ISSN 2415-3060 (print), ISSN 2522-4972 (online)
  • 47 of 61
Up
УЖМБС 2018, 3(5): 247–253
https://doi.org/10.26693/jmbs03.05.247
Medicine. Reviews

Structural and Functional Neuroimaging in the Investigation of the Brain Neuroplasticity in Post-Stroke Patients (Literature Review)

Potii D. A., Tatarko S. V., Snegir A. H., ProkopenkoG. A., Nikolaenko S. S.
Abstract

Despite the deep theoretical study of the problem of stroke, morbidity, mortality and disability in this pathology remain high, which requires a search for new approaches to the tactics of patients. In this situation, the efforts of doctors are aimed at minimizing the size of the focus of ischemia due to the effect on the ischemia zone. The lifespan of neurons in the ischemia zone in humans is extremely variable, depending on various factors, including the occlusion of the vessel, the adequacy of collateral blood flow, and the sensitivity of tissues to ischemia. Nevertheless, it is known that in the post-stroke period, the brain undergoes a series of different stages of recovery, during which the central nervous system is able to reorganize neural networks and, as determined as neuroplasticity of the brain. Direct visualization of the presence and prevalence of the ischemic zone can contribute to the development of optimal treatment tactics, which will be based on the true state of the lesion locus in each particular patient. Methods of neuroimaging help assess the overall structural and functional disorders associated with stroke and, more importantly, help predict the restoration of body functions. Thus, diffusion tensor imaging (DTI), allows determining the extent of damage to white matter, by identifying areas of the brain with increased total diffusion. The diffusion of free water in tissues due to Brownian motion of molecules is estimated by the DTI method. Magneto-resonance spectroscopy (MRS) is a marker of metabolic changes in undamaged neural tissue and serves as an indicator of brain function. With the help of MRS, it is possible to quantify the level of metabolites in different parts of the brain. Changes in brain neuronal activity in the post-stroke period are manifested by abnormal activity of the sensorimotor cortex and can be determined using functional magnetic resonance imaging (fMRI). The mechanism of fMRI is based on the fact that when the oxygen level in the blood fluctuates, the magnetic resonances signal changes, which can be estimated with the help of special equipment. Increased activity of groups of neurons leads to a significant increase in their metabolism. As a result, there is a sharp increase in oxygen consumption by blood. The article presents an overview of the data based on the use of structural and functional methods of neuroimaging, with the aim of assessing recovery in the post-stroke period.

Keywords: neuroimaging, stroke, neuroplasticity, diffusion-weighted magnetic resonance imaging, magnetic resonance spectroscopy, functional magnetic resonance imaging

Full text: PDF (Rus) 215K

References
  1. The GUSTO Investigators. An international randomized trial comparing four thrombolytic strategies for acute myocardial infarction. N Engl J Med. 1993; 329: 673–82. https://www.ncbi.nlm.nih.gov/pubmed/8204123. https://doi.org/10.1056/NEJM199309023291001
