FTIR-ATR and FT-Raman Spectroscopy  for Biochemical Changes in Oral Tissue

Naurecka, Magdalena Ligia; Sierakowski, Bartosz Michał; Kasprzycka, Wiktoria; Dojs, A; Dojs, Michał; Suszyński, Z.; Kwaśny, M.

doi:10.4236/ajac.2017.83015

Cited by 10 publications

(10 citation statements)

References 22 publications

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“…A number of new cases (275,000) are recorded yearly, mainly in developing countries, due to the population habits to use carcinogens, such as tobacco and betel quid. Oral squamous cell carcinoma (OSCC), identified in all oral cancer cases, develops from visible oral mucous membrane lesions like leukoplakia (OLK) and erythroplakia [137,138,139,140,141,142,143,144,145,146,147,148,149]. Other forms of oral precancer or premalignant lesions are oral submucous fibrosis (OSF), tobacco pouch keratosis, or lichen planus (OLP) [140].…”

Section: Drifting From Molecular To Clinical Practicementioning

confidence: 99%

“…Naurecka et al [145] compared in 2017 the FTIR-ATR and FT-Raman absorption spectra of abnormal (OLK and oral cancer) and normal tissues in the main regions of lipid (2800–3000 cm −1 ), protein (1500–1700 cm −1 ), and nucleic acids (1000–1250 cm −1 ), pointing out the OLK “fingerprint region” is in the range of 900–1800 cm −1 . The FTIR spectrum revealed the following modifications: the absorption peak at 1238 cm −1 is correlated with nucleic acids symmetrical stretching, the phosphate wavenumbers were notable lower compared with that of normal tissue, and the shifting of the 1030 cm −1 band was ascribed to –CH 2 OH vibrations (1024 cm −1 for OLK and 1030 cm −1 for cancer/normal tissue).…”

Section: Drifting From Molecular To Clinical Practicementioning

confidence: 99%

See 1 more Smart Citation

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

et al. 2019

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In the last two decades, Fourier Transform Infrared (FTIR) and Raman spectroscopies turn out to be valuable tools, capable of providing fingerprint-type information on the composition and structural conformation of specific molecular species. Vibrational spectroscopy’s multiple features, namely highly sensitive to changes at the molecular level, noninvasive, nondestructive, reagent-free, and waste-free analysis, illustrate the potential in biomedical field. In light of this, the current work features recent data and major trends in spectroscopic analyses going from in vivo measurements up to ex vivo extracted and processed materials. The ability to offer insights into the structural variations underpinning pathogenesis of diseases could provide a platform for disease diagnosis and therapy effectiveness evaluation as a future standard clinical tool.

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Section: Drifting From Molecular To Clinical Practicementioning

confidence: 99%

Section: Drifting From Molecular To Clinical Practicementioning

confidence: 99%

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

et al. 2019

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“…Bruni et al reported increased DNA, lipid, and collagen levels in OSCC samples [45]. However, their attribution of the 1026 cm −1 band to collagen is debatable, as many other studies assigned the same band to glycogen instead [47][48][49][50]. Sabbatini et al performed vibrational analyses of both epithelial and connective tissues of OSCC at various malignancy grades (G1-G3) and identified potential spectral markers for oral carcinogenesis, including the increase of free glycogen levels, structural alterations in nucleic acids, and a higher amount of RNA, which suggests an increase of the cellular transcriptional activity [51].…”

Section: Discussionmentioning

confidence: 99%

“…[48]. Naurecka et al used the FTIR-ATR technique to study normal, leukoplakia, and cancerous oral tissues and reported spectral differences at amide I at 1650 cm −1 , amide II at 1535 cm −1 , nuclei acids at 1238 cm −1 , and glycogen at 1024-1030 cm −1 [49].…”

Section: Discussionmentioning

confidence: 99%

Oral Cancer Discrimination and Novel Oral Epithelial Dysplasia Stratification Using FTIR Imaging and Machine Learning

2021

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The Fourier transform infrared (FTIR) imaging technique was used in a transmission model for the evaluation of twelve oral hyperkeratosis (HK), eleven oral epithelial dysplasia (OED), and eleven oral squamous cell carcinoma (OSCC) biopsy samples in the fingerprint region of 1800–950 cm−1. A series of 100 µm × 100 µm FTIR imaging areas were defined in each sample section in reference to the hematoxylin and eosin staining image of an adjacent section of the same sample. After outlier removal, signal preprocessing, and cluster analysis, a representative spectrum was generated for only the epithelial tissue in each area. Two representative spectra were selected from each sample to reflect intra-sample heterogeneity, which resulted in a total of 68 representative spectra from 34 samples for further analysis. Exploratory analyses using Principal component analysis and hierarchical cluster analysis showed good separation between the HK and OSCC spectra and overlaps of OED spectra with either HK or OSCC spectra. Three machine learning discriminant models based on partial least squares discriminant analysis (PLSDA), support vector machines discriminant analysis (SVMDA), and extreme gradient boosting discriminant analysis (XGBDA) were trained using 46 representative spectra from 12 HK and 11 OSCC samples. The PLSDA model achieved 100% sensitivity and 100% specificity, while both SVM and XGBDA models generated 95% sensitivity and 96% specificity, respectively. The PLSDA discriminant model was further used to classify the 11 OED samples into HK-grade (6), OSCC-grade (4), or borderline case (1) based on their FTIR spectral similarity to either HK or OSCC cases, providing a potential risk stratification strategy for the precancerous OED samples. The results of the current study support the application of the FTIR-machine learning technique in early oral cancer detection.

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“…Naurecka et al investigated the differences of FTIR-ATR and FT-Raman spectroscopy among leukoplakia, oral cancer, and normal tissues. FTIR spectral differences were observed at 1238 cm −1 (related to phosphate stretching in nucleic acids) between normal and cancer tissues and at 1030 cm −1 (related to –CH 2 OH vibration in glycogen) among normal, leucoplakia, and cancer tissues [ 94 ].…”

Section: Ftir For Oral Cancer Diagnosismentioning

confidence: 99%

Fourier Transform Infrared Spectroscopy in Oral Cancer Diagnosis

Wang

2021

IJMS

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Oral cancer is one of the most common cancers worldwide. Despite easy access to the oral cavity and significant advances in treatment, the morbidity and mortality rates for oral cancer patients are still very high, mainly due to late-stage diagnosis when treatment is less successful. Oral cancer has also been found to be the most expensive cancer to treat in the United States. Early diagnosis of oral cancer can significantly improve patient survival rate and reduce medical costs. There is an urgent unmet need for an accurate and sensitive molecular-based diagnostic tool for early oral cancer detection. Fourier transform infrared spectroscopy has gained increasing attention in cancer research due to its ability to elucidate qualitative and quantitative information of biochemical content and molecular-level structural changes in complex biological systems. The diagnosis of a disease is based on biochemical changes underlying the disease pathology rather than morphological changes of the tissue. It is a versatile method that can work with tissues, cells, or body fluids. In this review article, we aim to summarize the studies of infrared spectroscopy in oral cancer research and detection. It provides early evidence to support the potential application of infrared spectroscopy as a diagnostic tool for oral potentially malignant and malignant lesions. The challenges and opportunities in clinical translation are also discussed.

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FTIR-ATR and FT-Raman Spectroscopy for Biochemical Changes in Oral Tissue

Cited by 10 publications

References 22 publications

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

Oral Cancer Discrimination and Novel Oral Epithelial Dysplasia Stratification Using FTIR Imaging and Machine Learning

Fourier Transform Infrared Spectroscopy in Oral Cancer Diagnosis

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