Isaac D. Juárez, Aidan P. Holman, Elizabeth J. Horn, Artem S. Rogovskyy, Dmitry Kurouski
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External Validation of Raman Spectroscopy for Lyme Disease Diagnostics
Lyme disease (LD), caused by Borreliella burgdorferi, is the most common tick-borne illness in the United States, yet early-stage diagnosis remains challenging due to the limitations of current serological diagnostics. Raman spectroscopy (RS), paired with partial least squares discriminant analysis (PLS-DA), showed promise as an alternative diagnostic tool. Using RS, we analyzed 107 coded human blood samples (42 LD-positive and 65 LD-negative) obtained from the Lyme Disease Biobank. PLS-DA models showed nearly perfect internal validation performance with a sensitivity and specificity of 97.1% and 100.0%, respectively, indicating robust predictive capabilities. External validation of the developed chemometrics model with 80/20 training/validation split of all spectra gave true positive rates of 92.7% and 87.3% for serological positive and negative spectra, respectively. These findings highlight the potential of RS as a rapid and noninvasive diagnostic platform for LD, particularly when integrated with machine learning.
期刊介绍:
The first international journal dedicated to publishing reviews and original articles from this exciting field, the Journal of Biophotonics covers the broad range of research on interactions between light and biological material. The journal offers a platform where the physicist communicates with the biologist and where the clinical practitioner learns about the latest tools for the diagnosis of diseases. As such, the journal is highly interdisciplinary, publishing cutting edge research in the fields of life sciences, medicine, physics, chemistry, and engineering. The coverage extends from fundamental research to specific developments, while also including the latest applications.