Quantitative oxygenation venography from MRI phase
Corresponding Author
Audrey P. Fan
Magnetic Resonance Imaging Group, Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Address reprint requests to: Audrey Fan, S.M., 32 Vassar Street, Room 36-792, Massachusetts Institute of Technology, Cambridge, MA 02139. E-mail: [email protected]Search for more papers by this authorBerkin Bilgic
Magnetic Resonance Imaging Group, Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Search for more papers by this authorLouis Gagnon
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Harvard-MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
Search for more papers by this authorThomas Witzel
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Search for more papers by this authorHimanshu Bhat
Siemens Medical Solutions USA Inc., Charlestown, Massachusetts, USA
Search for more papers by this authorBruce R. Rosen
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Harvard-MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
Search for more papers by this authorElfar Adalsteinsson
Magnetic Resonance Imaging Group, Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Harvard-MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
Search for more papers by this authorCorresponding Author
Audrey P. Fan
Magnetic Resonance Imaging Group, Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Address reprint requests to: Audrey Fan, S.M., 32 Vassar Street, Room 36-792, Massachusetts Institute of Technology, Cambridge, MA 02139. E-mail: [email protected]Search for more papers by this authorBerkin Bilgic
Magnetic Resonance Imaging Group, Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Search for more papers by this authorLouis Gagnon
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Harvard-MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
Search for more papers by this authorThomas Witzel
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Search for more papers by this authorHimanshu Bhat
Siemens Medical Solutions USA Inc., Charlestown, Massachusetts, USA
Search for more papers by this authorBruce R. Rosen
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Harvard-MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
Search for more papers by this authorElfar Adalsteinsson
Magnetic Resonance Imaging Group, Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
Harvard-MIT Health Sciences and Technology, Cambridge, Massachusetts, USA
Search for more papers by this authorAbstract
Purpose
To demonstrate acquisition and processing methods for quantitative oxygenation venograms that map in vivo oxygen saturation (SvO2) along cerebral venous vasculature.
Methods
Regularized quantitative susceptibility mapping (QSM) is used to reconstruct susceptibility values and estimate SvO2 in veins. QSM with ℓ1 and ℓ2 regularization are compared in numerical simulations of vessel structures with known magnetic susceptibility. Dual-echo, flow-compensated phase images are collected in three healthy volunteers to create QSM images. Bright veins in the susceptibility maps are vectorized and used to form a three-dimensional vascular mesh, or venogram, along which to display SvO2 values from QSM.
Results
Quantitative oxygenation venograms that map SvO2 along brain vessels of arbitrary orientation and geometry are shown in vivo. SvO2 values in major cerebral veins lie within the normal physiological range reported by 15O positron emission tomography. SvO2 from QSM is consistent with previous MR susceptometry methods for vessel segments oriented parallel to the main magnetic field. In vessel simulations, ℓ1 regularization results in less than 10% SvO2 absolute error across all vessel tilt orientations and provides more accurate SvO2 estimation than ℓ2 regularization.
Conclusion
The proposed analysis of susceptibility images enables reliable mapping of quantitative SvO2 along venograms and may facilitate clinical use of venous oxygenation imaging. Magn Reson Med 72:149–159, 2014. © 2013 Wiley Periodicals, Inc.
REFERENCES
- 1Ito H, Ibaraki M, Kanno I, Fukuda H, Miura S. Changes in cerebral blood flow and cerebral oxygen metabolism during neural activation measured by positron emission tomography: comparison with blood oxygenation level-dependent contrast measured by functional magnetic resonance imaging. J Cereb Blood Flow Metab 2005; 25: 371–377.
- 2Davis TL, Kwong KK, Weisskoff RM, Rosen BR. Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proc Natl Acad Sci U S A 1998; 95: 1834–1839.
- 3Baron JC, Bousser MG, Rey A, Guillard A, Comar D, Castaigne P. Reversal of focal “misery-perfusion syndrome” by extra-intracranial arterial bypass in hemodynamic cerebral ischemia. A case study with 15O positron emission tomography. Stroke 1981; 12: 454–459.
