Advances in longitudinal MRI diagnostic tests

Expert Opinion on Medical Diagnostics

Volumn 6, Issue 4, 2012, Pages 309-321

  Hernandez Garcia, Luis ^a   Buschkuehl, Martin ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Arterial spin labeling; Diffusion imaging; Dynamic T2; Functional connectivity; Functional imaging; imaging; Longitudinal studies; Voxel based morphometry

Indexed keywords

ARTERIAL SPIN LABELING; BLOOD OXYGENATION LEVEL DEPENDENT WEIGHTED IMAGING; BRAIN; DIAGNOSTIC TEST; DIFFUSION COEFFICIENT; DIFFUSION TENSOR IMAGING; DISEASE COURSE; FRACTIONAL ANISOTROPY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HIGH ANGULAR DIFFUSION IMAGING; HUMAN; LONGITUDINAL STUDY; MENTAL DISEASE; NERVE CELL PLASTICITY; NEUROIMAGING; NEUROLOGIC DISEASE; NUCLEAR MAGNETIC RESONANCE IMAGING; PAIN; REVIEW; SPIN LABELING; STROKE; TRANSCRANIAL MAGNETIC STIMULATION; VOXEL BASED MORPHOMETRY;

EID: 84863113631     PISSN: 17530059     EISSN: 17530067     Source Type: Journal    
DOI: 10.1517/17530059.2012.686995     Document Type: Review

References (130)

1. MacKay Altman R, Petkau AJ, Vrecko D, Smith A: A longitudinal model for magnetic resonance imaging lesion count data in multiple sclerosis patients. Stat Med 2012;31:449-69
2. Kumari V, Fannon D, Peters ER, et al. Neural changes following cognitive behaviour therapy for psychosis: a longitudinal study. Brain 2011;134:2396-407
3. Buschkuehl M, Jaeggi SM, Jonides J. Neuronal effects following working memory training. Dev Cogn Neurosci 2012;2(Suppl 1):S167-79
4. Koolschijn PCMP, Schel MA, de Rooij M, et al. A three-year longitudinal functional magnetic resonance imaging study of performance monitoring and test-retest reliability from childhood to early adulthood. J Neurosci 2011;31:4204-12
5. Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci USA 1990;87:9868-72
6. Iadecola C. Neurovascular regulation in the normal brain and in Alzheimer's disease. Nat Rev Neurosci 2004;5:347-60
7. Logothetis NK, Wandell BA. Interpreting the BOLD signal. Annu Rev Physiol 2004;66:735-69
8. Pauling L, Coryell CD. The magnetic properties and structure of hemoglobin, oxyhemoglobin and carbonmonoxyhemoglobin. Proc Natl Acad Sci USA 1936;22:210-16
9. Duong TQ, Yacoub E, Adriany G, et al. High-resolution, spin-echo BOLD, and CBF fMRI at 4 and 7 T. Magn Reson Med 2002;48:589-93
10. Logothetis NK, Pauls J, Augath M, et al. Neurophysiological investigation of the basis of the fMRI signal. Nature 2001;412:150-7
11. Logothetis NK, Pfeuffer J. On the nature of the BOLD fMRI contrast mechanism. Magn Reson Imaging 2004;22:1517-31
12. van der Zwaag W, Francis S, Head K, et al. fMRI at 1.5, 3 and 7 T: characterising BOLD signal changes. Neuroimage 2009;47:1425-34
13. Vazquez AL, Noll DC. Nonlinear aspects of the BOLD response in functional MRI. Neuroimage 1998;7:108-18
14. Haller S, Wetzel SG, Radue EW, Bilecen D. Mapping continuous neuronal activation without an ON-OFF paradigm: initial results of BOLD ceiling fMRI. Eur J Neurosci 2006;24:2672-8
15. Bandettini PA, Wong EC, Hinks RS, et al. Time course EPI of human brain function during task activation. Magn Reson Med 1992;25:390-7
16. Kwong KK, Belliveau JW, Chesler DA, et al. Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci USA 1992;89:5675-9
17. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34:537-41
18. Aguirre GK, Detre JA, Alsop DC. Experimental design and the relative sensitivity of BOLD and perfusion fMRI. Neuroimage 2002;15:488-500
