Prediction of Motor Recovery Using Initial Impairment and fMRI 48 h Poststroke

The Neurological Institute, New York, NY 10032, USA.
Cerebral Cortex (Impact Factor: 8.67). 04/2011; 21(12):2712-21. DOI: 10.1093/cercor/bhr047
Source: PubMed


There is substantial interpatient variation in recovery from upper limb impairment after stroke in patients with severe initial impairment. Defining recovery as a change in the upper limb Fugl-Meyer score (ΔFM), we predicted ΔFM with its conditional expectation (i.e., posterior mean) given upper limb Fugl-Meyer initial impairment (FM(ii)) and a putative functional magnetic resonance imaging (fMRI) recovery measure. Patients with first time, ischemic stroke were imaged at 2.5 ± 2.2 days poststroke with 1.5-T fMRI during a hand closure task alternating with rest (fundamental frequency = 0.025 Hz, scan duration = 172 s). Confirming a previous finding, we observed that the prediction of ΔFM by FM(ii) alone is good in patients with nonsevere initial hemiparesis but is not good in patients with severe initial hemiparesis (96% and 16% of the total sum of squares of ΔFM explained, respectively). In patients with severe initial hemiparesis, prediction of ΔFM by the combination of FM(ii) and the putative fMRI recovery measure nonsignificantly increased predictive explanation from 16% to 47% of the total sum of squares of ΔFM explained. The implications of this preliminary negative result are discussed.

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Available from: Leeor Alon, Oct 09, 2015
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    • "Much of the focus of fMRI in stroke studies has been on whether its application provides a better understanding of brain functional reorganization accompanying motor recovery after stroke (Riecker et al., 2010; Garrison et al., 2013; Havsteen et al., 2013; Heiss and Kidwell, 2014). In a recent study, fMRI-derived measures have been correlated with movement recovery achieved with robot-assisted BCI therapy (Varkuti et al., 2013), while another study found that fMRI measures do not contribute significantly to the prediction of motor recovery (Zarahn et al., 2011). Another non-invasive MRI-based technique, DTI, has been widely used to evaluate the integrity of the white matter tracts after stroke. "
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    ABSTRACT: The relationship of the structural integrity of white matter tracts and cortical activity to motor functional outcomes in stroke patients is of particular interest in understanding mechanisms of brain structural and functional changes while recovering from stroke. This study aims to probe these underlying mechanisms using diffusion tensor imaging (DTI) and fMRI measures. We examined the structural integrity of the PLIC using DTI and corticomotor activity using motor-task fMRI in stroke patients who completed up to 15 sessions of rehabilitation therapy using Brain-Computer Interface (BCI) technology. We hypothesized that 1) the structural integrity of the posterior limb of the internal capsule (PLIC) and corticomotor activity are affected by stroke; 2) changes in structural integrity and corticomotor activity following BCI intervention are related to motor recovery; 3) there is a potential relationship between structural integrity and corticomotor activity. We found that 1) the ipsilesional PLIC showed significantly decreased fractional anisotropy (FA) values when compared to the contralesional PLIC; 2) lower PLIC-FA values were significantly associated with worse motor outcomes (i.e., positively correlated); 3) lower ipsilesional PLIC-FA values were significantly associated with greater ipsilesional corticomotor activity during impaired-finger-tapping-task fMRI (i.e., negatively correlated), with an overall bilateral pattern of corticomotor activity observed; and 4) baseline FA values predicted motor recovery assessed after BCI intervention. These findings suggest that greater vs. lesser microstructural integrity of the ipsilesional PLIC may contribute towards better vs. poor motor recovery respectively in the stroke-affected limb and demand lesser vs. greater cortical activity respectively from the ipsilesional motor cortex. PLIC-FA is a promising biomarker in tracking and predicting motor functional recovery in stroke patients receiving BCI intervention.
    Frontiers in Neuroengineering 07/2014; 7(22). DOI:10.3389/fneng.2014.00022
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    • "Moreover, functional gain has no direct correlation with ipsilesional motor cortex activity in the acute stage of stroke, but a pattern of cortical activation including the postcentral gyrus and cingulate cortex correlates with subsequent motor recovery [162]. Furthermore, in patients with stroke and severe initial hemiparesis, subsequent motor recovery was not predicted by task-related fMRI activation [163]. Thus, the effective neural activation pattern for neurorehabilitation might be different depending on time since stroke, lesion site, impairment of motor function, and/or rehabilitation technique due to the heterogeneous mechanisms underlying motor recovery and neurorehabilitation techniques. "
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    ABSTRACT: Motor recovery after stroke is related to neural plasticity, which involves developing new neuronal interconnections, acquiring new functions, and compensating for impairment. However, neural plasticity is impaired in the stroke-affected hemisphere. Therefore, it is important that motor recovery therapies facilitate neural plasticity to compensate for functional loss. Stroke rehabilitation programs should include meaningful, repetitive, intensive, and task-specific movement training in an enriched environment to promote neural plasticity and motor recovery. Various novel stroke rehabilitation techniques for motor recovery have been developed based on basic science and clinical studies of neural plasticity. However, the effectiveness of rehabilitative interventions among patients with stroke varies widely because the mechanisms underlying motor recovery are heterogeneous. Neurophysiological and neuroimaging studies have been developed to evaluate the heterogeneity of mechanisms underlying motor recovery for effective rehabilitation interventions after stroke. Here, we review novel stroke rehabilitation techniques associated with neural plasticity and discuss individualized strategies to identify appropriate therapeutic goals, prevent maladaptive plasticity, and maximize functional gain in patients with stroke.
    Stroke Research and Treatment 04/2013; 2013(12):128641. DOI:10.1155/2013/128641
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    • "Functional MRI data acquired in the first few days after stroke has also been used to try to predict a sub - sequent change in motor performance ( Marshall et al . 2009 ; Zarahn et al . 2011 ) . A particular pattern of brain activation was highly predictive of clinical change over the next 3 months , a finding that was independent of initial stroke severity and lesion volume . Although the multivariate analysis used did not allow anatomical inference to be made , it is clear that there is something"
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    ABSTRACT: Stroke often leads to impairment of hand function. Over the following months a variable amount of recovery can be seen. The evidence from animal and human studies suggests that reorganization rather than repair is the key. Surviving neural networks are important for recovery of function and non-invasive techniques such as functional magnetic resonance imaging allow us to study them in humans. For example, initial attempts to move a paretic limb following stroke are associated with widespread activity within the distributed motor system in both cerebral hemispheres, more so in patients with greater impairment. Disruption of activity in premotor areas using transcranial magnetic stimulation prior to movement can impair motor performance in stroke patients but not in controls suggesting that these new patterns of brain activity can support recovered function. In other words, this reorganisation is functionally relevant. More recently, research has been directed at understanding how surviving brain regions influence one another during movement. This opens the way for functional brain imaging to become a clinically useful tool in rehabilitation. Understanding the dynamic process of systems level reorganization will allow greater understanding of the mechanisms of recovery and potentially improve our ability to deliver effective restorative therapy.
    The Journal of Physiology 11/2011; 589(Pt 23):5625-32. DOI:10.1113/jphysiol.2011.220939 · 5.04 Impact Factor
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