Can Diffusion MRI Reveal Stroke-Induced Microstructural Changes in GM?

  • Lorenza BrusiniEmail author
  • Ilaria Boscolo Galazzo
  • Mauro Zucchelli
  • Cristina Granziera
  • Gloria Menegaz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11383)


The development of noninvasive techniques to image the human brain has enabled the demonstration of structural plasticity in response to motor learning. In the last years evidence has emerged on the potential of some measures derived from diffusion Magnetic Resonance Imaging (DMRI) as numerical biomarkers of tissue changes in regions involved in the motor network. In these works, the descriptors were extensively analysed in contralateral white matter (WM) along both single connections and networks relying on tract-based analyses and statistical evaluation. Though, their ability to detect changes in gray matter (GM) has been scarcely investigated. This work aims at the assessment of propagator-based microstructural indices in capturing GM changes and the relation of such changes to functional recovery at six months from the injury focusing on the Diffusion Tensor Imaging (DTI) and the three dimensional Simple Harmonics Oscillator based Reconstruction and Estimation (3D-SHORE) models.


  1. 1.
    Avram, A.V., et al.: Clinical feasibility of using mean apparent propagator (map) MRI to characterize brain tissue microstructure. NeuroImage 127, 422–434 (2016)CrossRefGoogle Scholar
  2. 2.
    Boscolo Galazzo, I., Brusini, L., Obertino, S., Zucchelli, M., Granziera, C., Menegaz, G.: On the viability of diffusion MRI-based microstructural biomarkers in ischemic stroke. Front. Neurosci. 12, 92 (2018)CrossRefGoogle Scholar
  3. 3.
    Brusini, L., et al.: Ensemble average propagator-based detection of microstructural alterations after stroke. Int. J. Comput. Assist. Radiol. Surg. 11(9), 1585–1597 (2016)CrossRefGoogle Scholar
  4. 4.
    Brusini, L., et al.: Assessment of mean apparent propagator-based indices as biomarkers of axonal remodeling after stroke. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9349, pp. 199–206. Springer, Cham (2015). Scholar
  5. 5.
    Cai, J., et al.: Contralesional cortical structural reorganization contributes to motor recovery after sub-cortical stroke: a longitudinal voxel-based morphometry study. Front. Hum. Neurosci. 10, 393 (2016)CrossRefGoogle Scholar
  6. 6.
    Dayan, E., Cohen, L.G.: Neuroplasticity subserving motor skill learning. Neuron 72(3), 443–454 (2011)CrossRefGoogle Scholar
  7. 7.
    Draganski, B., et al.: Decrease of thalamic gray matter following limb amputation. Neuroimage 31(3), 951–957 (2006)CrossRefGoogle Scholar
  8. 8.
    Fan, F., et al.: Dynamic brain structural changes after left hemisphere subcortical stroke. Hum. Brain Mapp. 34(8), 1872–1881 (2013)CrossRefGoogle Scholar
  9. 9.
    Lin, Y., et al.: The role of diffusion tensor imaging in the evaluation of ischemic brain injury-a review. Brain Connectomics 5(7), 401–412 (2015)CrossRefGoogle Scholar
  10. 10.
    Novikov, D., Veraart, J., Jelescu, I., Fieremans, E.: Rotationally-invariant mapping of scalar and orientational metrics of neuronal microstructure with diffusion MRI. NeuroImage 174, 518–538 (2018)CrossRefGoogle Scholar
  11. 11.
    Özarslan, E., et al.: Mean apparent propagator (map) MRI: a novel diffusion imaging method for mapping tissue microstructure. NeuroImage 78, 16–32 (2013)CrossRefGoogle Scholar
  12. 12.
    Palombo, M., Ligneul, C., Hernandez-Garzon, E., Valette, J.: Can we detect the effect of spines and leaflets on the diffusion of brain intracellular metabolites? NeuroImage (2017)Google Scholar
  13. 13.
    Sampaio-Baptista, C., Sanders, Z.B., Johansen-Berg, H.: Structural plasticity in adulthood with motor learning and stroke rehabilitation. Ann. Rev. Neurosci. 41, 25–40 (2018)CrossRefGoogle Scholar
  14. 14.
    Tardif, C.L., et al.: Advanced MRI techniques to improve our understanding of experience-induced neuroplasticity. NeuroImage 131, 55–72 (2016)CrossRefGoogle Scholar
  15. 15.
    Zatorre, R.J., Fields, R.D., Johansen-Berg, H.: Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nat. Neurosci. 15(4), 528 (2012)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Lorenza Brusini
    • 1
    Email author
  • Ilaria Boscolo Galazzo
    • 1
  • Mauro Zucchelli
    • 2
  • Cristina Granziera
    • 3
  • Gloria Menegaz
    • 1
  1. 1.Department of Computer ScienceUniversity of VeronaVeronaItaly
  2. 2.Inria, Sophia Antipolis MediterranéeBiotFrance
  3. 3.Department of NeurologyBasel University HospitalBaselSwitzerland

Personalised recommendations