ArticleEuropean radiology2019
Predictive value of pretreatment MRI texture analysis in patients with primary nasopharyngeal carcinoma.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Prognostic Analysis of Patients With N1 Nasopharyngeal Carcinoma With Different Lymph Node Characteristics.Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery · 2026Article
- Machine learning prognostication in nasopharyngeal carcinoma: a european multicentre analysis of survival and risk of second malignancy.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Habitat Analysis for Risk Prediction of Nasopharyngeal Carcinoma: A Comparative Study of Different MRI Sequences and Regional Combinations.Bioengineering (Basel, Switzerland) · 2026Article
- An interpretable machine learning model assists in predicting induction chemotherapy response and survival for locoregionally advanced nasopharyngeal carcinoma using MRI: a multicenter study.European radiology · 2025Article
- Integrating Radiomics and Deep-Learning for Prognostic Evaluation in Nasopharyngeal Carcinoma.Medicina (Kaunas, Lithuania) · 2025Review
- Development and validation of an MRI radiomics-based interpretable machine learning model for predicting the progression-free survival in locally advanced nasopharyngeal carcinoma.Quantitative imaging in medicine and surgery · 2025Article
- Deciphering the Prognostic Efficacy of MRI Radiomics in Nasopharyngeal Carcinoma: A Comprehensive Meta-Analysis.Diagnostics (Basel, Switzerland) · 2024Article
- Radiomics and PD-L1 expression predict immunotherapy benefits in patients with head and neck squamous cell carcinoma.Future oncology (London, England) · 2024Article
- Radiomics analysis of R2* maps to predict early recurrence of single hepatocellular carcinoma after hepatectomy.Frontiers in oncology · 2024Article
- Multimodality radiomics analysis based on [European radiology · 2023Article
- Intra- and peritumoral MRI radiomics assisted in predicting radiochemotherapy response in metastatic cervical lymph nodes of nasopharyngeal cancer.BMC medical imaging · 2023Article
- Pretreatment synthetic magnetic resonance imaging predicts disease progression in nonmetastatic nasopharyngeal carcinoma after intensity modulation radiation therapy.Insights into imaging · 2023Article
- Review
- The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study.BMC medical imaging · 2023Article
- Article
- A Clinical-Radiomics Nomogram Based on Magnetic Resonance Imaging for Predicting Progression-Free Survival After Induction Chemotherapy in 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
- Prognostic value of PET/CT and MR-based baseline radiomics among patients with non-metastatic nasopharyngeal carcinoma.Frontiers in oncology · 2022Article
- Establishment and Validation of a Novel MRI Radiomics Feature-Based Prognostic Model to Predict Distant Metastasis in Endemic Nasopharyngeal Carcinoma.Frontiers in oncology · 2022Article
- A Comprehensive Review on Radiomics and Deep Learning for Nasopharyngeal Carcinoma Imaging.Diagnostics (Basel, Switzerland) · 2021Review
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11 authors.
Funding
Abstract
objectivesTo determine the predictive value of pretreatment MRI texture analysis for progression-free survival (PFS) in patients with primary nasopharyngeal carcinoma (NPC).
methodsEthical approval by the institutional review board was obtained for this retrospective analysis. In 79 patients with primary NPC, texture analysis of the primary tumour was performed on pretreatment T2 and contrast-enhanced T1-weighted images (T2WIs and CE-T1WIs). The Cox proportional hazards model was used to determine the association of texture features, tumour volume and the tumour-node-metastasis (TNM) stage with PFS. Survival curves were plotted using the Kaplan-Meier method. The prognostic performance was evaluated with the receiver operating characteristic (ROC) analyses and C-index.
resultsTumour volume (hazard ratio, 1.054; 95% confidence interval [CI], 1.016-1.093) and CE-T1WI-based uniformity (hazard ratio, 0; 95% CI, 0-0.001) were identified as independent predictors for PFS (p < 0.05). Kaplan-Meier analysis showed that smaller tumour volume (less than the cut-off value, 11.699 cm
conclusionsA texture parameter of pretreatment CE-T1WI-based uniformity improves the prediction of PFS in NPC patients. KEY POINTS: • Higher CE-T1WI-based uniformity and smaller tumour volume are predictive of improved PFS in NPC patients. • The combination of CE-T1WI-based uniformity with tumour volume and the overall stage has a better predictive ability for PFS than the tumour volume or the overall stage alone. • Pretreatment MRI texture analysis has a prognostic value for NPC patients.
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