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Neuroradiology

, Volume 59, Issue 4, pp 343–351 | Cite as

Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke

  • Josep Puig
  • Gerard Blasco
  • Gottfried Schlaug
  • Cathy M Stinear
  • Pepus Daunis-i-Estadella
  • Carles Biarnes
  • Jaume Figueras
  • Joaquín Serena
  • Maria Hernández-Pérez
  • Angel Alberich-Bayarri
  • Mar Castellanos
  • David S Liebeskind
  • Andrew M Demchuk
  • Bijoy K Menon
  • Götz Thomalla
  • Kambiz Nael
  • Max Wintermark
  • Salvador Pedraza
Review

Abstract

Purpose

Despite improved acute treatment and new tools to facilitate recovery, most patients have motor deficits after stroke, often causing disability. However, motor impairment varies considerably among patients, and recovery in the acute/subacute phase is difficult to predict using clinical measures alone, particularly in severely impaired patients. Accurate early prediction of recovery would help rationalize rehabilitation goals and improve the design of trials testing strategies to facilitate recovery.

Methods

We review the role of diffusion tensor imaging (DTI) in predicting motor recovery after stroke, in monitoring treatment response, and in evaluating white matter remodeling. We critically appraise DTI studies and discuss their limitations, and we explore directions for future study.

Results

Growing evidence suggests that combining clinical scores with information about corticospinal tract (CST) integrity can improve predictions about motor outcome. The extent of CST damage on DTI and/or the overlap between the CST and a lesion are key prognostic factor that determines motor performance and outcome. Three main strategies to quantify stroke-related CST damage have been proposed: (i) measuring FA distal to the stroke area, (ii) measuring the number of fibers that go through the stroke with tractography, and (iii) measuring the overlap between the stroke and a CST map derived from healthy age- and gender-matched controls.

Conclusion

Recovery of motor function probably involves remodeling of the CST proper and/or a greater reliance on alternative motor tracts through spontaneous and treatment-induced plasticity. DTI-metrics represent promising clinical biomarkers to predict motor recovery and to monitor and predict the response to neurorehabilitative interventions.

Keywords

Stroke Recovery Rehabilitation MRI Diffusion tensor imaging 

Notes

Compliance with ethical standards

Funding

This study was funded by a grant from the Spanish Ministry of Health (Fondo de Investigaciones Sanitarias, Reference PI060745).

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Josep Puig
    • 1
    • 2
  • Gerard Blasco
    • 1
    • 2
  • Gottfried Schlaug
    • 3
  • Cathy M Stinear
    • 4
  • Pepus Daunis-i-Estadella
    • 5
  • Carles Biarnes
    • 2
  • Jaume Figueras
    • 6
  • Joaquín Serena
    • 7
  • Maria Hernández-Pérez
    • 8
  • Angel Alberich-Bayarri
    • 9
  • Mar Castellanos
    • 10
  • David S Liebeskind
    • 11
  • Andrew M Demchuk
    • 12
  • Bijoy K Menon
    • 12
  • Götz Thomalla
    • 13
  • Kambiz Nael
    • 14
  • Max Wintermark
    • 15
  • Salvador Pedraza
    • 2
    • 16
  1. 1.Institute of Diagnostic Imaging (IDI) – Research Unit (IDIR)Parc Sanitari Pere VirgiliBarcelonaSpain
  2. 2.Girona Biomedical Research Institute (IDIBGI) – Medical ImagingHospital Universitari de Girona Dr. Josep TruetaGironaSpain
  3. 3.Neuroimaging and Stroke Recovery Laboratory, Department of NeurologyBeth Israel Deaconess Medical Center and Harvard Medical SchoolBostonUSA
  4. 4.Department of Medicine, Centre for Brain ResearchUniversity of AucklandAucklandNew Zealand
  5. 5.Department of Computer Science, Applied Mathematics and StatisticsUniversity of GironaGironaSpain
  6. 6.Department of RehabilitationDr. Josep Trueta University HospitalGironaSpain
  7. 7.Department of NeurologyDr. Josep Trueta University HospitalGironaSpain
  8. 8.Stroke UnitGermans Trias i Pujol University HospitalBadalonaSpain
  9. 9.La Fe Polytechnics and University HospitalValenciaSpain
  10. 10.Department of NeurologyA Coruña University HospitalLa CoruñaSpain
  11. 11.UCLA Stroke CenterLos AngelesUSA
  12. 12.Calgary Stroke Program, Hotchkiss Brain InstituteUniversity of CalgaryCalgaryCanada
  13. 13.Department of NeurologyUniversity Medical Center Hamburg-EppendorfHamburgGermany
  14. 14.Department of RadiologyIcahn School of Medicine at Mount SinaiNew YorkUSA
  15. 15.Department of Radiology, Neuroradiology DivisionStanford UniversityStanfordUSA
  16. 16.Institute of Diagnostic Imaging (IDI)Dr. Josep Trueta University HospitalGironaSpain

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