  2. Boyd LA, Winstein CJ. Impact of explicit information on implicit motor-sequence learning following middle cerebral artery stroke. Phys Ther. 2003; 83 (11): 976–89. https://www.ncbi.nlm.nih.gov/pubmed/14577825
  3. Taub E, Miller NE, Novack TA, Cook EW, Fleming WC, Nepomuceno CS, Connell JS, Crago JE. Technique to improve chronic motor deficit after stroke. Arch Phys Med Rehabil. 1993; 74: 347–54. https://www.ncbi.nlm.nih.gov/pubmed/8466415
  4. Boyd LA, Winstein CJ. Providing explicit information disrupts implicit motor learning after basal ganglia stroke. Learn Mem. 2004; 11: 388–96. https://www.ncbi.nlm.nih.gov/pubmed/15286181. https://www.ncbi.nlm.nih.gov/pmc/articles/498316. https://doi.org/10.1101/lm.80104
  5. Boyd LA, Winstein CJ. Cerebellar stroke impairs temporal but not spatial accuracy during implicit motor learning. Neurorehabil Neural Repair. 2004; 18: 134–43. https://www.ncbi.nlm.nih.gov/pubmed/15375273. https://doi.org/10.1177/0888439004269072
  6. Boyd LA, Quaney BM, Pohl PS, Winstein CJ. Learning implicitly: effects of task and severity after stroke. Neurorehabil Neural Repair. 2006; 21: 444–54. https://www.ncbi.nlm.nih.gov/pubmed/17416874. https://doi.org/10.1177/1545968307300438
  7. Pohl PS, Winstein CJ. Practice effects on the less-affected upper extremity after stroke. Arch Phys Med Rehabil. 1999; 80: 668–75. https://www.ncbi.nlm.nih.gov/pubmed/10378493. https://doi.org/10.1016/ S0003-9993(99)90170-3
  8. Winstein CJ, Merians AS, Sullivan KJ. Motor learning after unilateral brain damage. Neuropsychologia. 1999; 37: 975–87. https://www.ncbi.nlm.nih.gov/pubmed/10426521. https://doi.org/10.1016/ S0028-3932(98)00145-6
  9. Boyd LA, Vidoni ED, Daly JJ. Answering the call: the influence of neuroim-aging and electrophysiological evidence on rehabilitation. Phys Ther. 2007; 87: 684–703. https://www.ncbi.nlm.nih.gov/pubmed/17429001. https://doi.org/10.2522/ptj.20060164
  10. Meehan SK, Randhawa B, Wessel B, Boyd LA. Implicit sequence-specific motor learning after subcortical stroke is associated with increased prefrontal brain activations: an {fMRI} study. Hum Brain Mapp. 2011; 32:2 90–303. https://www.ncbi.nlm.nih.gov/pubmed/20725908. https://www.ncbi.nlm.nih.gov/pmc/articles/3010500. https://doi.org/10.1002/hbm.21019
  11. Nudo RJ, Milliken GW, Jenkins WM, Merzenich MM. Use-dependent alterations of movement representations in primary motor cortex of adult squirrel monkeys. J Neurosci. 1996; 16: 785–807. https://www.ncbi.nlm.nih.gov/pubmed/8551360
  12. Nudo RJ, Wise BM, SiFuentes F, Milliken GW. Neural substrates for the effects of rehabilitative training on motor recovery after ischemic infarct. Science. 1996; 272: 1791–4. https://www.ncbi.nlm.nih.gov/pubmed/8650578. https://doi.org/10.1126/science.272.5269.1791
  13. Alexander LD, Black SE, Gao F, Szilagyi G, Danells CJ, McIlroy WE. Correlating lesion size and location to deficits after ischemic stroke: the influence of accounting for altered peri-necrotic tissue and incidental silent infarcts. Behav Brain Funct. 2010; 6: 6. https://www.ncbi.nlm.nih.gov/pubmed/20205779. https://www.ncbi.nlm.nih.gov/pmc/articles/2823642. https://doi.org/10.1186/1744-9081-6-6
  14. Sterr A, Dean PJ, Szameitat AJ, Conforto AB, Shen S. Corticospinal tract integrity and lesion volume play different roles in chronic hemiparesis and its improvement through motor practice. Neurorehabil Neural Repair. 2014; 28: 335–43. https://www.ncbi.nlm.nih.gov/pubmed/24334657. https://doi.org/10.1177/1545968313510972
