Illinois BioNanotechnology Seminar Series Spring 2011: Imaging Microvascular Blood Flow with MRI

By Brad Sutton

University of Illinois at Urbana-Champaign

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Blood flow in the brain is an important physiological quantity relating to vitality of brain tissue and performance of cognitive tasks. Current non-invasive methods to measure cerebral blood flow with magnetic resonance imaging (MRI) allow for the measurement of delivery of blood from feeding arteries and may be sensitive to disruptions in flow in pathways between where blood is tagged and where it is measured. Recently we have revived old techniques and developed new techniques for localized imaging of microvascular blood flow in the brain. In addition to flow quantification, our techniques allow for measurement of structural arrangement of microvasculature. In this talk, we will show how microvascular blood flow can be quantified in brain tissues using non-invasive methods of FENSI and diffusion weighted imaging.


Brad Sutton - Ph.D., Biomedical Engineering, University of Michigan, 2003

Sponsored by


Herrington, J.D., Sutton, B., & Miller, G.A. (2007). Data-file formats in neuroimaging: Background and tutorial. In J.T. Cacioppo, L.G. Tassinary, & G.G. Berntson (Eds.), Handbook of psychophysiology (third edition). New York: Cambridge University Press.

Fessler JA, Sutton BP. Nonuniform fast Fourier transforms using min-max interpolation. IEEE Tr. Sig. Proc., 51(2):560-574, 2003.

Sutton BP, Noll DC, Fessler JA. Fast, iterative, field-corrected image reconstruction for MRI. IEEE Tr. Med. Im., 22(2):178-188, 2003.

Sutton BP, Noll DC, Fessler JA. Dynamic field map estimation using a spiral-in/ spiral-out acquisition. Mag Res Med 51(6):1194-1204, 2004.

Noll DC, Fessler JA, Sutton BP. Conjugate phase MRI reconstruction with spatially variant sample density correction. IEEE Tr. Med. Im., 24(3):325-336, 2005.

Sutton BP, Ciobanu L, Zhang X, Webb A. Parallel imaging for NMR microscopy at 14.1 Tesla. Mag. Res. Med. 54(1): 9-13, 2005.

Payer D, Marshuetz C, Sutton B, Hebrank A, Welsh RC, Park DC. Decreased neural specialization in old adults on a working memory task. Neuroreport 17(5):487-91, 2006.

Shinkareva SV, Ombao HC, Sutton BP, Mohanty A, Miller GA. Classification of functional brain images with a spatio-temporal dissimilarity map. Neuroimage. 2006 Oct 15;33(1):63-71.

Chee MW, Goh JO, Venkatraman V, Tan JC, Gutchess A, Sutton B, Hebrank A, Leshikar E, Park D. Age-related changes in object processing and contextual binding revealed using fMR adaptation. J Cogn Neurosci. 2006 Apr;18(4):495-507.

Gutchess AH, Hebrank A, Sutton BP, Leshikar E, Chee MW, Tan JC, Goh JO, Park DC. Contextual interference in recognition memory with age. Neuroimage. 2007 Apr 15;35(3):1338-47.

Miller GA, Elbert T, Sutton BP, Heller W. Innovative clinical assessment technologies: challenges and opportunities in neuroimaging. Psychol Assess. 2007 Mar;19(1):58-73.

Sutton BP, Ouyang C, Ching BL, Ciobanu L. Functional Imaging with FENSI: Flow-ENhanced Signal Intensity. Magn Reson Med. 2007 Aug; 58(2):396-401.
Perry JL, Kuehn DP, Goldwasser MS, Sutton BP. Using magnetic resonance imaging and 3D computer technology to improve treatment and care for individuals born with cleft palate. Carle Selected Papers, Carle Foundation Hospital, Urbana. 2007; 50(1): 2-6.

Goh JO, Chee MW, Tan JC, Venkatraman V, Hebrank A, Leshikar ED, Jenkins L, Sutton BP, Gutchess AH, Park DC. Age and culture modulate object processing and object-scene binding in the ventral visual area. Cogn Affect Behav Neurosci. 2007 Mar;7(1):44-52.

Cite this work

Researchers should cite this work as follows:

  • Brad Sutton (2011), "Illinois BioNanotechnology Seminar Series Spring 2011: Imaging Microvascular Blood Flow with MRI,"

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Omar N Sobh

University of Illinois at Urbana-Champaign