New criteria for assessing fit quality in dynamic contrast‐enhanced T1‐weighted MRI for perfusion and permeability imaging

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.

[1]  Hadassa Degani,et al.  Parametric imaging of tumor perfusion using flow‐ and permeability‐limited tracers , 2002, Journal of magnetic resonance imaging : JMRI.

[2]  M. Knopp,et al.  Intracranial meningeomas: time- and dose-dependent effects of irradiation on tumor microcirculation monitored by dynamic MR imaging. , 1997, Magnetic resonance imaging.

[3]  H. Mehdorn,et al.  Differentiation of cerebral tumors using multi-section echo planar MR perfusion imaging. , 2003, European journal of radiology.

[4]  G Wu,et al.  Sensitivity analysis of pharmacokinetic parameters in one-compartment models. , 2000, Pharmacological research.

[5]  J. Jacquez Compartmental analysis in biology and medicine , 1985 .

[6]  M. Bahner,et al.  Regional blood flow, capillary permeability, and compartmental volumes: measurement with dynamic CT--initial experience. , 1999, Radiology.

[7]  S. Sourbron,et al.  Diffusion and perfusion MRI: basic physics. , 2001, European journal of radiology.

[8]  J. Lechner,et al.  Establishment and characterization of a human prostatic carcinoma cell line (PC-3). , 1979, Investigative urology.

[9]  Elliot K. Fishman,et al.  Functional Computed Tomography , 1997 .

[10]  M. Port,et al.  P792: a rapid clearance blood pool agent for magnetic resonance imaging: preliminary results , 2001, Magnetic Resonance Materials in Physics, Biology and Medicine.

[11]  M. Kaplan,et al.  Challenges in dynamic contrast‐enhanced MRI imaging of cervical lymph nodes to detect metastatic disease , 2003, Journal of magnetic resonance imaging : JMRI.

[12]  Egill Rostrup,et al.  Capillary transfer constant of Gd‐DTPA in the myocardium at rest and during vasodilation assessed by MRI , 1998, Magnetic resonance in medicine.

[13]  E de Kerviler,et al.  Contrast agents in magnetic resonance imaging of the liver: present and future. , 1998, Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie.

[14]  François Estève,et al.  Absolute Cerebral Blood Volume and Blood Flow Measurements Based on Synchrotron Radiation Quantitative Computed Tomography , 2003, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[15]  Socrates Dokos,et al.  Parameter estimation in cardiac ionic models. , 2004, Progress in biophysics and molecular biology.

[16]  F Frouin,et al.  Reduced capillary perfusion and permeability in human tumour xenografts treated with the VEGF signalling inhibitor ZD4190: an in vivo assessment using dynamic MR imaging and macromolecular contrast media. , 2003, Magnetic resonance imaging.

[17]  M. Bilgen,et al.  In vivo assessment of blood-spinal cord barrier permeability: serial dynamic contrast enhanced MRI of spinal cord injury. , 2002, Magnetic resonance imaging.

[18]  W Richter,et al.  Box-Jenkins intervention analysis of functional magnetic resonance imaging data , 1997, Neuroscience Research.

[19]  Ting-Yim Lee Functional CT: physiological models , 2002 .

[20]  France Mentré,et al.  Development and implementation of the population Fisher information matrix for the evaluation of population pharmacokinetic designs , 2001, Comput. Methods Programs Biomed..

[21]  A. Padhani Dynamic contrast‐enhanced MRI in clinical oncology: Current status and future directions , 2002, Journal of magnetic resonance imaging : JMRI.

[22]  Irwin W. Sandberg,et al.  On the mathematical foundations of compartmental analysis in biology, medicine, and ecology , 1978 .

[23]  J Sykes,et al.  Myocardial viability imaging using Gd‐DTPA: Physiological modeling of infarcted myocardium, and impact on injection strategy and imaging time , 2002, Magnetic resonance in medicine.

[24]  O Nalcioglu,et al.  Measurement of vascular volume fraction and blood‐tissue permeability constants with a pharmacokinetic model: Studies in rat muscle tumors with dynamic Gd‐DTPA enhanced MRI , 1994, Magnetic resonance in medicine.

[25]  P. Tofts,et al.  Measurement of the blood‐brain barrier permeability and leakage space using dynamic MR imaging. 1. Fundamental concepts , 1991, Magnetic resonance in medicine.

[26]  J. Chan,et al.  Discrimination of an infected brain tumor from a cerebral abscess by combined MR perfusion and diffusion imaging. , 2002, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[27]  F Lazeyras,et al.  Quantification of myocardial perfusion with FAST sequence and Gd bolus in patients with normal cardiac function , 1999, Journal of magnetic resonance imaging : JMRI.

[28]  Raimund J. Ober The Fisher information matrix for linear systems , 2002, Syst. Control. Lett..

[29]  H A Vrooman,et al.  Detection of areas with viable remnant tumor in postchemotherapy patients with Ewing's sarcoma by dynamic contrast-enhanced MRI using pharmacokinetic modeling. , 2000, Magnetic resonance imaging.

[30]  Sandro Macchietto,et al.  Designing robust optimal dynamic experiments , 2002 .

[31]  David L Buckley,et al.  Uncertainty in the analysis of tracer kinetics using dynamic contrast‐enhanced T1‐weighted MRI , 2002, Magnetic resonance in medicine.

[32]  R. Upton,et al.  Acute cardiovascular effects of magnesium and their relationship to systemic and myocardial magnesium concentrations after short infusion in awake sheep. , 2001, The Journal of pharmacology and experimental therapeutics.

[33]  J C Waterton,et al.  Quantification of endothelial permeability, leakage space, and blood volume in brain tumors using combined T1 and T2* contrast‐enhanced dynamic MR imaging , 2000, Journal of magnetic resonance imaging : JMRI.

[34]  G Brix,et al.  Pathophysiologic basis of contrast enhancement in breast tumors , 1999, Journal of magnetic resonance imaging : JMRI.

[35]  R. Brasch,et al.  MRI characterization of tumors and grading angiogenesis using macromolecular contrast media: status report. , 2000, European journal of radiology.

[36]  A. Jackson,et al.  Parametric mapping of scaled fitting error in dynamic susceptibility contrast enhanced MR perfusion imaging. , 2000, The British journal of radiology.

[37]  G. Zaharchuk,et al.  Delivery of imaging agents into brain. , 1999, Advanced drug delivery reviews.

[38]  G Brix,et al.  Classification of signal-time curves from dynamic MR mammography by neural networks. , 2001, Magnetic resonance imaging.