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Principles of BOLD Functional MRI

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Functional Neuroradiology

Abstract

Functional magnetic resonance imaging (fMRI) is one of the most important tools for visualizing neural activity in the human brain. The blood oxygenation level-dependent (BOLD) contrast has been most widely used for its easy implementation and high sensitivity. However, the BOLD signal is dependent on various anatomical, physiological, and imaging parameters, thus its interpretation with respect to physiological parameters is not straightforward. To understand the physiological source of the BOLD signal, measurements of cerebral blood flow (CBF) and cerebral blood volume (CBV) changes are helpful. In this chapter, we discussed (1) various fMRI techniques, (2) the sources of the BOLD fMRI signals, (3) improvement of BOLD techniques, (4) contrast-to-noise consideration, and (5) spatial and temporal resolution. CBF can be measured using arterial spin labeling MR methods, and CBV change can be detected using a vascular space occupancy-dependent technique. Conventional gradient-echo BOLD fMRI is sensitive to intravascular and extravascular signals of small and large venous vessels, while spin-echo BOLD fMRI is sensitive to intravascular signals of all-sized venous vessels and extravascular signals of small vessels. At high magnetic fields, intravascular signals can be reduced by shortening blood T2 relative to tissue T2. Thus, SE BOLD fMRI at high fields improves spatial specificity. Intrinsic spatial and temporal resolution of hemodynamic-based fMRI techniques is dependent on vascular structures and responses. Using fMRI, submillimeter functional structures can be mapped, and an order of second temporal resolution can be achieved. Overall, fMRI opened a window of basic and clinical neuroscience research.

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References

  1. Roy CS, Sherrington CS. On the regulation of blood supply of the brain. J Physiol. 1890;1:85–108.

    Google Scholar 

  2. Raichle ME. Circulatory and metabolic correlates of brain function in normal humans. In: Handbook of physiology—the nervous system. Bethesda: American Physiological Society; 1987. p. 643–74.

    Google Scholar 

  3. Fox PT, Raichle ME. Focal physiological uncoupling of cerebral blood flow and oxidative metabolism during somatosensory stimulation in human subjects. Proc Natl Acad Sci U S A. 1986;83:1140–4.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Fox PT, Raichle ME, Mintun MA, Dence C. Nonoxidative glucose consumption during focal physiologic neural activity. Science. 1988;241:462–4.

    CAS  PubMed  Google Scholar 

  5. Ogawa S, Lee T-M, Kay AR, Tank DW. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A. 1990;87:9868–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Ogawa S, Lee T-M, Nayak AS, Glynn P. Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn Reson Med. 1990;14:68–78.

    CAS  PubMed  Google Scholar 

  7. Ogawa S, Lee TM. Magnetic resonance imaging of blood vessels at high fields: in vivo and in vitro measurements and image simulation. Magn Reson Med. 1990;16(1):9–18.

    CAS  PubMed  Google Scholar 

  8. Thulborn KR, Waterton JC, Mattews PM, Radda GK. Oxygenation dependence of the transverse relaxation time of water protons in whole blood at high field. Biochem Biophys Acta. 1982;714:265–70.

    CAS  PubMed  Google Scholar 

  9. Pauling L, Coryell CD. The magnetic properties and structure of hemoglobin, oxyhemoglobin and carbonmonoxyhemoglobin. Proc Natl Acad Sci U S A. 1936;22:210–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Ogawa S, Tank DW, Menon R, Ellermann JM, Kim SG, Merkle H, et al. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A. 1992;89(13):5951–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP, et al. Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci U S A. 1992;89(12):5675–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Bandettini PA, Wang EC, Hinks RS, Rikofsky RS, Hyde JS. Time course EPI of human brain function during task activation. Magn Reson Med. 1992;25:390–7.

    CAS  PubMed  Google Scholar 

  13. Ogawa S, Menon RS, Kim S-G, Ugurbil K. On the characteristics of functional magnetic resonance imaging of the brain. Annu Rev Biophys Biomol Struct. 1998;27:447–74.

