Quantitative Analysis of DCE-MRI and RESOLVE-DWI for Differentiating Nasopharyngeal Carcinoma from Nasopharyngeal Lymphoid Hyperplasia

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作者
J. Y. Yu
D. Zhang
X. L. Huang
J. Ma
C. Yang
X. J. Li
H. Xiong
B. Zhou
R. K. Liao
Z. Y. Tang
机构
[1] University of Chinese Academy of Sciences,Department of Radiology, Chongqing General Hospital
[2] University of Chinese Academy of Sciences,Molecular and Functional Imaging Laboratory, Chongqing General Hospital
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Nasopharyngeal carcinoma; Nasopharyngeal lymphoid hyperplasia; DCE-MRI; RESOLVE-DWI;
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摘要
To explore the ability of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) analysis and readout segmentation of long variable echo-trains diffusion weighted imaging (RESOLVE-DWI) to distinguish nasopharyngeal carcinoma (NPC) from nasopharyngeal lymphoid hyperplasia (NPLH). Twenty-five patients with NPC and 30 patients with NPLH were evaluated. Three quantitative DCE-MRI parameters (Ktrans, Kep and Ve) and the apparent diffusion coeffcient (ADC) of lesions were calculated. The two independent samples t test or Mann-Whitney U test was used to compare the parameters between NPC and NPLH group. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic ability for distinguishing NPC from NPLH. A P value less than 0.05 was considered statistically significant. The difference in Ktrans value between the NPC group and the NPLH group was statistically significant, and the value of the NPC group was larger than that of the NPLH group. There was no statistical difference in Kep and Ve between the two groups. The ADC value of NPC group was smaller than that of NPLH group, and the difference was statistically significant. ROC curve analysis showed that both Ktrans and ADC were effective in diagnosing NPC and the area under the curve (AUC) was 0.773 and 0.704, respectively. In addition, the combination of Ktrans and ADC demonstrated the obviously improved AUC of 0.884. DCE-MRI and RESOLVE-DWI are effective in differentiating NPC from NPLH, especially the combination of the two models.
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