The objective of this project is to develop ultra-fast magnetic resonance imaging techniques and applying them to measuring flow and motion. This is accomplished by: (i) developing ultra-fast imaging for assessment of simple linear (i.e., one directional) flow; (ii) developing ultra-fast imaging for application and assessment of more complex and other rapidly-varying phenomena; (iii) applying ultra-fast imaging techniques developed for Specific Aims (i) and (ii) to the analysis of in-vivo flow and other dynamic in-vivo phenomena, such as heart motion. Rotating Ultra-Fast Imaging Sequence (RUFIS) developed in this Center uses free induction decays (FID) for image reconstruction, and usually the data points at the begining of the FID are not available because of finite recovery times of the hardware. We improved image reconstruction by substituting a Linear Algebra Method (LAM) to reconstruct image profiles directly from FID data. Simulations confirm that the LAM method can accurately reconstruct 1 D projections from oversampled data even when 1/4 of k-space is missing or noise is present. Simulations were also performed to examine and confirm the minimal effects of turbulence and diffusion on signal loss. Using a spin echo-based velocity-encoding preparation sequence followed by RUFIS, quantitative velocity profiles of laminarand turbulent flow have been obtained. Flow has been quantified inside a straightglass phantom, emerging from a stenosis, and traveling through a curved channel. We also used RUFIS to analyze flow boundary reattachment and the effects of secondary flow patterns in curved flow. We also began to adapt RUFIS sequences for in vivo imaging of the rat. RUFIS can be used as an accurate non-invasive technique for distinguishing laminar and turbulent flow, measuring flow velocities, observing eddies, and identifying shear boundary reattachment downstream of a stenosis.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR003631-13
Application #
6356298
Study Section
Project Start
2000-09-20
Project End
2001-08-14
Budget Start
1998-10-01
Budget End
1999-09-30
Support Year
13
Fiscal Year
2000
Total Cost
$63,215
Indirect Cost
Name
Carnegie-Mellon University
Department
Type
DUNS #
052184116
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Ramachandran, Suchitra; Meyer, Travis; Olson, Carl R (2016) Prediction suppression in monkey inferotemporal cortex depends on the conditional probability between images. J Neurophysiol 115:355-62
Meyer, Travis; Walker, Christopher; Cho, Raymond Y et al. (2014) Image familiarization sharpens response dynamics of neurons in inferotemporal cortex. Nat Neurosci 17:1388-94
Hall, Nathan; Colby, Carol (2014) S-cone visual stimuli activate superior colliculus neurons in old world monkeys: implications for understanding blindsight. J Cogn Neurosci 26:1234-56
Subramanian, Janani; Colby, Carol L (2014) Shape selectivity and remapping in dorsal stream visual area LIP. J Neurophysiol 111:613-27
Berdyyeva, Tamara K; Olson, Carl R (2014) Intracortical microstimulation of supplementary eye field impairs ability of monkeys to make serially ordered saccades. J Neurophysiol 111:1529-40
Meyer, Travis; Ramachandran, Suchitra; Olson, Carl R (2014) Statistical learning of serial visual transitions by neurons in monkey inferotemporal cortex. J Neurosci 34:9332-7
Hall, Nathan; Colby, Carol (2013) Psychophysical definition of S-cone stimuli in the macaque. J Vis 13:
Leathers, Marvin L; Olson, Carl R (2012) In monkeys making value-based decisions, LIP neurons encode cue salience and not action value. Science 338:132-5
Meyer, Travis; Olson, Carl R (2011) Statistical learning of visual transitions in monkey inferotemporal cortex. Proc Natl Acad Sci U S A 108:19401-6
Berdyyeva, Tamara K; Olson, Carl R (2011) Relation of ordinal position signals to the expectation of reward and passage of time in four areas of the macaque frontal cortex. J Neurophysiol 105:2547-59

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