    CAS  PubMed  Google Scholar 

  14. Detre JA, Leigh JS, Williams DS, Koretsky AP. Perfusion imaging. Magn Reson Med. 1992;23:37–45.

    CAS  PubMed  Google Scholar 

  15. Mandeville JB, Marota JJ, Kosofsky BE, Keltner JR, Weissleder R, Rosen BR, et al. Dynamic functional imaging of relative cerebral blood volume during rat forepaw stimulation. Magn Reson Med. 1998;39(4):615–24.

    CAS  PubMed  Google Scholar 

  16. Kim SG, Harel N, Jin T, Kim T, Lee P, Zhao F. Cerebral blood volume MRI with intravascular superparamagnetic iron oxide nanoparticles. NMR Biomed. 2013;26(8):949–62.

    CAS  PubMed  Google Scholar 

  17. Lu H, Golay X, Pekar J, Van Zijl P. Functional magnetic resonance imaging based on changes in vascular space occupancy. Mag Reson Med. 2003;50:263–74.

    Google Scholar 

  18. Grubb RL, Raichle ME, Eichling JO, Ter-Pogossian MM. The effects of changes in PaCO2 on cerebral blood volume, blood flow, and vascular mean transit time. Stroke. 1974;5:630–9.

    PubMed  Google Scholar 

  19. Buxton RB, Wong EC, Frank LR. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn Reson Med. 1998;39:855–64.

    CAS  PubMed  Google Scholar 

  20. Lee S-P, Duong T, Yang G, Iadecola C, Kim S-G. Relative changes of cerebral arterial and venous blood volumes during increased cerebral blood flow: Implications for BOLD fMRI. Magn Reson Med. 2001;45:791–800.

    CAS  PubMed  Google Scholar 

  21. Kim T, Masamoto K, Hendrich K, Kim S-G. Arterial versus total blood volume changes during neural activity-induced cerebral blood flow change: implication for BOLD fMRI. J Cereb Blood Flow Metab. 2007;27:1235–47.

    PubMed  Google Scholar 

  22. Hillman EM, Devor A, Bouchard MB, Dunn AK, Krauss GW, Skoch J, et al. Depth-resolved optical imaging and microscopy of vascular compartment dynamics during somatosensory stimulation. Neuroimage. 2007;35(1):89–104.

    PubMed  Google Scholar 

  23. Drew PJ, Shih AY, Kleinfeld D. Fluctuating and sensory-induced vasodynamics in rodent cortex extend arteriole capacity. Proc Natl Acad Sci U S A. 2011;108(20):8473–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Kim T, Kim S. Temporal dynamics and spatial specificity of arterial and venous blood volume changes during visual stimulation: implication for BOLD quantification. J Cereb Blood Flow Metab. 2011;31(5):1211–22.

    PubMed  Google Scholar 

  25. Ogawa S, Menon RS, Tank DW, Kim SG, Merkle H, Ellermann JM, et al. Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. Biophys J. 1993;64(3):803–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Turner R. How much cortex can a vein drain? Downstream dilution of activation-related cerebral blood oxygenation changes. Neuroimage. 2002;16:1062–7.

    PubMed  Google Scholar 

  27. Edelman RR, Siewert B, Darby DG, Thangaraj V, Nobre AC, Mesulam MM, et al. Qualitative mapping of cerebral blood flow and functional localization with echo-planar MR imaging and signal targeting with alternating radio frequency. Radiology. 1994;192:513–20.

    CAS  PubMed  Google Scholar 

  28. Kim S-G. Quantification of relative cerebral blood flow change by flow-sensitive alternating inversion recovery (FAIR) technique: application to functional mapping. Magn Reson Med. 1995;34:293–301.

    CAS  PubMed  Google Scholar 

  29. Kwong KK, Chesler DA, Weisskoff RM, Donahue KM, Davis TL, Ostergaard L, et al. MR perfusion studies with T1-weighted echo planar imaging. Magn Reson Med. 1995;34:878–87.

    CAS  PubMed  Google Scholar 

  30. Wong E, Buxton R, Frank L. Quantitative imaging of perfusion using a single subtraction (QUIPSS and QUIPSS II). Magn Reson Med. 1998;39:702–8.

    CAS  PubMed  Google Scholar 

  31. Alsop D, Detre J. Reduced transit-time sensitivity in noninvasive magnetic resonance imaging of human cerebral blood flow. J Cereb Blood Flow Metab. 1996;16:1236–49.

