Abstract
We developed a diagnostic tool to differentiate between endophthalmitis and uveitis using Raman spectroscopy. Twenty-two New Zealand rabbits with endophthalmitis induced by Staphylococcus aureus (10 animals), noninfectious uveitis induced by lipopolysaccharide from Escherichia coli (10 animals) and controls (two animals) were analyzed. Twenty-four hours after the eyes were inoculated, iris tissue was dissected and subjected to dispersive Raman spectroscopy using an excitation source at 830 nm and a spectrograph/CCD camera to detect a Raman signal with an integration time of 50 s. With the collected spectra of endophthalmitis and uveitis, we developed a routine to classify spectra in each specimen using principal components analysis, using a leave-one-out cross-validation procedure. The mean Raman spectra of tissues with uveitis and endophthalmitis showed several bands in the region of 800–1800 cm −1, which have been attributed to nucleic acids, amino acids, proteins, and lipids. The bands at 1004, 1339, and 1555 cm −1 differed significantly ( t-test, p < 0.05) between diseases. The principal components PC3 and PC4 differed significantly (ANOVA, p < 0.05) for the two tissue types, indicating that these PCs can be used to discriminate between the two diseases using Mahalanobis distance as a discriminator. This technique is useful for differentiating the spectral bands of uveitis and endophthalmitis, and the diagnostic model showed sensitivity of 89%, specificity of 100%, and accuracy of 92% using the leave-one-out cross-validation procedure. These results may be clinically relevant for differentiating endophthalmitis from uveitis, and this approach may become a noninvasive method to optimize the diagnosis of inflammatory and infectious vitreoretinal diseases.
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