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Creating a device that can detect and image Lateral Flow Assays paired with a software that can model a specified biomarker time series and quantifiably diagnose TBI severity.
Creating a device that can detect and image Lateral Flow Assays paired with a software that can model a specified biomarker time series and quantifiably diagnose TBI severity.
Hardware
Semi Portable, Short Wavelength Device
Finalized prototype that, due to limited near infrared LEDs, proved capable of imaging short wavelength fluorescence. The two main modes are a single image immediately after exposure and long term capture.
Software
Modeling GFAP Time Series
Using parameter estimation and modeling the increasing intensity of the analyte on the Lateral Flow Assay test strip over time, software that starts from a short video can then be analyzed and result in the figure on the left, which display the concentration of GFAP over time.
Optimizing the Results
The figure on the left illustrates how using a time series intensity spectra over time with the developed software has drastically improved the estimated curve of the intensity in comparison to the initial estimate that was found from previous methods of analysis. This improvement was made using parameter estimation and will be further improved with a data base that can train the data to better estimate LFA intensity over time.
Predictive TBI Diagnosis
Development of the following dynamics for TBI related biomarkers. The biomarkers of interest are GFAP and UCH-L1, a GFAP breakdown product that inhibits and counteracts GFAP concentrations in the bloodstream.
The figure on the right displayes the various thresholds along with their assoociated minimum and maximum concentrations differentiating TBI-negative patients from mild/moderate TBI cases (MMTBI) and severe TBI cases (STBI).
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