Literature DB >> 21264935

New criterion to aid manual and automatic selection of the arterial input function in dynamic susceptibility contrast MRI.

Egbert J W Bleeker1, Matthias J P van Osch, Alan Connelly, Mark A van Buchem, Andrew G Webb, Fernando Calamante.   

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 of the first passage. Unfortunately, partial volume effects can lead to shape errors in the bolus passage, including a narrower and higher peak, which might be selected as a "correct" AIF. In this study, a new criterion is proposed that detects shape errors based on tracer kinetic principles for computing cerebral blood volume. This criterion uses the ratio of the steady-state value to the area-under-the-curve of the first passage, which should result in an equal value for tissue and arterial responses. By using a reference value from tissue, partial volume effects-induced shape errors of the AIF measurement can be detected. Different factors affecting the ratio were investigated using simulations. These showed that the new criterion should only be used in studies with T(1) -insensitive acquisition. In vivo data were used to evaluate the proposed approach. The data showed that the new criterion enables detection of shape errors, although false positives do occur, which could be easily avoided when combined with current AIF selection criteria.
Copyright © 2010 Wiley-Liss, Inc.

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Year:  2010        PMID: 21264935     DOI: 10.1002/mrm.22599

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  13 in total

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8.  Automatic determination of the arterial input function in dynamic susceptibility contrast MRI: comparison of different reproducible clustering algorithms.

Authors:  Jiandong Yin; Jiawen Yang; Qiyong Guo
Journal:  Neuroradiology       Date:  2015-01-30       Impact factor: 2.804

9.  Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function.

Authors:  Jiandong Yin; Hongzan Sun; Jiawen Yang; Qiyong Guo
Journal:  PLoS One       Date:  2014-02-04       Impact factor: 3.240

10.  Evaluating the feasibility of an agglomerative hierarchy clustering algorithm for the automatic detection of the arterial input function using DSC-MRI.

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Journal:  PLoS One       Date:  2014-06-16       Impact factor: 3.240

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