scholarly journals Texture Analysis of Multi-Shot Echo-planar Diffusion-Weighted Imaging in Head and Neck Squamous Cell Carcinoma: The Diagnostic Value for Nodal Metastasis

2019 ◽  
Vol 8 (11) ◽  
pp. 1767 ◽  
Author(s):  
Park ◽  
Bae ◽  
Choi ◽  
Jung ◽  
Jeong ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Texture Analysis ◽  
Squamous Cell ◽  
Diffusion Weighted Imaging ◽  
Diagnostic Performance ◽  
Texture Features ◽  
Nodal Metastasis ◽  
Echo Planar

Accurate assessment of nodal metastasis in head and neck squamous cell carcinoma (SCC) is important, and diffusion-weighted imaging (DWI) has emerged as a potential technique in differentiating benign from malignant lymph nodes (LNs). This study aims to evaluate the diagnostic performance of texture analysis using apparent diffusion coefficient (ADC) data of multi-shot echo-planar imaging-based DWI (msEPI-DWI) in predicting metastatic LNs of head and neck SCC. 36 patients with pathologically proven head and neck SCC were included in this study. A total of 204 MRI-detected LNs, including 176 subcentimeter-sized LNs, were assigned to metastatic or benign groups. Texture features of LNs were compared using independent t-test. Hierarchical cluster analysis was performed to exclude redundant features. Multivariate logistic regression and receiver operating characteristic analysis were performed to assess the diagnostic performance. The discriminative texture features for predicting metastatic LNs were complexity, energy and roundness. Areas under the curves (AUCs) for diagnosing metastasis in all/subcentimeter-sized LNs were 0.829/0.767 using complexity, 0.699/0.685 using energy and 0.671/0.638 using roundness, respectively. The combination of three features resulted in higher AUC values of 0.836/0.781. In conclusion, texture analysis of ADC data using msEPI-DWI could be a useful tool for nodal staging in head and neck SCC.

P-113 Oncological Outcomes and Prognostication in Cutaneous Squamous Cell Carcinoma of the Head and Neck with Nodal Metastasis

Oral Oncology ◽  
2021 ◽  
Vol 118 ◽  
pp. 1
Author(s):  
Mark D. Wilkie ◽  
Dorota Chudek ◽  
Sankalap Tandon ◽  
Christopher Loh ◽  
Nicholas J. Roland ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Nodal Metastasis ◽  
Cutaneous Squamous Cell Carcinoma ◽  
Oncological Outcomes

scholarly journals N-cadherin and hyaluronan expression in head and neck squamous cell carcinoma, relation to patient outcomes

2017 ◽  
Vol 8 (1) ◽  
pp. 19
Author(s):  
Heba A. El Hendawy ◽  
Afaf Ibrahiem ◽  
El-Nagdy SY ◽  
Zedan W
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Epithelial Mesenchymal Transition ◽  
Clinical Stage ◽  
Nodal Metastasis ◽  
Large Tumor ◽  
Mesenchymal Transition ◽  
Oral Site

Background: Epithelial-mesenchymal transition (EMT) is regarded as an essential step for tumor invasion and metastasis. In squamous cell carcinoma of head and neck (HNSCC), N-Cadherin expression and its involvement in tumor progression remains a controversial topic.Aim of the study: The present study aimed to assess the expression of N-cadherin and HA in HNSCC and further study their relation to patients survival and outcomes.Material and methods: Fifty-eight retrospective selected cases of head and neck squamous carcinomas (HNSCCs) with available paraffin blocks. Complete clinico-pathological and follow-up data were recorded. Immune staining for N-cadherin and hyaluronan were done, also, we study the correlation of the results with patients survival data.Results: Squamous cell carcinoma islands demonstrated high N-cadherin expression in 55.2% and low expression in 44.8%. N-cadherin high expression was significantly (p < .05) associated with large tumor sizes, advanced TNM clinical stage, increased incidence of recurrence and patient’s death. A significant correlation was recorded between the presence of neural invasion and N-cadherin expression (p = .004). Strong intensity of stromal HA was significantly (p < .05) associated with an oral site, nodal metastasis, and higher TNM stage. Patients with high N-cadherin expression, diffuse hyaluronan, and strong stromal hyaluronanreaction had significantly lower DFS rates (p < .05). High N-cadherin expression, diffuse hyaluronan immunoreactivity, and strong stromal hyaluronan reaction intensity had significantly lower OS rates (p < .05).Conclusion: N-cadherin and hyaluronan could be important and promising biomarkers during surveillance of patients with HNSCC.

Predicting tumor mutational burden in head and neck squamous cell carcinoma based on CT imaging features: A TCGA/TCIA study.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15254-e15254
Author(s):  
Yangkun Luo ◽  
Lu Li ◽  
Gang Yin ◽  
Jin Yi Lang
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Sensitivity And Specificity ◽  
Squamous Cell ◽  
Texture Features ◽  
Performance Estimation ◽  
Neck Squamous Cell Carcinoma ◽  
Imaging Features ◽  
Mutation Burden

e15254 Background: Immunotherapy has substantially changed the therapeutic strategies for cancers. Unfortunately, only 20–50% of patients with advanced solid tumours respond to treatment. There is therefore a need for the development of methods to identify patients who are most likely to respond to immunotherapy. Tumor mutation burden (TMB) have been served as the most prevalent biomarkers to predict immunotherapy response. This study was designed to investigate the ability of radiomics to predict TMB status in patients with head and neck squamous cell carcinoma (HNSCC). Methods: TMB values were calculated using genomic data obtained from the HNSCC dataset in The Cancer Genome Atlas (TCGA).We identified matching patients (n = 100) who underwent contrast-enhanced CT scan prior to treatment from The Cancer Imaging Archive (TCIA),and patients were grouped based on the cutoff value; high group(>4.2 mutations/Mb) and low group(≤4.2 mutations/Mb). A total of 249 radiomics features(9 non-texture features and 240 scan-texture-parameter features) were extracted from CT images of the tumor. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved imbalance-adjusted bootstrap resampling in the following four steps leading to final prediction model construction: (1) feature set reduction; (2) feature selection; (3) prediction performance estimation; and (4) computation of model coefficients. The performance was evaluated in terms of area under the curve (AUC), sensitivity, and specificity. Results: Among all the features, twenty features were found to have the most impact on the predictive value; the two top texture parameters were GLCM-Variance and GLCM-Sum Average. In multivariable analysis, the best performance was obtained using a combination of seven texture features that can discriminate between high mutation burden versus low mutation burden. The AUC, sensitivity, and specificity of this model were 0.97 ± 0.01, 0.92 ± 0.04, and 0.92 ±0.01, respectively. Conclusions: The proposed CT-derived predictive model can accurately predict TMB status in patients with HNSCC. It may be helpful in guiding immunotherapy in clinical practice and deserves further analysis.

scholarly journals Yes-Associated Protein Expression in Head and Neck Squamous Cell Carcinoma Nodal Metastasis

PLoS ONE ◽  
2011 ◽  
Vol 6 (11) ◽  
pp. e27529 ◽  
Author(s):  
Lin Ge ◽  
Matthew Smail ◽  
Wenxia Meng ◽  
Yu Shyr ◽  
Fei Ye ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Protein Expression ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Nodal Metastasis ◽  
Neck Squamous Cell Carcinoma
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