- 4Sobesky J, Zaro Weber O, Lehnhardt FG, Hesselmann V, Neveling M, Jacobs A, Heiss WD. Does the mismatch match the penumbra? Magnetic resonance imaging and positron emission tomography in early ischemic stroke. Stroke 2005; 36: 980–985.
- 5Heiss WD, Kracht L, Grond M, Rudolf J, Bauer B, Wienhard K, Pawlik G. Early [(11)C]Flumazenil/H(2)O positron emission tomography predicts irreversible ischemic cortical damage in stroke patients receiving acute thrombolytic therapy. Stroke 2000; 31: 366–369.
- 6Nordsmark M, Bentzen SM, Rudat V, et al. Prognostic value of tumor oxygenation in 397 head and neck tumors after primary radiation therapy. An international multi-center study. Radiother Oncol 2005; 77: 18–24.
- 7Leenders KL, Beaney RP, Brooks DJ, Lammertsma AA, Heather JD, McKenzie CG. Dexamethasone treatment of brain tumor patients: effects on regional cerebral blood flow, blood volume, and oxygen utilization. Neurology 1985; 35: 1610–1616.
- 8Fan AP, Kinkel RP, Madigan NK, Nielsen AS, Benner T, Tinelli E, Rosen BR, Adalsteinsson E, Mainero C. Cortical oxygen extraction as a marker of disease stage and function in multiple sclerosis: a quantitative study using 7 Tesla MRI susceptibility. In Proceedings of the 20th Annual Meeting of ISMRM, Melbourne, Australia, 2012. Abstract 498.
- 9Ge Y, Zhang Z, Lu H, Tang L, Jaggi H, Herbert J, Babb JS, Rusinek H, Grossman RI. Characterizing brain oxygen metabolism in patients with multiple sclerosis with T2-relaxation-under-spin-tagging MRI. J Cereb Blood Flow Metab 2012; 32: 403–412.
- 10Weisskoff RM, Kiihne S. MRI susceptometry: image-based measurement of absolute susceptibility of MR contrast agents and human blood. Magn Reson Med 1992; 24: 375–383.
- 11Sedlacik J, Rauscher A, Reichenbach JR. Obtaining blood oxygenation levels from MR signal behavior in the presence of single venous vessels. Magn Reson Med 2007; 58: 1035–1044.
- 12Sedlacik J, Rauscher A, Reichenbach JR. Quantification of modulated blood oxygenation levels in single cerebral veins by investigating their MR signal decay. Z Med Phys 2009; 19: 48–57.
- 13Dagher J, Du YP. Efficient and robust estimation of blood oxygenation levels in single cerebral veins. Med Biol Eng Comput 2012; 50: 473–482.
- 14Fernandez-Seara MA, Techawiboonwong A, Detre JA, Wehrli FW. MR susceptometry for measuring global brain oxygen extraction. Magn Reson Med 2006; 55: 967–973.
- 15Jain V, Langham MC, Wehrli FW. MRI estimation of global brain oxygen consumption rate. J Cereb Blood Flow Metab 2010; 30: 1598–1607.
- 16Fan AP, Benner T, Bolar DS, Rosen BR, Adalsteinsson E. Phase-based regional oxygen metabolism (PROM) using MRI. Magn Reson Med 2012; 67: 669–678.
- 17Haacke EM, Lai S, Reichenbach JR, Kuppusamy K, Hoogenraad FG, Takeichi H, Lin W. In vivo measurement of blood oxygen saturation using magnetic resonance imaging: a direct validation of the blood oxygen level-dependent concept in functional brain imaging. Hum Brain Mapp 1997; 5: 341–346.