19. Smith AM, Lewis BK, Ruttimann UE, et al. Investigation of low frequency drift in fMRI signal. Neuroimage 1999;9:526-33
20. Wang J, Aguirre GK, Kimberg DY, et al. Arterial spin labeling perfusion fMRI with very low task frequency. Magn Reson Med 2003;49:796-802
21. Yan L, Zhuo Y, Ye Y, et al. Physiological origin of low-frequency drift in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Magn Reson Med 2009;61:819-27
22. Greicius MD, Krasnow B, Reiss AL, Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 2003;100:253-8
23. Peltier SJ, Noll DC. T(2)(. *) dependence of low frequency functional connectivity. Neuroimage 2002;16:985-92
24. Bhattacharyya PK, Lowe MJ. Cardiac-induced physiologic noise in tissue is a direct observation of cardiac-induced fluctuations. Magn Reson Imaging 2004;22:9-13
25. Frank LR, Buxton RB, Wong EC. Estimation of respiration-induced noise fluctuations from undersampled multislice fMRI data. Magn Reson Med 2001;45:635-44
26. McGonigle DJ, Howseman AM, Athwal BS, et al. Variability in fMRI: an examination of intersession differences. Neuroimage 2000;11:708-34
27. Davis TL, Kwong KK, Weisskoff RM, Rosen BR. Calibrated functional MRI: mapping the dynamics of oxidative metabolism. Proc Natl Acad Sci USA 1998;95:1834-9
28. Hoge RD, Atkinson J, Gill B, et al. Investigation of BOLD signal dependence on cerebral blood flow and oxygen consumption: the deoxyhemoglobin dilution model. Magn Reson Med 1999;42:849-63
29. Chiarelli PA, Bulte DP, Wise R, et al. A calibration method for quantitative BOLD fMRI based on hyperoxia. Neuroimage 2007;37:808-20
30. Friedman L, Stern H, Brown GG, et al. Test-retest and between-site reliability in a multicenter fMRI study. Hum Brain Mapp 2008;29:958-72
31. Aron AR, Gluck MA, Poldrack RA. Long-term test-retest reliability of functional MRI in a classification learning task. Neuroimage 2006;29:1000-6
32. Genovese CR, Noll DC, Eddy WF. Estimating test-retest reliability in functional MR imaging. I: statistical methodology. Magn Reson Med 1997;38:497-507
33. Gonzalez-Castillo J, Talavage TM. Reproducibility of fMRI activations associated with auditory sentence comprehension. Neuroimage 2011;54:2138-55
34. Rombouts SA, Barkhof F, Hoogenraad FG, et al. Test-retest analysis with functional MR of the activated area in the human visual cortex. AJNR Am J Neuroradiol 1997;18:1317-22
35. Manoach DS, Halpern EF, Kramer TS, et al. Test-retest reliability of a functional MRI working memory paradigm in normal and schizophrenic subjects. Am J Psychiatry 2001;158:955-8
36. Loubinoux I, Carel C, Alary F, et al. Within-session and between-session reproducibility of cerebral sensorimotor activation: a test-retest effect evidenced with functional magnetic resonance imaging. J Cereb Blood Flow Metab 2001;21:592-607
37. Bennett CM, Miller MB. How reliable are the results from functional magnetic resonance imaging? Ann NY Acad Sci 2010;1191:133-55
38. Balduzzi D, Riedner BA, Tononi G. A BOLD window into brain waves. Proc Natl Acad Sci USA 2008;105:15641-2
39. Li K, Guo L, Nie J, et al. Review of methods for functional brain connectivity detection using fMRI. Comput Med Imaging Graph 2009;33:131-9
40. Hyvarinen A, Oja E. Independent component analysis: algorithms and applications. Neural Netw 2000;13:411-30
41. van den Heuvel MP, Hulshoff Pol HE. Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharmacol 2010;20:519-34
