ArticleBMC medical imaging2025
The use of diffusion-weighted magnetic resonance imaging and parametric response mapping for disease outcome prediction in nasopharyngeal carcinoma.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- MRI-based assessment of tumor aggressiveness in nasopharyngeal carcinoma: risk stratification and survival prediction.European radiology · 2026Article
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6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNasopharyngeal carcinoma (NPC) shows variable treatment responses due to tumor heterogeneity and individual radiosensitivity, complicating the early identification of patients at risk for recurrence. Developing reliable imaging biomarkers could help predict treatment outcomes, enabling timely treatment adjustments and improved prognosis. Therefore, we aimed to evaluate the use of the apparent diffusion coefficient (ADC), based on diffusion-weighted imaging, and parametric response mapping (PRM), a voxel-wise imaging analysis method, in predicting treatment outcomes of patients with NPC.
methodsThis retrospective and prospective cohort study included 70 patients with NPC, treated with radiotherapy or concurrent chemoradiation therapy with or without induction chemotherapy. Imaging examinations were performed before (pre-treatment) and 5 weeks after initiating treatment (intra-treatment). Tumor volume at pre- and intra-treatment, percentage change in tumor volume (%∆Vol), pre- and intra-treatment ADC, percentage change in ADC (%∆ADC), and voxels with increased ADC values within the tumor (PRM+) were used to predict correlation with treatment outcomes. Poor outcomes were defined as developing locoregional recurrence, distant metastases, or death. The primary endpoint was progression-free survival, defined as the time to these events. Kaplan-Meier survival analysis, Cox regression, and multivariate models were used to determine predictive factors.
resultsOverall, 17 and 53 patients had poor and good outcomes, respectively. The PRM+ was lower in patients with poor outcomes than in those with good outcomes (22.4% vs. 64.1%; p < 0.001). In the multivariate analyses, cut-off values of PRM+ < 35% and initial T-stage 3-4 were identified as two risk factors associated with poor outcomes, with adjusted hazard ratios (95% confidence intervals) of 22.53 (5.09-99.8; p < 0.001), and 3.45 (1.10-10.77; p = 0.033), respectively.
conclusionsLow PRM+ and high initial T-stage were associated with poor treatment outcomes. Therefore, PRM+ can be a predictive tool for NPC treatment outcomes. Integrating PRM into clinical practice could enhance individualized treatment planning, leading to better patient outcomes and reduced treatment-related side effects.
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