Quantitative phenomenological model of the BOLD contrast mechanism.

Different theoretical models of the BOLD contrast mechanism are used for many applications including BOLD quantification (qBOLD) and vessel size imaging, both in health and disease. Each model simplifies the system under consideration, making approximations about the structure of the blood vessel network and diffusion of water molecules through inhomogeneities in the magnetic field created by deoxyhemoglobin-containing blood vessels. In this study, Monte-Carlo methods are used to simulate the BOLD MR signal generated by diffusing water molecules in the presence of long, cylindrical blood vessels. Using these simulations we introduce a new, phenomenological model that is far more accurate over a range of blood oxygenation levels and blood vessel radii than existing models. This model could be used to extract physiological parameters of the blood vessel network from experimental data in BOLD-based experiments. We use our model to establish ranges of validity for the existing analytical models of Yablonskiy and Haacke, Kiselev and Posse, Sukstanskii and Yablonskiy (extended to the case of arbitrary time in the spin echo sequence) and Bauer et al. (extended to the case of randomly oriented cylinders). Although these models are shown to be accurate in the limits of diffusion under which they were derived, none of them is accurate for the whole physiological range of blood vessels radii and blood oxygenation levels. We also show the extent of systematic errors that are introduced due to the approximations of these models when used for BOLD signal quantification.

[1]  B. Douglas Ward,et al.  A novel technique for modeling susceptibility-based contrast mechanisms for arbitrary microvascular geometries: The finite perturber method , 2008, NeuroImage.

[2]  E. Haacke,et al.  Theory of NMR signal behavior in magnetically inhomogeneous tissues: The static dephasing regime , 1994, Magnetic resonance in medicine.

[3]  James L Tatum,et al.  Hypoxia: Importance in tumor biology, noninvasive measurement by imaging, and value of its measurement in the management of cancer therapy , 2006, International journal of radiation biology.

[4]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[5]  Ravi S. Menon,et al.  Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. , 1993, Biophysical journal.

[6]  W. Heiss Best measure of ischemic penumbra: positron emission tomography. , 2003, Stroke.

[7]  A. Sukstanskii,et al.  Gaussian approximation in the theory of MR signal formation in the presence of structure-specific magnetic field inhomogeneities. Effects of impermeable susceptibility inclusions. , 2004, Journal of magnetic resonance.

[8]  A Gregory Sorensen,et al.  In vivo validation of MRI vessel caliber index measurement methods with intravital optical microscopy in a U87 mouse brain tumor model. , 2010, Neuro-oncology.

[9]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. 1996. , 1996, Journal of magnetic resonance.

[10]  D. Yablonskiy,et al.  Validation of oxygen extraction fraction measurement by qBOLD technique , 2008, Magnetic resonance in medicine.

[11]  Francis Cassot,et al.  Morphometry of the human cerebral cortex microcirculation: General characteristics and space-related profiles , 2008, NeuroImage.

[12]  J C Gore,et al.  Asymmetric spin‐echo imaging of magnetically inhomogeneous systems: Theory, experiment, and numerical studies , 1998, Magnetic resonance in medicine.

[13]  Kamil Ugurbil,et al.  An integrative model for neuronal activity-induced signal changes for gradient and spin echo functional imaging , 2009, NeuroImage.

[14]  Yulin Ge,et al.  Baseline blood oxygenation modulates response amplitude: Physiologic basis for intersubject variations in functional MRI signals , 2008, Magnetic resonance in medicine.

[15]  Egill Rostrup,et al.  Determination of relative CMRO2 from CBF and BOLD changes: Significant increase of oxygen consumption rate during visual stimulation , 1999, Magnetic resonance in medicine.

[16]  J. R. Baker,et al.  The intravascular contribution to fmri signal change: monte carlo modeling and diffusion‐weighted studies in vivo , 1995, Magnetic resonance in medicine.

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

[18]  William J Powers,et al.  Variability of cerebral blood volume and oxygen extraction: stages of cerebral haemodynamic impairment revisited. , 2002, Brain : a journal of neurology.

[19]  V. Kiselev,et al.  Theory of susceptibility‐induced transverse relaxation in the capillary network in the diffusion narrowing regime , 2005, Magnetic resonance in medicine.

[20]  Ying Zheng,et al.  Theory and generalization of monte carlo models of the BOLD signal source , 2008, Magnetic resonance in medicine.

[21]  D. Yablonskiy,et al.  Water proton MR properties of human blood at 1.5 Tesla: Magnetic susceptibility, T1, T2, T  *2 , and non‐Lorentzian signal behavior , 2001, Magnetic resonance in medicine.

[22]  T. Bezabeh,et al.  Advances in methods for assessing tumor hypoxia in vivo: Implications for treatment planning , 2006, Cancer and Metastasis Reviews.

[23]  T. L. Davis,et al.  Calibrated functional MRI: mapping the dynamics of oxidative metabolism. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Guy B. Williams,et al.  Quantitative BOLD: The effect of diffusion , 2010, Journal of magnetic resonance imaging : JMRI.

[25]  B R Rosen,et al.  NMR imaging of changes in vascular morphology due to tumor angiogenesis , 1998, Magnetic resonance in medicine.

[26]  D. Yablonskiy,et al.  Quantitation of intrinsic magnetic susceptibility‐related effects in a tissue matrix. Phantom study , 1998, Magnetic resonance in medicine.

[27]  L. Schad,et al.  Susceptibility‐related MR signal dephasing under nonstatic conditions: Experimental verification and consequences for qBOLD measurements , 2011, Journal of Magnetic Resonance Imaging.

[28]  V. Kiselev,et al.  Theoretical model of intravascular paramagnetic tracers effect on tissue relaxation , 2006, Magnetic resonance in medicine.

[29]  P. Jakob,et al.  Local frequency density of states around field inhomogeneities in magnetic resonance imaging: effects of diffusion. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  J. Jensen,et al.  NMR relaxation in tissues with weak magnetic inhomogeneities , 2000, Magnetic resonance in medicine.

[31]  THEORY OF COHERENT AND INCOHERENT NUCLEAR SPIN DEPHASING IN THE HEART , 1999, cond-mat/9910006.

[32]  M. Décorps,et al.  Vessel size imaging , 2001, Magnetic resonance in medicine.

[33]  B. D. Ward,et al.  Characterization of a first-pass gradient-echo spin-echo method to predict brain tumor grade and angiogenesis. , 2004, AJNR. American journal of neuroradiology.

[34]  D. Yablonskiy,et al.  Quantitative BOLD: Mapping of human cerebral deoxygenated blood volume and oxygen extraction fraction: Default state , 2007, Magnetic resonance in medicine.

[35]  José P Marques,et al.  Using forward calculations of the magnetic field perturbation due to a realistic vascular model to explore the BOLD effect , 2008, NMR in biomedicine.

[36]  D. Tank,et al.  Brain magnetic resonance imaging with contrast dependent on blood oxygenation. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[37]  R. Strecker,et al.  Vessel size imaging in humans , 2005, Magnetic resonance in medicine.

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

[39]  V. Kiselev,et al.  Transverse NMR relaxation in magnetically heterogeneous media. , 2008, Journal of magnetic resonance.

[40]  Dmitriy A Yablonskiy,et al.  Gaussian approximation in the theory of MR signal formation in the presence of structure-specific magnetic field inhomogeneities. , 2003, Journal of magnetic resonance.