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Clinical Implementation of fMRI and EEG to Detect Cognitive Motor Dissociation: Lessons Learned in an Acute Care
Yelena G Bodien1, Matteo Fecchio1, Holly J Freeman1
1Center for Neurotechnology and Neurorecovery (YGB, MF, HJF, WRS, AM, PKL, DF, LRH, SSC, MJY, BLE), Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA; Department of Physical Medicine and Rehabilitation (YGB), Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA; Geisel School of Medicine at Dartmouth Medical School College (WRS), Hanover, NH; Athinoula A. Martinos Center for Biomedical Imaging (JEK, BLE), Massachusetts General Hospital, Charlestown, MA; Department of Radiology (JEK, JHH, PWS, OR), Massachusetts General Hospital and Harvard Medical School, Boston, MA; Department of Neurology (DF), Hospital of the University of Pennsylvania, Philadelphia, PA; and Departments of Neurology (JC) and Medicine (ER), Massachusetts General Hospital and Harvard Medical School, Boston, MA.
Background:
Cognitive motor dissociation (CMD) occurs when patients with severe brain injury follow commands on task-based functional MRI or EEG assessment despite demonstrating no behavioral evidence of language function. Recognizing the value of identifying patients with CMD, evidence-based guidelines published in the United States and Europe now recommend that these assessments are conducted as part of clinical care for select patients.
Recent Findings:
We describe our institutionally supported approach for clinical assessment of CMD and report lessons learned so that other centers can more easily implement these evaluations. Among the key lessons are the need to consider ethical implications of CMD assessment; establish standardized local protocols for patient selection, data acquisition, analysis, and interpretation; and develop effective strategies for communication of test results.
Implications For Practice:
Independent validation of methods to assess CMD is not available. Our approach for clinical CMD assessment is intended to be flexible, allowing for iterative improvements as the evidence base grows.
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