## Abstract ## Purpose To determine the true impact of dispersion upon cerebral blood flow (CBF) quantification by removing an algorithm implementation‐induced systematic error. ## Materials and Methods The impact of dispersion on the arterial input function (AIF) between measurement and entry i
Bolus dispersion issues related to the quantification of perfusion MRI data
✍ Scribed by Fernando Calamante
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 344 KB
- Volume
- 22
- Category
- Article
- ISSN
- 1053-1807
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✦ Synopsis
Abstract
Quantification of cerebral blood flow (CBF) using dynamic‐susceptibility contrast (DSC) MRI relies on the deconvolution of the arterial input function (AIF). The AIF is commonly measured in a major artery (e.g., the middle cerebral artery), and the estimated function is used as a global AIF for the whole slice. However, the presence of bolus delay and dispersion between the artery and the tissue of interest can introduce significant errors in CBF quantification. While several methods have been introduced to minimize or eliminate the effects of bolus delay, the correction of bolus dispersion is more difficult to address because it requires a model for the vascular bed. This article summarizes how this dispersion effect can be incorporated into the model for CBF quantification, and discusses the magnitude of the errors introduced. Furthermore, alternative methods for correcting or minimizing the effects of bolus dispersion in the quantification of CBF are reviewed. J. Magn. Reson. Imaging 2005. © 2005 Wiley‐Liss, Inc.
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## Abstract Cerebral blood flow (CBF) is commonly estimated from the maximum of the residue function deconvolved from bolus‐tracking data. The bolus may become delayed and/or dispersed in the vessels feeding the tissue, resulting in the calculation of an effective residue function, __R__~__eff__~(_