Multimodal magnetic resonance imaging of the brain at different stages of rehabilitation after ischemic stroke
A. P. Kurazhov,
V. M. Alifirova,
E. S. Koroleva,
I. Yu. Degtyarev,
Yu. N. Loiko,
K. S. Kucherova,
K. S. Sukhanova,
V. D. Zavadovskaya https://doi.org/10.20538/1682-0363-2026-2-150-160
Abstract
Stroke is an important medical and social problem in the world and in the Russian Federation, which is due to high rates of morbidity, mortality, and disability. The basis for the development of innovative approaches to the accelerated rehabilitation of individuals after an ischemic stroke is the study of neuroplasticity using modern neuroimaging methods, such as multimodal magnetic resonance imaging (MRI).
The present literature review describes diagnostic capabilities of different multimodal MRI modalities, such as functional MRI (fMRI), ASL MR perfusion, and diffusion tensor MRI, including their advantages and drawbacks in assessing rehabilitation potential of patients after ischemic stroke. These MRI modalities can be successfully utilized to study the mechanisms of neuroplasticity and identify reliable markers of a response to therapy in context of rehabilitation measures in stroke patients.
It was shown that broad implementation of multimodal MRI in clinical practice is hindered by a lack of profound knowledge about its diagnostic capabilities in certain clinical settings, complexity of its use, and insufficient evidence base.
About the Authors
A. P. Kurazhov
Siberian State Medical University
Russian Federation
Russian Federation
2 Moscovsky trakt, 634050 Tomsk, Russian Federation
V. M. Alifirova
Siberian State Medical University
Russian Federation
Russian Federation
2 Moscovsky trakt, 634050 Tomsk, Russian Federation
E. S. Koroleva
Siberian State Medical University
Russian Federation
Russian Federation
2 Moscovsky trakt, 634050 Tomsk, Russian Federation
I. Yu. Degtyarev
Siberian State Medical University
Russian Federation
Russian Federation
2 Moscovsky trakt, 634050 Tomsk, Russian Federation
Yu. N. Loiko
Treatment and Diagnostic Center, Dr. Berezin Medical Institute
Russian Federation
Russian Federation
105 Michurin St., 634063 Tomsk, Russian Federation
K. S. Kucherova
Siberian State Medical University
Russian Federation
Russian Federation
2 Moscovsky trakt, 634050 Tomsk, Russian Federation
K. S. Sukhanova
Siberian State Medical University
Russian Federation
Russian Federation
2 Moscovsky trakt, 634050 Tomsk, Russian Federation
V. D. Zavadovskaya
Siberian State Medical University
Russian Federation
Russian Federation
2 Moscovsky trakt, 634050 Tomsk, Russian Federation
References
1. Osborne A.G., Zaltsman K.L., Assure M.D. Radiation diagnostics. Brain. 2018;248.
2. Campbell B.C.V., De Silva D.A., Macleod M.R. Ischaemic stroke. Nat. Rev. Dis. Primers 5. 2019;70. DOI: 10.1038/s41572-019-0118-8.
3. Zhao Y., Zhang X., Chen X., Wei Y. Neuronal injuries in cerebral infarction and ischemic stroke: From mechanisms to treatment (Review). Int. J. Mol. Med. 2022;49(2):15. DOI: 10.3892/ijmm.2021.5070.
4. Feigin V.L., Brainin M., Norrving B., Martins S., Sacco R.L., Hacke W. et al. World Stroke Organization (WSO): Global Stroke Fact Sheet 2022. Int. J. Stroke. 2022;17(1):18–29. DOI: 10.1177/17474930211065917.
5. Saini V., Guada L., Yavagal D.R. Global epidemiology of stroke and access to acute ischemic stroke interventions. Neurology. 2021;16(97):S6–S16. DOI: 10.1212/WNL.0000000000012781.
6. Zhang J., Lu C., Wu X., Nie D., Yu H. Neuroplasticity of Acupuncture for Stroke: An Evidence-Based Review of MRI. Neural. Plast. 2021;2021:2662585. DOI: 10.1155/2021/2662585.
