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- Title
MRI estimation of contrast agent concentration in tissue using a neural network approach.
- Authors
Bagher-Ebadian, Hassan; Nagaraja, Tavarekere N.; Paudyal, Ramesh; Whitton, Polly; Panda, Swayamprava; Fenstermacher, Joseph D.; Ewing, James R.
- Abstract
Using an MRI T1 by multiple readout pulses (TOMROP) image set, an adaptive neural network (ANN) was trained to directly estimate the concentration of a contrast agent (CA), gadolinium-bovine serum albumin (Gd-BSA), in tissue. In nine rats implanted with a 9L cerebral tumor, MRI acquisition of TOMROP inversion-recovery data was followed by quantitative autoradiography (QAR) using radioiodinated serum albumin (RISA). QAR autoradiograms were used as a training set for the ANN. Precontrast and 25 min postcontrast TOMROP image sets were shown to the ANN in the form of a physical feature set related to 24 inversion-recovery images; QAR autoradiograms at 30 min after injection of RISA were taken as the training standard for the network. After training and optimization, the ANN produced a map of Gd-BSA concentration [g-moles/liter]. The prediction by the ANN of CA concentration at 25 min after injection was well correlated ( r = 0.82, P < 0.0001) with the corresponding autoradiogram's measure of CA concentration. Magn Reson Med 58:290-297, 2007. © 2007 Wiley-Liss, Inc.
- Publication
Magnetic Resonance in Medicine, 2007, Vol 58, Issue 2, p290
- ISSN
0740-3194
- Publication type
Article
- DOI
10.1002/mrm.21332