Possibilities of diff usion-weighted magnetic resonance imaging in determining the rehabilitation potential of the acute period of ischemic stroke

Studies over the past decade demonstrate the high potential of diff usion-weighted MRI (dMRI) as a modern technique for non-invasive quantitative assessment of the microstructural integrity of the white matter of the brain, which allows predicting some aspects of the rehabilitation potential. 
Purpose of the study: to calculate the threshold values of fractional anisotropy (FA) of some cerebral tracts, which are informative in determining various aspects of the rehabilitation potential in the acute period of ischemic stroke. Patients and methods. We examined 100 patients with ischemic stroke and 10 persons without stroke and cognitive impairment. All patients underwent dMRI and clinical assessment of indicators of rehabilitation potential at discharge. 
Results. The NIHSS at discharge is associated with the size of infarction, the FA of the anterior, posterior leg and knee of the internal capsule, the superior longitudinal, cingular and inferior fronto-occipital bundles. Similar associations were noted for the Rivermead mobility index and the Rankin scale. The function of the hand according to the Frenchay scale is associated with the size of the lesion, FA of the anterior leg of the internal capsule, superior longitudinal, inferior fronto-occipital and cingular bundles. The MoCA is interrelated only with the size of the infarction and the FA of the anterior leg of the internal capsule, the Berg scale — with the size of the lesion and the FA of the upper longitudinal bundle, the FIM scale — with the FA of the upper longitudinal, inferior fronto-occipital and cingular bundles. The threshold values of FA of the cerebral tracts which are most informative in determining various aspects of the rehabilitation potential in the acute period of ischemic stroke were determined. 
Conclusion. The quantitative assessment of the FA of the main projection and associative tracts is informative in relation to the determination of the rehabilitation potential in the acute period of ischemic stroke.

1. Nazarova M., Kulikova S., Piradov M.A., Limonova A.S., Dobrynina L.A., Konovalov R.N. et al. Multimodal Assessment of the Motor System in Patients With Chronic Ischemic Stroke. Stroke. 2021;52(1):241–249. doi: 10.1161/STROKEAHA.119.028832

2. Tulyaganova N.M. Qualitative and Quantitative Evaluation of Pathways by Diff usion Tensor Imaging in Children with Cerebral Stroke. Medical Visualization. 2017;(1):5–12. (In Russian). https://doi.org/10.24835/1607-0763-2017-1-5-12

3. Dobrynina L.A., Konovalov R.N., Kremneva E.I., Kadykov A.S. MRI in the assessment of motor function restoration in patients with chronic supratentorial infarction. Annals of Clinical and Experimental Neurology. 2012;6(2):4–10. (In Russian).

4. Maximova M.Y., Popova T.A., Konovalov R.N. Prоgnosis of motor function recovery in ischemic stroke using diff usion tensor MRI. Zh. Nevrol. Psikhiatr. imeni S.S. Korsakova. 2016;116 (8Pt2):57–64. (in Russian). https://doi.org/10.17116/jnevro20161168257-64

5. Belova A.N., Grygorieva V.N., Sushin V.O., Belova E.M., Israelyan Y.A., Sheyko G.E. Anatomical and functional features of corticospinal tracts and their role in restoration of motor functions after brain injury. Bulletin of rehabilitation medicine. 2020;1(95):9–18. (in Russian).

6. Stebbins G.T., Murphy C.M. Diff usion tensor imaging in Alzheimer’s disease and mild cognitive impairment. Behav Neurol. 2009;21(1):39–49. https://doi.org/10.3233/BEN-2009-0234

7. Lindenberg R., Zhu L.L., Rüber T., Schlaug G. Predicting functional motor potential in chronic stroke patients using diff usion tensor imaging. Hum. Brain Mapp. 2012;33(5):1040–51. https://doi.org/10.1002/hbm.21266

8. Puig J., Blasco G., Schlaug G., Stinear C.M., Daunis-I-Estadella P., Biarnes C. et al. Diff usion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke. Neuroradiology. 2017;59(4):343–351. https://doi.org/10.1007/s00234-017-1816-0

9. Soulard J., Huber C., Baillieul S., Thuriot A., Renard F., Aubert Broche B. et al. Motor tract integrity predicts walking recovery: A diff usion MRI study in subacute stroke. Neurology. 2020;94(6):583–593. https://doi.org/10.1212/WNL.0000000000008755

10. Yeo S.S., Jang S.H., Park G.Y., Oh S. Eff ects of injuries to descending motor pathways on restoration of gait in patients with pontine hemorrhage. J. Stroke Cerebrovasc. Dis. 2020;29(7):104857. https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.104857

