<i>Handbook of MRI Pulse Sequences</i>

Fong, Wilson

doi:10.1118/1.1904597

Cited by 23 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Diffusion is usually studied in NMR with ''reciprocal space'' approaches, in which the signal attenuation of a gradient or spin echo is measured as a function of gradient amplitude [2,[18][19][20]. Measurements of slow diffusion coefficients by singlet state spectroscopy have already been reported [21] where singlet state preparation is combined with pulsed field gradients to investigate diffusion constants in reciprocal space.…”

Section: Macroscopic Diffusion Imagingmentioning

confidence: 99%

See 1 more Smart Citation

Real-space imaging of macroscopic diffusion and slow flow by singlet tagging MRI

Pileio

Dumez

Pop

et al. 2015

Journal of Magnetic Resonance

View full text Add to dashboard Cite

Magnetic resonance imaging can be used to study motional processes such as flow and diffusion, but the accessible timescales are limited by longitudinal relaxation. The spatially selective conversion from magnetization to long-lived singlet order in designer molecules makes it possible to tag a region of interest for an extended period of time, of the order of several minutes. Here we exploit this concept of "singlet tagging" to monitor diffusion over a macroscopic scale as well as very slow flow.

show abstract

Section: Macroscopic Diffusion Imagingmentioning

confidence: 99%

“…Beyond anatomical images, magnetic resonance can provide detailed information on motional processes, over a large range of temporal and spatial scales [1][2][3]. Many techniques rely on the concept of ''time-of-flight'' imaging, which consists of tagging a region of interest and tracking its subsequent evolution.…”

Section: Introductionmentioning

confidence: 99%

Real-space imaging of macroscopic diffusion and slow flow by singlet tagging MRI

Pileio

Dumez

Pop

et al. 2015

Journal of Magnetic Resonance

View full text Add to dashboard Cite

show abstract

“…The worm is assumed to reside within a strong and constant magnetic field B = (0, 0, B z ) of the MRI scanner. The software mimics a simplified yet acceptably accurate MR image acquisition process via a standard gradient-echo sequence [11] that takes place during worm motion as follows: An image slice at a parametrised position s along the worm axis is defined as the image plane perpendicular to the worm axis. This slice is excited by assigning a signal intensity value for each voxel of the slice as a function of the corresponding phantom TEM image.…”

Section: Resultsmentioning

confidence: 99%

Motion prediction enables simulated MR-imaging of freely moving model organisms

Reischl

Jouda

MacKinnon

et al. 2019

Preprint

View full text Add to dashboard Cite

14Magnetic resonance tomography typically applies the Fourier transform to 15 k-space signals repeatedly acquired from a frequency encoded spatial region of 16 interest, therefore requiring a stationary object during scanning. Any movement of 17 the object results in phase errors in the recorded signal, leading to deformed 18 images, phantoms, and artifacts, since the encoded information does not originate 19 from the intended region of the object. However, if the type and magnitude of 20 movement is known instantaneously, the scanner or the reconstruction algorithm 21 could be adjusted to compensate for the movement, directly allowing high quality 22 imaging with non-stationary objects. This would be an enormous boon to studies 23 that tie cell metabolomics to spontaneous organism behaviour, eliminating the 24 stress otherwise necessitated by restraining measures such as anesthesia or 25 clamping. 26In the present theoretical study, we use a phantom of the animal model 27 C. elegans to examine the feasibility to automatically predict its movement and 28 position, and to evaluate the impact of movement prediction, within a sufficiently 29 long time horizon, on image reconstruction. For this purpose, we use automated 30 image processing to annotate body parts in freely moving C. elegans, and predict 31 their path of movement. We further introduce an MRI simulation platform based 32 on brightfield-videos of the moving worm, combined with a stack of high resolution 33 transmission electron microscope (TEM) slice images as virtual high resolution 34 phantoms. A phantom provides an indication of the spatial distribution of 35 signal-generating nuclei on a particular imaging slice. We show that adjustment of 36 the scanning to the predicted movements strongly reduces distortions in the 37 resulting image, opening the door for implementation in a high-resolution NMR 38 scanner. 39 1 Introduction 40 A major challenge in biological science is to relate molecular regulation at the cellular 41 level to response and behaviour at the organism level. Knowing this relationship lies at 42 the foundation of every disease, and indeed also in understanding the healthy organism. 43 An experiment establishing this relationship, as schematically shown in Fig. 1, requires 44 i) in vivo cellular-level detection of regulation-relevant molecules, such as metabolites 45 March 30, 2019 1/18and their production rates, ii) precise access to and application of biological 46 perturbation mechanisms, and iii) an unburdened (naturally responding) organism. 47Clearly, even taken individually, these items are very hard to achieve in general, and 48 correspond to major research areas in their own right. 49 Experimental control Output Stimulus Organism Response Fig 1. A freely moving organism is subject to a stimulus (mechanical, chemical, light, etc.) causing a response at all levels of detail (metabolomic, behaviour, etc.). The experiment designer relates the correlated output to a biological hypothesis and may adapt the stimulus. Small or...

show abstract

“…Diffusion-weighted imaging (DWI) is used to quantify the freedom of water diffusion in tissue. Images are sensitized to diffusion through the addition of motion-sensitizing gradients to a spin echo acquisition; this causes signal loss from moving spins but not from those that are stationary [15][16][17].…”

Section: Diffusion Weighted Imagingmentioning

confidence: 99%

Emerging quantitative MR imaging biomarkers in inflammatory arthritides

Barendregt

Bray

Hall‐Craggs

et al. 2019

European Journal of Radiology

View full text Add to dashboard Cite

Structured abstract (as per journal requirement) Purpose: To review quantitative magnetic resonance imaging (qMRI) methods for imaging inflammation in connective tissues and the skeleton in inflammatory arthritis. This review is designed for a broad audience including radiologists, imaging technologists, rheumatologists and other healthcare professionals. Methods: We discuss the use of qMRI for imaging skeletal inflammation from both technical and clinical perspectives. We consider how qMRI can be targeted to specific aspects of the pathological process in synovium, cartilage, bone, tendons and entheses. Evidence for the various techniques from studies of both adults and children with inflammatory arthritis is reviewed and critically appraised. Results: qMRI has the potential to objectively identify, characterize and quantify inflammation of the connective tissues and skeleton in both adult and pediatric patients. Measurements of tissue properties derived using qMRI methods can serve as imaging biomarkers, which are potentially more reproducible and informative than conventional MRI methods. Several qMRI methods are nearing transition into clinical practice and may inform diagnosis and treatment decisions, with the potential to improve patient outcomes. Conclusions: qMRI enables specific assessment of inflammation in synovium, cartilage, bone, tendons and entheses, and can facilitate a more consistent, personalized approach to diagnosis, characterisation and monitoring of disease. 3

show abstract

Handbook of MRI Pulse Sequences

Cited by 23 publications

References 0 publications

Real-space imaging of macroscopic diffusion and slow flow by singlet tagging MRI

Real-space imaging of macroscopic diffusion and slow flow by singlet tagging MRI

Motion prediction enables simulated MR-imaging of freely moving model organisms

Emerging quantitative MR imaging biomarkers in inflammatory arthritides

Contact Info

Product

Resources

About