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Raman spectroscopy for differential diagnosis of endophthalmitis and uveitis in rabbit iris in vitro
Authors:Eglas Emanuel Rossi  Antonio Luiz Barbosa Pinheiro  Flávio Aimbire  Marcos Tadeu Tavares Pacheco
Institution:a Health Sciences Center - CCS, Universidade Comunitária Regional de Chapecó - UNOCHAPECÓ, Chapecó, SC 89809-000, Brazil
b Biomedical Engineering Center, Universidade Camilo Castelo Branco - UNICASTELO, São José dos Campos, SP 12247-004, Brazil
c School of Dentistry, Universidade Federal da Bahia - UFBA, Salvador, BA 40110-150, Brazil
d Rehabilitation Sciences Master's Program, Nove de Julho University - UNINOVE, São Paulo, SP 05001-100, Brazil
e Ophthalmology Department, Vitreoretinal Surgery Unit, Universidade Federal de São Paulo - UNIFESP, São Paulo, SP 04023-062, Brazil
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.
Keywords:Raman spectroscopy  iris  endophthalmitis  uveitis  differential diagnosis  principal components analysis  Mahalanobis distance  discriminant analysis
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