Cerebral Perfusion Imaging by Bolus Tracking

Summary: Cerebral perfusion may be visualized by the dynamic imaging of an intravenously injected bolus (a few milliliters) of clinically approved gadolinium-containing contrast media. During its passage through the vasculature of the brain, the contrast agent induces magnetic field disturbances, which can be seen as signal loss on appropriately weighted dynamic MRI. This article deals with the quantitative analysis of such signal changes, first in terms of tracer concentration and then, via the mathematical approach of deconvolution, in terms of tissue microvascular physiology, culminating in quantitative estimates on a pixel-by-pixel basis of physiologic parameters, such as cerebral blood volume, mean transit time, and cerebral blood flow.

[1]  J. Bassingthwaighte,et al.  A vascular transport operator. , 1993, The American journal of physiology.

[2]  B. Rosen,et al.  Modeling Cerebral Blood Flow and Flow Heterogeneity from Magnetic Resonance Residue Data , 1999, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[3]  V G Kiselev On the theoretical basis of perfusion measurements by dynamic susceptibility contrast MRI , 2001, Magnetic resonance in medicine.

[4]  P. Johannsen,et al.  Cerebral Blood Flow Measurements by Magnetic Resonance Imaging Bolus Tracking: Comparison with [15O]H2O Positron Emission Tomography in Humans , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[5]  M. Viergever,et al.  Maximum likelihood estimation of cerebral blood flow in dynamic susceptibility contrast MRI , 1999, Magnetic resonance in medicine.

[6]  Jeffry R Alger,et al.  Perfusion-Weighted Magnetic Resonance Imaging Thresholds Identifying Core, Irreversibly Infarcted Tissue , 2003, Stroke.

[7]  J. Fike,et al.  A deconvolution method for evaluating indicator-dilution curves. , 1994, Physics in medicine and biology.

[8]  B. Rosen,et al.  MR Contrast Due to Microscopically Heterogeneous Magnetic Susceptibility: Numerical Simulations and Applications to Cerebral Physiology , 1991, Magnetic resonance in medicine.

[9]  K. B. Larson,et al.  Tracer-kinetic analysis for measuring regional cerebral blood flow by dynamic nuclear magnetic resonance imaging. , 1994, Journal of theoretical biology.

[10]  G. Brix,et al.  Cerebral Blood Flow and Cerebrovascular Reserve Capacity: Estimation by Dynamic Magnetic Resonance Imaging , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[11]  B. Rosen,et al.  Dynamic imaging with lanthanide chelates in normal brain: Contrast due to magnetic susceptibility effects , 1988, Magnetic resonance in medicine.

[12]  G N Stewart,et al.  Researches on the Circulation Time in Organs and on the Influences which affect it , 1893, The Journal of physiology.

[13]  T. A. Bronikowski,et al.  Model-free deconvolution techniques for estimating vascular transport functions. , 1983, International journal of bio-medical computing.

[14]  Mark S. Cohen,et al.  Contrast agents and cerebral hemodynamics , 1991, Magnetic resonance in medicine.

[15]  Leif Østergaard,et al.  Magnetic Resonance Perfusion-Weighted Imaging of Acute Cerebral Infarction: Effect of the Calculation Methods and Underlying Vasculopathy , 2002, Stroke.

[16]  B. Rosen,et al.  Perfusion imaging with NMR contrast agents , 1990, Magnetic resonance in medicine.

[17]  B. Rosen,et al.  Microscopic susceptibility variation and transverse relaxation: Theory and experiment , 1994, Magnetic resonance in medicine.

[18]  G. Cosnard,et al.  Whole brain quantitative CBF and CBV measurements using MRI bolus tracking: Comparison of methodologies , 2000, Magnetic resonance in medicine.

[19]  K. Zierler Equations for Measuring Blood Flow by External Monitoring of Radioisotopes , 1965, Circulation research.

[20]  C. Rasmussen,et al.  Perfusion quantification using Gaussian process deconvolution , 2002, Magnetic resonance in medicine.

[21]  D. Gadian,et al.  Delay and dispersion effects in dynamic susceptibility contrast MRI: Simulations using singular value decomposition , 2000, Magnetic resonance in medicine.

[22]  Leif Østergaard,et al.  Evaluation of four postprocessing methods for determination of cerebral blood volume and mean transit time by dynamic susceptibility contrast imaging , 2002, Magnetic resonance in medicine.

[23]  W. J. Lorenz,et al.  Quantification of regional cerebral blood flow and volume with dynamic susceptibility contrast-enhanced MR imaging. , 1994, Radiology.

[24]  Jianfeng Gao,et al.  Cerebral blood flow measurement by dynamic contrast MRI using singular value decomposition with an adaptive threshold , 1999, Magnetic resonance in medicine.

[25]  S. Van Huffel,et al.  Reliable and efficient deconvolution technique based on total linear least squares for calculating the renal retention function , 2006, Medical and Biological Engineering and Computing.

[26]  B R Rosen,et al.  Mr contrast due to intravascular magnetic susceptibility perturbations , 1995, Magnetic resonance in medicine.

[27]  F. Ståhlberg,et al.  Assessment of regional cerebral blood flow by dynamic susceptibility contrast MRI using different deconvolution techniques , 2000, Magnetic resonance in medicine.

[28]  S. Posse,et al.  Analytical model of susceptibility‐induced MR signal dephasing: Effect of diffusion in a microvascular network , 1999, Magnetic resonance in medicine.

[29]  C. Starmer,et al.  Indicator Transit Time Considered as a Gamma Variate , 1964, Circulation research.

[30]  B. Rosen,et al.  Pitfalls in MR measurement of tissue blood flow with intravascular tracers: Which mean transit time? , 1993, Magnetic resonance in medicine.

[31]  Leif Østergaard,et al.  CBF and CBV measurements by USPIO bolus tracking: Reproducibility and comparison with Gd‐based values , 1999, Journal of magnetic resonance imaging : JMRI.

[32]  N. Lassen,et al.  Cerebral Transit of an Intravascular Tracer May Allow Measurement of Regional Blood Volume but Not Regional Blood Flow , 1984, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[33]  B. Rosen,et al.  Susceptibility contrast imaging of cerebral blood volume: Human experience , 1991, Magnetic resonance in medicine.

[34]  B. Rosen,et al.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis , 1996, Magnetic resonance in medicine.

[35]  K. Zierler Theoretical Basis of Indicator‐Dilution Methods For Measuring Flow and Volume , 1962 .

[36]  V. G. Kiselev,et al.  ANALYTICAL THEORY OF SUSCEPTIBILITY INDUCED NMR SIGNAL DEPHASING IN A CEREBROVASCULAR NETWORK , 1998 .

[37]  Leif Østergaard,et al.  Effects of tracer arrival time on flow estimates in MR perfusion‐weighted imaging , 2003, Magnetic resonance in medicine.

[38]  B. Rosen,et al.  Tracer arrival timing‐insensitive technique for estimating flow in MR perfusion‐weighted imaging using singular value decomposition with a block‐circulant deconvolution matrix , 2003, Magnetic resonance in medicine.

[39]  K. Zierler,et al.  On the theory of the indicator-dilution method for measurement of blood flow and volume. , 1954, Journal of applied physiology.

[40]  A. Gjedde,et al.  Absolute Cerebral Blood Flow and Blood Volume Measured by Magnetic Resonance Imaging Bolus Tracking: Comparison with Positron Emission Tomography Values , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[41]  B. Rosen,et al.  Functional mapping of the human visual cortex by magnetic resonance imaging. , 1991, Science.