    CAS  PubMed  Google Scholar 

  32. Dai WGD, de Bazelaire C, Alsop DC. Continuous flow driven inversion for arterial spin labeling using pulsed radiofrequency and gradient fields. Magn Reson Med. 2008;60:1488–97.

    PubMed  PubMed Central  Google Scholar 

  33. Ye F, Berman K, Ellmore T, Esposito G, van Horn J, Yang Y, et al. H215O PET validation of steady-state arterial spin tagging cerebral blood flow measurements in humans. Magn Reson Med. 2000;44:450–6.

    CAS  PubMed  Google Scholar 

  34. Alsop DC, Detre JA, Golay X, Gunther M, Hendrikse J, Hernandez-Garcia L, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 2015;73(1):102–16.

    PubMed  Google Scholar 

  35. Jezzard P, Chappell MA, Okell TW. Arterial spin labeling for the measurement of cerebral perfusion and angiography. J Cereb Blood Flow Metab. 2018;38(4):603–26.

    PubMed  Google Scholar 

  36. Zaini MR, Strother SC, Andersen JR, Liow J-S, Kjems U, Tegeler C, et al. Comparison of matched BOLD and FAIR 4.0T-fMRI with [15O]water PET brain volumes. Med Phys. 1999;26:1559–67.

    CAS  PubMed  Google Scholar 

  37. Feng CM, Narayana S, Lancaster JL, Jerabek PA, Arnow TL, Zhu F, et al. CBF changes during brain activation: fMRI vs. PET. Neuroimage. 2004;22(1):443–6.

    PubMed  Google Scholar 

  38. Duong TQ, Kim D-S, Ugurbil K, Kim S-G. Localized cerebral blood flow response at submillimeter columnar resolution. Proc Natl Acad Sci U S A. 2001;98:10904–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Wang J, Aguirre GK, Kimberg DY, Roc AC, Li L, Detre JA. Arterial spin labeling perfusion fMRI with very low task frequency. Magn Reson Med. 2003;49(5):796–802.

    PubMed  Google Scholar 

  40. Aguirre GK, Detre JA, Zarahn E, Alsop DC. Experimental design and the relative sensitivity of BOLD and perfusion fMRI. Neuroimage. 2002;15(3):488–500.

    CAS  PubMed  Google Scholar 

  41. Belliveau JW, Kennedy DN, McKinstry RC, Buchbinder BR, Weisskoff RM, Cohen MS, et al. Functional mapping of the human visual cortex by magnetic resonance imaging. Science. 1991;254:716–9.

    CAS  PubMed  Google Scholar 

  42. Kim S-G, Ugurbil K. High-resolution functional magnetic resonance imaging of the animal brain. Methods. 2003;30:28–41.

    CAS  PubMed  Google Scholar 

  43. Jin T, Kim SG. Improved cortical-layer specificity of vascular space occupancy fMRI with slab inversion relative to spin-echo BOLD at 9.4 T. Neuroimage. 2008;40:59–67.

    PubMed  Google Scholar 

  44. Hua J, Qin Q, Donahue MJ, Zhou J, Pekar JJ, van Zijl PC. Inflow-based vascular-space-occupancy (iVASO) MRI. Magn Reson Med. 2011;66(1):40–56.

    PubMed  PubMed Central  Google Scholar 

  45. Huber L, Ivanov D, Krieger SN, Streicher MN, Mildner T, Poser BA, et al. Slab-selective, BOLD-corrected VASO at 7 Tesla provides measures of cerebral blood volume reactivity with high signal-to-noise ratio. Magn Reson Med. 2014;72(1):137–48.

    PubMed  Google Scholar 

  46. Hua J, Liu P, Kim T, Donahue M, Rane S, Chen JJ, et al. MRI techniques to measure arterial and venous cerebral blood volume. Neuroimage. 2019;187:17–31.

    PubMed  Google Scholar 

  47. Huber L, Ivanov D, Handwerker DA, Marrett S, Guidi M, Uludag K, et al. Techniques for blood volume fMRI with VASO: from low-resolution mapping towards sub-millimeter layer-dependent applications. Neuroimage. 2018;164:131–43.