- 18Jain V, Langham MC, Floyd TF, Jain G, Magland JF, Wehrli FW. Rapid magnetic resonance measurement of global cerebral metabolic rate of oxygen consumption in humans during rest and hypercapnia. J Cereb Blood Flow Metab 2011; 31: 1504–1512.
- 19Langham MC, Magland JF, Epstein CL, Floyd TF, Wehrli FW. Accuracy and precision of MR blood oximetry based on the long paramagnetic cylinder approximation of large vessels. Magn Reson Med 2009; 62: 333–340.
- 20Li C, Langham MC, Epstein CL, Magland JF, Wu J, Gee J, Wehrli FW. Accuracy of the cylinder approximation for susceptometric measurement of intravascular oxygen saturation. Magn Reson Med 2012; 67: 808–813.
- 21Bilgic B, Pfefferbaum A, Rohlfing T, Sullivan EV, Adalsteinsson E. MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping. Neuroimage 2012; 59: 2625–2635.
- 22Schweser F, Deistung A, Lehr BW, Reichenbach JR. Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: an approach to in vivo brain iron metabolism? Neuroimage 2011; 54: 2789–2807.
- 23Liu C, Li W, Wu B, Jiang Y, Johnson GA. 3D fiber tractography with susceptibility tensor imaging. Neuroimage 2012; 59: 1290–1298.
- 24Schweser F, Deistung A, Lehr BW, Reichenbach JR. Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping. Med Phys 2010; 37: 5165–5178.
- 25Liu T, Surapaneni K, Lou M, Cheng L, Spincemaille P, Wang Y. Cerebral microbleeds: burden assessment by using quantitative susceptibility mapping. Radiology 2012; 262: 269–278.
- 26Marques JP, Bowtell R. Application of a fourier-based method for rapid calculation of field inhomogeneity due to spatial variation of magnetic susceptibility. Concepts Magn Reson Part B Magn Reson Eng 2005; 25B: 65–78.
- 27Salomir R, De Senneville BD, Moonen CTW. A fast calculation method for magnetic field inhomogeneity due to an arbitrary distribution of bulk susceptibility. Concepts Magn Reson Part B Magn Reson Eng 2003; 19B: 26–34.
- 28Wharton S, Schafer A, Bowtell R. Susceptibility mapping in the human brain using threshold-based k-space division. Magn Reson Med 2010; 63: 1292–1304.
- 29Shmueli K, de Zwart JA, van Gelderen P, Li TQ, Dodd SJ, Duyn JH. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data. Magn Reson Med 2009; 62: 1510–1522.
- 30Liu T, Spincemaille P, de Rochefort L, Kressler B, Wang Y. Calculation of Susceptibility Through Multiple Orientation Sampling (COSMOS): a method for conditioning the inverse problem from measured magnetic field map to susceptibility source image in MRI. Magn Reson Med 2009; 61: 196–204.
- 31Schweser F, Sommer K, Deistung A, Reichenbach JR. Quantitative susceptibility mapping for investigating subtle susceptibility variations in the human brain. Neuroimage 2012; 62: 2083–2100.
- 32Liu J, Liu T, de Rochefort L, et al. Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map. Neuroimage 2012; 59: 2560–2568.
- 33de Rochefort L, Liu T, Kressler B, Liu J, Spincemaille P, Lebon V, Wu JL, Wang Y. Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: validation and application to brain imaging. Magn Reson Med 2010; 63: 194–206.
- 34Liu T, Liu J, de Rochefort L, Spincemaille P, Khalidov I, Ledoux JR, Wang Y. Morphology Enabled Dipole Inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging. Magn Reson Med 2011; 66: 777–783.
- 35Tsai PS, Kaufhold JP, Blinder P, Friedman B, Drew PJ, Karten HJ, Lyden PD, Kleinfeld D. Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels. J Neurosci 2009; 29: 14553–14570.
- 36Spees WM, Yablonskiy DA, Oswood MC, Ackerman JJH. Water proton MR properties of human blood at 1.5 Tesla: magnetic susceptibility, T-1, T-2, T-2* and non-Lorentzian signal behavior. Magn Reson Med 2001; 45: 533–542.
