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Stroke prevention and early treatment to ameliorate long-term disability are the main focus of stroke medicine, but despite advancements in these areas, approximately 6 million stroke survivors today are living with disability.1 Stroke researchers have responded by honing ways to predict which patients will respond best to which rehabilitation treatments.
“That is where we are now. We know that most repairs happen in the first three to six months. We also know that there is no outer limit for repair in some people,” said Jill Stewart, PhD, assistant professor of physical therapy and exercise science at the University of South Carolina in Columbia. “Being able to predict and measure response to rehabilitation will help us learn what works best for each patient, how often to use the therapy, and when therapy has hit its limit. That will improve outcomes.”
“Predictors tell us who is likely to respond. Biomarkers tell us how effective the treatment is. Together they tell us what we need to know,” said Steven C. Cramer, MD, professor of neurology at the University of California Irvine School of Medicine. “Some treatments are uniform. Flu shots work about the same for everybody. But stroke rehabilitation is at the bottom of the uniformity ladder. It is far from one size fits all.”
Another reason better predictors of recovery are needed is to better allocate resources. One-on-one physical therapy and occupational therapy are labor intensive, robotic therapies are expensive, and new technologies may be even more expensive. Knowing where and when to use limited resources will maximize their benefits.1
What the Latest Research Tells Us
Cramer and colleagues most recently analyzed stroke recovery in 29 patients with upper extremity paralysis three to six months after stroke. Before starting three weeks of standardized upper extremity robotic therapy, patients underwent a battery of neurologic tests to see which findings would best predict response to therapy. The study will be published in the Annals of Neurology.2
“The best predictors were a percent of corticospinal tract injury and degree of cortical connectivity. Connectivity is a measure of the way different parts of the brain talk to each other. In simple terms, it’s all about function and injury. Each has good predictive value, but taken together they have better predictive value,” Cramer said.
In the study, patients who had greater than 63% loss of corticospinal tract were unable to benefit from the therapy.2 “The corticospinal tract connects the motor cortex to muscle. There needs to be enough connection to effect change. You either have enough or you don’t,” Stewart said.
“It’s safe to say that the bedside exam is still the best predictor, but neurological measurements and imaging also have a front row seat at the table,” Cramer said.
The best tools for predicting improved gait velocity were functional MRI (fMRI) and a Fugl-Meyer score (a clinical assessment system) of the leg, according to findings from a 2014 Stroke study that examined baseline multimodal testing on patients with hemiparesis one to 12 months after stroke.3
Baseline motor-evoked potential (MEP) amplitude was the most effective predictor of functional gain before an eight-week course of robotic exoskeleton training for the arm after stroke, findings from a separate 2014 Neurorehabilitation & Neural Repair study indicate.4
“The best tools right now are transcranial MEP and fMRI. Also important are enhanced MRI technologies that show both gray matter and white matter,” Stewart said.
Future Rehabilitation Technologies: Robotics, Stem Cells, and Brain-Computer Interfaces
Robotic technologies are already here and may eventually be laborsaving devices for therapists. In the future, robotic therapies may be used primarily at home, or patients may be able to go to a robotic gym and be supervised by one therapist.1
But these machines can cost hundreds of thousands of dollars, and so far have not been shown to be superior to dose-matched, human-delivered therapy.
“Right now robots are clunky and expensive. They will get better, but they will have to prove to be affordable, safe, and practical before they can be used more widely,” Cramer said.
As for stem cells, it’s known that they have the ability to migrate to the site of brain injury. Preclinical studies suggest they can also promote neurogenesis, angiogenesis, and synapse formation.
What researchers still need to determine is which stem cells to use, the best routes of administration, and the optimal time to treat. “We are very early in stem cell technology for stroke recovery. Initial results are astounding, but we have a whole lot to learn yet,” Cramer said.
As for patients with more severe disabilities, including paralysis, brain-computer interfacing can allow for movement of robotic limbs via cortical activity.
Using fMRI to precisely map motor-related cortical activity, researchers place electrodes in the brain that are stimulated by imagined movement. Patients have been able to make a state-of-the-art motorized prosthetic limb shake hands, stack cones, and perform a wide variety of other tasks.1
In the future, new, high-tech innovations may be combined for best results. A person who suffers a stroke may be treated with stem cells, while brain-computer interfacing is used to trigger the stem cells. At the same time, robotic technology may be used to maximize neural plasticity and reorganization.1
Low-Tech Can Also Be Effective
Some innovations are less technical, like adding techniques based on the imagination. In a study that both Stewart and Cramer worked on, patients were asked to move a stroke-paralyzed arm on visual cue. The patients were then asked to do the movements while they imagined opening and closing a door. Adding imagery to movement lit up additional brain regions, fMRI findings showed.5
“Don’t forget about low-tech options,” Steward said. Transcranial direct stimulation during exercise — a simple, safe, and painless procedure — can help maximize daily exercise, and many physical therapists are incorporating this technique into their practice.
“There are lots of possibilities for the future, but they all have some big safety and financial obstacles to overcome. Will they work better than what we have now and will they be cost effective? Time will tell,” Stewart said.
Chris Iliades, MD, is a full-time freelance writer based in Cape Cod, Massachusetts. This article was medically reviewed by Pat F. Bass III, MD, MS, MPH.
References
- Boninger ML, Wechsler LR, Stein J. Robotics, stem cells, and brain-computer interfaces in rehabilitation and recovery from stroke: updates and advances. Am J Phys Med Rehabil. 2014;93(11 Suppl 3):S145-54.
- Neural function, injury, and stroke subtype predict treatment gains after stroke, Annals of Neurology. Author Manuscript.
- Burke E, Dobkin BH, Noser EA, Enney LA, Cramer SC. Predictors and biomarkers of treatment gains in a clinical stroke trial targeting the lower extremity. Stroke. 2014;45(8):2379-84.
- Milot MH, Spencer SJ, Chan V, et al. Corticospinal excitability as a predictor of functional gains at the affected upper limb following robotic training in chronic stroke survivors. Neurorehabil Neural Repair. 2014;28(9):819-27.
- Dodakian L, Stewart JC, Cramer SC. Motor imagery during movement activates the brain more than movement alone after stroke: A pilot study. J Rehabil Med. 2014;46(9):843-8.
