scholarly journals Prediction of the degree of pathological differentiation in tongue squamous cell carcinoma based on radiomics analysis of magnetic resonance images

2020 ◽  
Author(s):  
Baoting Yu ◽  
Chencui Huang ◽  
Jingxu Xu ◽  
Shuo Liu ◽  
Yuyao Guan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Magnetic Resonance ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Characteristic Curve ◽  
Magnetic Resonance Images ◽  
Tongue Squamous Cell Carcinoma ◽  
Mri Features ◽  
Pathological Differentiation

Abstract Background: To explore the value of radiomics based on magnetic resonance fat-suppressed T2-weighted images in predicting the degree of pathological differentiation of tongue squamous cell carcinoma (TSCC).Methods: Retrospective analysis of 87 TSCC patients who were randomly divided into a primary cohort and a test cohort. The tumour regions were manually labelled in fat-suppressed T2-weighted imaging (FS-T2WI) and PyRadiomics was used to extract radiomics features. The radiomics features were then selected by the least absolute shrinkage and selection operator (LASSO) method. The model was established by the logistic regression classifier using a 5-fold cross-validation method, applied to the set and evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. Results: In total, 1132 features were extracted, and seven features were selected for modelling. The AUC in the logistic regression model for well-differentiated TSCC was 0.90 with specificity and precision values of 0.92 and 0.78, respectively, and the sensitivity for poorly differentiated TSCC was 0.74.Conclusion: In this model, there was a significant relationship between radiomics characteristics and the degree of pathological differentiation, and the degree can be predicted from MRI features using machine learning. Advances in knowledge: Texture analysis and prediction of the differentiation degree of TSCC by MRI are not only a breakthrough and innovation in the diagnosis of TSCC but are also of significance in clinical diagnosis and treatment.

scholarly journals Prediction of the degree of pathological differentiation in tongue squamous cell carcinoma based on radiomics analysis of magnetic resonance images

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Baoting Yu ◽  
Chencui Huang ◽  
Jingxu Xu ◽  
Shuo Liu ◽  
Yuyao Guan ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Magnetic Resonance ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Magnetic Resonance Images ◽  
Tongue Squamous Cell Carcinoma ◽  
Pathological Differentiation ◽  
Poorly Differentiated ◽  
Well Differentiated

Abstract Background Tongue squamous cell carcinoma (TSCC) is one of the most difficult malignancies to control. It displays particular and aggressive behaviour even at an early stage. The purpose of this paper is to explore the value of radiomics based on magnetic resonance fat-suppressed T2-weighted images in predicting the degree of pathological differentiation of TSCC. Methods Retrospective analysis of 127 patients with TSCC who were randomly divided into a primary cohort and a test cohort, including well-differentiated, moderately differentiated and poorly differentiated. The tumour regions were manually labelled in fat-suppressed T2-weighted imaging (FS-T2WI), and PyRadiomics was used to extract radiomics features. The radiomics features were then selected by the least absolute shrinkage and selection operator (LASSO) method. The model was established by the logistic regression classifier using a 5-fold cross-validation method, applied to all data and evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. Results In total, 1132 features were extracted, and seven features were selected for modelling. The AUC in the logistic regression model for well-differentiated TSCC was 0.90 with specificity and precision values of 0.92 and 0.78, respectively, and the sensitivity for poorly differentiated TSCC was 0.74. Conclusions The MRI-based radiomics signature could discriminate between well-differentiated, moderately differentiated and poorly differentiated TSCC and might be used as a biomarker for preoperative grading.

scholarly journals Modeling the Risk of Radiation Pneumonitis in Esophageal Squamous Cell Carcinoma Treated with Definitive Chemoradiotherapy

2020 ◽  
Author(s):  
Kaiqi Lan ◽  
Cheng Xu ◽  
Shiliang Liu ◽  
Jinhan Zhu ◽  
Yadi Yang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Radiation Pneumonitis ◽  
Smoking Status ◽  
Characteristic Curve ◽  
Smoking History ◽  
Prediction Ability

Abstract Purpose: To develop and validate a nomogram for the prediction of symptomatic radiation pneumonitis (RP) in patients with esophageal squamous cell carcinoma (ESCC) who received definitive concurrent chemoradiotherapy.Methods: Clinical factors, dose-volume histogram parameters, and pulmonary function parameters were collected from 402 ESCC patients between 2010 and 2017, including 321 patients in the primary cohort and 81 in the validation cohort. The end-point was the occurrence of symptomatic RP (grade ≥2) within the first 12 months after radiotherapy. Univariate and multivariate logistic regression analyses were applied to evaluate the predictive value of each factor for RP. A prediction model was generated in the primary cohort, which was internally validated to assess its performance.Results: In the primary cohort, 31 patients (9.7%) experienced symptomatic RP. Based on logistic regression model, patients with larger planning target volumes (PTVs) or higher lung V20 had a higher predictive risk of RP, whereas the overall risk was substantially higher for three-dimensional conformal radiotherapy (3DCRT) than intensity-modulated radiotherapy. On multivariate analysis, independent predictive factors for RP were smoking history (P=0.018), radiotherapy modality (P<0.001), PTV (P=0.014), and lung V20 (P=0.002), which were incorporated into the nomogram. The areas under the receiver operating characteristic curve of the nomogram in the primary and validation cohorts were 0.772 and 0.900, respectively, which were superior to each predictor alone.Conclusions: Non-smoking status, 3DCRT, lung V20 (>27.5%), and PTV (≥713.0 cc) were significantly associated with a higher risk of RP. A nomogram was built with satisfactory prediction ability.

