rare reflex epilepsy syndrome in which seizures can be elicited by musical stimuli and thus represents a unique possibility to investigate complex human brain networks and test connectivity analysis tools. We investigated effective connectivity in a case of musicogenic epilepsy using DCM for fMRI, high-density (hd-) EEG and MEG and validated results with intracranial EEG recordings. A patient with musicogenic seizures was examined using hd-EEG/fMRI and simultaneous '256-channel hd-EEG'/'whole head MEG' to characterize the epileptogenic focus and propagation effects using source analysis techniques and DCM. Results were validated with invasive EEG recordings. We recorded one seizure with hd-EEG/fMRI and four auras with hd-EEG/MEG. During the seizures, increases of activity could be observed in the right mesial temporal re...

MR diffusion tensor imaging (DTI) allows the visualization of location and course of brain fiber bundles. To obtain these results, however, special evaluation techniques are necessary in addition to image acquisition and reconstruction. These include first the calculation of a preferential diffusional direction of water molecules in each voxel and then the tracking of brain fibers or segmentation of regions with similar fiber directions. In both cases, the procedures available thus far require the interactive definition of seed points. In this paper, we propose a method to segment voxel groups of connected data points without the need of setting seed points. This method is based first on the identification of all voxels of a brain volume with a sufficiently unique preferential diffusional direction and with interconnection. For each selected voxel, neighboring voxels are then identified that have a small deviation from the chosen preferential direction and can therefore be grouped w...