Validation of a T1 and T2* leakage correction method based on multiecho dynamic susceptibility contrast MRI using MION as a reference standard

A combined biophysical‐ and pharmacokinetic‐based method is proposed to separate, quantify, and correct for both T1 and T2* leakage effects using dual‐echo dynamic susceptibility contrast (DSC) acquisitions to provide more accurate hemodynamic measures, as validated by a reference intravascular contrast agent (CA).

[1]  M A Viergever,et al.  Simultaneous quantitative cerebral perfusion and Gd‐DTPA extravasation measurement with dual‐echo dynamic susceptibility contrast MRI , 2000, Magnetic resonance in medicine.

[2]  Tracy T Batchelor,et al.  Increased survival of glioblastoma patients who respond to antiangiogenic therapy with elevated blood perfusion. , 2012, Cancer research.

[3]  R M Weisskoff,et al.  Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. , 2006, AJNR. American journal of neuroradiology.

[4]  Glyn Johnson,et al.  Measuring blood volume and vascular transfer constant from dynamic, T  2* ‐weighted contrast‐enhanced MRI , 2004, Magnetic resonance in medicine.

[5]  J. Boxerman,et al.  The Role of Preload and Leakage Correction in Gadolinium-Based Cerebral Blood Volume Estimation Determined by Comparison with MION as a Criterion Standard , 2012, American Journal of Neuroradiology.

[6]  Ashley M Stokes,et al.  Assessment of a combined spin- and gradient-echo (SAGE) DSC-MRI method for preclinical neuroimaging. , 2014, Magnetic resonance imaging.

[7]  Matus Straka,et al.  Simultaneous Perfusion and Permeability Measurements Using Combined Spin- and Gradient-Echo MRI , 2013, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[8]  Eric S. Paulson,et al.  Comparison of Dynamic Susceptibility-weighted , 2008 .

[9]  E. Edmund Kim Clinical Perfusion MRI: Techniques and Applications , 2014, The Journal of Nuclear Medicine.

[10]  Joanna M. Wardlaw,et al.  Assessment of blood–brain barrier disruption using dynamic contrast-enhanced MRI. A systematic review , 2014, NeuroImage: Clinical.

[11]  D L Buckley,et al.  Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability , 2012, Physics in medicine and biology.

[12]  V. Haughton,et al.  Automatic calculation of the arterial input function for cerebral perfusion imaging with MR imaging. , 2003, Radiology.

[13]  Fernando Calamante,et al.  The 39 steps: evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI , 2013, NMR in biomedicine.

[14]  Kim Mouridsen,et al.  T1- and T*2-Dominant Extravasation Correction in DSC-MRI: Part I—Theoretical Considerations and Implications for Assessment of Tumor Hemodynamic Properties , 2011, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[15]  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.

[16]  W. Rooney,et al.  Determination of the MRI contrast agent concentration time course in vivo following bolus injection: Effect of equilibrium transcytolemmal water exchange , 2000, Magnetic resonance in medicine.

[17]  D. Noll,et al.  Homodyne detection in magnetic resonance imaging. , 1991, IEEE transactions on medical imaging.

[18]  G S Karczmar,et al.  Differentiating between T1 and T2* changes caused by gadopentetate dimeglumine in the kidney by using a double‐echo dynamic MR imaging sequence , 1996, Journal of magnetic resonance imaging : JMRI.

[19]  Jingping Xie,et al.  Assessing tumor cytoarchitecture using multiecho DSC‐MRI derived measures of the transverse relaxivity at tracer equilibrium (TRATE) , 2015, Magnetic resonance in medicine.

[20]  Paul W. Cleary,et al.  An Efficient Computational Approach to Characterize DSC-MRI Signals Arising from Three-Dimensional Heterogeneous Tissue Structures , 2014, PloS one.

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

[22]  J. Mintorovitch,et al.  Comparison of Magnetic Properties of MRI Contrast Media Solutions at Different Magnetic Field Strengths , 2005, Investigative radiology.

[23]  Glyn Johnson,et al.  Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. , 2004, AJNR. American journal of neuroradiology.

[24]  B. D. Ward,et al.  Improving the reliability of obtaining tumor hemodynamic parameters in the presence of contrast agent extravasation , 2005, Magnetic resonance in medicine.

[25]  S Ekholm,et al.  Percentage Signal Recovery Derived from MR Dynamic Susceptibility Contrast Imaging Is Useful to Differentiate Common Enhancing Malignant Lesions of the Brain , 2011, American Journal of Neuroradiology.

[26]  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.

[27]  P. Tofts Modeling tracer kinetics in dynamic Gd‐DTPA MR imaging , 1997, Journal of magnetic resonance imaging : JMRI.

[28]  Ting-Yim Lee,et al.  An Adiabatic Approximation to the Tissue Homogeneity Model for Water Exchange in the Brain: I. Theoretical Derivation , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[29]  David A Hormuth,et al.  A comparison of individual and population-derived vascular input functions for quantitative DCE-MRI in rats. , 2014, Magnetic resonance imaging.

[30]  M Takahashi,et al.  Correlation of MR imaging-determined cerebral blood volume maps with histologic and angiographic determination of vascularity of gliomas. , 1998, AJR. American journal of roentgenology.

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

[32]  T E Yankeelov,et al.  A theoretical framework to model DSC-MRI data acquired in the presence of contrast agent extravasation , 2009, Physics in medicine and biology.

[33]  Thomas E Yankeelov,et al.  Comparison of dual-echo DSC-MRI- and DCE-MRI-derived contrast agent kinetic parameters. , 2012, Magnetic resonance imaging.

[34]  A P Pathak,et al.  Utility of simultaneously acquired gradient‐echo and spin‐echo cerebral blood volume and morphology maps in brain tumor patients , 2000, Magnetic resonance in medicine.

[35]  E F Halpern,et al.  Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. , 1994, Radiology.

[36]  Thomas E Yankeelov,et al.  A novel AIF tracking method and comparison of DCE-MRI parameters using individual and population-based AIFs in human breast cancer , 2011, Physics in medicine and biology.

[37]  S. T. Nichols,et al.  Quantitative evaluation of several partial fourier reconstruction algorithms used in mri , 1993, Magnetic resonance in medicine.

[38]  G. Zaharchuk,et al.  Combined spin‐ and gradient‐echo perfusion‐weighted imaging , 2012, Magnetic resonance in medicine.

[39]  M. Knopp,et al.  Estimating kinetic parameters from dynamic contrast‐enhanced t1‐weighted MRI of a diffusable tracer: Standardized quantities and symbols , 1999, Journal of magnetic resonance imaging : JMRI.

[40]  Yuan-Yu Hsu,et al.  Is Weisskoff model valid for the correction of contrast agent extravasation with combined T1 and T2* effects in dynamic susceptibility contrast MRI? , 2011, Medical physics.

[41]  S Sourbron,et al.  Bolus‐tracking MRI with a simultaneous T1‐ and T  2* ‐measurement , 2009, Magnetic resonance in medicine.

[42]  Steven Sourbron,et al.  T2*‐relaxivity contrast imaging: First results , 2013, Magnetic Resonance in Medicine.