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Automatic selection of arterial input function using cluster analysis

✍ Scribed by Kim Mouridsen; Søren Christensen; Louise Gyldensted; Leif Østergaard


Book ID
102956222
Publisher
John Wiley and Sons
Year
2006
Tongue
English
Weight
630 KB
Volume
55
Category
Article
ISSN
0740-3194

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✦ Synopsis


Abstract

Quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast MRI requires determination of the arterial input function (AIF) representing the delivery of intravascular tracer to tissue. This is typically accomplished manually by inspection of concentration time curves (CTCs) in regions containing the ICA, VA, and MCA. This is, however, a time consuming and operator dependent procedure. We suggest a completely automatic procedure for establishing the AIF based on a cluster analysis algorithm. In 20 normal subjects CBF maps calculated in 2 slices by the automatic procedure were compared to maps obtained with AIFs selected individually by 7 experienced operators. The average manual to automatic CBF ratio was 1.03 ± 0.15 in the lower slice and 1.05 ± 0.12 in the upper slice, demonstrating excellent agreement between the manual and automatic method. The algorithm provides means for objectively assessing AIF candidates in local AIF search algorithms designed to reduce bias due to delay and dispersion. Given the reproducibility and speed (10 s) of the automatic method, we speculate that it will greatly improve the accuracy of perfusion images and facilitate their use in clinical diagnosis and decision‐making, particularly in acute stroke but also in cerebrovascular disease in general. Magn Reson Med, 2006. © 2006 Wiley‐Liss, Inc.


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## Abstract Dynamic susceptibility contrast‐MRI requires an arterial input function (AIF) to obtain cerebral blood flow, cerebral blood volume, and mean transit time. The current AIF selection criteria discriminate venous, capillary, and arterial profiles based on shape and timing characteristics o