Raman difference spectroscopy: a non-invasive method for identification of oral squamous cell carcinoma: publisher’s note

Knipfer, Christian; Motz, Johanna; Adler, Werner; Brunner, K.; Gebrekidan, Medhaine Tesfay; Hankel, Robert Fabian; Agaimy, Abbas; Will, Stefan; Braeuer, Andreas; Neukam, Friedrich Wilhelm; Stelzle, Florian

doi:10.1364/boe.6.002675

Cited by 4 publications

(1 citation statement)

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“…A recently published systematic review reported on a large number of biomolecules (e.g., lipids, proteins, DNA, b-carotene, and amino acids, such as phenylalanine, tryptophan, and tyrosine), discriminating cancer from healthy tissue in certain circumstances [ 77 , 78 ]. These biomolecules may provide the opportunity to detect oral cancer at an early stage, reveal malignant transformation or recurrence, or evaluate the resection margin [ 70 , 79 , 80 , 81 ]. A further clinical investigation demonstrated that the water concentration from inside the tumor toward the surgical margin shows a negative gradient, even in bone infiltration of the head neck region [ 66 , 82 ].…”

Section: Spectroscopy For the Intraoperative Assessment Of The Resect...mentioning

confidence: 99%

Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy

Vlocskó,

Piffkó,

Janovszky

2023

Cancers

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In parallel with the increasing number of oncological cases, the need for faster and more efficient diagnostic tools has also appeared. Different diagnostic approaches are available, such as radiological imaging or histological staining methods, but these do not provide adequate information regarding the resection margin, intraoperatively, or are time consuming. The purpose of this review is to summarize the current knowledge on spectrometric diagnostic modalities suitable for intraoperative use, with an emphasis on their relevance in the management of oral cancer. The literature agrees on the sensitivity, specificity, and accuracy of spectrometric diagnostic modalities, but further long-term prospective, multicentric clinical studies are needed, which may standardize the intraoperative assessment of the resection margin and the use of real-time spectroscopic approaches.

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Section: Spectroscopy For the Intraoperative Assessment Of The Resect...mentioning

confidence: 99%

Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy

Vlocskó,

Piffkó,

Janovszky

2023

Cancers

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Raman spectroscopic analysis of the molecular composition of oral cavity squamous cell carcinoma and healthy tongue tissue

Cals

Schut

Caspers

et al. 2018

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A Raman tissue spectrum is a quantitative representation of the overall molecular composition of that tissue. Raman spectra are often used as tissue fingerprints without further interpretation of the specific information that they contain about the tissue's molecular composition. In this study, we analyzed the differences in molecular composition between oral cavity squamous cell carcinoma (OCSCC) and healthy tissue structures in tongue, based on their Raman spectra. A total of 1087 histopathologically annotated spectra (142 OCSCC, 202 surface squamous epithelium, 61 muscle, 65 adipose tissue, 581 connective tissue, 26 gland, and 10 nerve) were obtained from Raman maps of 44 tongue samples from 21 patients. A characteristic, average spectrum of each tissue structure was fitted with a set of 55 pure-compound reference spectra, to define the best library of fit-spectra. Reference spectra represented proteins, lipids, nucleic acids, carbohydrates, amino acids and other miscellaneous molecules. A non-negative least-squares algorithm was used for fitting. Individual spectra per histopathological annotation were then fitted with this selected library in order to determine the molecular composition per tissue structure. The spectral contribution per chemical class was calculated. The results show that all characteristic tissue-type spectra could be fitted with a low residual of <4.82%. The content of carbohydrates, proteins and amino acids was the strongest discriminator between OCSCC and healthy tissue. The combination of carbohydrates, proteins and amino acids was used for a classification model of 'tumor' versus 'healthy tissue'. Validation of this model on an independent dataset showed a specificity of 93% at a sensitivity of 100%.

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Diagnosing the degree of differentiation between types of oral cancer based on extreme deep neural network model and Raman spectroscopy

Chen,

Gong,

Chang

et al. 2024

Spectroscopy Letters

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Raman difference spectroscopy: a non-invasive method for identification of oral squamous cell carcinoma: publisher’s note

Abstract: The author list appeared incorrectly in [Biomed. Opt. Express 5(9), 3252-3265 (2014)]. The author names were corrected online as of January 17, 2015: https://www.osapublishing.org/boe/abstract.cfm?uri=boe-5-9-3252.[This corrects the article on p. 3252 in vol. 5, PMID: 25401036.].

Cited by 4 publications

References 1 publication

Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy

Intraoperative Assessment of Resection Margin in Oral Cancer: The Potential Role of Spectroscopy

Raman spectroscopic analysis of the molecular composition of oral cavity squamous cell carcinoma and healthy tongue tissue

Diagnosing the degree of differentiation between types of oral cancer based on extreme deep neural network model and Raman spectroscopy

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