A diffusion gradient optimization framework for spinal cord diffusion tensor imaging

Magnetic Resonance Imaging

Volumn 29, Issue 6, 2011, Pages 789-804

  Majumdar, Shantanu ^a   Zhu, David C ^b,c   Udpa, Satish S ^a   Raguin, L Guy ^a,b  

^a Michigan State University   (United States)

^b St John Hospital and Medical Center   (United States)

^c MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

Cramer Rao lower bound; Diffusion tensor imaging; MRI; Optimization; Rician noise; Spinal cord

Indexed keywords

ADULT; ARTICLE; BRAIN STEM; CERVICAL SPINAL CORD; CONTROLLED STUDY; DIFFUSION GRADIENT; DIFFUSION TENSOR IMAGING; FEMALE; HUMAN; HUMAN EXPERIMENT; IMAGE PROCESSING; MALE; MATHEMATICAL MODEL; NERVE TRACT; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSICAL PARAMETERS; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SIGNAL NOISE RATIO; SIMULATION; UNCERTAINTY; VALIDATION PROCESS; VARIANCE; WHITE MATTER;

ADULT; ALGORITHMS; ANISOTROPY; BRAIN STEM; DIFFUSION TENSOR IMAGING; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; NERVE FIBERS; SPINAL CORD;

EID: 79959196629     PISSN: 0730725X     EISSN: 18735894     Source Type: Journal    
DOI: 10.1016/j.mri.2011.02.025     Document Type: Article

References (36)

