A silent gradient axis for soundless spatial encoding to enable fast and quiet brain imaging

Purpose: A novel silent imaging method is proposed that combines a gradient insert oscillating at the inaudible frequency 20 kHz with slew rate-limited gradient waveforms to form a silent gradient axis that enable quiet and fast imaging. Methods: The gradient insert consisted of a plug-and-play (45 kg) single axis z-gradient, which operated as an additional fourth gradient axis. This insert was made resonant using capacitors and combined with an audio amplifier to allow for operation at 20 kHz. The gradient field was characterized using field measurements and the physiological effects of operating a gradient field at 20 kHz were explored using peripheral nerve stimulation experiments, tissue heating simulations and sound measurements. The imaging sequence consisted of a modified gradient-echo sequence which fills k-space in readout lanes with a width proportional to the oscillating gradient amplitude. The feasibility of the method was demonstrated in-vivo using 2D and 3D gradient echo (GRE) sequences which were reconstructed using a conjugate-gradient SENSE reconstruction. Results: Field measurements yielded a maximum gradient amplitude and slew rate of 40.8 mT/m and 5178T/m/s at 20 kHz. Physiological effects such as peripheral nerve stimulation and tissue heating were found not to be limiting at this amplitude and slew rate. For a 3D GRE sequence, a maximum sound level of 85 db(A) was measured during scanning. Imaging experiments using the silent gradient axis produced artifact free images while also featuring a 5.3-fold shorter scan time than a fully sampled acquisition. Conclusion: A silent gradient axis provides a novel pathway to fast and quiet brain imaging

A silent echo-planar spectroscopic imaging readout with high spectral bandwidth MRSI using an ultrasonic gradient axis

Purpose: We present a novel silent echo-planar spectroscopic imaging (EPSI) readout, which uses an ultrasonic gradient insert to accelerate MRSI while producing a high spectral bandwidth (20 kHz) and a low sound level. Methods: The ultrasonic gradient insert consisted of a single-axis (z-direction) plug-and-play gradient coil, powered by an audio amplifier, and produced 40 mT/m at 20 kHz. The silent EPSI readout was implemented in a phase-encoded MRSI acquisition. Here, the additional spatial encoding provided by this silent EPSI readout was used to reduce the number of phase-encoding steps. Spectroscopic acquisitions using phase-encoded MRSI, a conventional EPSI-readout, and the silent EPSI readout were performed on a phantom containing metabolites with resonance frequencies in the ppm range of brain metabolites (0–4 ppm). These acquisitions were used to determine sound levels, showcase the high spectral bandwidth of the silent EPSI readout, and determine the SNR efficiency and the scan efficiency. Results: The silent EPSI readout featured a 19-dB lower sound level than a conventional EPSI readout while featuring a high spectral bandwidth of 20 kHz without spectral ghosting artifacts. Compared with phase-encoded MRSI, the silent EPSI readout provided a 4.5-fold reduction in scan time. In addition, the scan efficiency of the silent EPSI readout was higher (82.5% vs. 51.5%) than the conventional EPSI readout. Conclusions: We have for the first time demonstrated a silent spectroscopic imaging readout with a high spectral bandwidth and low sound level. This sound reduction provided by the silent readout is expected to have applications in sound-sensitive patient groups, whereas the high spectral bandwidth could benefit ultrahigh-field MR systems

