Posts Tagged DTI
[Abstract] Predicting REcovery Potential of Upper Limb Function After Stroke to Increase Rehabilitation Efficiency
Introduction: The PREP algorithm combines clinical assessment [Shoulder Abduction Finger Extension (SAFE) score], transcranial magnetic stimulation (TMS) and diffusion-tensor imaging to predict potential for upper limb recovery following stroke. Patients’ recovery potential is predicted to be Complete, Notable, Limited or None.
Hypothesis: The PREP algorithm may be used in a ‘real world’ clinical setting to set individual rehabilitation goals.
Methods: This study recruited 194 patients with upper limb weakness within 3 days of stroke. Assessments were made at baseline and 12 weeks by assessors blinded to PREP algorithm prediction. The initial benchmarking phase recruited 85 patients and PREP algorithm information was not shared with clinical teams or patients. The results were used to refine the algorithm and guide implementation in three ways. First, patients with a SAFE score > 7, predicted to have Complete upper limb recovery, were given a self-directed therapy program. Second, patients with a SAFE score of 5-7 could be given a Notable recovery prognosis, without requiring TMS. Third, 19% of patients exceeded their predicted upper limb recovery, so this possibility was conveyed to patients and clinical teams. The implementation phase recruited 109 patients, and PREP algorithm predictions were shared with patients and clinical teams.
Results: Interim analyses (n = 135) find that the PREP algorithm correctly predicted upper limb function at 12 weeks for 85% of patients. Implementation of the algorithm decreased length of stay by 7 days (95%CI 2 – 15 days, p < 0.05) and increased the proportion of patients discharged home from the acute stroke unit from 28% to 49% (p < 0.01). Implementation also decreased upper limb therapy dose (p < 0.01), yet patient outcomes were similar between the two phases. Primary endpoint analysis will be complete in November 2015.
Conclusions: Making predictions about the potential for recovery of upper limb function, and setting individual rehabilitation goals accordingly, may increase the efficiency of post-stroke rehabilitation.
[ARTICLE] A review of transcranial magnetic stimulation and multimodal neuroimaging to characterize post-stroke neuroplasticity – Full Text PDF
Following stroke, the brain undergoes various stages of recovery where the central nervous system can reorganize neural circuitry (neuroplasticity) both spontaneously and with the aid of behavioural rehabilitation and non-invasive brain stimulation. Multiple neuroimaging techniques can characterize common structural and functional stroke-related deficits, and importantly, help predict recovery of function. Diffusion tensor imaging (DTI) typically reveals increased overall diffusivity throughout the brain following stroke, and is capable of indexing the extent of white matter damage. Magnetic resonance spectroscopy (MRS) provides an index of metabolic changes in surviving neural tissue after stroke, serving as a marker of brain function. The neural correlates of altered brain activity after stroke have been demonstrated by abnormal activation of sensorimotor cortices during task performance, and at rest, using functional magnetic resonance imaging (fMRI). Electroencephalography (EEG) has been used to characterize motor dysfunction in terms of increased cortical amplitude in the sensorimotor regions when performing upper-limb movement, indicating abnormally increased cognitive effort and planning in individuals with stroke. Transcranial magnetic stimulation (TMS) work reveals changes in ipsilesional and contralesional cortical excitability in the sensorimotor cortices. The severity of motor deficits indexed using TMS has been linked to the magnitude of activity imbalance between the sensorimotor cortices.
In this paper we will provide a narrative review of data from studies utilizing DTI, MRS, fMRI, EEG and brain stimulation techniques focusing on TMS and its combination with uni and multi-modal neuroimaging methods to assess recovery after stroke. Approaches that delineate the best measures with which to predict or positively alter outcomes will be highlighted.
The eyes may be the window to the soul, but neuroimages — from DTI to fMRI — can tell us a lot about the brain.