Image-Guided Magnetic Thermoseed Navigation and Tumor Ablation Using a Magnetic Resonance Imaging System.

Medical therapies achieve their control at expense to the patient in the form of a range of toxicities, which incur costs and diminish quality of life. Magnetic resonance navigation is an emergent technique that enables image-guided remote-control of magnetically labeled therapies and devices in the body, using a magnetic resonance imaging (MRI) system. Minimally INvasive IMage-guided Ablation (MINIMA), a novel, minimally invasive, MRI-guided ablation technique, which has the potential to avoid traditional toxicities, is presented.

Physiological effects of human body imaging with 300 mT/m gradients.

Purpose: The use of high-performance gradient systems (i.e., high gradient strength and/or high slew rate) for human MRI is limited by physiological effects (including the elicitation of magnetophosphenes and peripheral nerve stimulation (PNS)).

Resolving bundle-specific intra-axonal T values within a voxel using diffusion-relaxation tract-based estimation.

At the typical spatial resolution of MRI in the human brain, approximately 60-90% of voxels contain multiple fiber populations. Quantifying microstructural properties of distinct fiber populations within a voxel is therefore challenging but necessary. While progress has been made for diffusion and T-relaxation properties, how to resolve intra-voxel T heterogeneity remains an open question.

MICRA: Microstructural image compilation with repeated acquisitions.

We provide a rich multi-contrast microstructural MRI dataset acquired on an ultra-strong gradient 3T Connectom MRI scanner comprising 5 repeated sets of MRI microstructural contrasts in 6 healthy human participants. The availability of data sets that support comprehensive simultaneous assessment of test-retest reliability of multiple microstructural contrasts (i.e.

A comparative study of gradient nonlinearity correction strategies for processing diffusion data obtained with ultra-strong gradient MRI scanners.

Purpose: The analysis of diffusion data obtained under large gradient nonlinearities necessitates corrections during data reconstruction and analysis. While two such preprocessing pipelines have been proposed, no comparative studies assessing their performance exist. Furthermore, both pipelines neglect the impact of subject motion during acquisition, which, in the presence of gradient nonlinearities, induces spatio-temporal B-matrix variations.

Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results.

Cross-scanner and cross-protocol variability of diffusion magnetic resonance imaging (dMRI) data are known to be major obstacles in multi-site clinical studies since they limit the ability to aggregate dMRI data and derived measures. Computational algorithms that harmonize the data and minimize such variability are critical to reliably combine datasets acquired from different scanners and/or protocols, thus improving the statistical power and sensitivity of multi-site studies. Different computational approaches have been proposed to harmonize diffusion MRI data or remove scanner-specific differences.

Strong diffusion gradients allow the separation of intra- and extra-axonal gradient-echo signals in the human brain.

The quantification of brain white matter properties is a key area of application of Magnetic Resonance Imaging (MRI), with much effort focused on using MR techniques to quantify tissue microstructure. While diffusion MRI probes white matter (WM) microstructure by characterising the sensitivity of Brownian motion of water molecules to anisotropic structures, susceptibility-based techniques probe the tissue microstructure by observing the effect of interaction between the tissue and the magnetic field. Here, we unify these two complementary approaches by combining ultra-strong (300mT/m) gradients with a novel Diffusion-Filtered Asymmetric Spin Echo (D-FASE) technique.

Nonivasive quantification of axon radii using diffusion MRI.

Axon caliber plays a crucial role in determining conduction velocity and, consequently, in the timing and synchronization of neural activation. Noninvasive measurement of axon radii could have significant impact on the understanding of healthy and diseased neural processes. Until now, accurate axon radius mapping has eluded in vivo neuroimaging, mainly due to a lack of sensitivity of the MRI signal to micron-sized axons.

Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms.

Diffusion MRI is being used increasingly in studies of the brain and other parts of the body for its ability to provide quantitative measures that are sensitive to changes in tissue microstructure. However, inter-scanner and inter-protocol differences are known to induce significant measurement variability, which in turn jeopardises the ability to obtain 'truly quantitative measures' and challenges the reliable combination of different datasets. Combining datasets from different scanners and/or acquired at different time points could dramatically increase the statistical power of clinical studies, and facilitate multi-centre research.

Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI.

The key component of a microstructural diffusion MRI 'super-scanner' is a dedicated high-strength gradient system that enables stronger diffusion weightings per unit time compared to conventional gradient designs. This can, in turn, drastically shorten the time needed for diffusion encoding, increase the signal-to-noise ratio, and facilitate measurements at shorter diffusion times. This review, written from the perspective of the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure, an initiative to establish a shared 300 mT/m-gradient facility amongst the microstructural imaging community, describes ten advantages of ultra-strong gradients for microstructural imaging.

Prediction of hemorrhagic transformation after experimental ischemic stroke using MRI-based algorithms.

Estimation of hemorrhagic transformation (HT) risk is crucial for treatment decision-making after acute ischemic stroke. We aimed to determine the accuracy of multiparametric MRI-based predictive algorithms in calculating probability of HT after stroke. Spontaneously, hypertensive rats were subjected to embolic stroke and, after 3 h treated with tissue plasminogen activator (Group I: n = 6) or vehicle (Group II: n = 7).

Magnetic resonance imaging of local and remote vascular remodelling after experimental stroke.

The pattern of vascular remodelling in relation to recovery after stroke remains largely unclear. We used steady-state contrast-enhanced magnetic resonance imaging to assess the development of cerebral blood volume and microvascular density in perilesional and exofocal areas from (sub)acutely to chronically after transient stroke in rats. Microvascular density was verified histologically after infusion with Evans Blue dye.

Impact of hemodynamic effects on diffusion-weighted fMRI signals.

In some recent studies, diffusion weighted functional MRI has been proposed to provide contrast immune to vascular changes. Increases in relative signal change during neuronal activation observed under increasing diffusion weighting support the possible diffusion based origin of this contrast. A recent diffusion tensor imaging (DTI) study has also reported the use of Fractional Anisotropy (FA) to track activation in white matter.