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Journal article

Defining a local arterial input function for perfusion MRI using independent component analysis : Defining a Local AIF for Perfusion MRI

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Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark1

Department of Informatics and Mathematical Modeling, Technical University of Denmark2

Quantification of cerebral blood flow (CBF) using dynamic-susceptibility contrast MRI relies on the deconvolution of the arterial input function (AIF), which is commonly estimated from the signal changes in a major artery. However, it has been shown that the presence of bolus delay/dispersion between the artery and the tissue of interest can be a significant source of error.

These effects could be minimized if a local AIF were used, although the measurement of a local AIF can be problematic. This work describes a new methodology to define a local AIF using independent component analysis (ICA). The methodology was tested on data from patients with various cerebrovascular abnormalities and compared to the conventional approach of using a global AIF.

The new methodology produced higher CBF and shorter mean transit time values (compared to the global AIF case) in areas with distorted AIFs, suggesting that the effects of delay/dispersion are minimized. The minimization of these effects using the calculated local AIF should lead to a more accurate quantification of CBF, which can have important implications for diagnosis and management of patients with cerebral ischemia.

Language: English
Publisher: Wiley Subscription Services, Inc., A Wiley Company
Year: 2004
Pages: 789-797
ISSN: 15222594 and 07403194
Types: Journal article
DOI: 10.1002/mrm.20227
ORCIDs: Mørup, Morten and Hansen, Lars Kai

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