## 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
Reexamining the quantification of perfusion MRI data in the presence of bolus dispersion
✍ Scribed by Linda Ko; Marina Salluzzi; Richard Frayne; Michael Smith
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 117 KB
- Volume
- 25
- Category
- Article
- ISSN
- 1053-1807
No coin nor oath required. For personal study only.
✦ Synopsis
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 into the tissue of interest on CBF estimates was simulated assuming: 1) contralateral circulation flow that introduces a true arterial tissue delay (ATD)‐related dispersive component; and 2) the presence of an arterial stenosis that disperses and shifts the AIF peak entering the tissue; increasing the apparent ATD relative to the original AIF.
Results
Previously reported CBF estimates for the stenosis dispersion model were found to be a mixture of true dispersive effects and an algorithm implementation‐induced systematic error. The true CBF~MEASURED~/CBF~NO‐DISPERSION~ ratios for short mean transit times (MTT) (normal) and long MTT (infarcted) tissue were similar for both dispersion models evaluated; this was an unanticipated result. The CBF quantification inaccuracies induced through the dispersion model truly related to ATD were lower than for the local stenosis‐based dispersion for small ATD values.
Conclusion
Correcting the systematic error present in a previous deconvolution study removes the reported ATD‐related impact on CBF quantification. The impact of dispersion was smaller than half that reported in previous simulation studies. J. Magn. Reson. Imaging 2007;25:639–643. © 2007 Wiley‐Liss, Inc.
📜 SIMILAR VOLUMES
## 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__~(_
## Abstract Quantification of cerebral blood flow (CBF) and the tissue residue function (__R__) using bolus‐tracking MRI requires deconvolution of the arterial input function (AIF). Currently, the most commonly used deconvolution method is singular value decomposition (SVD), which has been shown to
## Abstract Measurement of myocardial and brain perfusion when using exogenous contrast agents (CAs) such as gadolinium‐DTPA (Gd‐DTPA) and MRI is affected by the diffusion of water between compartments. This water exchange may have an impact on signal enhancement, or, equivalently, on the longitudi
## Abstract ## Purpose To investigate whether bolus delay‐corrected dynamic susceptibility contrast (DSC) perfusion MRI measures allowed a more accurate estimation of eventual infarct volume in 14 acute stroke patients using a predictive tissue classifier algorithm. ## Materials and Methods Tiss