Automatic Segmentation of Human Cortical Layer-Complexes and Architectural Areas Using Ex vivo Diffusion MRI and Its Validation

Recently, several magnetic resonance imaging contrast mechanisms have been shown to distinguish cortical substructure corresponding to selected cortical layers. Here, we investigate cortical layer and area differentiation by automatized unsupervised clustering of high-resolution diffusion MRI data. Several groups of adjacent layers could be distinguished in human primary motor and premotor cortex. We then used the signature of diffusion MRI signals along cortical depth as a criterion to detect area boundaries and find borders at which the signature changes abruptly. We validate our clustering results by histological analysis of the same tissue. These results confirm earlier studies which show that diffusion MRI can probe layer-specific intracortical fiber organization and, moreover, suggests that it contains enough information to automatically classify architecturally distinct cortical areas. We discuss the strengths and weaknesses of the automatic clustering approach and its appeal for MR-based cortical histology

9.4 T small animal MRI using clinical components for direct translational studies

BackgroundMagnetic resonance is a major preclinical and clinical imaging modality ideally suited for longitudinal studies, e.g. in pharmacological developments. The lack of a proven platform that maintains an identical imaging protocol between preclinical and clinical platforms is solved with the construction of an animal scanner based on clinical hard- and software.MethodsA small animal magnet and gradient system were connected to a clinical MR system. Several hardware components were either modified or built in-house to achieve compatibility. The clinical software was modified to account for the different field-of-view of a preclinical MR system. The established scanner was evaluated using clinical QA protocols, and platform compatibility for translational research was verified against clinical scanners of different field strength.ResultsThe constructed animal scanner operates with the majority of clinical imaging sequences. Translational research is greatly facilitated as protocols can be shared between preclinical and clinical platforms. Hence, when maintaining sequences parameters, maximum similarity between pulses played out on a human or an animal system is maintained.ConclusionCoupling of a small animal magnet with a clinical MR system is a flexible, easy to use way to establish and advance translational imaging capability. It provides cost and labor efficient translational capability as no tedious sequence reprogramming between moieties is required and cross-platform compatibility of sequences facilitates multi-center studies

MR-Based PET Motion Correction Procedure for Simultaneous MR-PET Neuroimaging of Human Brain

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Design and Construction of a PET-Compatible Double-Tuned 1H/31P MR Head Coil

Simultaneous MR-PET is an increasingly popular multimodal imaging technique that is able to combine metabolic information obtained from PET with anatomical/functional information from MRI. One of the key technological challenges of the technique is the integration of a PET-transparent MR coil system, a solution to which is demonstrated here for a double-tuned 1 H/ 31 P head coil at 3 T. Two single-resonant birdcage coils tuned to the 1 H and 31 P resonances were arranged in an interleaved fashion and electrically decoupled with the use of trap circuits. All high 511 keV quanta absorbing components were arranged outside the PET field-of-view in order to minimize count rate reduction. The materials inside the PET field-of-view were carefully evaluated and chosen for minimum impact on the PET image quality. As far as possible, the coil case was geometrically optimized to avoid sharp transitions in attenuation, which may potentially result in streaking artefacts during PET image reconstruction. The coil caused a count rate loss of just above 5% when inserted into the PET detector ring. Except for the anterior region, which was designed to maintain free openings for increased patient comfort, an almost uniform distribution of 511 keV attenuation was maintained around the circumference of the coil. MR-related performance for both nuclei was similar or slightly better than that of a commercial double-tuned coil, despite the MR-PET coil having a close-fitting RF screen to shield the PET and MR electronics from possible electromagnetic interferences

[18F]Altanserin and small animal PET: Impact of multidrug efflux transporters on ligand brain uptake and subsequent quantification of 5-HT2A receptor densities in the rat brain

The selective 5-hydroxytryptamine type 2a receptor (5-HT2AR) radiotracer [18F]altanserin is a promising ligand for in vivo brain imaging in rodents. However, [18F]altanserin is a substrate of P-glycoprotein (P-gp) in rats. Its applicability might therefore be constrained by both a differential expression of P-gp under pathological conditions, e.g. epilepsy, and its relatively low cerebral uptake. The aim of the present study was therefore twofold: (i) to investigate whether inhibition of multidrug transporters (MDT) is suitable to enhance the cerebral uptake of [18F]altanserin in vivo and (ii) to test different pharmacokinetic, particularly reference tissue-based models for exact quantification of 5-HT2AR densities in the rat brain

