Near‐infrared Raman spectroscopic characterization of salivary metabolites in the discrimination of normal from oral premalignant and malignant conditions

Abstract

In the present study, Raman spectroscopy has been employed in the discrimination of the saliva of normal subjects from patients with oral submucous fibrosis and oral squamous cell carcinomaat 785-nm excitation. From the spectral signatures, prominent difference between normal and abnormal group because of variations in metabolic and pathological conditions of the subjects was observed. Principal component analysis coupled with linear discriminant analysis yielded a diagnostic sensitivity of 96.4 and 93.8% and a specificity of 70.2 and 95.7% in the classification of normal from premalignant and normal from malignant, respectively, confirming the efficacy of Raman spectroscopy in the classification of normal and oral abnormalities.

Saliva Preparation Method Exploration for ATR-FTIR Spectroscopy: Towards Bio-fluid Based Disease Diagnosis

“…Collected by spit method, centrifuged at 4000 rpm for 20 minutes, and supernatant used, 6. Gargling with water for 15 minutes, secreted into container, and used directly 26 .…”

“…Previous FT-IR study of saliva exosome from oral cancer patients showed a difference in nucleic acids (1072 cm -1 ), proteins (1543 cm -1 ), and lipids (2924 and 2854 cm -1 ) compared to healthy subjects 28 . Raman spectroscopy, a technique complementary to FT-IR, showed a major difference in proteins (specifically Amide III), and to less extent in carbohydrates and amino acids, compared to healthy 22,23,26 . Raman spectroscopy of saliva from premalignant oral lesions differs from healthy in protein, nucleic acid, and amino acid groups 22,26 .…”

Simultaneous isolation and label‐free identification of bacteria using contactless dielectrophoresis and Raman spectroscopy

“…Raman spectroscopy has previously been applied directly to clinical samples such as saliva, urine, blood, and tissues to accurately identify diseased states. For example, researchers have used urine [40] or saliva samples [41] to distinguish between patients with and without oral cancer. Using spatially offset Raman spectroscopy, Keller et al [42] accurately (94-100%) identified cancer tissues from breast tissue samples.…”

Recent advances in linear and non‐linear Raman spectroscopy. Part XI

“…Rekha and co‐workers used near‐infrared Raman spectroscopic to characterize salivary metabolites in the discrimination of normal from oral premalignant and malignant conditions. Principal component analysis coupled with linear discriminant analysis yielded a diagnostic sensitivity of 96.4% and 93.8% and a specificity of 70.2% and 95.7% in the classification of normal from premalignant and normal from malignant, respectively, confirming the efficacy of Raman spectroscopy in the classification of normal and oral abnormalities . Sowoidnich and co‐workers studied photon migration of Raman signal in bone as measured with spatially offset Raman spectroscopy.…”

“…Principal component analysis coupled with linear discriminant analysis yielded a diagnostic sensitivity of 96.4% and 93.8% and a specificity of 70.2% and 95.7% in the classification of normal from premalignant and normal from malignant, respectively, confirming the efficacy of Raman spectroscopy in the classification of normal and oral abnormalities. [72] Sowoidnich and co-workers studied photon migration of Raman signal in bone as measured with spatially offset Raman spectroscopy. Their study seeks to develop our general understanding of the sampling depths of SORS in bone specimens as a function of the applied spatial offset.…”