ArticleLa Radiologia medica2019
CT assessment of tumor heterogeneity and the potential for the prediction of human papillomavirus status in oropharyngeal squamous cell carcinoma.
Article in La Radiologia medica, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: systematic review and radiomics quality score assessment.Neuroradiology · 2022Pooled it
- Integrating CT radiomics and morphologic features for preoperative risk stratification of gastrointestinal stromal tumours.Scientific reports · 2026Article
- Review
- CT Texture Patterns Reflect HPV Status but Not Histological Differentiation in Oropharyngeal Squamous Cell Carcinoma.Cancers · 2025Article
- Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer.Frontiers in immunology · 2025Article
- Role of Artificial Intelligence in Human Papillomavirus Status Prediction for Oropharyngeal Cancer: A Scoping Review.Cancers · 2024Article
- Head and Neck Squamous Cell Carcinoma: Insights from Dual-Energy Computed Tomography (DECT).Tomography (Ann Arbor, Mich.) · 2024Review
- Enhanced Diagnostic Precision: Assessing Tumor Differentiation in Head and Neck Squamous Cell Carcinoma Using Multi-Slice Spiral CT Texture Analysis.Journal of clinical medicine · 2024Article
- Predicting Response to Exclusive Combined Radio-Chemotherapy in Naso-Oropharyngeal Cancer: The Role of Texture Analysis.Diagnostics (Basel, Switzerland) · 2024Article
- Radiomics Features in Predicting Human Papillomavirus Status in Oropharyngeal Squamous Cell Carcinoma: A Systematic Review, Quality Appraisal, and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2024Review
- Radiomics-based model for prediction of TGF-β1 expression in head and neck squamous cell carcinoma.American journal of nuclear medicine and molecular imaging · 2024Article
- Development and Validation of a Radiomics Nomogram for Liver Metastases Originating from Gastric and Colorectal Cancer.Diagnostics (Basel, Switzerland) · 2023Article
- Magnetic resonance imaging in naso-oropharyngeal carcinoma: role of texture analysis in the assessment of response to radiochemotherapy, a preliminary study.La Radiologia medica · 2023Observational
- External validation of a radiomic signature to predict p16 (HPV) status from standard CT images of anal cancer patients.Scientific reports · 2023Article
- Applying multisequence MRI radiomics of the primary tumor and lymph node to predict HPV-related p16 status in patients with oropharyngeal squamous cell carcinoma.Quantitative imaging in medicine and surgery · 2023Article
- Cone-beam computed tomography texture analysis can help differentiate odontogenic and non-odontogenic maxillary sinusitis.Imaging science in dentistry · 2023Article
- Reproducibility of CT radiomic features in lung neuroendocrine tumours (NETs) patients: analysis in a heterogeneous population.La Radiologia medica · 2023Article
- Article
- Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature.Cancers · 2022Review
- Histogram analysis of arterial spin labeling perfusion data to determine the human papillomavirus status of oropharyngeal squamous cell carcinomas.Neuroradiology · 2021Article
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Authors and funding
8 authors.
Funding
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Abstract
The aim of this study is to find a correlation between tumoral heterogeneity of squamous cell carcinoma of the oropharynx and human papillomavirus (HPV) status and to determine whether analysis of texture features of primary lesion on contrast-enhanced CT (CECT) images can be useful in predicting the HPV positivity. Fifty patients with diagnosis of oropharyngeal carcinoma and pre-treatment CECT were included; tumoral heterogeneity of each lesion was evaluated by extracting quantitative texture parameters of first and higher orders. T test and logistic regression were conducted to evaluate the effects of different textural characteristics. There were 35 HPV+ and 15 HPV- lesions. Statistically significant (p < 0.05) differences were seen in multiple higher-order extracted parameters. The logistic regression model correctly classified lesions with an accuracy of 95.2%. CT texture analysis of primary oropharyngeal cancer may be used as a tool for predicting the HPV status.
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