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Fiber-Optic Raman Spectroscopy with Nature-Inspired Genetic Algorithms Enhances Real-Time in Vivo Detection and Diagnosis of Nasopharyngeal Carcinoma

Žuvela, Petar, Lin, Kan, Shu, Chi, Zheng, Wei, Lim, Chwee Ming, Huang, Zhiwei
Analytical chemistry 2019 v.91 no.13 pp. 8101-8108
Raman spectroscopy, algorithms, carcinoma, discriminant analysis, endoscopy, fiber optics, lipids, models, nucleic acids, patients, phenylalanine, porphyrins, proteins, tryptophan
Raman spectroscopy is an optical vibrational spectroscopic technique capable of probing specific biochemical structures and conformation of tissue and cells in biomedical systems. This work aims to assess the clinical utility of a fiber-optic Raman spectroscopy with nature-inspired genetic algorithms for enhancing in vivo detection and diagnosis of nasopharyngeal carcinoma (NPC) patients. The Raman diagnostic platform is developed based on simultaneous fingerprint (FP) and high-wavenumber (HW) fiber-optic Raman endoscopy associated with genetic algorithms-partial least-squares-linear discriminant analysis (GA-PLS-LDA). A total of 2126 in vivo FP/HW Raman spectra (598 NPC, 1528 normal) acquired from 113 tissue sites of 14 NPC patients and 48 healthy subjects during nasopharyngeal endoscopic examinations. Distinct Raman peaks have been identified (853 cm–¹ - proteins, 1209 cm–¹ - phenylalanine, 1265 cm–¹ - proteins, 1335 cm–¹ - proteins and nucleic acids, 1554 cm–¹ - tryptophan, porphyrin, 2885 cm–¹ - lipids, 2940 cm–¹ - proteins, 3009 cm–¹ - lipids, and 3250 cm–¹ - water) that are related to the significant biochemical changes (p < 1 × 10–⁵) in NPC compared to normal tissue. Raman diagnostic performance is evaluated through the leave-one-object (tissue site)-out cross-validation (LOOCV) method. A statistically significant GA-PLS-LDA model (p < 1 × 10–⁵) on FP/HW Raman yields a CV diagnostic accuracy of 98.23% (111/113), sensitivity of 93.33% (28/30), and specificity of 100% (83/83) for NPC classification. This work demonstrates that the fiber-optic FP/HW Raman diagnostic platform developed has great promise for improving real-time in vivo detection and diagnosis of NPC at the molecular level during clinical nasopharyngeal endoscopy.