Decreased Corticospinal Tract Fractional Anisotropy Predicts Long-term Motor Outcome After Stroke

Puig, Josep; Blasco, Gerard; Daunis‐i‐Estadella, Pepus; Thomalla, Götz; Castellanos, Mar; Figueras, Jaume; Remollo, Sebastián; Eendenburg, Cecile van; Sánchez‐González, Javier; Serena, Joaquı́n; Pedraza, Salvador

doi:10.1161/strokeaha.111.000382

Cited by 115 publications

(117 citation statements)

References 15 publications

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“…10 Measurement of CST integrity with diffusion tensor imaging (DTI) 11 has been proposed both by assessment of decreases in FA distal to the stroke area and by the quantification of a decrease in the number of CST fibers, as an index of fiber degeneration (Wallerian degeneration). 12,13 In most previous work, including the one by Byblow et al, 10 these measurements were primarily obtained weeks or months after stroke 14,15 precluding their use for early prognostication. At the subacute stage, Feng et al 16 quantified the overlap of the acute stroke with a canonical CST derived from DTI of healthy controls instead of using DTI in patients.…”

Section: April 2016mentioning

confidence: 99%

Early Fiber Number Ratio Is a Surrogate of Corticospinal Tract Integrity and Predicts Motor Recovery After Stroke

Bigourdan

Munsch

Coupé

et al. 2016

Stroke

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≈70% of their initial motor impairment, 4,5 which, therefore, already conveys strong predictive information. Nevertheless, this 70% rule fails in patients with initial severe deficit, 4,5 and the variability in medium to long-term outcome is not adequately explained by initial clinical severity alone for those patients. The interindividual variability in the relation between initial impairment and subsequent recovery hampers accurate individualized prognosis. 6 Although infarct volume could be helpful to improve prognostication, 7 its power as an independent predictor of clinical outcome is still debated. 8Background and Purpose-The contribution of imaging metrics to predict poststroke motor recovery needs to be clarified.We tested the added value of early diffusion tensor imaging (DTI) of the corticospinal tract toward predicting long-term motor recovery. Methods-One hundred seventeen patients were prospectively assessed at 24 to 72 hours and 1 year after ischemic stroke with diffusion tensor imaging and motor scores (Fugl-Meyer). The initial fiber number ratio (iFNr) and final fiber number ratio were computed as the number of streamlines along the affected corticospinal tract normalized to the unaffected side and were compared with each other. The prediction of motor recovery (ΔFugl-Meyer) was first modeled using initial Fugl-Meyer and iFNr. Multivariate ordinal logistic regression models were also used to study the association of iFNr, initial Fugl-Meyer, age, and stroke volume with Fugl-Meyer at 1 year. Results-The iFNr correlated with the final fiber number ratio at 1 year (r=0.70; P<0.0001). The initial Fugl-Meyer strongly predicted motor recovery (≈73% of initial impairment) for all patients except those with initial severe stroke (FuglMeyer<50). For these severe patients (n=26), initial Fugl-Meyer was not correlated with motor recovery (R 2 =0.13; p=ns), whereas iFNr showed strong correlation (R 2 =0.56; P<0.0001). In multivariate analysis, the iFNr was an independent predictor of motor outcome (β=2.601; 95% confidence interval=0.304-5.110; P=0.031), improving prediction compared with using only initial Fugl-Meyer, age, and stroke volume (P=0.026). Conclusions-Early measurement of FNr at 24 to 72 hours poststroke is a surrogate marker of corticospinal tract integrity and provides independent prediction of motor outcome at 1 year especially for patients with severe initial impairment.

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Section: April 2016mentioning

confidence: 99%

Early Fiber Number Ratio Is a Surrogate of Corticospinal Tract Integrity and Predicts Motor Recovery After Stroke

Bigourdan

Munsch

Coupé

et al. 2016

Stroke

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“…MRI can also be used to derive biomarkers of the motor system after stroke 10. Worse upper limb motor recovery and outcomes are predicted by greater stroke lesion load on descending corticomotor pathways,11 and greater asymmetry in fractional anisotropy along the corticospinal tracts 12, 13, 14, 15. To date no single clinical measure or neurological biomarker has been able to accurately predict motor recovery or outcome for all patients, and therefore approaches using combinations of measures and biomarkers are needed 6…”

Section: Introductionmentioning

confidence: 99%

PREP2: A biomarker‐based algorithm for predicting upper limb function after stroke