7. Guggisberg A.G., Koch P.J., Hummel F.C., Buetefisch C.M. Brain networks and their relevance for stroke rehabilitation. Clin. Neurophysiol. 2019;130(7):1098–1124. DOI: 10.1016/j.clinph.2019.04.004.
8. Hartwigsen G., Volz L.J. Probing rapid network reorganization of motor and language functions via neuromodulation and neuroimaging. Neuroimage. 2021;224:117449. DOI: 10.1016/j.neuroimage.2020.117449.
9. Innocenti G.M. Defining neuroplasticity. Handb. Clin. Neurol. 2022;184:3–18. DOI: 10.1016/B978-0-12-819410-2.00001-1. PMID: 35034744.
10. Joy M.T., Carmichael S.T. Encouraging an excitable brain state: mechanisms of brain repair in stroke. Nat. Rev. Neurosci. 2021;22(1):38–53. DOI: 10.1038/s41583-020-00396-7.
11. Johnson B.P., Cohen L.G. Applied strategies of neuroplasticity. Handb. Clin. Neurol. 2023;196:599–609. DOI: 10.1016/B978-0-323-98817-9.00011-9.
12. Xing Y., Bai Y. A Review of Exercise-Induced Neuroplasticity in Ischemic Stroke: Pathology and Mechanisms. Mol. Neurobiol. 2020;57(10):4218–4231. DOI: 10.1007/s12035-020-02021-1.
13. Włodarczyk L., Cichon N., Saluk-Bijak J., Bijak M., Majos A., Miller E. Neuroimaging techniques as potential tools for assessment of angiogenesis and neuroplasticity processes after stroke and their clinical implications for rehabilitation and stroke recovery prognosis. J. Clin. Med. 2022;11(9):2473. DOI: 10.3390/jcm11092473.
14. Bhasin A., Srivastava P., Kumaran S.S. Correlation of DTI-derived measures to therapy-mediated recovery after stroke: preliminary findings. Neurol. India. 2021;69(5):1210–1216. DOI: 10.4103/0028-3886.329584.
15. Yang H.E., Kyeong S., Kang H., Kim D.H. Multimodal magnetic resonance imaging correlates of motor outcome after stroke using machine learning. Neurosci. Lett. 2021;741:135451. DOI: 10.1016/j.neulet.2020.135451.
16. Ball E.L., Shah M., Ross E., Sutherland R., Squires C., Mead G.E. et al. Predictors of post-stroke cognitive impairment using acute structural MRI neuroimaging: A systematic review and meta-analysis. Int. J. Stroke. 2023;18(5):543–554. DOI: 10.1177/17474930221120349.
17. Nael K., Yoo B., Salamon N., Liebeskind D.S. Acute ischemic stroke: MR imaging-based paradigms. Neuroimaging Clin. N. Am. 2021;31(2):177–192. DOI: 10.1016/j.nic.2021.01.002. PMID: 33902873.
18. Garcia-Esperon C., Raposo N., Seners P., Spratt N., Parsons M., Olivot J.M. Role of neuroimaging before reperfusion therapy. Part 1 – IV thrombolysis – Review. Rev. Neurol. (Paris). 2021;177(8):908–918. DOI: 10.1016/j.neurol.2020.10.007.
19. Zhang Y.L., Zhang J.F., Wang X.X., Wang Y., Anderson C.S., Wu Y.C. Wake-up stroke: imaging-based diagnosis and recanalization therapy. J. Neurol. 2021;268(11):4002–4012. DOI: 10.1007/s00415-020-10055-7.
20. Atchaneeyasakul K., Liebeskind D.S., Jahan R., Starkman S., Sharma L., Yoo B. et al. UCLA reperfusion therapy investigators. Efficient multimodal MRI evaluation for endovascular thrombectomy of anterior circulation large vessel occlusion. J. Stroke Cerebrovasc. Dis. 2020;29(12):105271. DOI: 10.1016/j.jstrokecerebrovasdis.2020.105271.