    PubMed  Google Scholar 

  48. Lu H, Patel S, Luo F, Li SJ, Hillard CJ, Ward BD, et al. Spatial correlations of laminar BOLD and CBV responses to rat whisker stimulation with neuronal activity localized by Fos expression. Magn Reson Med. 2004;52(5):1060–8.

    PubMed  Google Scholar 

  49. Zhao F, Wang P, Hendrich K, Ugurbil K, Kim S-G. Cortical layer-dependent BOLD and CBV responses measured by spin-echo and gradient-echo fMRI: insights into hemodynamic regulation. Neuroimage. 2006;30:1149–60.

    PubMed  Google Scholar 

  50. Poplawsky AJ, Fukuda M, Murphy M, Kim SG. Layer-specific fMRI responses to excitatory and inhibitory neuronal activities in the olfactory bulb. J Neurosci. 2015;35(46):15263–75.

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Zhao F, Wang P, Hendrich K, Kim S-G. Spatial specificity of cerebral blood volume-weighted fMRI responses at columnar resolution. Neuroimage. 2005;27:416–24.

    CAS  PubMed  Google Scholar 

  52. Fukuda M, Moon C-H, Wang P, Kim S-G. Mapping iso-orientation columns by contrast agent-enhanced functional MRI: reproducibility, specificity and evaluation by optical imaging of intrinsic signal. J Neurosci. 2006;26:11821–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Huber L, Handwerker DA, Jangraw DC, Chen G, Hall A, Stuber C, et al. High-resolution CBV-fMRI allows mapping of laminar activity and connectivity of cortical input and output in human M1. Neuron. 2017;96(6):1253–63.e7.

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Wright GA, Hu BS, Macovski A. Estimating oxygen saturation of blood in vivo with MR imaging at 1.5 T. J Magn Reson Imag. 1991;1:275–83.

    CAS  Google Scholar 

  55. Zhao J, Clingman C, Närväinen M, Kauppinen R, van Zijl P. Oxygenation and hemotocrit dependence of transverse relaxation rates of blood at 3T. Magn Reson Med. 2007;58:592–7.

    PubMed  Google Scholar 

  56. Ogawa S, Lee TM, Barrere B. Sensitivity of magnetic resonance image signals of a rat brain to changes in the cerebral venous blood oxygenation. Magn Reson Med. 1993;29:205–10.

    CAS  PubMed  Google Scholar 

  57. Lee S-P, Silva AC, Ugurbil K, Kim S-G. Diffusion-weighted spin-echo fMRI at 9.4 T: microvascular/tissue contribution to BOLD signal changes. Magn Reson Med. 1999;42:919–28.

    CAS  PubMed  Google Scholar 

  58. Breger RK, Rimm AA, Fischer ME, Papke RA, Haughten VM. T1 and T2 measurements on a 1.5 Tesla commercial imager. Radiology. 1989;171:273–6.

    CAS  PubMed  Google Scholar 

  59. Gelman N, Gorell J, Barker P, Savage R, Spickler E, Windham J, et al. MR imaging of human brain at 3.0 T: preliminary report on transverse relaxation rates and relation to estimated iron content. Radiology. 1999;210:759–67.

    CAS  PubMed  Google Scholar 

  60. Yacoub E, Shmuel A, Pfeuffer J, Van De Moortele P, Adriany G, Andersen P, et al. Imaging brain function in humans at 7 Tesla. Magn Reson Med. 2001;45:588–94.

    CAS  PubMed  Google Scholar 

  61. Haacke EM, Lai S, Reichenbach JR, Kuppusamy K, Hoogenraad FG, Takeichi H, et al. In vivo measurement of blood oxygen saturation using magnetic resonance imaging: a direct validation of the blood oxygen level-dependent concept in functional brain mapping. Hum Brain Mapp. 1997;5:341–7.

    CAS  PubMed  Google Scholar 

  62. Boxerman JL, Bandettini PA, Kwong KK, Baker JR, Davis TL, Rosen BR, et al. The intravascular contribution to fMRI signal change: Monte Carlo modeling and diffusion-weighted studies in vivo. Magn Reson Med. 1995;34:4–10.

    CAS  PubMed  Google Scholar 

  63. Han S, Son JP, Cho H, Park JY, Kim SG. Gradient-echo and spin-echo blood oxygenation level-dependent functional MRI at ultrahigh fields of 9.4 and 15.2 Tesla. Magn Reson Med. 2019;81(2):1237–46.