1. Basser P.J., Matiello J., Le Bihan D. MR diffusion tensor spectroscopy and imaging. Biophys J 1994, 66(1):259-267.
2. Werring D.J., Clark C.A., Barker G.J., Thompson A.J., Miller D.H. Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis. Neurology 1999, 52(8):1626-1632.
3. Ellis C.M., Simmons A., Jones D.K., Bland J., Dawson J.M., Horsfield M.A., et al. Diffusion tensor MRI assesses corticospinal tract damage in ALS. Neurology 1999, 53(5):1051-1058.
4. Mamata H., Jolesz F.A., Maier S.E. Apparent diffusion coefficient and fractional anisotropy in spinal cord: age and cervical spondylosis-related changes. J Magn Reson Imaging 2005, 22(1):38-43.
5. Facon D., Ozanne A., Fillard P., Lepeintre J.F., Tournoux-Facon C., Ducreux D. MR diffusion tensor imaging and fiber tracking in spinal cord compression. Am J Neuroradiol 2005, 26(6):1587-1594.
6. Beck J.V., Arnold K.J. Parameter estimation in engineering and science 1977, John Wiley & Sons, New York.
7. Beck J.V., Woodbury K.A. Inverse problems and parameter estimation: integration of measurements and analysis. Meas Sci Technol 1998, 9:839-847.
8. Raguin LG, Hernando D, Karampinos DC, Ciobanu L, Sutton BP, Liang Z-P, Georgiadis JG Quantitative Analysis of q-Space MRI Data 2005.
9. Majumdar S., Udpa S.S., Raguin L.G. Robust optimization of diffusion-weighted MRI protocols used for fiber reconstruction. J. Phys: Conf. Series 2008, 135:012069.
10. Anderson A.W. Measurement of fiber orientation distributions using high angular resolution diffusion imaging. Magn Reson Med 2005, 54(5):1194-1206.
11. Assaf Y., Freidlin R.Z., Rohde G.K., Basser P.J. New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter. Magn. Reson. Med 2004, 52(5):965-978.
12. Onu M., Gervai P., Cohen-Adad J., Lawrence J., Kornelsen J., Tomanek B., et al. Human cervical spinal cord funiculi: investigation with magnetic resonance diffusion tensor imaging. J Magn Reson Imaging 2010, 31:829-837.
13. Gullapalli J., Krejza J., Schwartz E.D., In vivo D.T.I. evaluation of white matter tracts in rat spinal cord. J Magn. Reson Imaging 2006, 24(1):231-234.
14. Gulani V., Iwamoto G.A., Jiang H., Shimony J.S., Webb A.G., Lauterbur P.C. A multiple echo pulse sequence for diffusion tensor imaging and its application in excised rat spinal cords. Mag. Res. Med 1997, 38(6):868-873.
15. Hasan K.M., Parker D.L., Alexander A.L. Comparison of gradient encoding schemes for diffusion-tensor MRI. J. Magn. Reson. Imag 2001, 13(5):769-780.
16. Jones D.K., Horsfield M.A., Simmons A. Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn Reson Med 1999, 42(3):515-525.
17. Alexander D.C. A general framework for experiment design in diffusion MRI and its application in measuring direct tissue-microstructure features. Mag Res Med 2008, 60(2):439-448.
18. Peng H., Arfanakis K. Diffusion tensor encoding schemes optimized for white matter fibers with selected orientations. Magn Reson Imaging 2007, 25:147-153.
19. Gao W., Zhu H., Lin W. A unified optimization approach for diffusion tensor imaging technique. NeuroImage 2009, 44:729-741.
20. Yanasak N., Allison J.D., Zhao Q., Hu T.C.C., Dhandapani K. Non-uniform gradient prescription for precise angular measurements using DTI. Med Image Comput Comput Assist Interv 2008, 5241:866-873.
21. Brihuega-Moreno O., Heese F.P., Hall L.D. Optimization of diffusion measurements using Cramer-Rao lower bound theory and its application to articular cartilage. Mag. Res. Med 2003, 50(5):1069-1076.
22. Andersson J.L.R. Maximum a posteriori estimation of diffusion tensor parameters using a Rician noise model: why, how and but. NeuroImage 2008, 42(4):1340-1356.
23. Kay S.M. Fundamentals of statistical signal processing: estimation theory 1993, Prentice Hall, Upper Saddle River, NJ.
24. Alexander DC Axon radius measurements in vivo from diffusion MRI: a feasibility study. Proc. Eleventh IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, 2007: IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis 2007 2007, 1-8. IEEE Computer Society Press, Los Alamitos, USA.
25. Trosset M.W. Taguchi and robust optimization. 1997, Technical Report, Department of Computational & Applied Mathematics, Rice University, Houston, Texas, USA.
26. Boyd G., Vandenberghe L. Convex optimization 2004, Cambridge University Press, Cambridge, UK.
27. Majumdar S, Zhu DC, Raguin G, Udpa SS Optimization of diffusion encoding gradients in axisymmetric diffusion tensor imaging using a priori structure information 2009.
28. Poonawalla A.H., Zhou X.J. Analytical error propagation in diffusion anisotropy calculations. J. Mag. Res. Imag 2004, 19:489-498.
29. Jenkinson M., Bannister P.R., Brady J.M., Smith S.M. Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage 2002, 17(2):825-841.
30. Pajevic S., Basser P.J. Parametric and non-parametric statistical analysis of DT-MRI data. JMR 2003, 161:1-14.
31. Sijbers J., Dekker A.J., de Scheunders P., Van Dyck D. Maximum-likelihood estimation of Rician distribution parameters. IEEE Trans. Med. Imag 1998, 17(3):357-361.
32. Nair G., Carew J.D., Usher S., Lu D., Hu X.P., Benatar M. Diffusion tensor imaging reveals regional differences in the cervical spinal cord in amyotrophic lateral sclerosis. Neuroimage 2010, 53(2):576-583.
33. Shanmuganathan K., Gullapalli R.P., Zhuo J., Mirvis S.E. Diffusion tensor MR imaging in cervical spine trauma. AJNR Am J Neuroradiol 2008, 29(4):655-659.
34. Scharf LL, McWhorter LT Geometry of the Cramer-Rao bound. Proc. IEEE Sixth SP Workshop on Statistical Signal and Array Processing 1992, 5-8. Victoria, BC, Canada.
35. Meek M.F., Stenekes M.W., Hoogduin H.M., Nicolai J.P. In vivo three-dimensional reconstruction of human median nerves by diffusion tensor imaging. Exp Neurol 2006, 198(2):479-482.
36. Kan J.H., Heemskerk A.M., Ding Z., Gregory A., Mencio G., Spindler K., et al. DTI-based muscle fiber tracking of the quadriceps mechanism in lateral patellar dislocation. J Magn Reson Imaging 2009, 29(3):663-670.