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Defining a local arterial input function for perfusion MRI using independent component analysis
Author(s) -
Calamante Fernando,
Mørup Morten,
Hansen Lars Kai
Publication year - 2004
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.20227
Subject(s) - independent component analysis , cerebral blood flow , deconvolution , perfusion scanning , medicine , perfusion , computer science , radiology , algorithm , cardiology , artificial intelligence
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. Magn Reson Med 52:789–797, 2004. © 2004 Wiley‐Liss, Inc.