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Improving the arterial input function in dynamic contrast enhanced MRI by fitting the signal in the complex plane
Author(s) -
Simonis Frank F.J.,
Sbrizzi Alessandro,
Beld Ellis,
Lagendijk Jan J.W.,
van den Berg Cornelis A.T.
Publication year - 2016
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.26023
Subject(s) - voxel , signal (programming language) , imaging phantom , dynamic contrast , dynamic contrast enhanced mri , standard deviation , computer science , contrast (vision) , phase (matter) , magnetic resonance imaging , nuclear medicine , mathematics , artificial intelligence , statistics , physics , medicine , radiology , quantum mechanics , programming language
Purpose Dynamic contrast enhanced (DCE) imaging is a widely used technique in oncologic imaging. An essential prerequisite for obtaining quantitative values from DCE‐MRI is the determination of the arterial input function (AIF). However, it is very challenging to accurately estimate the AIF using MR. A comprehensive model, which uses complex data instead of either magnitude or phase, was developed to improve AIF estimation. Theory and Methods The model was first applied to simulated data. Subsequently, the accuracy of the estimated contrast agent concentration was validated in a phantom. Finally the method was applied to existing DCE scans of 13 prostate cancer patients. Results The complex signal method combines the complementary strengths of the magnitude and phase method, increasing the precision and accuracy of concentration estimation in simulated and phantom data. The in vivo AIFs show a good agreement between arterial voxels (standard deviation in the peak and tail equal 0.4 mM and 0.12 mM, respectively). Furthermore, the dynamic behavior closely followed the AIF obtained with DCE‐CT in the same patients (mean correlation coefficient: 0.92). Conclusion By using the complex signal, the AIF estimation becomes more accurate and precise. This might enable patient specific AIFs, thereby improving the quantitative values obtained from DCE‐MRI. Magn Reson Med 76:1236–1245, 2016. © 2015 Wiley Periodicals, Inc.