High SNR full brain relaxometry at 7T by accelerated MR-STAT

Purpose: To demonstrate the feasibility and robustness of the Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) framework for fast, high SNR relaxometry at 7T. Methods: To deploy MR-STAT on 7T-systems, we designed optimized flip-angles using the BLAKJac-framework that incorporates the SAR-constraints. Transmit RF-inhomogeneities were mitigated by including a measured (Formula presented.) -map in the reconstruction. Experiments were performed on a gel-phantom and on five volunteers to explore the robustness of the sequence and its sensitivity to (Formula presented.) inhomogeneities. The SNR-gain at 7T was explored by comparing phantom and in vivo results to MR-STAT at 3T in terms of SNR-efficiency. Results: The higher SNR at 7T enabled two-fold acceleration with respect to current 2D MR-STAT protocols at lower field strengths. The resulting scan had whole-brain coverage, with 1 x 1 x 3 mm3 resolution (1.5 mm slice-gap) and was acquired within 3 min including the (Formula presented.) -mapping. After (Formula presented.) -correction, the estimated T1 and T2 in a phantom showed a mean relative error of, respectively, 1.7% and 4.4%. In vivo, the estimated T1 and T2 in gray and white matter corresponded to the range of values reported in literature with a variation over the subjects of 1.0%–2.1% (WM-GM) for T1 and 4.3%–5.3% (WM-GM) for T2. We measured a higher SNR-efficiency at 7T (R = 2) than at 3T for both T1 and T2 with, respectively, a 4.1 and 2.3 times increase in SNR-efficiency. Conclusion: We presented an accelerated version of MR-STAT tailored to high field (7T) MRI using a low-SAR flip-angle train and showed high quality parameter maps with an increased SNR-efficiency compared to MR-STAT at 3T

A three-dimensional Magnetic Resonance Spin Tomography in Time-domain protocol for high-resolution multiparametric quantitative magnetic resonance imaging

Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) is a multiparametric quantitative MR framework, which allows for simultaneously acquiring quantitative tissue parameters such as T1, T2, and proton density from one single short scan. A typical two-dimensional (2D) MR-STAT acquisition uses a gradient-spoiled, gradient-echo sequence with a slowly varying RF flip-angle train and Cartesian readouts, and the quantitative tissue maps are reconstructed by an iterative, model-based optimization algorithm. In this work, we design a three-dimensional (3D) MR-STAT framework based on previous 2D work, in order to achieve better image signal-to-noise ratio, higher though-plane resolution, and better tissue characterization. Specifically, we design a 7-min, high-resolution 3D MR-STAT sequence, and the corresponding two-step reconstruction algorithm for the large-scale dataset. To reduce the long acquisition time, Cartesian undersampling strategies such as SENSE are adopted in our transient-state quantitative framework. To reduce the computational burden, a data-splitting scheme is designed for decoupling the 3D reconstruction problem into independent 2D reconstructions. The proposed 3D framework is validated by numerical simulations, phantom experiments, and in vivo experiments. High-quality knee quantitative maps with 0.8 × 0.8 × 1.5 mm 3 resolution and bilateral lower leg maps with 1.6 mm isotropic resolution can be acquired using the proposed 7-min acquisition sequence and the 3-min-per-slice decoupled reconstruction algorithm. The proposed 3D MR-STAT framework could have wide clinical applications in the future

Efficient Double Fragmentation ChIP-seq Provides Nucleotide Resolution Protein-DNA Binding Profiles

Immunoprecipitated crosslinked protein-DNA fragments typically range in size from several hundred to several thousand base pairs, with a significant part of chromatin being much longer than the optimal length for next-generation sequencing (NGS) procedures. Because these larger fragments may be non-random and represent relevant biology that may otherwise be missed, but also because they represent a significant fraction of the immunoprecipitated material, we designed a double-fragmentation ChIP-seq procedure. After conventional crosslinking and immunoprecipitation, chromatin is de-crosslinked and sheared a second time to concentrate fragments in the optimal size range for NGS. Besides the benefits of increased chromatin yields, the procedure also eliminates a laborious size-selection step. We show that the double-fragmentation ChIP-seq approach allows for the generation of biologically relevant genome-wide protein-DNA binding profiles from sub-nanogram amounts of TCF7L2/TCF4, TBP and H3K4me3 immunoprecipitated material. Although optimized for the AB/SOLiD platform, the same approach may be applied to other platforms

Extensive Promoter-Centered Chromatin Interactions Provide a Topological Basis for Transcription Regulation

Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIAPET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells

