ArticleClinical and translational radiation oncology2017
Radiomic analysis in prediction of Human Papilloma Virus status.
Article in Clinical and translational radiation oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
35 citing papers in PubMed, 2 syntheses or guidelines pooled it, 63 citations in OpenAlex.
- The impact of radiomics for human papillomavirus status prediction in oropharyngeal cancer: systematic review and radiomics quality score assessment.Neuroradiology · 2022Pooled it
- Quantitative diffusion magnetic resonance imaging for prediction of human papillomavirus status in head and neck squamous-cell carcinoma: A systematic review and meta-analysis.The neuroradiology journal · 2019Pooled it
- Role of artificial intelligence in head and neck surgery - A narrative review.Turkish journal of surgery · 2026Article
- Review
- Human Papillomavirus-Positive Oropharyngeal Cancer: Clinical and Radiologic Characteristics.Journal of the Korean Society of Radiology · 2026Review
- Radiomic-Based Machine Learning Classifiers for HPV Status Prediction in Oropharyngeal Cancer: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.European radiology · 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
- The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey.Journal of personalized medicine · 2024Article
- Multi-Modal Ensemble Deep Learning in Head and Neck Cancer HPV Sub-Typing.Bioengineering (Basel, Switzerland) · 2023Article
- Article
- Article
- Imaging of human papilloma virus (HPV) related oropharynx tumour: what we know to date.Infectious agents and cancer · 2023Review
- The Use of Radiomic Features to Predict Human Papillomavirus (HPV) Status in Head and Neck Tumors: A Review.Cureus · 2023Review
- 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
- Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature.Cancers · 2022Review
- Translation of Precision Medicine Research Into Biomarker-Informed Care in Radiation Oncology.Seminars in radiation oncology · 2022Review
- Advances in Imaging for HPV-Related Oropharyngeal Cancer: Applications to Radiation Oncology.Seminars in radiation oncology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oropharynx cancer patients. We designed a statistical radiomics approach analyzing CT images to predict HPV status. Various radiomics features were extracted from CT scans, and analyzed using statistical feature selection and prediction methods. Our approach ranked the highest in the 2016 Medical Image Computing and Computer Assisted Intervention (MICCAI) grand challenge: Oropharynx Cancer (OPC) Radiomics Challenge, Human Papilloma Virus (HPV) Status Prediction. Further analysis on the most relevant radiomic features distinguishing HPV positive and negative subjects suggested that HPV positive patients usually have smaller and simpler tumors.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.