- 37Jain V, Abdulmalik O, Propert KJ, Wehrli FW. Investigating the magnetic susceptibility properties of fresh human blood for noninvasive oxygen saturation quantification. Magn Reson Med 2012; 68: 863–867.
- 38Thulborn KR, Waterton JC, Matthews PM, Radda GK. Oxygenation dependence of the transverse relaxation time of water protons in whole blood at high field. Biochim Biophys Acta 1982; 714: 265–270.
- 39Plyavin YA, Blum EY. Magnetic parameters of blood cells and high-gradient paramagnetic and diamagnetic phoresis. Magnetohydrodynamics 1983; 19: 349–359.
- 40Guyton AC, Hall JE. Red blood cells, anemia, and polycythemia. Philadelphia: Saunders; 2000.
- 41Duyn JH, van Gelderen P, Li TQ, de Zwart JA, Koretsky AP, Fukunaga M. High-field MRI of brain cortical substructure based on signal phase. Proc Natl Acad Sci U S A 2007; 104: 11796–11801.
- 42Li W, Wu B, Liu C. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition. Neuroimage 2011; 55: 1645–1656.
- 43Yao B, Li TQ, van Gelderen P, Shmueli K, de Zwart JA, Duyn JH. Susceptibility contrast in high field MRI of human brain as a function of tissue iron content. Neuroimage 2009; 44: 1259–1266.
- 44Deistung A, Schafer A, Schweser F, Biedermann U, Turner R, Reichenbach JR. Toward in vivo histology: a comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2*-imaging at ultra-high magnetic field strength. Neuroimage 2013; 65: 299–314.
- 45Kressler B, de Rochefort L, Liu T, Spincemaille P, Jiang Q, Wang Y. Nonlinear regularization for per voxel estimation of magnetic susceptibility distributions from MRI field maps. IEEE Trans Med Imaging 2010; 29: 273–281.
- 46Rohlfing T, Zahr NM, Sullivan EV, Pfefferbaum A. The SRI24 multichannel atlas of normal adult human brain structure. Hum Brain Mapp 2010; 31: 798–819.
- 47Hansen PC. Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion. Philadelphia: SIAM; 1998.
10.1137/1.9780898719697 Google Scholar
- 48Deistung A, Dittrich E, Sedlacik J, Rauscher A, Reichenbach JR. ToF-SWI: simultaneous time of flight and fully flow compensated susceptibility weighted imaging. J Magn Reson Imaging 2009; 29: 1478–1484.
- 49Robinson S, Grabner G, Witoszynskyj S, Trattnig S. Combining phase images from multi-channel RF coils using 3D phase offset maps derived from a dual-echo scan. Magn Reson Med 2011; 65: 1638–1648.
- 50Hammond KE, Lupo JM, Xu D, Metcalf M, Kelley DA, Pelletier D, Chang SM, Mukherjee P, Vigneron DB, Nelson SJ. Development of a robust method for generating 7.0 T multichannel phase images of the brain with application to normal volunteers and patients with neurological diseases. Neuroimage 2008; 39: 1682–1692.
- 51Jenkinson M. Fast, automated, N-dimensional phase-unwrapping algorithm. Magn Reson Med 2003; 49: 193–197.
- 52Smith SM. Fast robust automated brain extraction. Hum Brain Mapp 2002; 17: 143–155.
- 53Liu T, Khalidov I, de Rochefort L, Spincemaille P, Liu J, Tsiouris AJ, Wang Y. A novel background field removal method for MRI using projection onto dipole fields (PDF). NMR Biomed 2011; 24: 1129–1136.
- 54Fang Q, Sakadzic S, Ruvinskaya L, Devor A, Dale AM, Boas DA. Oxygen advection and diffusion in a three-dimensional vascular anatomical network. Opt Express 2008; 16: 17530–17541.