21. Lee H., Jung K., Kang D.W., Kim N. Fully Automated and real-time volumetric measurement of infarct core and penumbra in diffusion- and perfusion-weighted mri of patients with hyper-acute stroke. J. Digit. Imaging. 2020;33(1):262–272. DOI: 10.1007/s10278-019-00222-2.
22. Xiao Z.P., Jin K., Wan J.Q., Lin Y., Pan Y.H., Jin Y.C. et al. Measurement of cerebrovascular reserve by multimodal imaging for cerebral arterial occlusion or stenosis patients: protocol of a prospective, randomized, controlled clinical study. Trials. 2020;21(1):49. DOI: 10.1186/s13063-019-3967-2.
23. Liu J., Wang Q., Liu F., Song H., Liang X., Lin Z. et al. Altered functional connectivity in patients with post-stroke memory impairment: A resting fMRI study. Exp. Ther. Med. 2017;14(3):1919–1928. DOI: 10.3892/etm.2017.4751.
24. Wu C.W., Lin S.N., Hsu L.M., Yeh S.C., Guu F., Lee S.H., Chen C.C. Synchrony Between Default-Mode and Sensorimotor Networks Facilitates Motor Function in Stroke Rehabilitation: A Pilot fMRI Study. Front. Neurosci. 2020;14:548. DOI: 10.3389/fnins.2020.00548.
25. Du J., Yang F., Zhang Z. et al. Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study. Brain Imaging and Behavior. 2018;12:1804–1813. DOI: 10.1007/s11682-018-9851-y.
26. Belani P., Kihira S., Pacheco F., Pawha P., Cruciata G., Nael K. Addition of arterial spin-labelled MR perfusion to conventional brain MRI: clinical experience in a retrospective cohort study. BMJ Open. 2020;10(6):e036785. DOI: 10.1136/bmjopen-2020-036785.
27. Wang J., Pan L.J., Zhou B., Zu J.Y., Zhao YX, Li Y. et al. Crossed cerebellar diaschisis after stroke detected noninvasively by arterial spin-labeling MR imaging. BMC Neurosci. 2020;21(1):46. DOI: 10.1186/s12868-020-00595-z.
28. Lu S.S., Cao Y.Z., Su C.Q., Xu X.Q., Zhao L.B., Jia Z.Y. et al. Hyperperfusion on arterial spin labeling MRI predicts the 90-day functional outcome after mechanical thrombectomy in ischemic stroke. J. Magn. Reson. Imaging. 2021;53(6):1815–1822. DOI: 10.1002/jmri.27455.
29. Crisi G., Filice S., Scoditti U. Arterial spin labeling mri to measure cerebral blood flow in untreated ischemic stroke. J. Neuroimaging. 2019;29(2):193–197. DOI: 10.1111/jon.12569.
30. Verclytte S., Fisch O., Colas L., Vanaerde O., Toledano M., Budzik J.F. ASL and susceptibility-weighted imaging contribution to the management of acute ischaemic stroke. Insights Imaging. 2017;8(1):91–100. DOI: 10.1007/s13244-016-0529-y.
31. Santos L.A., Sullivan B., Kvist O., Jambawalikar S., Mostoufi-Moab S., Raya J.M. et al. Diffusion tensor imaging of the physis: the ABC’s. Pediatr. Radiol. 2023;53(12):2355–2368. DOI: 10.1007/s00247-023-05753-z.
32. Lyu J., Ma N., Tian C. et. аl. Perfusion and plaque evaluation to predict recurrent stroke in symptomatic middle cerebral artery stenosis. Stroke and Vascular Neurology. 2019;4(3):129–134. DOI: 10.1136/svn-2018-000228.
33. Umarova R.M., Beume L., Reisert M., Kaller C.P., Klöppel S., Mader I. et аl. Distinct white matter alterations following severe stroke: Longitudinal DTI study in neglect. Neurology. 2017;88(16):1546–1555. DOI: 10.1212/WNL.0000000000003843.