  15. Carrera E, Tononi G. Diaschisis: past, present, future. Brain. 2014; 137 (Pt 9): 2408–22. https://www.ncbi.nlm.nih.gov/pubmed/24871646. https://doi.org/10.1093/brain/awu101
  16. Kraemer M, Schormann T, Hagemann G, Qi B, Witte OW, Seitz RJ. Delayed shrinkage of the brain after ischemic stroke: preliminary observations with {voxel-guided} morphom-etry. J Neuroimaging. 2004; 14 (3): 265–72. https://www.ncbi.nlm.nih.gov/pubmed/15228769. https://doi.org/10.1111/j.1552-6569.2004. tb00249.x
  17. Dade LA, Gao FQ, Kovacevic N, Roy P, Rockel C, O'Toole CM, Lobaugh NJ, Feinstein A, Levine B, Black SE. Semiautomatic brain region extraction: a method of parcellating brain regions from structural magnetic resonance images. Neuroimage. 2004; 22: 1492–502. https://www.ncbi.nlm.nih.gov/pubmed/15275906. https://doi.org/10.1016/j. neuroimage.2004.03.023
  18. Ramirez J, Scott CJ, McNeely AA, Berezuk C, Gao F, Szilagyi GM, et al. Lesion explorer: a video-guided, standardized protocol for accurate and reliable {MRI-derived} volumetrics in Alzheimer’s disease and normal elderly. J Vis Exp. 2013; 86: e50887: 1–12. https://doi.org/10.3791/50887
  19. Brodie SM, Borich MR, Boyd LA. Impact of 5-Hz rTMS over the primary sensory cortex is related to white matter volume in individuals with chronic stroke. Eur J Neurosci. 2014; 40: 3405–12. https://www.ncbi.nlm.nih.gov/pubmed/25223991. https://doi.org/10.1111/ejn.12717
  20. Naama L-C, Ramirez J, Lobaugh NJ, Black SE. Misclassified tissue volumes in Alzheimer disease patients with white matter hyperintensities: importance of lesion segmentation procedures for volumetric analysis. Stroke. 2008; 39: 1134–41. https://www.ncbi.nlm.nih.gov/pubmed/18323507. https://doi.org/10.1161/STROKEAHA.107.498196
  21. Jang SH. Prediction of motor outcome for hemiparetic stroke patients using diffusion tensor imaging?: a review. Neuro Rehabilitation. 2010; 27: 367–72. https://www.ncbi.nlm.nih.gov/pubmed/21160127. https://doi.org/10.3233/NRE-2010-0621
  22. Stinear CM, Barber PA, Smale PR, Coxon JP, Fleming MK, Byblow WD. Functional potential in chronic stroke patients depends on corticospinal tract integrity. Brain. 2007; 130: 170–80. https://www.ncbi.nlm.nih.gov/pubmed/17148468. https://doi.org/10.1093/brain/awl333
  23. Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson. 1996; 111: 209–19. https://www.ncbi.nlm.nih.gov/pubmed/22152371. https://doi.org/10.1006/jmrb.1996.0086
  24. Assaf Y, Pasternak O. Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review. J Mol Neurosci. 2008; 34: 51–61. https://www.ncbi.nlm.nih.gov/pubmed/18157658. https://doi.org/10.1007/s12031-007-0029-0
  25. Basser P. Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed. 1995); 8: 333–44. https://www.ncbi.nlm.nih.gov/pubmed/8739270. https://doi.org/10.1002/nbm.1940080707
  26. Borich MR, Wadden KP, Boyd LA. Establishing the reproducibility of two approaches to quantify white matter tract integrity in stroke. Neuroimage. 2012; 59: 2393–400. https://www.ncbi.nlm.nih.gov/pubmed/21945470. https://www.ncbi.nlm.nih.gov/pmc/articles/3249015. https://doi.org/10.1016/j.neuroimage.2011.09.009
  27. Danielian L, Iwata N, Thomasson D, Floeter M. Reliability of fiber tracking measurements in diffusion tensor imaging for longitudinal study. Neuroimage. 2011; 49: 1572–80. https://www.ncbi.nlm.nih.gov/pubmed/19744567. https://www.ncbi.nlm.nih.gov/pmc/articles/2789889. https://doi.org/10.1016/j.neuroimage.2009.08.062.Reliability
