Estimation of cerebral blood flow from dynamic susceptibility contrast MRI using a tissue model

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Cerebral perfusion measurements are of great clinical and research interest. Positron emission tomography (PET) is considered the gold standard for cerebral perfusion measurement, but is not widely available and entails exposure of the subject to radioactivity. Dynamic susceptibility contrast (DSC) MRI methods are becoming more widely available on the newest generation of MRI scanners. The standard analysis methods of this data have significant disadvantages that include the use of a single, difficult to measure, arterial input function for the entire brain and the need to perform a numerical deconvolution on the logarithm of noisy data. These methods are not yet fully validated and remain qualitative in nature. Using a modification of the standard tracer kinetic principles we implemented a tissue perfusion model that has several advantages over standard methods. The model parameters were estimated using Bayes probability theory in a group of patients with varying degrees of hemodynamic impairment and were found to provide additional physiologic information that was not available using standard techniques.

Original languageEnglish
Title of host publicationBAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING
Subtitle of host publication25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Pages535-542
Number of pages8
DOIs
StatePublished - Nov 23 2005
Event25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering - San Jose, CA, United States
Duration: Aug 7 2005Aug 12 2005

Publication series

NameAIP Conference Proceedings
Volume803
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering
CountryUnited States
CitySan Jose, CA
Period08/7/0508/12/05

Keywords

  • Bayes probability theory
  • Carotid occlusion
  • Cerebral perfusion
  • MRI

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    Shimony, J. S., Lee, J. J., & Bretthorst, G. L. (2005). Estimation of cerebral blood flow from dynamic susceptibility contrast MRI using a tissue model. In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (pp. 535-542). (AIP Conference Proceedings; Vol. 803). https://doi.org/10.1063/1.2149835