Stinear

Byblow

Ackerley

et al. 2017

Ann Clin Transl Neurol

254

321

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ObjectiveRecovery of motor function is important for regaining independence after stroke, but difficult to predict for individual patients. Our aim was to develop an efficient, accurate, and accessible algorithm for use in clinical settings. Clinical, neurophysiological, and neuroimaging biomarkers of corticospinal integrity obtained within days of stroke were combined to predict likely upper limb motor outcomes 3 months after stroke.MethodsData from 207 patients recruited within 3 days of stroke [103 females (50%), median age 72 (range 18–98) years] were included in a Classification and Regression Tree analysis to predict upper limb function 3 months poststroke.ResultsThe analysis produced an algorithm that sequentially combined a measure of upper limb impairment; age; the presence or absence of upper limb motor evoked potentials elicited with transcranial magnetic stimulation; and stroke lesion load obtained from MRI or stroke severity assessed with the NIHSS score. The algorithm makes correct predictions for 75% of patients. A key biomarker obtained with transcranial magnetic stimulation is required for one third of patients. This biomarker combined with NIHSS score can be used in place of more costly magnetic resonance imaging, with no loss of prediction accuracy.InterpretationThe new algorithm is more accurate, efficient, and accessible than its predecessors, which may support its use in clinical practice. While further work is needed to potentially incorporate sensory and cognitive factors, the algorithm can be used within days of stroke to provide accurate predictions of upper limb functional outcomes at 3 months after stroke. www.presto.auckland.ac.nz

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“…1,4 In addition, diffusion tensor imaging (DTI) studies have reported that the use of fractional anisotropy (FA) of corticospinal tract (CST) alone to predict future motor function of the upper extremity in patients with stroke in the acute period is also unreliable. [8][9][10][11] Researchers have proposed that more accurate prognoses may be made by combining behavioral tests with magnetic resonance imaging (MRI) determinations of the functional or structural integrity of the ipsilesional corticomotor tract. 12,13 However, it has been reported that on the base of initial impairment, adding functional MRI task-related brain activation patterns (during hand closure task) to their prediction model did…”

mentioning

confidence: 99%

Motor Recovery Prediction With Clinical Assessment and Local Diffusion Homogeneity After Acute Subcortical Infarction

Liu

Tan

Dang

et al. 2017

Stroke

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Background and Purpose-Initial clinical assessment or conventional diffusion tensor imaging parameters alone do not reliably predict poststroke recovery of motor function. Recently, local diffusion homogeneity (LDH) has been proposed to represent the local coherence of water molecule diffusion and can serve as a complementary marker for investigating white matter alterations of the brain. We aimed to determine whether a combination of initial clinical assessment and LDH could predict motor recovery after acute subcortical infarction. Methods-Standard upper extremity Fugl-Meyer assessment and diffusion tensor imaging were performed 1, 4, and 12 weeks after onset in 50 patients with subcortical infarction. Proportional recovery model residuals were used to assign patients to proportional recovery and poor recovery groups. Tract-based spatial statistics analysis was used to compare diffusion differences between proportional and poor recovery outcomes. Multivariate logistic regression model was used to identify the predictors of motor improvement within 12 weeks after stroke. Results-The poor recovery group had lower LDH than the proportional recovery group, mainly in the ipsilesional corticospinal tract in the superior corona radiate and posterior limb of internal capsule 1 week after stroke (P<0.005; family-wise error corrected). Multivariate logistic regression analysis indicated that both initial Fugl-Meyer assessment and LDH in the ipsilesional corticospinal tract in the superior corona radiate and posterior limb of internal capsule were predictors of motor improvement within 12 weeks after stroke (G=47.22; P<0.001). Leave-one-out cross-validation confirmed a positive predictive value of 0.818, a negative predictive value of 0.833, and an accuracy of 0.824 (P<0.00 001; permutation test). Conclusions-These

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Decreased Corticospinal Tract Fractional Anisotropy Predicts Long-term Motor Outcome After Stroke

Cited by 115 publications

References 15 publications

Early Fiber Number Ratio Is a Surrogate of Corticospinal Tract Integrity and Predicts Motor Recovery After Stroke

Early Fiber Number Ratio Is a Surrogate of Corticospinal Tract Integrity and Predicts Motor Recovery After Stroke

PREP2: A biomarker‐based algorithm for predicting upper limb function after stroke

Motor Recovery Prediction With Clinical Assessment and Local Diffusion Homogeneity After Acute Subcortical Infarction

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