  28. Auriat AM, Borich MR, Snow NJ, Wadden KP, Boyd LA. Comparing a diffusion tensor and non-tensor approach to white matter fiber tractog-raphy in chronic stroke. Neuroimage Clin. 2015; 7: 771–81. https://www.ncbi.nlm.nih.gov/pubmed/25844329. https://www.ncbi.nlm.nih.gov/pmc/articles/4375634. https://doi.org/10.1016/j. nicl.2015.03.007
  29. Farquharson S, Tournier JD, Calamante F, Fabinya G, Schneider-Kolsky M, Jackson GD, et al. White matter fiber tractography: why we need to move beyond DTI. J Neurosurg. 2013; 118: 1367–77. https://www.ncbi.nlm.nih.gov/pubmed/23540269. https://doi.org/10.3171/2013.2.JNS121294
  30. Hallett M, Wassermann E, Cohen L, Chmielowska J, Gerloff C. Cortical mechanisms of recovery of function after stroke. Neuro Rehabilitation. 1998; 10: 131–42. https://doi.org/10.3233/NRE-1998-10205
  31. Davidoff R. The pyramidal tract. Neurology. 1990; 40: 332–9. https://www.ncbi.nlm.nih.gov/pubmed/2405296. https://doi.org/10.1212/ WNL.40.2.332
  32. Borich MR, Mang C, Boyd LA. Both projection and commissural pathways are disrupted in individuals with chronic stroke: investigating microstruc-tural white matter correlates of motor recovery. BMC Neurosci. 2012; 13: 107. https://doi.org/10.1186/1471-2202-13-107
  33. Takenobu Y, Hayashi T, Moriwaki H, Nagatsuka K, Naritomi H, Fukuyama H. Motor recovery and microstructural change in rubro-spinal tract in subcor-tical stroke. Neuroimage Clin. 2014; 4: 201–8. https://www.ncbi.nlm.nih.gov/pubmed/24432247. https://www.ncbi.nlm.nih.gov/pmc/articles/3891492. https://doi.org/10.1016/j.nicl.2013.12.003
  34. Gujar SK, Maheshwari S, Bjorkman-Burtscher I, Sundgren PC.Magnetic resonance spectroscopy. J Neuroophthalmol. 2005; 25: 217–26. https://www.ncbi.nlm.nih.gov/pubmed/16148633. https://doi.org/10.1089/ ars.2010.3453
  35. Puts N, Edden R. In vivo magnetic spectroscopy of GABA: a methodolog-ical review. Prog Nucl Magn Reson Spectrosc. 2012; 60: 1–26. https://www.ncbi.nlm.nih.gov/pubmed/22293397. https://www.ncbi.nlm.nih.gov/pmc/articles/3383792. https://doi.org/10.1016/j. pnmrs.2011.06.001.In
  36. Tallan HH, Moore S, Stein WH. N-acetyl-L-aspartic acid in brain. J Biol Chem. 1956; 219: 257–64. https://www.ncbi.nlm.nih.gov/pubmed/13295277
  37. Kobayashi M, Takayama H, Suga S, Mihara B. Longitudinal changes of metabolites in frontal lobes after hemorrhagic stroke of basal ganglia: A proton magnetic resonance spectroscopy study. Stroke. 2001; 32: 2237–45.
  38. Moffett JR, Ross B, Arun P, Madhavarao CN, Namboodiri AM. N-acetylaspartate in the CNS: From neurodiagnostics to neurobiology. Prog Neurobiol. 2007; 81: 89–131. https://www.ncbi.nlm.nih.gov/pubmed/17275978. https://www.ncbi.nlm.nih.gov/pmc/articles/1919520. https://doi.org/10.1016/j.pneurobio.2006.12.003
  39. Gideon P, Henriksen O, Sperling B, Christiansen P, Olsen TS, Jørgensen HS, Arlien-Søborg P. Early time course of N-acetylaspartate, creatine and phosphocreatine, and compounds containing choline in the brain after acute stroke. A proton magnetic resonance spectroscopy study. Stroke. 1992; 23: 1566–72. https://www.ncbi.nlm.nih.gov/pubmed/1440704
  40. Graham GD, Blamire AM, Rothman DL, et al. Early temporal variation of cerebral metabolites after human stroke. A proton magnetic resonance spectroscopy study. Stroke. 1993; 24: 1891–6.
