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New criteria for assessing fit quality in dynamic contrast‐enhanced T 1 ‐weighted MRI for perfusion and permeability imaging
Author(s) -
Balvay Daniel,
Frouin Frédérique,
Calmon Guillaume,
Bessoud Bertrand,
Kahn Edmond,
Siauve Nathalie,
Clément Olivier,
Cuenod Charles A.
Publication year - 2005
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.20650
Subject(s) - contrast (vision) , residual , dimensionless quantity , computer science , perfusion , dynamic contrast enhanced mri , mathematics , magnetic resonance imaging , data mining , artificial intelligence , algorithm , medicine , radiology , physics , mechanics
Contrast‐enhanced (CE) MRI provides in vivo physiological information that cannot be obtained by conventional imaging methods. This information is generally extracted by using models to represent the circulation of contrast agent in the body. However, the results depend on the quality of the fit obtained with the chosen model. Therefore, one must check the fit quality to avoid working on physiologically irrelevant parameters. In this study two dimensionless criteria—the fraction of modeling information (FMI) and the fraction of residual information (FRI)—are proposed to identify errors caused by poor fit. These are compared with more conventional criteria, namely the quadratic error and the correlation coefficient, both theoretically and with the use of simulated and real CE‐MRI data. The results indicate the superiority of the new criteria. It is also shown that these new criteria can be used to detect oversimplified models. Magn Reson Med, 2005. © 2005 Wiley‐Liss, Inc.