A plug-and-play gradient insert for fast and silent MRI

The aim of this thesis was to present a novel plug-and-play gradient insert for enhanced brain imaging and silent or ultrasonic encoding, which was designed to operate with a 7T MR-scanner. In particular, we showcased the benefits of using this gradient insert for echo-planar imaging readouts for fMRI and introduced a novel silent imaging method leveraging the fast switching capabilities of this gradient insert. Furthermore, we explored the potential use of this novel silent imaging method for acceleration and investigated its application to T1-weighted anatomical imaging and spectroscopic imaging. Chapter 2 focused on the design and characterization of the plug-and-play gradient insert. The novel design feature of this gradient insert is its ease-of-use, with only 45 kg it can be (de)-installed within 15 minutes, and its high slew rate of 1300 T/m/s. We characterized the gradient insert in terms of its field distribution, geometric distortion, minimal-echo spacing and peripheral nerve stimulation threshold. We showed that compared to a conventional setup, at least a 2-fold reduction in echo-spacing was possible while not being limited by peripheral nerve stimulation. In Chapter 3, we introduced a novel silent gradient-axis and method for sound reduction. The silent gradient-axis consisted of the gradient insert from Chapter 2, modified to be resonant at the inaudible frequency of 20 kHz. We characterized this setup in terms of PNS, SAR and sound level to showcase its safety. Furthermore, we presented an imaging sequence that uses the silent gradient-axis to yield fast and quiet imaging. Chapter 4 explored the acceleration capabilities of the silent gradient-axis. The acceleration capabilities were assessed based on g-factor maps for different combinations of scan parameters like the silent gradient amplitude and readout bandwidth. Here, we showed that the silent gradient can provide acceleration similar to other WAVE-imaging methods but without an additional sound burden. Chapter 5 showcased the application of the silent gradient to a T1-weighted anatomical imaging sequence. We compared a quiet T1-weighted acquisition using the silent gradient with a conventional T1 weighted acquisition in terms of quantitative and qualitative image quality, sound level and subject experience. We showed that the quiet T1-weighted acquisition produced acceptable image quality and provided a more comfortable experience while significantly reducing sound. In Chapter 6, we applied the silent gradient-axis to spectroscopic imaging by introducing a silent EPSI readout. Phantom measurements were used to compare spectra from conventional phase-encoded spectroscopic imaging, the silent EPSI readout and a conventional EPSI readout and compare their SNR. We showed that the silent EPSI readout was faster than conventional phase-encoded spectroscopic imaging without any additional sound while featuring a higher SNR efficiency. All in all, this thesis showed that even a single-axis gradient insert can offer a substantial increase in scan efficiency and spatiotemporal resolution for EPI-readouts, which was achieved without affecting the day-to-day operation of the MR-scanner. In addition, this thesis introduced a novel silent gradient and silent imaging method that leveraged the fast-switching capabilities of this gradient insert and could yield sound reduction without compromising scan time

Probabilistic tractography for complex fiber orientations with automatic model selection: A tool to study structural connectivity in stroke patients

Stroke is one of the leading causes of both death and disability in the world. Consequently, the processes underlying motor recovery are a hot research topic. Electroencephalography (EEG) and diffusion weighted magnetic resonance imaging (dMRI) are two modalities that can be used to find functional and structural predictors for this motor recovery, respectively. Specifically, EEG measures the sources of activity (dipoles) in the brain while dMRI provides estimates of the properties of white matter (WM) tracts such as the fiber orientation. The estimated fiber orientations can be used to reconstruct WM connections in the brain by performing fiber tractography.In this thesis, we aim to introduce a framework for model selection and probabilistic tractography with parsimonious model selection. Practically, we use a range of multi-tensor models to cope with regions with multiple fiber populations. Furthermore, our probabilistic tractography uses the Cram\'er-Rao lower bound to capture the uncertainty in the fiber orientations. We mitigate the effect of overfitting by using a model selection method that incorporates the ICOMP-TKLD criterion to determine the most appropriate tensor model in each voxel. Ultimately, this framework can be applied to data from stroke patients and combined with functional regions obtained from EEG.We assessed the performance of the model selection method by investigating the influence of b-value and noise on the ability to detect crossing fibers in the fibercup phantom and human data. In the phantom, our model selection reconstructed all the crossings for the b-value combination of 1500 and \SI{2000}{\s\per\mm\squared} and at a signal-to-noise-ratio (SNR) comparable to clinical acquisitions. Moreover, our model selection method was able to identify the crossing of the corpus callosum and corticospinal tract in the human data.A range of step sizes and curvature thresholds was used to investigate the sensitivity of our tractography to its input parameters. In general, a smaller step size and lower curvature thresholds resulted in more deterministic behavior, while a larger step sizes and higher curvature thresholds led to more probabilistic behavior and deeper propagation into the gray matter in human data. We compared the performance of our framework and the open source diffusion MRI toolkit Camino on the fibercup phantom and healthy control data. In this comparison, our framework performed better in curved bundles and reconstructed more lateral projections of the corpus callosum.Lastly, we explored the subdivision of the brain into modules for stroke patients and healthy controls, by combining our framework with sources obtained from EEG. Fewer modules were found in the patient group, which might be attributed to a change in structural connections after stroke.Altogether, we have shown that our framework was able to select the appropriate diffusion models in crossing fiber regions and track across these crossings both in a phantom and human data. Furthermore, we demonstrated that it is feasible to combine our framework with source locations obtained from EEG

