Corticospinal Tract Injury Estimated From Acute Stroke Imaging Predicts Upper Extremity Motor Recovery After Stroke

Abstract

Background and Purpose— Injury to the corticospinal tract (CST) has been shown to have a major effect on upper extremity motor recovery after stroke. This study aimed to examine how well CST injury, measured from neuroimaging acquired during the acute stroke workup, predicts upper extremity motor recovery. Methods— Patients with upper extremity weakness after ischemic stroke were assessed using the upper extremity Fugl-Meyer during the acute stroke hospitalization and again at 3-month follow-up. CST injury was quantified and compared, using 4 different methods, from images obtained as part of the stroke standard-of-care workup. Logistic and linear regression were performed using CST injury to predict ΔFugl-Meyer. Injury to primary motor and premotor cortices were included as potential modifiers of the effect of CST injury on recovery. Results— N=48 patients were enrolled 4.2±2.7 days poststroke and completed 3-month follow-up (median 90-day modified Rankin Scale score, 3; interquartile range, 1.5). CST injury distinguished patients who reached their recovery potential (as predicted from initial impairment) from those who did not, with area under the curve values ranging from 0.70 to 0.8. In addition, CST injury explained ≈20% of the variance in the magnitude of upper extremity recovery, even after controlling for the severity of initial impairment. Results were consistent when comparing 4 different methods of measuring CST injury. Extent of injury to primary motor and premotor cortices did not significantly influence the predictive value that CST injury had for recovery. Conclusions— Structural injury to the CST, as estimated from standard-of-care imaging available during the acute stroke hospitalization, is a robust way to distinguish patients who achieve their predicted recovery potential and explains a significant amount of the variance in poststroke upper extremity motor recovery.

Does Measurement of Corticospinal Tract Involvement Add Value to Clinical Behavioral Biomarkers in Predicting Motor Recovery after Stroke?

“…Moreover, the explanatory power of the prediction model made by combining CST injury and initial FMA-UE score in these patients was lower than that of only the initial FMA-UE score in all patients. This initial score (35) was different from 22, which was the reported value distinguishing patients with proportional recovery from those with limited recovery [ 2 ]. The same study also stated that a dichotomy based on the degree of CST injury could help distinguish patients with limited recovery from those with proportional recovery [ 2 ].…”

“…Since motor impairment is the most common cause of disability in patients with stroke, the prediction of motor recovery after stroke has been and remains an important issue [ 1 , 2 ]. The initial state of motor impairment of the upper extremity has been reported as the most influential predictor of upper extremity recovery [ 3 ].…”

“…Using conventional MRI is beneficial in terms of its availability and standardization [ 2 ]. To this end, spatial normalization has been carried out, in which lesion images are transformed into reference images of normal subjects [ 12 , 13 ].…”

Statistical Considerations for Drawing Conclusions About Recovery

“…Random uniform recovery is a reasonable distribution in this situation because it allows for the fact that different levels of recovery exist 15,31,32 but that the overall distribution of recovery can cover the entire available space. Patterns like uniform recovery have been shown in animal data 33,34 and human data using the FMA for the upper extremity, 19 the FMA for the lower extremity, 3 and the Arm Activity Measure.…”

Statistical considerations for drawing conclusions about recovery

“…was not certified by peer review) (which The copyright holder for this preprint this version posted November 27, 2019. . https://doi.org/10.1101/19013060 doi: medRxiv preprint strata of recovery exist, 12,25,26 but that the overall distribution of recovery covers the entire available space (e.g., as shown in animal data 27,28 ). In contrast, proportional recovery asserts the distribution of change scores is biased towards a certain level and advocates of the rule argue this level is about 70% of initial impairment across various scales and measures.…”