11. Fan Y.T., Lin K.C., Liu H.L., Chen Y.L., Wu C.Y. Changes in structural integrity are correlated with motor and functional recovery after post-stroke rehabilitation. Restor Neurol Neurosci. 2015;33(6):835–44. https://doi.org/10.3233/RNN-150523

12. Forkel S.J., Thiebaut de Schotten M., Dell’Acqua F., Kalra L., Murphy D.G., Williams S.C. et al. Anatomical predictors of aphasia recovery: a tractography study of bilateral perisylvian language networks. Brain. 2014;137(7):2027–39. https://doi.org/10.1093/brain/awu113

13. Ivanova M.V., Isaev D.Y., Dragoy O.V., Akinina Y.S., Petrushevskiy A.G., Fedina O.N., et al. Diff usion-tensor imaging of major white matter tracts and their role in language processing in aphasia. Cortex. 2016;85:165–181. https://doi.org/10.1016/j.cortex.2016.04.019

14. Kulesh A., Drobakha V., Kuklina E., Nekrasova I., Shestakov V. Cytokine Response, Tract-Specifi c Fractional Anisotropy, and Brain Morphometry in Post-Stroke Cognitive Impairment. J. Stroke Cerebrovasc. Dis. 2018;27(7):1752–1759. https://doi.org/10.1016/j.jstrokecerebrovasdis.2018.02.004

15. Zamboni G., Griff anti L., Mazzucco S., Pendlebury S.T., Rothwell P.M. Age-dependent association of white matter abnormality with cognition after TIA or minor stroke. Neurology. 2019;93(3):272–282. https://doi.org/10.1212/WNL.0000000000007772

16. Galovic M., Leisi N., Pastore-Wapp M., Zbinden M., Vos S.B., Mueller M. et al. Diverging lesion and connectivity patterns infl uence early and late swallowing recovery after hemispheric stroke. Hum. Brain Mapp. 2017;38(4):2165–2176. https://doi.org/10.1002/hbm.23511

17. Jang S.H. Diff usion tensor imaging studies on arcuate fasciculus in stroke patients: a review. Front. Hum. Neurosci. 2013;7:749. https://doi.org/10.3389/fnhum.2013.00749

18. Kulikova S.P., Nikulin V.V., Dobrynina L.A., Nazarova M.A. А Possible Sensory Interpretation of Alternate Motor Fibers Relating to Structural Reserve during Stroke. Front. Neurol. 2017;8:355. https://doi.org/10.3389/fneur.2017.00355

19. Kulesh A.A., Drobakha V.E., Sobyanin K.V., Kulikova S.P., Bykova A.Yu., Kaileva N.A. et al. Role of cerebral reserve assessed using diff usion-weighted magnetic resonance imaging in determining the rehabilitation potential of acute ischemic stroke. Neurology, Neuropsychiatry, Psychosomatics. 2019;11(3):26–34. (In Russian). https://doi.org/10.14412/2074-2711-2019-3-26-34

20. Nanda P., Banks G.P., Pathak Y.J., Sheth S.A. Connectivity-based parcellation of the anterior limb of the internal capsule. Hum. Brain Mapp. 2017;38(12):6107–6117. https://doi.org/10.1002/hbm.23815

21. Mithani K., Davison B., Meng Y., Lipsman N. The anterior limb of the internal capsule: Anatomy, function, and dysfunction. Behav. Brain Res. 2020;387:112588. https://doi.org/10.1016/j.bbr.2020.112588

22. Zhao L., Biesbroek J.M., Shi L., Liu W., Kuijf H.J., Chu W.W. et al. Strategic infarct location for post-stroke cognitive impairment: A multivariate lesion-symptom mapping study. J. Cereb. Blood Flow Metab. 2018;38(8):1299–1311

23. Aben H.P., Biessels G.J., Weaver N.A., Spikman J.M., VisserMeily J.M.A., de Kort P.L.M. et al. Extent to Which Network Hubs Are Aff ected by Ischemic Stroke Predicts Cognitive Recovery. Stroke. 2019;50(10):2768–2774. https://doi.org/10.1161/STROKEAHA.119.025637

24. Bournonville C., Hénon H., Dondaine T., Delmaire C., Bombois S., Mendyk A.M. et al. Identifi cation of a specifi c functional network altered in poststroke cognitive impairment. Neurology. 2018;90(21):1879–1888. https://doi.org/10.1212/WNL.0000000000005553

25. Linacre J.M., Heinemann A.W., Wright B.D., Granger C.V., Hamilton B.B. The structure and stability of the Functional Independence Measure. Arch Phys. Med. Rehabil. 1994;75(2):127–32.