- 55Fang QQ, Boas DA. Tetrahedral mesh generation from volumetric binary and gray-scale images. In: Proceedings of the 6th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Vols 1 and 2. Piscataway, NJ: IEEE Press; 2009. p 1142–1145.
- 56Wang Y, Yu Y, Li D, Bae KT, Brown JJ, Lin W, Haacke EM. Artery and vein separation using susceptibility-dependent phase in contrast-enhanced MRA. J Magn Reson Imaging 2000; 12: 661–670.
- 57Hattori N, Bergsneider M, Wu HM, Glenn TC, Vespa PM, Hovda DA, Phelps ME, Huang SC. Accuracy of a method using short inhalation of O-15-O-2 for measuring cerebral oxygen extraction fraction with PET in healthy humans. J Nucl Med 2004; 45: 765–770.
- 58Bremmer JP, van Berckel BN, Persoon S, Kappelle LJ, Lammertsma AA, Kloet R, Luurtsema G, Rijbroek A, Klijn CJ, Boellaard R. Day-to-day test-retest variability of CBF, CMRO2, and OEF measurements using dynamic 15O PET studies. Mol Imaging Biol 2011; 13: 759–768.
- 59Haacke EM, Tang J, Neelavalli J, Cheng YC. Susceptibility mapping as a means to visualize veins and quantify oxygen saturation. J Magn Reson Imaging 2010; 32: 663–676.
- 60Hansen PC. The L-curve and its use in the numerical treatment of inverse problems. Comput Inverse Probl Electrocardiol 2000: 119–142.
- 61Langham MC, Magland JF, Floyd TF, Wehrli FW. Retrospective correction for induced magnetic field inhomogeneity in measurements of large-vessel hemoglobin oxygen saturation by MR susceptometry. Magn Reson Med 2009; 61: 626–633.
- 62Reichenbach JR, Haacke EM. High-resolution BOLD venographic imaging: a window into brain function. NMR Biomed 2001; 14: 453–467.
- 63Christen T, Bolar DS, Zaharchuk G. Imaging brain oxygenation with MRI using blood oxygenation approaches: methods, validation, and clinical applications. AJNR Am J Neuroradiol 2013; 34: 1113–1123.
- 64Wu B, Li W, Guidon A, Liu C. Whole brain susceptibility mapping using compressed sensing. Magn Reson Med 2012; 67: 137–147.
- 65Abuhashem OA, Bilgic B, Adalsteinsson E. GPU Accelerated quantitative susceptibility mapping. In Proceedings of the 20th Annual Meeting of ISMRM, Melbourne, Australia, 2012. Abstract 3442.
- 66Ishii K, Sasaki M, Kitagaki H, Sakamoto S, Yamaji S, Maeda K. Regional difference in cerebral blood flow and oxidative metabolism in human cortex. J Nucl Med 1996; 37: 1086–1088.
- 67Sehgal V, Delproposto Z, Haacke EM, Tong KA, Wycliffe N, Kido DK, Xu Y, Neelavalli J, Haddar D, Reichenbach JR. Clinical applications of neuroimaging with susceptibility-weighted imaging. J Magn Reson Imaging 2005; 22: 439–450.
- 68Idbaih A, Boukobza M, Crassard I, Porcher R, Bousser MG, Chabriat H. MRI of clot in cerebral venous thrombosis: high diagnostic value of susceptibility-weighted images. Stroke 2006; 37: 991–995.
- 69Hammond KE, Lupo JM, Xu D, Veeraraghavan S, Lee H, Kincaid A, Vigneron DB, Manley GT, Nelson SJ, Mukherjee P. Microbleed detection in traumatic brain injury at 3T and 7T: comparing 2D and 3D Gradient-Recalled Echo (GRE) imaging with Susceptibility-Weighted Imaging (SWI). In Proceedings of the 18th Annual Meeting of ISMRM, Honolulu, Hawaii, 2009. Abstract 248.