42. Raichle ME, MacLeod AM, Snyder AZ, et al. A default mode of brain function. Proc Natl Acad Sci USA 2001;98:676-82
43. Goebel R, Roebroeck A, Kim D-S, Formisano E. Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping. Magn Reson Imaging 2003;21:1251-61
44. Roebroeck A, Formisano E, Goebel R. Mapping directed influence over the brain using Granger causality and fMRI. Neuroimage 2005;25:230-42
45. Friston KJ, Harrison L, Penny W. Dynamic causal modelling. Neuroimage 2003;19:1273-302
46. Penny WD, Stephan KE, Mechelli A, Friston KJ. Modelling functional integration: a comparison of structural equation and dynamic causal models. Neuroimage 2004;23(Suppl 1):S264-74
47. Penny W, Ghahramani Z, Friston K. Bilinear dynamical systems. Philos Trans R Soc Lond B Biol Sci 2005;360:983-93
48. Smith SM, Miller KL, Salimi-Khorshidi G, et al. Network modelling methods for FMRI. Neuroimage 2011;54:875-91
49. Taubert M, Lohmann G, Margulies DS, et al. Long-term effects of motor training on resting-state networks and underlying brain structure. Neuroimage 2011;57:1492-8
50. Cerullo MA, Fleck DE, Eliassen JC, et al. A longitudinal functional connectivity analysis of the amygdala in bipolar I disorder across mood states. Bipolar Disord 2012;14:175-84
51. Zuo X-N, Kelly C, Adelstein JS, et al. Reliable intrinsic connectivity networks: test-retest evaluation using ICA and dual regression approach. Neuroimage 2010;49:2163-77
52. Jahanian H, Noll DC, Hernandez-Garcia L: B0 field inhomogeneity considerations in pseudo-continuous arterial spin labeling (pCASL): effects on tagging efficiency and correction strategy. NMR Biomed 2011, 24:1202-1209.
53. Shehzad Z, Kelly AMC, Reiss PT, et al. The resting brain: unconstrained yet reliable. Cereb Cortex 2009;19:2209-29
54. Thomason ME, Dennis EL, Joshi AA, et al. Resting-state fMRI can reliably map neural networks in children. Neuroimage 2011;55:165-75
55. Hernandez-Garcia L, Lewis DP, Moffat B, Branch CA. Magnetization transfer effects on the efficiency of flow-driven adiabatic fast passage inversion of arterial blood. NMR Biomed 2007;20:733-42
56. Jahanian H, Noll DC, Hernandez-Garcia L. B0 field inhomogeneity considerations in pseudo-continuous arterial spin labeling (pCASL): effects on tagging efficiency and correction strategy. NMR Biomed 2011;24:1202-09
57. Zhang W, Silva AC, Williams DS, Koretsky AP. NMR measurement of perfusion using arterial spin labeling without saturation of macromolecular spins. Magn Reson Med 1995;33:370-6
58. Wang J, Alsop DC, Song HK, et al. Arterial transit time imaging with flow encoding arterial spin tagging (FEAST). Magn Reson Med 2003;50:599-607
59. Alsop DC, Detre JA. Reduced transit-time sensitivity in noninvasive magnetic resonance imaging of human cerebral blood flow. J Cereb Blood Flow Metab 1996;16:1236-49
60. Wang J, Alsop DC, Li L, et al. Comparison of quantitative perfusion imaging using arterial spin labeling at 1.5 and 4.0 Tesla. Magn Reson Med 2002;48:242-54
61. Lee GR, Hernandez-Garcia L, Noll DC. Functional imaging with Turbo-CASL: transit time and multislice imaging considerations. Magn Reson Med 2007;57:661-9
62. Hernandez-Garcia L, Lee GR, Vazquez AL, et al. Quantification of perfusion fMRI using a numerical model of arterial spin labeling that accounts for dynamic transit time effects. Magn Reson Med 2005;54:955-64