Mapping tissue sodium concentration in the human brain: A comparison of MR sequences at 9.4Tesla

Sodium is the second most abundant MR-active nucleus in the human body and is of fundamental importance for the function of cells. Previous studies have shown that many pathophysiological conditions induce an increase of the average tissue sodium concentration. To date, several MR sequences have been used to measure sodium. The aim of this study was to evaluate the performance and suitability of five different MR sequences for quantitative sodium imaging on a whole-body 9.4 Tesla MR scanner. Numerical simulations, phantom experiments and in vivo imaging on healthy subjects were carried out. The results demonstrate that, of these five sequences, the Twisted Projection Imaging sequence is optimal for quantitative sodium imaging, as it combines a number of features which are particularly relevant in order to obtain high quality quantitative images of sodium. These include: ultra-short echo times, efficient k-space sampling, and robustness against off-resonance effects. Mapping of sodium in the human brain is a technique not yet fully explored in neuroscience. Ultra-high field sodium MRI may provide new insights into the pathogenesis of neurological disorders, and may help to develop new and disease-specific biomarkers for the early diagnosis and therapeutic intervention before irreversible brain damage has taken place

EEG acquisition in ultra-high static magnetic fields up to 9.4T

The simultaneous acquisition of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data has gained momentum in recent years due to the synergistic effects of the two modalities with regard to temporal and spatial resolution. Currently, only EEG-data recorded in fields of up to 7T have been reported. We investigated the feasibility of recording EEG inside a 9.4T static magnetic field, specifically to determine whether meaningful EEG information could be recovered from the data after removal of the cardiac-related artefact. EEG-data were recorded reliably and reproducibly at 9.4T and the cardiac-related artefact increased in amplitude with increasing B0, as expected. Furthermore, we were able to correct for the cardiac-related artefact and identify auditory event related responses at 9.4T in 75% of subjects using independent component analysis (ICA). Also by means of ICA we detected event related spectral perturbations (ERSP) in subjects at 9.4T in response to opening/closing the eyes comparable with the response at 0T. Overall our results suggest that it is possible to record meaningful EEG data at ultra-high magnetic fields. The simultaneous EEG-fMRI approach at ultra-high-fields opens up the horizon for investigating brain dynamics at a superb spatial resolution and a temporal resolution in the millisecond domain

B0 insensitive multiple-quantum resolved sodium imaging using a phase-rotation scheme

Triple-quantum filtering has been suggested as a mechanism to differentiate signals from different physiological compartments. However, the filtering method is sensitive to static field inhomogeneities because different coherence pathways may interfere destructively. Previously suggested methods employed additional phase-cycles to separately acquire pathways. Whilst this removes the signal dropouts, it reduces the signal-to-noise per unit time. In this work we suggest the use of a phase-rotation scheme to simultaneously acquire all coherence pathways and then separate them via Fourier transform. Hence the method yields single-, double- and triple-quantum filtered images. The phase-rotation requires a minimum of 36 instead of six cycling steps. However, destructive interference is circumvented whilst maintaining full signal-to-noise efficiency for all coherences

Automatic segmentation of human cortical layer-complexes and architectural areas using ex vivo diffusion MRI and its validation

Recently, several magnetic resonance imaging contrast mechanisms have been shown to distinguish cortical substructure corresponding to selected cortical layers. Here, we investigate cortical layer and area differentiation by automatized unsupervised clustering of high-resolution diffusion MRI data. Several groups of adjacent layers could be distinguished in human primary motor and premotor cortex. We then used the signature of diffusion MRI signals along cortical depth as a criterion to detect area boundaries and find borders at which the signature changes abruptly. We validate our clustering results by histological analysis of the same tissue. These results confirm earlier studies which show that diffusion MRI can probe layer-specific intracortical fiber organization and, moreover, suggests that it contains enough information to automatically classify architecturally distinct cortical areas. We discuss the strengths and weaknesses of the automatic clustering approach and its appeal for MR-based cortical histology