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Researchers have developed an optical fiber sensor patient monitoring system AI-enabled to examine multiple biomarkers simultaneously after an acquired or traumatic injury to the brain. 

Results from tests on animal brain tissues propose it could help clinicians to monitor disease progression easily and patients' response to treatment than is presently possible.

Traumatic brain injury (TBI) is one of the leading cause of death and disability worldwide. A silent epidemic that can result in long term difficulties with concentration, problem-solving, and memory.

TBIs need to be constantly monitored during treatment. And that is why intracranial probes are used in neurocritical care settings to monitor key indicators of injury progression (biomarkers), such as the brain's oxygen and pressure.

Some of these probes can measure just one biomarker at a time, while others can monitor several biomarkers. This involves several tubes to be inserted into the brain, which risks causing additional tissue infections or damage.

The new device is known to combine the ability to monitor four biomarkers together with machine learning algorithms. It uses previous data to guess biomarker concentrations based on obtained data in real time. If optimized and verified for use in humans, the device could aid hospitals in monitoring TBI more efficiently.

Promising results show accurate biomarker monitoring and accurate predictions of injury progression which, after further development, could help clinicians monitor patients' brain health and response to treatment."

The device is designed comprising of a flexible silica-based optical fibre that is introduced into brain tissue to monitor the cerebrospinal fluid (CSF) around the spinal cord and brain. At the tip of the fibre are attached four detecting films that concurrently and continuously measure levels of one biomarker within the CSF; namely pH, dissolved oxygen, temperature, and glucose. The films are enclosed with a black sheath to decrease background noise and improve data precision.

To check the device, the scientists continuously observed levels of these biomarkers in a lamb brain under different states. The lamb brain had not suffered TBI and was suspended in artificial CSF that researchers adjusted to mimic the chemistry of the brain during mild and severe TBI.

First, biomarkers were measured in healthy CSF before measuring them in mild and then severe TBI states. To mimic the setting when TBI patients get better from medical treatments, they then measured them again in a mild TBI state.

The device collects a breadth of medical data that's only currently attainable with many different sensors. The optical fiber sensor device combined with artificial intelligence reduces cross-talks.

Its high performance included high sensitivity, stability, selectivity, toughness, and biocompatibility, 

The machine learning models could precisely predict biomarker concentrations in real-time using readouts from a collection of earlier measurements. It was also able to recognize the transition between the diverse stages of TBI simulated by researchers.

The researchers continue to advance the sensor by using optical bundles to develop a range of testable biomarkers, such as neurotransmitters and inflammatory agents. They are also evolving a more complex machine learning system to make the most of the data and predictive mechanisms available. They note that more tests using living animals are required to evaluate the whole body's response to the probe, and to try the ability of fiber sensors in real-case applications.