Restoring the past, forging the present:Scapegoating and redemption in calvaire and these are the names

This article is a comparison of two works of fiction, a film and a novel, that both address the question of how people deal with intense memories of tragic events from their past. Both works are characterized by crucial references to religious phenomena. In the Belgian cult horror film Calvaire and the bestselling Dutch novel These Are The Names, stories are told about the desire to restore what was lost. In order to deal with past realities, the characters in these works of fiction impose the past, in an imaginative form, upon the present, which inevitably seems to create violence and conflict. The introduction of violence, and the way this violence destroys identities as a means to restore a lost world, calls the possibility and credibility of restoration into question. In order to explore the phenomenon of restoration, we introduce a concept of substitution (inspired by René Girard) to investigate the power of violence in these two narratives. In Calvaire, violence leads to the perversion of identity, ultimately leading to the latter’s destruction, yet at the same time it can be understood to result in love and absolution. In These Are The Names, sacrificing acts first seem to bring a new beginning but in the end redemption is substituted by accusations of severe crimes. However, in this novel the past is also present in such a way that lost identities could be restored. How both stories look at the relation between past and present and in which way they present the possibility of restoring painful events, will be our main questions

Accelerating Brain Imaging Using a Silent Spatial Encoding Axis

PURPOSE: To characterize the acceleration capabilities of a silent head insert gradient axis that operates at the inaudible frequency of 20 kHz and a maximum gradient amplitude of 40 mT/m without inducing peripheral nerve stimulation. METHODS: The silent gradient axis' acquisitions feature an oscillating gradient in the phase-encoding direction that is played out on top of a cartesian readout, similarly as done in Wave-CAIPI. The additional spatial encoding fills k-space in readout lanes allowing for the acquisition of fewer phase-encoding steps without increasing aliasing artifacts. Fully sampled 2D gradient echo datasets were acquired both with and without the silent readout. All scans were retrospectively undersampled (acceleration factors R = 1 to 12) to compare conventional SENSE acceleration and acceleration using the silent gradient. The silent gradient amplitude and the readout bandwidth were varied to investigate the effect on artifacts and g-factor. RESULTS: The silent readout reduced the g-factor for all acceleration factors when compared to SENSE acceleration. Increasing the silent gradient amplitude from 31.5 mT/m to 40 mT/m at an acceleration factor of 10 yielded a reduction in the average g-factor (gavg ) from 1.3 ± 0.14 (gmax = 1.9) to 1.1 ± 0.09 (gmax = 1.6). Furthermore, reducing the number of cycles increased the readout bandwidth and the g-factor that reached gavg = 1.5 ± 0.16 for a readout bandwidth of 651 Hz/pixel and an acceleration factor of R = 8. CONCLUSION: A silent gradient axis enables high acceleration factors up to R = 10 while maintaining a g-factor close to unity (gavg = 1.1 and gmax = 1.6) and can be acquired with clinically relevant readout bandwidths