  41. Saunders DE, Howe FA, van den Boogaart A, McLean MA, Griffiths JR, Brown MM. Continuing ischemic damage after acute middle cerebral artery infarction in humans demonstrated by short-echo proton spectroscopy. Stroke. 1995; 26: 1007–13. https://www.ncbi.nlm.nih.gov/pubmed/7762015
  42. Saunders DE. MR spectroscopy in stroke. Br Med Bull. 2000; 56: 334–5. https://www.ncbi.nlm.nih.gov/pubmed/11092084
  43. Urenjak J, Williams SR, Gadian DG, Noble M. Proton nuclear magnetic resonance spectroscopy unambiguously identifies different neural cell types. J Neurosci. 1993; 13: 981–9. https://www.ncbi.nlm.nih.gov/pubmed/8441018
  44. Miller BL. A review of chemical issues in 1H NMR spectroscopy: N-acetyl-L-aspartate, creatine and choline. NMR Biomed. 1991; 4: 47–52. https://www.ncbi.nlm.nih.gov/pubmed/1650241
  45. Hugg JW, Duijn JH, Matson GB, et al. Elevated lactate and alkalosis in chronic human brain infarction observed by 1H and 31P MR spectroscopic imaging. J Cereb Blood Flow Metab. 1992; 12: 734–44.
  46. Gillard JH, Barker PB, van Zijl PC, Bryan RN, Oppenheimer SM. Proton MR spectroscopy in acute middle cerebral artery stroke. Am J Neuroradiol. 1996; 17: 873–86. https://www.ncbi.nlm.nih.gov/pubmed/8733962
  47. Hu J, Yang S, Xuan Y, Jiang Q, Yang Y, Haacke EM. Simultaneous detection of resolved glutamate, glutamine, and gamma-aminobutyric acid at 4 T. J Magn Reson. 2007; 185: 204–13. https://www.ncbi.nlm.nih.gov/pubmed/17223596. https://www.ncbi.nlm.nih.gov/pmc/articles/1995429. https://doi.org/10.1016/j.jmr.2006.12.010
  48. Hurd R, Sailasuta N, Srinivasan R, Vigneron DB, Pelletier D, Nelson SJ. Measurement of brain glutamate using TE-averaged PRESS at 3T. Magn Reson Med. 2004; 51: 435–40. https://www.ncbi.nlm.nih.gov/pubmed/15004781. https://doi.org/10.1002/mrm.20007
  49. Norris DG. Principles of magnetic resonance assessment of brain function. J Magn Reson Imaging. 2006; 23: 794–807. https://www.ncbi.nlm.nih.gov/pubmed/16649206. https://doi.org/10.1002/jmri.20587
  50. Fox MD, Greicius M. Clinical applications of resting state functional connec-tivity. Front Syst Neurosci. 2010; 4: 19. https://www.ncbi.nlm.nih.gov/pubmed/20592951. https://www.ncbi.nlm.nih.gov/pmc/articles/2893721. https://doi.org/10.3389/fnsys.2010.00019
  51. Ward N. Assessment of cortical reorganisation for hand function after stroke. J Physiol. 2011; 589: 5625–32. https://www.ncbi.nlm.nih.gov/pubmed/22063630. https://www.ncbi.nlm.nih.gov/pmc/articles/3249038. https://doi.org/10.1113/jphysiol.2011.220939
  52. Boyd LA, Vidoni ED, Wessel BD. Motor learning after stroke: is skill acqui-sition a prerequisite for contralesional neuroplastic change? Neurosci Lett. 2010; 482: 21–5. https://www.ncbi.nlm.nih.gov/pubmed/20609381. https://doi.org/10.1016/j.neulet.2010.06.082
  53. Park C, Chang WH, Ohn SH, Kim ST, Bang OY, Pascual-Leone A, Kim YH. Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke. 2011; 42: 1357–62. https://www.ncbi.nlm.nih.gov/pubmed/21441147. https://www.ncbi.nlm.nih.gov/pmc/articles/3589816. https://doi.org/10.1161/ STROKEAHA.110.596155