Isoliquiritigenin Inhibits Proliferation and Induces Apoptosis in Tongue Squamous Cell Carcinoma by Modulating miR-21/FOXG1 Pathway

2019 ◽  
Vol 17 (4) ◽  
pp. 463-469
Author(s):  
Hou Deqiang ◽  
Gao Yufeng ◽  
Bai Ning ◽  
Dong Yu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Carcinoma Cells ◽  
Tongue Squamous Cell Carcinoma ◽  
Luciferase Assay ◽  
Forkhead Box ◽  
Proliferation And Apoptosis ◽  
Mrna And Protein Expression ◽  
Induced Apoptosis

Isoliquiritigenin is a flavonoid commonly found in liquorice and has been identified as a potent anti-tumor agent. The aim of this study was to investigate whether isoliquiritigenin regulates the proliferation and apoptosis of tongue squamous cell carcinoma cells by regulating forkhead box G1 expression via miR-21. MTT assay and flow cytometry were used to analyze cell proliferation and apoptosis, respectively. Quantitative real time polymerase chain reaction and western blotting were used to detect mRNA and protein expression levels, respectively. The relationship between miR-21 and forkhead box G1 was detected by dual luciferase assay. Isoliquiritigenin inhibited proliferation and induced apoptosis of tongue squamous cell carcinoma cells, and decreased miR-21 levels and promoted forkhead box G1 expression. Forkhead box G1 was then identified as a target of miR-21 and ISL could promote forkhead box G1 expression by inhibiting miR-21. Further analysis suggested that upregulation of miR-21 improved proliferation and suppressed apoptosis of tongue squamous cell carcinoma cells by inhibiting forkhead box G1 expression. Finally, our results revealed that isoliquiritigenin inhibited proliferation and induced apoptosis of tongue squamous cell carcinoma cells by regulating miR-21. Isoliquiritigenin might act as a novel therapeutic treatment for tongue squamous cell carcinoma cells through up-regulation of forkhead box G1 expression via inhibiting miR-21expression.

Characterization of Healthy and Tumor Oral Cell Lines of Human Origin. The preliminary stage in the assessment of relevant chemical compounds with impact on dentistry

2018 ◽  
Vol 69 (10) ◽  
pp. 2889-2894
Author(s):  
Ion Virgil Corlan ◽  
Adelina Cheveresan ◽  
Delia Berceanu Vaduva ◽  
Cristian Nica ◽  
Alin Faur ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cell Lines ◽  
Squamous Cell ◽  
Chemical Compounds ◽  
Tongue Squamous Cell Carcinoma ◽  
Gingival Fibroblasts ◽  
Human Origin ◽  
Preliminary Stage

The present study was aimed to evaluate the confluence percentage of three oral cell lines, namely primary gingival keratinocytes (PGK), primary gingival fibroblasts (HGF) and tongue squamous cell carcinoma (SCC-4). All cells have been monitored at different passages for 21 days. Evaluation of confluence percentage reveals the fact that primary gingival keratinocytes and tongue squamous cell carcinoma at small passages requires a period of about two weeks to reach a confluence of approximately 80% while for the gingival fibroblasts a period of about three times smaller is satisfactory.

scholarly journals Prognostic value of MRI-measured tumor thickness in patients with tongue squamous cell carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ki-Sun Park ◽  
Yangsean Choi ◽  
Jiwoong Kim ◽  
Kook-Jin Ahn ◽  
Bum-soo Kim ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Proportional Hazards ◽  
Correlation Coefficients ◽  
Cox Proportional Hazards ◽  
Tumor Thickness ◽  
Tongue Squamous Cell Carcinoma ◽  
Depth Of Invasion

AbstractThis study aimed to assess the prognostic value of MRI-measured tumor thickness (MRI-TT) in patients with tongue squamous cell carcinoma (SCC). This single-center retrospective cohort study included 133 pathologically confirmed tongue SCC patients between January 2009 and October 2019. MRI measurements of tongue SCC were based on axial and coronal T2-weighted (T2WI) and contrast-enhanced T1-weighted (CE-T1WI) images. Two radiologists independently measured MRI-TT. Intraclass correlation coefficients (ICC) were calculated for inter-rater agreements. Spearman’s rank correlation between MRI-TT and pathologic depth of invasion (pDOI) was assessed. Cox proportional hazards analyses on recurrence-free (RFS) and overall survival (OS) were performed for MRI-TT and pDOI. Kaplan–Meier survival curves were plotted with log-rank tests. The intra- and inter-rater agreements of MRI-TT were excellent (ICC: 0.829–0.897, all P < 0.001). The correlation between MRI-TT and pDOI was good (Spearman’s correlation coefficients: 0.72–0.76, P < 0.001). MRI-TT were significantly greater than pDOI in all axial and coronal T2WI and CE-T1WI (P < 0.001). In multivariate Cox proportional hazards analysis, MRI-TT measured on axial CE-T1WI yielded a significant prognostic value for OS (hazards ratio 2.77; P = 0.034). MRI-TT demonstrated excellent intra- and inter-rater agreements as well as high correlation with pDOI. MRI-TT may serve as a prognostic predictor in patients with tongue SCC.

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