2008
DOI: 10.1002/mrm.21612
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Evaluation of an AIF correction algorithm for dynamic susceptibility contrast‐enhanced perfusion MRI

Abstract: For longitudinal studies in patients suffering from cerebrovascular diseases the poor reproducibility of perfusion measurements via dynamic susceptibility-weighted contrast-enhanced MRI (DSC-MRI) is a relevant concern. We evaluate a novel algorithm capable of overcoming limitations in DSC-MRI caused by partial volume and saturation issues in the arterial input function (AIF) by a blood flow stimulation-study. In 21 subjects, perfusion parameters before and after administration of blood flow stimulating L-argin… Show more

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Cited by 9 publications
(7 citation statements)
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“…1. For each VOF and AIF, the AUC of the first pass was calculated using a γ‐variate curve fit to reduce the effects of recirculation (4, 15, 20, 30, 36, 38).…”
Section: Methodsmentioning
confidence: 99%
“…1. For each VOF and AIF, the AUC of the first pass was calculated using a γ‐variate curve fit to reduce the effects of recirculation (4, 15, 20, 30, 36, 38).…”
Section: Methodsmentioning
confidence: 99%
“…The algorithm included fitting a gamma-variate function to the measured concentration-time curve of the artery, modified to include only the points on the signal curve that did not fall below a specific threshold. Brunecker et al [64,65] proposed and evaluated an algorithm for correcting distortions of the AIF caused by peak saturation of the concentration curve. This algorithm separated the AIF into a reliable part at low contrast agent concentrations and an unreliable part at high concentrations.…”
Section: Geometric Distortion and Signal Saturation At Peak Concentramentioning
confidence: 99%
“…In a different approach, Brunecker et al . proposed a post‐processing method to correct distorted AIFs by separating the profile into ‘reliable’ and ‘unreliable’ phases, using a parametric description to reconstruct the most probable profile of the unreliable phase. However, like any parametric model approach (see step 23), the accuracy of this correction method will depend on the validity of the model used.…”
Section: The Arterial Input Functionmentioning
confidence: 99%