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Meeting Abstract

Application of two-compartmental model on non-human primate perfusion data: quantification and sensitivity mapping

MPS-Authors
/persons/resource/persons84163

Reichold,  J
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84326

Zappe,  A-C
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84304

Weber,  B
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84137

Pfeuffer,  J
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84063

Logothetis,  NK
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

https://link.springer.com/content/pdf/10.1007%2Fs10334-006-0041-3.pdf
(Abstract)

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Citation

Reichold, J., Zappe, A.-C., Burger, C., Weber, B., Buck, A., Pfeuffer, J., et al. (2006). Application of two-compartmental model on non-human primate perfusion data: quantification and sensitivity mapping. Magnetic Resonance Materials in Physics, Biology and Medicine, 19(Supplement 1): 177, 121-122.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D01B-C
Abstract
Quantification of cerebral blood flow (CBF) using magnetic resonance imaging still suffers from many unresolved
methodological issues. In this study we report the successful modeling of monkey CBF data, using the two-compartmental model introduced by Parkes et al. [1]. Absolute flow and transit times were derived including uncertainties of the assumed parameters as well as the signal noise. The
precision of the model's result was investigated and an acquisition paradigm to maximize the information content is proposed.