26. Stern Y., Barnes C.A., Grady C., Jones R.N., Raz N. Brain reserve, cognitive reserve, compensation, and maintenance: operationalization, validity, and mechanisms of cognitive resilience. Neurobiol Aging. 2019;83:124–129. https://doi.org/10.1016/j.neurobiolaging.2019.03.022

27. Bubb E.J., Metzler-Baddeley C, Aggleton J.P. The cingulum bundle: Anatomy, function, and dysfunction. Neurosci. Biobehav. Rev. 2018;92:104–127. https://doi.org/10.1016/j.neubiorev.2018.05.008

28. Lebel C., Gee M., Camicioli R., Wieler M., Martin W., Beaulieu C. Diff usion tensor imaging of white matter tract evolution over the lifespan. Neuroimage. 2012;60(1):340–52. https://doi.org/10.1016/j.neuroimage.2011.11.094

29. Delano-Wood L., Stricker N.H., Sorg S.F., Nation D.A., Jak A.J., Woods S.P. et al. Posterior cingulum white matter disruption and its associations with verbal memory and stroke risk in mild cognitive impairment. J. Alzheimers Dis. 2012;29(3):589–603. https://doi.org/10.3233/JAD-2012-102103

30. Haque M.E., Gabr R.E., Hasan K.M., George S., Arevalo O.D., Zha A. et al. Ongoing Secondary Degeneration of the Limbic System in Patients With Ischemic Stroke: A Longitudinal MRI Study. Front Neurol. 2019;10:154. https://doi.org/10.3389/fneur.2019.00154

31. Kaileva N.A., Kulesh A.A., Gorst N.Kh., Bykova A.Yu., Drobakha V.E., Sobyanin K.V., Shardakov I.N., Shestakov V.V. Role of the intact hemisphere in determining the rehabilitation potential in the acute period of ischemic stroke: a diff usion and perfusion model. Neurology, Neuropsychiatry, Psychosomatics. 2019;11(1):28–35. (In Russian). https://doi.org/10.14412/2074-2711-2019-1-28-35

32. Lawes I.N., Barrick T.R., Murugam V., Spierings N., Evans D.R, Song M. et al. Atlas-based segmentation of white matter tracts of the human brain using diff usion tensor tractography and comparison with classical dissection. NeuroImage. 2008;39(1):62–79. https://doi.org/10.1016/j.neuroimage.2007.06.041

33. 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. https://doi.org/10.1177/1545968320940982

34. Chen H.F., Huang L.L., Li H.Y., Qian Y., Yang D., Qing Z. et al. Microstructural disruption of the right inferior fronto-occipital and inferior longitudinal Fasciculus contributes to WMH-related cognitive impairment. CNS Neurosci Ther. 2020;26(5):576–588. https://doi.org/10.1111/cns.13283

35. Kulesh A.A., Drobakha V.E., Nekrasova I.V., Shestakov V.V., Kuklina E.M. Neuroinfl ammatory, Neurodegenerative and Structural Brain Biomarkers of the Main Types of Post-Stroke Cognitive Impairment in Acute Period of Ischemic Stroke. Annals of the Russian academy of medical sciences. 2016;71(4):304−312. (In Russian). https://doi.org/10.15690/vramn685

36. Mandonnet E., Sarubbo S., Petit L. The Nomenclature of Human White Matter Association Pathways: Proposal for a Systematic Taxonomic Anatomical Classifi cation. Front Neuroanat. 2018;12:94. https://doi.org/10.3389/fnana.2018.00094

37. Schmahmann J.D., Pandya D.N., Wang R., Dai G., D’Arceuil H.E., Crespigny A.J. et al. Association fi bre pathways of the brain: parallel observations from diff usion spectrum imaging and autoradiography. Brain. 2007;130(3):630–53. https://doi.org/10.1093/brain/awl359

38. Li Y., Feng F., Lin P., Huang Z.G., Liu T., Zhou B. et al. Cognitionrelated white matter integrity dysfunction in Alzheimer’s disease with diff usion tensor image. Brain Res. Bull. 2018;143:207–216. https://doi.org/10.1016/j.brainresbull.2018.09.010

39. Luo C., Li M., Qin R., Chen H., Huang L., Yang D. et al. Long Longitudinal Tract Lesion Contributes to the Progression of Alzheimer’s isease. Front Neurol. 2020;11:503235. https://doi.org/10.3389/fneur.2020.503235