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Algorithms for calculation of kinetic parameters from T1‐weighted dynamic contrast‐enhanced magnetic resonance imaging
Author(s) -
Horsfield Mark A.,
Morgan Bruno
Publication year - 2004
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.20161
Subject(s) - computer science , dynamic contrast , contrast (vision) , dynamic contrast enhanced mri , algorithm , magnetic resonance imaging , visualization , dynamic imaging , image processing , data mining , artificial intelligence , image (mathematics) , medicine , radiology , digital image processing
Purpose To quantify the errors involved in calculating dynamic parameters ( K trans and v e ) from dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) scans, and to develop alternative analyses to improve accuracy or increase processing speed. Materials and Methods This paper presents three different ways of handling the discrete samples of the arterial input and tissue response data with increasing fidelity, with which this continuous arterial input function (AIF) is represented. Also, a new noniterative approach to parameter estimation was developed from one used previously for analysis of radioactive tracer concentrations in radioangiography. The analysis methods were tested using simulated data. Results The more sophisticated schemes for data processing give more accurate parameter estimates when data are sparsely sampled, at least for the AIF that we modeled. The noniterative algorithm is very rapid in execution, but was more susceptible to measurement errors. Conclusion The improved algorithms presented should be useful when the AIF and tissue response are sparsely sampled. The noniterative approach may be suitable for semiquantitative visualization, or where the AIF and tissue response are sampled accurately and with a small time interval between samples. J. Magn. Reson. Imaging 2004;20:723–729. © 2004 Wiley‐Liss, Inc.