According to sources of the Centers for Disease Control and Prevention, approximately 1.7 million traumatic brain injury (TBI) cases occur annually in the United States. TBI results in 50 thousand deaths, nearly 300 thousand hospitalizations and 2.2 million emergency room visits causing a $76 billion economic burden in direct and indirect costs. Furthermore, it is estimated that over 5 million TBI survivors in the US are struggling with long-term disabilities. And yet, a point-of-care TBI diagnostic has not replaced the non-quantitative cognitive and physiological methods used today. Presently, pupil dilation and the Glasgow Coma Scale (GCS) are clinically used to diagnose TBI. However, GSC presents difficulties in detecting subtle patient changes, oftentimes leaving mild TBI undiagnosed. Given the long-term deficits associated with TBIs, a quantitative method that enables capturing of subtle and changing TBI pathologies is of great interest to the field.
The goal of this research is to work towards a test strip and meter point-of-care technology (similar to the glucose meter) that will quantify several TBI biomarkers in a drop of whole blood simultaneously. It is generally understood that measuring only one blood biomarker may not accurately diagnose TBI, thus this work lays the foundation to develop a multi-analyte approach to detect four promising TBI biomarkers: glial fibrillary acidic protein (GFAP), neuron specific enolase (NSE), S-100β protein, and tumor necrosis factor-α (TNF-α). To achieve this, each biomarker was individually assessed and modeled using sensitive and label-free electrochemical impedance techniques first in purified, then in blood solutions using standard electrochemical electrodes. Next, the biomarkers were individually characterized using novel mesoporous carbon electrode materials to facilitate detection in blood solutions and compared to the commercial standard Nafion coating. Finally, the feasibility of measuring these biomarkers in the same sample simultaneously was explored in purified and blood solutions. This work shows that a handheld TBI blood diagnostic is feasible if the electronics can be miniaturized and large quantity production of these sensors can be achieved.