63. Kazan SM, Chappell MA, Payne SJ. Modeling the effects of flow dispersion in arterial spin labeling. IEEE Trans Biomed Eng 2009;56:1635-43
64. Hrabe J, Lewis DP. Two analytical solutions for a model of pulsed arterial spin labeling with randomized blood arrival times. J Magn Reson 2004;167:49-55
65. Jiang Q, Ewing JR, Ding GL, et al. Quantitative evaluation of BBB permeability after embolic stroke in rat using MRI. J Cereb Blood Flow Metab 2005;25:583-92
66. Cao Y, Shen Z, Chenevert TL, Ewing JR. Estimate of vascular permeability and cerebral blood volume using Gd-DTPA contrast enhancement and dynamic T2.-weighted MRI. J Magn Reson Imaging 2006;24:288-96
67. Ewing JR, Brown SL, Lu M, et al. Model selection in magnetic resonance imaging measurements of vascular permeability: gadomer in a 9L model of rat cerebral tumor. J Cereb Blood Flow Metab 2006;26:310-20
68. Perthen JE, Bydder M, Restom K, Liu TT. SNR and functional sensitivity of BOLD and perfusion-based fMRI using arterial spin labeling with spiral SENSE at 3 T. Magn Reson Imaging 2008;26:513-22
69. Yang Y, Gu H, Stein EA. Simultaneous MRI acquisition of blood volume, blood flow, and blood oxygenation information during brain activation. Magn Reson Med 2004;52:1407-17
70. van Osch MJP, Teeuwisse WM, van Walderveen MAA, et al. Can arterial spin labeling detect white matter perfusion signal? Magn Reson Med 2009;62:165-73
71. Miller KL, Luh WM, Liu TT, et al. Nonlinear temporal dynamics of the cerebral blood flow response. Hum Brain Mapp 2001;13:1-12
72. Hernandez-Garcia L, Buschkuehl M, Jaeggi SM, Jonides J. Longitudinal, pseudo-continuous ASL imaging of perfusion during a working memory task: How does training change the activation pattern? Presented at the 16th Annual Meeting of the Organization for Human Brain Mapping, Barcelona (Spain), 2010
73. Jaeggi SM, Buschkuehl M, Hernandez-Garcia L, Bernard J, Jonides J. Neural Correlates of N-back Training - A Pseudo-Continuous Arterial Spin Labeling (pCASL) Study. Presented at the 17th Annual Cognitive Neuroscience Society Meeting, Montreal (Canada), 2010
74. Jaeggi SM, Buschkuehl M, Jonides J, Perrig WJ. Improving fluid intelligence with training on working memory. Proc Natl Acad Sci USA 2008;105:6829-33
75. Jaeggi SM, Studer-Luethi B, Buschkuehl M, et al. The relationship between n-back performance and matrix reasoning - implications for training and transfer. Intelligence 2010;38:625-35
76. Jaeggi SM, Buschkuehl M, Jonides J, Shah P. Short- and long-term benefits of cognitive training. Proc Natl Acad Sci USA 2011;108:10081-6
77. Mumford JA, Hernandez-Garcia L, Lee GR, Nichols TE. Estimation efficiency and statistical power in arterial spin labeling fMRI. Neuroimage 2006;33:103-14
78. Mumford JA, Nichols TE. Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation. Neuroimage 2008;39:261-8
79. Liu TT, Wong EC. A signal processing model for arterial spin labeling functional MRI. Neuroimage 2005;24:207-15
80. Wang J, Aguirre GK, Kimberg DY, Detre JA. Empirical analyses of null-hypothesis perfusion FMRI data at 1.5 and 4 T. Neuroimage 2003;19:1449-62
81. Petersen ET, Mouridsen K, Golay X. The QUASAR reproducibility study, part II: results from a multi-center Arterial Spin Labeling test-retest study. Neuroimage 2010;49:104-13
82. Xu G, Rowley HA, Wu G, et al. Reliability and precision of pseudo-continuous arterial spin labeling perfusion MRI on 3.0 T and comparison with 15O-water PET in elderly subjects at risk for Alzheimer's disease. NMR Biomed 2010;23:286-93
