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Purpose: This paper aimed to establish and verify a radiomics model based on magnetic resonance imaging (MRI) for predicting the progression-free survival of nasopharyngeal carcinoma (NPC) after induction chemotherapy (IC). Materials and Methods: This cohort consists of 288 patients with clinical pathologically confirmed NPC, which was collected from January 2015 to December 2018. All NPC patients were randomly divided into two cohorts: training (n=202) and validation (n=86). Radiomics features from the MRI images of NPC patients were extracted and selected before IC. The patients were classified into high- and low-risk groups according to the median of Radscores. The significant imaging features and clinical variables in the univariate analysis were constructed for progression-free survival (PFS) using the multivariate Cox regression model. A survival analysis was performed using Kaplan-Meier with log-rank test and then each model's stratification ability was evaluated. Results: Epstein-Barr virus (EBV) DNA before treatment was an independent predictor for PFS (p < 0.05). Based on the pyradiomic platform, we extracted 1,316 texture parameters in total. Finally, 16 texture features were used to build the model. The clinical radiomics-based model had good prediction capability for PFS, with a C-index of 0.827. The survival curve revealed that the PFS of the high-risk group was poorer than that of the low-risk group. Conclusion: This research presents a nomogram that merges the radiomics signature and the clinical feature of the plasma EBV DNA load, which may improve the ability of preoperative prediction of progression-free survival and facilitate individualization of treatment in NPC patients before IC.
RESUMEN
Purpose: We developed a contrast agent for targeting E-selectin expression. We detected the agent using magnetic resonance imaging (MRI) in vivo in nude mice that had undergone nasopharyngeal carcinoma (NPC) metastasis. Methods: Sialyl Lewis X (sLeX) was conjugated with ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles. Hydrodynamic size, polydispersity index, and ζ-potential of USPIO-polyethylene glycol (PEG) nanoparticles and USPIO-PEG-sLeX nanoparticles were measured. Component changes in nanoparticles of USPIO, USPIO-PEG, and USPIO-PEG-sLeX were analyzed by thermogravimetric analysis and Fourier-transform infrared spectroscopy. A model of NPC metastasis to inguinal lymph nodes in nude mice was used to investigate characteristics of the USPIO-PEG-sLeX nanoparticles in vivo. We investigated the ability of the T2* value, change in T2* value (ΔT2* value), and enhancement rate (ER) to assess accumulation of USPIO-PEG-sLeX nanoparticles quantitatively in mice of a metastasis group and control group. Four MRI scans were undertaken for each mouse. The first scan (t0) was done before administration of USPIO-PEG-sLeX nanoparticles (0.1 mL) via the tail vein. The other scans were carried out at 0 (t1), 1 (t2), and 2 hours (t3) postinjection. The mean optical density was used to reflect E-selectin expression. Results: sLeX was labeled onto USPIO successfully. In vivo, there were significant interactions between the groups and time for T2* values after administration of USPIO-PEG-sLeX nanoparticles. Six parameters (T2* at t2, ΔT2* at t1, ΔT2* at t2, ER at t1, ER at t2, and ER at t3) were correlated with the mean optical density. Conclusion: USPIO-PEG-sLeX nanoparticles can be used to assess E-selectin expression quantitatively. Use of such molecular probes could enable detection of early metastasis of NPC, more accurate staging, and treatment monitoring.
