Fast quantitative susceptibility mapping with L1-regularization and automatic parameter selection

Magnetic Resonance in Medicine

Volumn 72, Issue 5, 2014, Pages 1444-1459

  Bilgic, Berkin ^a   Fan, Audrey P ^a,b   Polimeni, Jonathan R ^a,c   Cauley, Stephen F ^a   Bianciardi, Marta ^a,c   Adalsteinsson, Elfar ^a,b,d   Wald, Lawrence L ^a,c,d   Setsompop, Kawin ^a,c  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b USA   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

^d HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; CONJUGATE GRADIENT METHOD; FAST FOURIER TRANSFORMS; MAPPING; NONLINEAR PROGRAMMING; PARAMETERIZATION;

BLOOD OXYGEN LEVEL DEPENDENTS; FAST RECONSTRUCTION; ISOTROPIC RESOLUTION; NONLINEAR CONJUGATE GRADIENT; ONLINE RECONSTRUCTION; OPTIMIZATION PROBLEMS; REGULARIZATION PARAMETERS; SUSCEPTIBILITY MAPPING;

PARAMETER ESTIMATION;

ADULT; ALGORITHM; ARTICLE; BOLD SIGNAL; DIPOLE; FEMALE; FOURIER TRANSFORMATION; HUMAN; HUMAN EXPERIMENT; IMAGE RECONSTRUCTION; NEUROIMAGING; NORMAL HUMAN; OPTICAL RESOLUTION; QUANTITATIVE STUDY; RADIOLOGICAL PARAMETERS; RADIOLOGY PHANTOM; SUSCEPTIBILITY WEIGHTED IMAGING; BRAIN MAPPING; COMPUTER SIMULATION; ECHO PLANAR IMAGING; FOURIER ANALYSIS; IMAGE PROCESSING; IMAGE QUALITY; MALE; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES; THREE DIMENSIONAL IMAGING;

ADULT; ALGORITHMS; BRAIN MAPPING; COMPUTER SIMULATION; ECHO-PLANAR IMAGING; FOURIER ANALYSIS; HEALTHY VOLUNTEERS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MALE; PHANTOMS, IMAGING;

EID: 84907954001     PISSN: 07403194     EISSN: 15222594     Source Type: Journal    
DOI: 10.1002/mrm.25029     Document Type: Article

References (40)