    PubMed  Google Scholar 

  64. Bandettini PA, Wong EC. Effects of biophysical and physiologic parameters on brain activation-induced R2* and R2 changes: simulations using deterministic diffusion model. Int J Imaging Syst Technol. 1995;6:133–52.

    Google Scholar 

  65. Uludag K, Blinder P. Linking brain vascular physiology to hemodynamic response in ultra-high field MRI. Neuroimage. 2018;168:279–95.

    PubMed  Google Scholar 

  66. Uludag K, Muller-Bierl B, Ugurbil K. An integrative model for neuronal activity-induced signal changes for gradient and spin echo functional imaging. Neuroimage. 2009;48(1):150–65.

    PubMed  Google Scholar 

  67. Song AW, Wong EC, Tan SG, Hyde JS. Diffusion weighted fMRI at 1.5 T. Magn Reson Med. 1996;35(2):155–8.

    CAS  PubMed  Google Scholar 

  68. Zhong J, Kennan RP, Fulbright RK, Gore JC. Quantification of intravascular and extravascular contributions to BOLD effects induced by alteration in oxygenation or intravascular contrast agents. Magn Reson Med. 1998;40(4):526–36.

    CAS  PubMed  Google Scholar 

  69. Duong TQ, Yacoub E, Adriany G, Hu X, Ugurbil K, Kim S-G. Microvascular BOLD contribution at 4 and 7T in the human brain: Gradient-echo and spin-echo fMRI with suppression of blood effects. Magn Reson Med. 2003;49(6):1019–27.

    PubMed  Google Scholar 

  70. Zhao F, Wang P, Kim SG. Cortical depth-dependent gradient-echo and spin-echo BOLD fMRI at 9.4T. Magn Reson Med. 2004;51(3):518–24.

    PubMed  Google Scholar 

  71. Yacoub E, Harel N, Ugurbil K. High-field fMRI unveils orientation columns in humans. Proc Natl Acad Sci U S A. 2008;105:10607–12.

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Moon CH, Fukuda M, Park SH, Kim SG. Neural interpretation of blood oxygenation level-dependent fMRI maps at submillimeter columnar resolution. J Neurosci. 2007;27(26):6892–902.

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Duvernoy HM, Delon S, Vannson JL. Cortical blood vessels of the human brain. Brain Res Bull. 1981;7(5):519–79.

    CAS  PubMed  Google Scholar 

  74. Kruger G, Glover GH. Physiological noise in oxygenation-sensitive magnetic resonance imaging. Magn Reson Med. 2001;46(4):631–7.

    CAS  PubMed  Google Scholar 

  75. Hu X, Le TH, Parrish T, Erhard P. Retrospective estimation and compensation of physiological fluctuation in functional MRI. Magn Reson Med. 1995;34:210–21.

    Google Scholar 

  76. Glover GH, Li TQ, Ress D. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med. 2000;44(1):162–7.

    CAS  PubMed  Google Scholar 

  77. Triantafyllou C, Hoge RD, Krueger G, Wiggins CJ, Potthast A, Wiggins GC, et al. Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. Neuroimage. 2005;26(1):243–50.

    CAS  PubMed  Google Scholar 

  78. Murphy K, Bodurka J, Bandettini PA. How long to scan? The relationship between fMRI temporal signal to noise ratio and necessary scan duration. Neuroimage. 2007;34(2):565–74.

    PubMed  Google Scholar 

  79. Bandettini PA. The temporal resolution of Functional MRI. In: Moonen CTW, Bandettini PA, editors. Functional MRI. New York: Springer; 1999. p. 205–20.

    Google Scholar 

  80. Kim S-G, Tsekos NV, Ashe J. Multi-slice perfusion-based functional MRI using the FAIR technique: comparison of CBF and BOLD effects. NMR n Biomed. 1997;10:191–6.

    CAS  Google Scholar 

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Kim, SG., Bandettini, P.A. (2023). Principles of BOLD Functional MRI. In: Faro, S.H., Mohamed, F.B. (eds) Functional Neuroradiology. Springer, Cham. https://doi.org/10.1007/978-3-031-10909-6_19

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