After suffering a traumatic brain injury, patients are often placed in a coma, which is induced with anaesthesia drugs, and can last for days. During that time, nurses must closely monitor patients to make sure they are at the right level of sedation – a process which Emery Brown describes as “totally inefficient.”
Brown, Professor of Medical Engineering in MIT’s Institute for Medical Engineering and Science, who is also an anaesthetist at Massachusetts General Hospital (MGH), and colleagues have now developed a computerised system that can track patients’ brain activity and automatically adjust drug dosages to maintain the correct state. They have tested the system – which could also help patients who suffer from severe epileptic seizures – in rats and are now planning to begin human trials.
Maryam Shanechi, a former MIT graduate student, now an assistant professor at Cornell University, is the lead author of the paper describing the computerised system in the journal PLOS Computational Biology.
Tracking the brain
Brown et al have previously analysed the electrical waves produced by the brain in different states of activity. Each state – awake, asleep, sedated, anaesthetised and so on – has a distinctive electroencephalogram (EEG) pattern.
When patients are in a medically induced coma, the brain is quiet for up to several seconds at a time, punctuated by short bursts of activity. This pattern, known as burst suppression, allows the brain to conserve vital energy during times of trauma.
With an induced coma, the doctor or nurse controlling the infusion of anaesthesia drugs tries to aim for a particular number of ‘bursts per screen’ as the EEG pattern streams across the monitor. This pattern has to be maintained for hours or days at a time, which Brown says is the perfect time for an “autopilot.”
To achieve automated control, Brown and colleagues built a brain-machine interface – a direct communication pathway between the brain and an external device that typically assists human cognitive, sensory or motor functions. In this case, the device – an EEG system, a drug-infusion pump, a computer and a control algorithm – uses propofol to maintain the brain at a target level of burst suppression.
The system is a feedback loop; the control algorithm interprets the rat’s EEG, calculates how much drug is in the brain, and adjusts the amount of propofol infused into the animal second by second.
The controller can increase the depth of a coma almost instantaneously, which would be impossible for a human to do accurately by hand. The system could also be programmed to bring a patient out of an induced coma periodically so doctors could perform neurological tests, Brown says.
Sydney Cash, an associate professor of neurology at Harvard Medical School is also in favour:
“Much of what we do in medicine is making educated guesses as to what’s best for the patient at any given time,” says Cash, who was not part of the research team. “This approach introduces a methodology where doctors and nurses don’t need to guess, but can rely on a computer to figure out – in much more detail and in a time-efficient fashion – how much drug to give.”
Monitoring anaesthesia
Brown believes that this approach could easily be extended to control other brain states, including general anaesthesia, because each level of brain activity has its own distinctive EEG signature.
“If you can quantitatively analyse each state’s signature in real time and you have some notion of how the drug moves through the brain to generate those states, then you can build a controller.”
There are currently no devices approved by the Food and Drug Administration (FDA) to control general anaesthesia or induced coma, but there is a device available in Europe and South America, based on an algorithm that uses the patient’s EEG to compute an index on a 100-point scale. However, that system keeps the patient’s brain activity within a very wide range and does not allow for precise control, Brown says.
The MIT and MGH researchers are now preparing applications to the FDA to test the controller in humans.