Raman Spectroscopy as a Screening Method
Raman spectroscopy has the potential to be implemented in screening tests based on the analysis of bodily fluids due to the monitoring of disease-caused changes in their biochemical composition. The spectral analysis of urine from mice with different disorders illustrated a very accurate diagnosis of diseases directly connected with urine formation and pointed to respiratory disorders.
By Olga Žukovskaja // Thomas W. Bocklitz // Karina Weber // Jürgen Popp
The objective of medical screening is to detect disease in its early stages and thereby increase the chances of successful treatment. Based on criteria provided by the World Health Organization, screening tests should be easy to perform and interpret, should be cost effective for the healthcare system and, of course, should be highly accurate. For this purpose, analysis of bodily fluids is particularly attractive because they provide different biochemical information which may point to an emerging disease. Thus, the development of an easy and cheap technique that is able to register this information would be advantageous for clinical applications. In this context, Raman spectroscopy shows significant diagnostic promise because it provides a snapshot of the biomolecular composition of the sample and its variations.
To investigate the potential of Raman spectroscopy for screening purposes, urine samples were considered, and two groups of animal disease models were included. The first group included diseases in direct connection to urine formation (e.g., distal renal tubular acidosis and reversible nephrogenic diabetes insipidus), while the second group considered respiratory diseases which possess no direct connection to urine formation (e.g., asthma and aspergillosis). To build a diagnostic model, Raman spectra of urine from healthy and sick mice were obtained and analyzed using principal component analysis followed by linear discriminant analysis. Reliability of the model was evaluated using a leave-one-mouse-out cross-validation approach.
In kidney disorders, a 100% classification was achieved not only for distinguishing between healthy and sick mice but also for identifying the exact kidney disease of the two included in this model. This shows that urine is very informative for the diseases with a direct connection to its formation. Raman spectroscopy is a good technique for “reading out” this information. Considering respiratory tract diseases, which do not have a direct influence on urine composition, much smaller differences between control and sick mice were registered; however, Raman spectroscopy still showed promise for diagnosis. To detect allergic asthma, an accuracy rate of 77.27% was achieved. However, it is worth noting that the false negative results that occurred could have been caused by the organism’s capacity for self-regeneration. This is because the urine samples that were included were collected on different days after inducing allergic asthma. After analyzing the aspergillosis model, a sensitivity of 50% and a specificity of 90% were achieved. More detailed clinical data revealed that some of the infected mice did not develop an infection, which could lead to misclassifications. After rebuilding the model with only mice diagnosed with acute aspergillosis, the identification accuracy reached 100%.
This shows that urine-based Raman spectroscopy not only has the potential to be a fast screening test for diagnosing any urinary tract dysfunctions but also bears some potential for the screening of diseases not directly connected with urine formation.
Funded by BMBF