34. Levashkina I.M., Serebryakova S.V., Efimtsev A. Yu. Diffusion-tensor MRI – the most up-to-date method to research microstructual changes in white matter (publications’ review). Vestnik SPbSU. Series 11. Medicine. 2016;4:39–54. DOI: 10.21638/11701/spbu11.2016.404.
35. Visser M.M., Yassi N., Campbell B.C.V., Desmond P.M., Davis S.M., Spratt N. et al. White Matter Degeneration after Ischemic Stroke: A Longitudinal Diffusion Tensor Imaging Study. J. Neuroimaging. 2019;29(1):111–118. DOI: 10.1111/jon.12556.
36. Egorova-Brumley N., Dhollander T., Khan W., Khlif M.S., Ebaid D., Brodtmann A. Changes in white matter microstructure over 3 years in people with and without stroke. Neurology. 2023;100(16):e1664–e1672. DOI: 10.1212/WNL.0000000000207065.
37. Lewis A.F., Myers M., Heiser J., Kolar M., Baird J.F., Stewart J.C. Test-retest reliability and minimal detectable change of corticospinal tract integrity in chronic stroke. Hum. Brain Mapp. 2020;41(9):2514–2526. DOI: 10.1002/hbm.24961.
38. Liu J., Wang C., Qin W., Ding H., Guo J., Han T. et аl. Corticospinal fibers with different origins impact motor outcome and brain after subcortical stroke. Stroke. 2020;51(7):2170–2178. DOI: 10.1161/STROKEAHA.120.029508.
39. Blom-Smink M., Verly M., Spielmann K., Smits M., Ribbers G.M., van de Sandt-Koenderman M.W.M.E. Change in right inferior longitudinal fasciculus integrity is associated with naming recovery in subacute poststroke aphasia. Neurorehabil. Neural Repair. 2020;34(9):784–794. DOI: 10.1177/1545968320940982.
40. Keser Z., Meier E.L., Stockbridge M.D., Hillis A.E. The role of microstructural integrity of major language pathways in narrative speech in the first year after stroke. J. Stroke Cerebrovasc. Dis. 2020;29(9):105078. DOI: 10.1016/j.jstrokecerebrovasdis.2020.105078.
41. Mochizuki M., Uchiyama Y., Domen K. et аl. Associations between stroke outcome assessments and automated tractography fractional anisotropy incorporating age. Ann. Rehabil. Med. 2025;49(1):15–22. DOI: 10.5535/arm.240073.
42. Mahmoud B.E., Mohammad M.E., Serour D.K. What can DTI add in acute ischemic stroke patients? Egypt J. Radiol. Nucl. Med. 2019;50:67. DOI: 10.1186/s43055-019-0058-z.
43. Puig J., Blasco G., Schlaug G. et al. Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke. Neuroradiology. 2017;59:343–351. DOI: 10.1007/s00234-017-1816-0.
44. Keser Z. et al. The role of microstructural integrity of major language pathways in narrative speech in the first year after stroke. Journal of Stroke and Cerebrovascular Diseases. 2020;29(9). DOI: 1016/j.jstrokecerebrovasdis.2020.105078.
45. Nägele F.L., Petersen M., Mayer C. et аl. Longitudinal microstructural alterations surrounding subcortical ischemic stroke lesions detected by free-water imaging. Hum. Brain Mapp. 2024;45(8):e26722. DOI: 10.1002/hbm.26722.
46. Gong Z., Zhang R., Jiang W. et аl. Integrity of the hand fibers of the corticospinal tract shown by diffusion tensor imaging predicts hand function recovery after hemorrhagic stroke. J. Stroke Cerebrovasc. Dis. 2021;30(1):105447. DOI: 10.1016/j.jstrokecerebrovasdis.2020.105447.
Review
For citations:
Kurazhov A.P., Alifirova V.M., Koroleva E.S., Degtyarev I.Yu., Loiko Yu.N., Kucherova K.S., Sukhanova K.S., Zavadovskaya V.D. Multimodal magnetic resonance imaging of the brain at different stages of rehabilitation after ischemic stroke. Bulletin of Siberian Medicine. 2026;25(2):150-160. https://doi.org/10.20538/1682-0363-2026-2-150-160
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