1. Langkammer C, Schweser F, Krebs N, et al. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study. NeuroImage 2012;62:1593-1599.
2. Zheng W, Nichol H, Liu S, Cheng Y, Haacke E. Measuring iron in the brain using quantitative susceptibility mapping and X-ray fluorescence imaging. NeuroImage 2013;78:68-74.
3. Fan AP, Bilgic B, Benner T, Rosen BR, Adalsteinsson E. Regularized quantitative susceptibility mapping for phase-based regional oxygen metabolism (PROM) at 7T. In Proceedings of the 19th Annual Meeting of ISMRM, Montreal, Canada, 2011. p. 7942.
4. Fan AP, Benner T, Bolar DS, Rosen BR, Adalsteinsson E. Phase-based regional oxygen metabolism (PROM) using MRI. Magn Reson Med 2012;67:669-78.
5. Haacke E, Tang J, Neelavalli J, Cheng Y. Susceptibility mapping as a means to visualize veins and quantify oxygen saturation. J Magn Reson Imaging 2010;32:663-676.
6. Bianciardi M, van Gelderen P, Duyn JH. Investigation of BOLD fMRI resonance frequency shifts and quantitative susceptibility changes at 7 T. Hum Brain Mapp 2014;35:2191-2205.
7. Langkammer C, Liu T, Khalil M, Enzinger C, Jehna M, Fuchs S, Fazekas F, Wang Y, Ropele S. Quantitative susceptibility mapping in multiple sclerosis. Radiology 2013;267:551-559.
8. Schweser F, Deistung A, Lehr B, Reichenbach J. Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping. Med Phys 2010;37:5165-178.
9. Marques 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.
10. De Rochefort L, Liu T, Kressler B, Liu J, Spincemaille P, Lebon V, Wu J, 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.
11. Liu T, Liu J, de Rochefort L, Spincemaille P, Khalidov I, Ledoux JR, Wang Y. Morphology enabled dipole inversion (MEDI) from a singleangle acquisition: comparison with COSMOS in human brain imaging. Magn Reson Med 2011;66:777-83.
12. Liu 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.
13. Liu 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.
14. Schweser 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.
15. Wharton S, Bowtell R. Whole-brain susceptibility mapping at high field: A comparison of multiple- And single-orientation methods. NeuroImage 2010;53:515-25.
16. Bilgic B, Pfefferbaum A, Rohlfing T, Sullivan E V, Adalsteinsson E. MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping. NeuroImage 2012;59: 2625-35.
17. Wu B, Li W, Guidon A, Liu C. Whole brain susceptibility mapping using compressed sensing. Magn Reson Med 2012;67:137-147.
18. Hansen PC. The L-curve and its use in the numerical treatment of inverse problems. In Johnston P, editor. Computational inverse problems in electrocardiology. Southampton: WIT Press; 2000. p. 119-142.
19. Morozov V. On the solution of functional equations by the method of regularization. Soviet Math Dokl 1966;7:414-417.
20. Bilgic B, Chatnuntawech I, Fan AP, Adalsteinsson E. Regularized QSM in seconds. In Proceedings of the 21st Annual Meeting of ISMRM, Salt Lake City, Utah, USA, 2013. p. 168.
21. Goldstein T, Osher S. The split Bregman method for L1-regularized problems. SIAM J Imaging Sci 2009;2:323-343.
22. Li W, Wu B, Avram A V, Liu C. Magnetic susceptibility anisotropy of human brain in vivo and its molecular underpinnings. NeuroImage 2012;59:2088-2097.
23. Chen Z, Calhoun V. Computed inverse resonance imaging for magnetic susceptibility map reconstruction. J Comput Assist Tomogr 2012;36:265-274.
24. Balla DZ, Sanchez-Panchuelo RM, Wharton S, Hagberg GE, Scheffler K, Francis ST, Bowtell RW. Functional quantitative susceptibility mapping (fQSM). In Proceedings of the 20th Annual Meeting of ISMRM, Melbourne, Australia, 2012. p. 325.
25. Balla DZ, Sanchez-Panchuelo RM, Wharton S, Hagberg GE, Scheffler K, Francis ST, Bowtell RW. Experimental investigation of the relation between gradient echo BOLD fMRI contrast and underlying susceptibility changes at 7T. In Proceedings of the 21st Annual Meeting of ISMRM, Salt Lake City, Utah, USA, 2013. p. 300.
26. Liu T, Xu W, Spincemaille P, Avestimehr AS, Wang Y. Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI. IEEE Trans Med Imaging 2012;31:816-824.
27. Duyn J, van Gelderen P, Tie-Qiang L, 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.
28. Deistung A, Dittrich E, Sedlacik J, Rauscher A, Reichenbach JR. ToFSWI: Simultaneous time of flight and fully flow compensated susceptibility weighted imaging. J Magnc Reson Imaging 2009;29:1478-1484.
29. Robinson S, Grabner G, Witoszynskyj S, Trattnig S. Combining phase images from multi-channel radiofrequency coils using 3D phase offset maps derived from a dual-echo scan. Magn Reson Med 2011;65: 1638-1648.
30. Hammond KE, Lupo JM, Xu D, Metcalf M, Kelley DAC, 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.
31. Smith S. Fast robust automated brain extraction. Hum Brain Mapp 2002;17:143-155.
32. Sun H, Wilman AH. Susceptibility mapping using regularization enabled harmonic artifact removal. In Proceedings of the 21st Annual Meeting of ISMRM, Salt Lake City, Utah, USA, 2013. p. 169.
33. Keil B, Triantafyllou C, Hamm M, Wald LL. Design optimization of a 32-channel head coil at 7 T. In Proceedings of the 18th Annual Meeting of ISMRM, Stockholm, Sweden, 2010. p. 1493.
34. Montesinos P, Abascal JJ, Chamorro J, Chavarrias C, Benito M, Vaquero JJ, Desco M.High-resolution dynamic cardiac MRI on small animals using reconstruction based on Split Bregman methodology. Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) 2011:3462-3464.
35. Schweser F, Deistung A, Sommer K, Reichenbach JR. Toward online reconstruction of quantitative susceptibility maps: Superfast dipole inversion. Magn Reson Med 2012;69:1581-1593.
36. Shmueli K, Zwart J De. Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data. Magn Reson Med 2009;62:1510- 1511.
37. Xia J, Chandrasekaran S, Gu M, Xiaoye S. Fast algorithms for hierarchically semiseparable matrices. Numerical Linear Algebra with Applications 2010;17:953-976.
38. Xia J, Chandrasekaran S, Gu M, Li X. Superfast multifrontal method for large structured linear systems of equations. SIAM Journal on Matrix Analysis and Applications 2009;31:1382-1411.
39. Sun H, Wilman A. Background field removal using spherical mean value filtering and Tikhonov regularization. Magn Reson Med 2014; 71:1151-1157.
40. Wu B, Li W, Avram AV, Gho S-M, Liu C. Fast and tissue-optimized mapping of magnetic susceptibility and T2∗ with multi-echo and multi-shot spirals. NeuroImage 2012;59:297-305.