83. Raoult H, Petr J, Bannier E, et al. Arterial spin labeling for motor activation mapping at 3T with a 32-channel coil: reproducibility and spatial accuracy in comparison with BOLD fMRI. Neuroimage 2011;58:157-67
84. Wang Y, Saykin AJ, Pfeuffer J, et al. Regional reproducibility of pulsed arterial spin labeling perfusion imaging at 3T. Neuroimage 2011;54:1188-95
85. Chen Y, Wang DJJ, Detre JA. Test-retest reliability of arterial spin labeling with common labeling strategies. J Magn Reson Imaging 2011;33:940-9
86. Asllani I, Borogovac A, Wright C, et al. An investigation of statistical power for continuous arterial spin labeling imaging at 1.5 T. Neuroimage 2008;39:1246-56
87. Hoge RD, Atkinson J, Gill B, et al. Linear coupling between cerebral blood flow and oxygen consumption in activated human cortex. Proc Natl Acad Sci USA 1999;96:9403-8
88. Haacke EM, Brown RW, Thompson MR, Venkatesan R. Magnetic Resonance Imaging: Physical Principles and Sequence Design (1st ed.). Wiley-Liss, New York, NY, USA; 1999
89. Olafsson VT, Noll DC, Fessler JA. Fast joint reconstruction of dynamic R2 and field maps in functional MRI. IEEE Trans Med Imaging 2008;27:1177-88
90. Krafnick AJ, Flowers DL, Napoliello EM, Eden GF. Gray matter volume changes following reading intervention in dyslexic children. Neuroimage 2011;57:733-41
91. Steinmetz H, Rademacher J, Huang YX, et al. Cerebral asymmetry: MR planimetry of the human planum temporale. J Comput Assist Tomogr 1989;13:996-1005
92. Frackowiak RSJ, Ashburner JT, Penny WD, Zeki S. Human Brain Function, Second Edition (2nd ed.). Academic Press, San Diego, CA, USA; 2004
93. Frackowiak RSJ, Friston KJ, Frith CD, Dolan RJ, Mazziotta JC. Human Brain Function (1st ed.). Academic Press, San Diego, CA, USA; 1997
94. Toga AW. Brain Warping (1st ed.). Academic Press, San Diego, CA, USA; 1998
95. Ashburner J, Friston KJ. Voxel-based morphometry - the methods. Neuroimage 2000;11:805-21
96. Good CD, Johnsrude IS, Ashburner J, et al. A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage 2001;14:21-36
97. Chung MK, Worsley KJ, Paus T, et al. A unified statistical approach to deformation-based morphometry. Neuroimage 2001;14:595-606
98. Chung MK, Worsley KJ, Robbins S, et al. Deformation-based surface morphometry applied to gray matter deformation. Neuroimage 2003;18:198-213
99. Thompson PM, Giedd JN, Woods RP, et al. Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature 2000;404:190-3
100. Kulynych JJ, Vladar K, Jones DW, Weinberger DR. Three-dimensional surface rendering in MRI morphometry: a study of the planum temporale. J Comput Assist Tomogr 1993;17:529-35
101. Xu L, Groth KM, Pearlson G, et al. Source-based morphometry: the use of independent component analysis to identify gray matter differences with application to schizophrenia. Hum Brain Mapp 2009;30:711-24
102. Bookstein FL. "Voxel-based morphometry" should not be used with imperfectly registered images. Neuroimage 2001;14:1454-62
103. Jones DK, Symms MR, Cercignani M, Howard RJ. The effect of filter size on VBM analyses of DT-MRI data. Neuroimage 2005;26:546-54
104. Nichols TE, Holmes AP. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 2002;15:1-25
105. Rorden C, Bonilha L, Nichols TE. Rank-order versus mean based statistics for neuroimaging. Neuroimage 2007;35:1531-7
