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- Title
Saliva Based Diagnostic Prediction of Oral Squamous Cell Carcinoma using FTIR Spectroscopy.
- Authors
Shree, Priya; Aggarwal, Yogendra; Kumar, Manish; Majhee, Lakhan; Singh, Narendra Nath; Prakash, Om; Chandra, Akhilesh; Mahuli, Simpy Amit; Shamsi, Shoa; Rai, Arpita
- Abstract
Oral cancer ranks as the sixth most prevalent form of cancer worldwide, presenting a significant public health concern. According to the World Health Organization (WHO), within a 5-year period following diagnosis, the mortality rate among oral cancer patients of all stages stands at 45%. In this study, a total of 60 patients divided into 2 groups were recruited. Group A included 30 histo-pathologically confirmed OSCC patients and Group B included 30 healthy controls. A standardized procedure was followed to collect saliva samples. FTIR spectroscopy was done for all the saliva samples collected from both Group A and B. An IR Prestige-21 (Shimadzu Corp, Japan) spectrometer was used to record IR spectra in the 40–4000 cm−1 range SVM classifier was applied in the classification of disease state from normal subjects using FTIR data. The peaks were identified at wave no 1180 cm−1, 1230 cm−1, 1340 cm−1, 1360 cm−1, 1420 cm−1, 1460 cm−1, 1500 cm−1, 1540 cm−1, 1560 cm−1, and 1637 cm−1. The observed results of SVM demonstrated the accuracy of 91.66% in the classification of Cancer tissues from the normal subjects with sensitivity of 83.33% while specificity and precision of 100.0%. The development of oral cancer leads to noticeable alterations in the secondary structure of proteins. These findings emphasize the promising use of ATR-FTIR platforms in conjunction with machine learning as a reliable, non-invasive, reagent-free, and highly sensitive method for screening and monitoring individuals with oral cancer.
- Subjects
WORLD Health Organization; FOURIER transform infrared spectroscopy; SQUAMOUS cell carcinoma; NOSOLOGY; SALIVA; ORAL cancer
- Publication
Indian Journal of Otolaryngology & Head & Neck Surgery, 2024, Vol 76, Issue 3, p2282
- ISSN
2231-3796
- Publication type
Article
- DOI
10.1007/s12070-023-04294-z