期刊
MAGNETIC RESONANCE IN MEDICINE
卷 58, 期 2, 页码 290-297出版社
WILEY
DOI: 10.1002/mrm.21332
关键词
artificial neural network; MRI contrast agent; quantitative autoradiography; MRI image processing; capillary permeability; Look-Locker
Using an MRI T, 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 (OAR) using radioiodinated serum albumin (RISA). OAR 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; OAR 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.
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