106. Li X, Messe A, Marrelec G, et al. An enhanced voxel-based morphometry method to investigate structural changes: application to Alzheimer's disease. Neuroradiology 2010;52:203-13
107. Le Bihan D, Breton E, Lallemand D, et al. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986;161:401-7
108. Kucharczyk J, Mintorovitch J, Asgari HS, Moseley M. Diffusion/perfusion MR imaging of acute cerebral ischemia. Magn Reson Med 1991;19:311-15
109. Warach S, Chien D, Li W, et al. Fast magnetic resonance diffusion-weighted imaging of acute human stroke. Neurology 1992;42:1717-23
110. Basser PJ, Mattiello J, LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys J 1994;66:259-67
111. Basser PJ, Mattiello J, LeBihan D. Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 1994;103:247-54
112. Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 1996;111:209-19
113. Basser PJ, Jones DK. Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR Biomed 2002;15:456-67
114. Mattiello J, Basser PJ, Le Bihan D. The b matrix in diffusion tensor echo-planar imaging. Magn Reson Med 1997;37:292-300
115. Pierpaoli C, Jezzard P, Basser PJ, et al. Diffusion tensor MR imaging of the human brain. Radiology 1996;201:637-48
116. van den Heuvel MP, Sporns O. Rich-club organization of the human connectome. J Neurosci 2011;31:15775-86
117. Davenport ND, Lim KO, Armstrong MT, Sponheim SR. Diffuse and spatially variable white matter disruptions are associated with blast-related mild traumatic brain injury. Neuroimage 2012;59:2017-24
118. Yu C, Zhu C, Zhang Y, et al. A longitudinal diffusion tensor imaging study on Wallerian degeneration of corticospinal tract after motor pathway stroke. Neuroimage 2009;47:451-8
119. Goto T, Saitoh Y, Hashimoto N, et al. Diffusion tensor fiber tracking in patients with central post-stroke pain; correlation with efficacy of repetitive transcranial magnetic stimulation. Pain 2008;140:509-18
120. Tournier J-D, Calamante F, King MD, et al. Limitations and requirements of diffusion tensor fiber tracking: an assessment using simulations. Magn Reson Med 2002;47:701-8
121. Dyrby TB, Søgaard LV, Parker GJ, et al. Validation of in vitro probabilistic tractography. Neuroimage 2007;37:1267-77
122. Dauguet J, Peled S, Berezovskii V, et al. Comparison of fiber tracts derived from in-vivo DTI tractography with 3D histological neural tract tracer reconstruction on a macaque brain. Neuroimage 2007;37:530-8
123. Ordidge RJ, Helpern JA, Qing ZX, et al. Correction of motional artifacts in diffusion-weighted MR images using navigator echoes. Magn Reson Imaging 1994;12:455-60
124. Turner R, Le Bihan D, Chesnick AS. Echo-planar imaging of diffusion and perfusion. Magn Reson Med 1991;19:247-53
125. Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med 1999;42:952-62
126. Griswold MA, Jakob PM, Heidemann RM, et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med 2002;47:1202-10
127. Blaimer M, Breuer F, Mueller M, et al. SMASH, SENSE, PILS, GRAPPA: how to choose the optimal method. Top Magn Reson Imaging 2004;15:223-36
128. Tuch DS. Q-ball imaging. Magn Reson Med 2004;52:1358-72
129. Berman JI, Chung S, Mukherjee P, et al. Probabilistic streamline q-ball tractography using the residual bootstrap. Neuroimage 2008;39:215-22
130. Song AW, Harshbarger T, Li T, et al. Functional activation using apparent diffusion coefficient-dependent contrast allows better spatial localization to the neuronal activity: evidence using diffusion tensor imaging and fiber tracking. Neuroimage 2003;20:955-61