Neural function, injury, and stroke subtype predict treatment gains after stroke

Abstract

Objective To better understand the high variability in response seen when treating human subjects with restorative therapies post-stroke. Preclinical studies suggest that neural function, neural injury, and clinical status each influence treatment gains, therefore the current study hypothesized that a multivariate approach incorporating these three measures would have the greatest predictive value. Methods Patients 3-6 months post-stroke underwent a battery of assessments before receiving 3-weeks of standardized upper extremity robotic therapy. Candidate predictors included measures of brain injury (including to gray and white matter), neural function (cortical function and cortical connectivity), and clinical status (demographics/medical history, cognitive/mood, and impairment). Results Among all 29 patients, predictors of treatment gains identified measures of brain injury (smaller corticospinal tract (CST) injury), cortical function (greater ipsilesional motor cortex (M1) activation), and cortical connectivity (greater inter-hemispheric M1-M1 connectivity). Multivariate modeling found that best prediction was achieved using both CST injury and M1-M1 connectivity (r2=0.44, p=0.002), a result confirmed using Lasso regression. A threshold was defined whereby no subject with >63% CST injury achieved clinically significant gains. Results differed according to stroke subtype: gains in patients with lacunar stroke were exclusively predicted by a measure of intra-hemispheric connectivity. Interpretation Response to a restorative therapy after stroke is best predicted by a model that includes measures of both neural injury and function. Neuroimaging measures were the best predictors and may have an ascendant role in clinical decision-making for post-stroke rehabilitation, which remains largely reliant on behavioral assessments. Results differed across stroke subtypes, suggesting utility of lesion-specific strategies.

Increased Brain Sensorimotor Network Activation after Incomplete Spinal Cord Injury

“…71 A third limitation for this study is potential issues related to the focus on traumatic SCI, and not addressing injury to the spinal cord attributed to other etiologies, such as inflammation or infection. In stroke and other forms of acute CNS injury, measures of brain function show increasing promise to inform therapeutic approaches and clinical trial methodology, 72,73 for example, to serve as biomarkers or to stratify patients. The current study supports extension of this approach to the setting of incomplete SCI.…”

Neurorehabilitation in Stroke: The Role of Functional Connectivity

“…These findings suggest that cortical stimulation may be a promising approach to improve synaptic dysfunction and functional reorganization of motor networks after stroke, enhancing clinical recovery [2]. In support to this view, other studies exploring the effects of robotic therapy on brain function pointed out that motor recovery after stroke is best predicted by neuroimaging measures, including interhemispheric functional connectivity within the motor network [3]. Based on these studies, a successful motor recovery produced by conventional physiotherapy, robot-assisted therapy, or transcranial magnetic stimulation over the motor cortex is likely mediated by cortical network reorganization.…”

“…In an attempt to answer this question, new research looks at changes in neuronal reorganization or functional connectivity dynamics following neurorehabilitation in patients with stroke [2,3]. It is known that after focal lesions, cerebral networks reorganize themselves both functionally and structurally to compensate for the effects of the lesion and for those of remote areas.…”

“…It has been proposed that neuroimaging and functional measures may potentially have a role in clinical decision making for rehabilitation therapy after stroke [3]. A recent review of the use of non-invasive brain stimulation techniques to monitor and modulate the excitability of intracranial neuronal circuits highlights that transcranial magnetic stimulation can produce lasting effects on brain motor function.…”

Imaging in StrokeNet

“…There are increasing data that neuroimaging measures have value as stratifying variables in the context of stroke recovery where specific measures of brain injury or function markedly enhance the ability to classify subjects at baseline according to their likelihood of having a robust response to a proposed therapy. 21, 22 Nested or embedded imaging analyses could disclose critical findings regarding the interaction of specific therapies with baseline pathophysiology. For instance, the relative benefit of endovascular therapy based on collateral status could be integrated into the analysis plan and examined by the DSMB during, rather than after trial completion.…”