Incidence and survival trends of lip, intra-oral cavity and tongue base cancers in south-east England

Electrical impedance tomography: a potential tool for intraoperative imaging of the tongue base

The presence of a tumor in the tongue is a pathology that requires surgical intervention from a certain stage. This type of surgery is difficult to perform because of the limited space available around the base of the tongue for the insertion of surgical tools. During the procedure, the surgeon has to stretch and then fix the tongue firmly in order to optimize the available space and prevent tissue movement. As a result, the preoperative images of the inside of the tongue no longer give a reliable indication of the position and shape of the cancerous tissue due to the deformation of the overall tissue in the area. Thus, new images are needed during the operation, but are very difficult to obtain using conventional techniques due to the presence of surgical tools. Electrical Impedance Tomography (EIT) is an imaging technique that maps the resistivity or difference of resistivity of biological tissues from electrical signals. The small size of the electrodes makes it a potentially interesting tool to obtain intraoperative images of the inside of the tongue. In this paper, the possibility of using EIT for this purpose is investigated. A detection method is proposed, including an original configuration of the electrodes, consistent with the anatomical specificities of the tongue. The proposed method is studied in simulation and then a proof of concept is obtained experimentally on a 3D printed test tank filled with saline solution and plant fibres.

Diverging incidence trends of oral tongue cancer compared to other head and neck cancers in young adults in France

While head and neck cancer incidence decreased worldwide due to reduced tobacco and alcohol consumption, oral tongue cancer (OTC) incidence has been reported to be increasing in several countries. Our study examines the incidence trends of OTC in France from 1990 to 2018, globally and by age; and compares the incidence trends with the evolution of the incidence of other human papilloma virus-unrelated head and neck squamous cell carcinoma, that is, cancers of the remaining subsites of the oral cavity (RSOCC) and laryngeal cancers for the period 1990 to 2018. World age-standardized incidence rates of oral tongue cancers (C02), cancers of the remaining subsites of the oral cavity (RSOCC, C03-06) and laryngeal cancers (C32) were estimated using the French National Network of Cancer Registries for the period 1990 to 2018. Trends in national incidence rates were estimated from a mixed-effect Poisson model including age and year effects using penalized splines and a district-random effect. In women aged 30 and 40, a significant increase in OTC incidence was observed, while ROSCC showed a nonsignificant incidence decrease. In young men aged 25, a marginally significant increase of OTC incidence years was observed, while incidence rates of RSOCC significantly declined. The results suggest a tendency towards diverging incidence trends for OTC compared to RSOCC and laryngeal cancer in young adults. The observed trends may reflect changes in underlying exposures or emerging exposures not yet identified, and stress the need to further investigate the etiology of oral tongue cancers.

Role of Twist and Podoplanin in Partial Epithelial-Mesenchymal Transition in Oral Squamous Cell Carcinoma

The aim of this study was to perform a comparative analysis of podoplanin (PDPN) and Twist immunoexpressions in lower lip and oral tongue squamous cell carcinomas (LLSCC and OTSCC, respectively). PDPN and Twist immunoexpressions were semi-quantitatively evaluated by analyzing the invasion front, the compressive areas, the large islands and nests and dissociated cells of the chosen carcinomas. Their statistical associations and correlations with clinical-pathological characteristics were verified by the Mann-Whitney and Spearman's test. Twist expression was low in both carcinomas, with <25% labeling on the invasive front. Significant differences were observed for LLSCC (p=0.032) and OTSCC (p=0.025) regarding PDPN immunoexpression in relation to the worst invasion patterns determined by a histological malignancy gradation system. Statistically significant negative correlations between PDPN membrane expression and general (r=-0.356, p=0.024) and cytoplasmic Twist expressions (r=-0.336; p=0.034) in LLSCC were also observed. Twist and PDPN are suggested to be associated to a more aggressive invasion pattern in both LLSCC and OTSCC cases but not related to the different biological behaviors on these anatomical sites. Also, it was seen that PDPN membrane expression is inversely related to general and cytoplasmic Twist expression in LLSCC cases.

Risk of second primary cancer in oral squamous cell carcinoma

BACKGROUND

The incidence and survival of oral squamous cell carcinoma (OSCC) patients have increased in recent years. Understanding their long-term survival aspects is essential for optimal treatment and follow-up planning. Almost one in five cancers diagnosed occurs nowadays in individuals with a previous diagnosis of cancer.

METHODS

Patients diagnosed with primary OSCC during 1953-2015 were retrieved from the Finnish Cancer Registry. Both standardized incidence ratios (SIR) and excess absolute risk (EAR) per 1000 person-years at risk (PYR) of second primary cancer (SPC) were calculated relative to the general population.

