Observational studyMedicine2018
Predicting chemoradiotherapy response of nasopharyngeal carcinoma using texture features based on intravoxel incoherent motion diffusion-weighted imaging.
Observational study in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diffusion-weighted MRI for predicting treatment response in patients with nasopharyngeal carcinoma: a systematic review and meta-analysis.Scientific reports · 2021Pooled it
- Early detection treatment response for head and neck carcinomas using intravoxel incoherent motion-magnetic resonance imaging: a meta-analysis.Dento maxillo facial radiology · 2021Pooled it
- Integrated clinical-radiomic model for predicting treatment response of concurrent chemo-radiotherapy and radiotherapy alone in controversial subgroup of AJCC/UICC ninth edition stage I nasopharyngeal cancer.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2025Article
- Synthetic MRI Combined With Clinicopathological Characteristics for Pretreatment Prediction of Chemoradiotherapy Response in Advanced Nasopharyngeal Carcinoma.Korean journal of radiology · 2025Article
- Non-invasive imaging biomarkers of cellular injury and proliferation in nasopharyngeal carcinoma: insights from multiparametric MRI.Frontiers in cell and developmental biology · 2025Article
- The value of predicting neoadjuvant chemotherapy early efficacy in nasopharyngeal carcinoma based on amide proton transfer imaging and diffusion weighted imaging.Quantitative imaging in medicine and surgery · 2024Article
- Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) combined with conventional MRI for the detection of skull-base invasion in nasopharyngeal carcinoma: comparison withQuantitative imaging in medicine and surgery · 2024Article
- Deciphering the Prognostic Efficacy of MRI Radiomics in Nasopharyngeal Carcinoma: A Comprehensive Meta-Analysis.Diagnostics (Basel, Switzerland) · 2024Article
- Feasibility evaluation of intravoxel incoherent motion diffusion-weighted imaging in the diagnosis of skull-base invasion in nasopharyngeal carcinoma.Journal of Cancer · 2023Article
- Prediction of short-term treatment outcome of nasopharyngeal carcinoma based on voxel incoherent motion imaging and arterial spin labeling quantitative parameters.European journal of radiology open · 2023Article
- The value of intravoxel incoherent motion model-based diffusion-weighted imaging for predicting long-term outcomes in nasopharyngeal carcinoma.Frontiers in oncology · 2022Article
- Chemotherapy Potentially Facilitates the Occurrence of Radiation Encephalopathy in Patients With Nasopharyngeal Carcinoma Following Radiotherapy: A Multiparametric Magnetic Resonance Imaging Study.Frontiers in oncology · 2019Article
- Potentials of radiomics for cancer diagnosis and treatment in comparison with computer-aided diagnosis.Radiological physics and technology · 2018Review
Corrections and comments
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9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the study was to investigative the utility of gray-level co-occurrence matrix (GLCM) texture analysis based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for predicting the early response to chemoradiotherapy for nasopharyngeal carcinoma (NPC).Baseline IVIM-DWI was performed on 81 patients with NPC receiving chemoradiotherapy in a prospective nested case-control study. The patients were categorized into the residue (n = 11) and nonresidue (n = 70) groups, according to whether there was local residual lesion or not at the end of chemoradiotherapy. The pretreatment tumor volume and the values of IVIM-DWI parameters (apparent diffusion coefficient [ADC], D, D, and f) and GLCM features based on IVIM-DWI were compared between the 2 groups. Receiver operating characteristic (ROC) curves in univariate and multivariate logistic regression analysis were generated to determine significant indicator of treatment response.The nonresidue group had lower tumor volume, ADC, D, CorrelatADC, CorrelatD, InvDfMomADC, InvDfMomD and InvDfMomD values, together with higher ContrastD, Contrastf, SumAvergADC, SumAvergD, and SumAvergD values, than the residue group (all P < .05). Based on ROC curve in univariate analysis, the area under the curve (AUC) values for individual GLCM features in the prediction of the treatment response ranged from 0.635 to 0.879, with sensitivities from 54.55% to 100.00% and specificities from 52.86% to 85.71%. Multivariate logistic regression analysis demonstrated D (P = .026), InvDfMomADC (P = .033) and SumAvergD (P = .015) as the independent predictors for identifying NPC without residue, with an AUC value of 0.977, a sensitivity of 90.91% and a specificity of 95.71%.Pretreatment GLCM features based on IVIM-DWI, especially on the diffusion-related maps, may have the potential to predict the early response to chemoradiotherapy for NPC.
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