ArticleAnnals of nuclear medicine2021
Prediction of local recurrence and distant metastasis using radiomics analysis of pretreatment nasopharyngeal [18F]FDG PET/CT images.
Article in Annals of nuclear medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- A systematic review and meta-analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck squamous cell carcinoma patients.Cancer medicine · 2023Pooled it
- The prognostic value of radiomic features from pre- and post-treatmentScientific reports · 2023Trial
- Recent Advances in Surveillance Strategies for Nasopharyngeal Carcinoma.Current oncology reports · 2026Review
- Article
- Strategies and challenges of toxicity reduction in nasopharyngeal carcinoma in the era of precision radiotherapy: from paradigm shift to integrated decision-making.Frontiers in oncology · 2026Review
- PET-based radiomic analysis in multicentre lung cancer study and impact of feature domain harmonization.Physical and engineering sciences in medicine · 2025Article
- Tumor habitat-derived radiomics features in pretreatment CT scans for predicting concurrent chemoradiotherapy responses in nasopharyngeal carcinoma: a retrospective study.Quantitative imaging in medicine and surgery · 2025Article
- Construction of an oligometastatic prediction model for nasopharyngeal carcinoma patients based on pathomics features and dynamic multi-swarm particle swarm optimization support vector machine.Frontiers in oncology · 2025Article
- Recurrent Versus Metastatic Head and Neck Cancer: An Evolving Landscape and the Role of Immunotherapy.Biomedicines · 2024Review
- Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study.Journal of applied clinical medical physics · 2024Article
- Article
- Clinical application ofJapanese journal of radiology · 2024Review
- Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques.Statistics in medicine · 2023Article
- Deep Learning for Predicting Distant Metastasis in Patients with Nasopharyngeal Carcinoma Based on Pre-Radiotherapy Magnetic Resonance Imaging.Combinatorial chemistry & high throughput screening · 2023Article
- Article
- Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.Diagnostics (Basel, Switzerland) · 2022Review
- [Research progress in CT-based radiomics constructing hypopharyngeal cancer and multisystem tumor prediction model].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2022Review
- Artificial intelligence for nuclear medicine in oncology.Annals of nuclear medicine · 2022Review
- Prognostic value of PET/CT and MR-based baseline radiomics among patients with non-metastatic nasopharyngeal carcinoma.Frontiers in oncology · 2022Article
- Dynamic contrast-enhanced magnetic resonance imaging-based radiomics for the prediction of progression-free survival in advanced nasopharyngeal carcinoma.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesTo develop a radiomics signature to predict locoregional recurrence (LR) and distant metastasis (DM), as extracted from pretreatment 2-deoxy-2-[ MATERIALS AND
methodsEighty-five patients with Stage III-IVB NPC underwent pretreatment [
resultsTwenty features had significant differences between disease control and treatment failure. NPC patients with values of Compactness1, Compactness2, Coarseness_NGTDM or SGE_GLGLM above the median as well as patients with values of Irregularity, RLN_GLRLM or GLV_GLSZM below the median, showed a significant (p < 0.05) higher risk of treatment failure (about 50% vs. 25%). The derived radiomics signature consisted of 5 features with the highest AUC value of 0.8290 (sensitivity: 0.8438, specificity: 0.7736) using leave-one-out-cross-validation.
conclusionLocoregional recurrence (LR) and DM of locally advanced NPC can be predicted using radiomics analysis of pretreatment [
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