RESULTS

Among 6602 first primary OSCC patients there were 640 (10%) SPCs. The SIR for SPCs was 1.85 (95% CI: 1.71-1.99, P < .001) corresponding to an EAR of 8.78 (95% CI: 7.29-10.26).

CONCLUSIONS

Health care professionals should be aware of the second primary cancer risk after management of primary OSCC and patients need to be counseled about this phenomenon.

Heavy-ion beam irradiation inhibits invasion of tongue squamous cell carcinoma Tca8113 cells

Tongue squamous cell carcinoma (TSCC) is a common malignant tumor type with aggressive biological characteristics, located in the oral and maxillofacial region. Vascular endothelial growth factor (VEGF) and matrix metalloproteinases (MMPs) have been implicated in the invasion and metastasis of various malignant tumor types, such as lung cancer and gastric carcinoma. High linear energy transfer (LET) particle irradiation has several advantages over conventional X-rays in suppressing the invasion and metastasis of malignant tumors. The objective of the present study was to investigate the effects of high-LET carbon ions and low-LET X-rays on the expression of VEGF and MMPs, and to identify the associated mechanisms in the Tca8113 TSCC cell line. Tca8113 cells were irradiated with carbon ions or X-rays at doses of 1 and 4 Gy. An immunofluorescence assay indicated that VEGF expression was notably decreased at 24 and 48 h after heavy ion irradiation compared with irradiation with conventional X-rays. The expression of MMP-2 and MMP-9 also decreased in a dose-dependent manner following heavy ion irradiation. These findings indicate that compared with low-LET X-ray irradiation, high-LET carbon ions possess higher biological efficacy in inhibiting the invasive ability of Tca8113 cells via reduction of VEGF, MMP-2 and MMP-9 expression.

Deep convolutional neural networks for tongue squamous cell carcinoma classification using Raman spectroscopy

With deep convolutional neural networks and fiber optic Raman spectroscopy, this study presents a novel classification method that discriminates tongue squamous cell carcinoma (TSCC) from non-tumorous tissue. To achieve this purpose, 24 tissues spectral data were first collected from 12 patients who had undergone a surgical resection due to the tongue squamous cell carcinomas. Then 6 blocks with each block including 1 convolutional layer and 1 max-pooling layer are used to extract the nonlinear feature representations from Raman spectra. The derived features form a representative vector, which is fed into a fully-connected network for performing classification task. Experimental results demonstrated that the proposed method achieved high sensitivity (99.31%) and specificity (94.44%). To show the superiority for the ConvNets classifier, comparison results with the state-of-the-art methods show it had a competitive classification accuracy. Moreover, these promising results may pave the way to apply the deep ConvNets model in the fiber optic Raman instrument for intra-operative evaluation of TSCC resection margins and improve patient survival.

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

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%.

Development and validation of Raman spectroscopic classification models to discriminate tongue squamous cell carcinoma from non-tumorous tissue

BACKGROUND

Currently, up to 85% of the oral resection specimens have inadequate resection margins, of which the majority is located in the deeper soft tissue layers. The prognosis of patients with oral cavity squamous cell carcinoma (OCSCC) of the tongue is negatively affected by these inadequate surgical resections. Raman spectroscopy, an optical technique, can potentially be used for intra-operative evaluation of resection margins.

OBJECTIVE

To develop in vitro Raman spectroscopy-based tissue classification models that discriminate OCSCC of the tongue from (subepithelial) non-tumorous tissue.

MATERIALS AND METHODS

Tissue classification models were developed using Principal Components Analysis (PCA) followed by (hierarchical) Linear Discriminant Analysis ((h)LDA). The models were based on a training set of 720 histopathologically annotated Raman spectra, obtained from 25 tongue samples (11 OCSCC and 14 normal) of 10 patients, and were validated by means of an independent validation set of 367 spectra, obtained from 19 tongue samples (6 OCSCC and 13 normal) of 11 patients.

RESULTS

A PCA-LDA tissue classification model 'tumor' versus 'non-tumorous tissue' (i.e. surface squamous epithelium, connective tissue, muscle, adipose tissue, gland and nerve) showed an accuracy of 86% (sensitivity: 100%, specificity: 66%). A two-step PCA-hLDA tissue classification model 'tumor' versus 'non-tumorous tissue' showed an accuracy of 91% (sensitivity: 100%, specificity: 78%).

CONCLUSION

An accurate PCA-hLDA Raman spectroscopy-based tissue classification model for discrimination between OCSCC and (especially the subepithelial) non-tumorous tongue tissue was developed and validated. This model with high sensitivity and specificity may prove to be very helpful to detect tumor in the resection margins.