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

TY - JOUR

T1 - Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke

AU - Puig, Josep

AU - Blasco, Gerard

AU - Schlaug, Gottfried

AU - Stinear, Cathy M

AU - Daunis-I-Estadella, Pepus

AU - Biarnes, Carles

AU - Figueras, Jaume

AU - Serena, Joaquín

AU - Hernández-Pérez, Maria

AU - Alberich-Bayarri, Angel

AU - Castellanos, Mar

AU - Liebeskind, David S

AU - Demchuk, Andrew M

AU - Menon, Bijoy K

AU - Thomalla, Götz

AU - Nael, Kambiz

AU - Wintermark, Max

AU - Pedraza, Salvador

PY - 2017/4

Y1 - 2017/4

N2 - 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.

AB - 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.

KW - Diffusion Tensor Imaging

KW - Humans

KW - Prognosis

KW - Recovery of Function

KW - Stroke

KW - Stroke Rehabilitation

KW - Journal Article

KW - Review

U2 - 10.1007/s00234-017-1816-0

DO - 10.1007/s00234-017-1816-0

M3 - SCORING: Review article

C2 - 28293701

VL - 59

SP - 343

EP - 351

JO - NEURORADIOLOGY

JF - NEURORADIOLOGY

SN - 0028-3940

IS - 4

ER -