| Differentiation of orbital lymphoma and inflammatory pseudotumor using texture analysis based on contrast-enhanced T1-weighted images of 3.0T MRI |
| Received:September 08, 2019 Revised:October 12, 2019 Click here to download the full text |
| Citation of this paper:HAN Ting-ting,LU Qin.Differentiation of orbital lymphoma and inflammatory pseudotumor using texture analysis based on contrast-enhanced T1-weighted images of 3.0T MRI[J].Chinese Journal of Clinical Medicine,2020,27(1):98-101 |
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| Abstract:Objective: To investigate the diagnostic value of texture analysis in differentiating orbital lymphoma from inflammatory pseudotumor. Methods: There were 25 patients with orbital lymphoma and 24 patients with orbital inflammatory pseudotumor confirmed by postoperative pathological test. MaZda software was used to extract tumor texture features of contrast-enhanced T1-weighted images (CE-T1W). Twenty texture feature parameters of run-length matrix (RLM) between the two groups were compared. Principal component analysis (PCA) was performed for the parameters with statistical significance between the two groups. Multivariate logistic regression was used to model the features that showed statistical significance between the two groups and principal components respectively, then ROC curve was drawn to evaluate the efficiency of the models. Results: Four parameters of grey level non-uniformity (GLNU) and long run emphasis (LRE) were higher in lymphoma than inflammatory pseudotumor (P<0.001). Four parameters of short run emphasis (SRE) and fraction of image in runs (FIR) were lower in the lymphoma group than those in the inflammatory pseudotumor group (P<0.001). There were no significant differences of four parameters of run length non-uniformity (RLNU) between the two groups. Among the features that showed statistically significant differences between the two groups, the model with GLNU parameters showed the highest effect with sensitivity, specificity, and area under curve (AUC) of 95.9%, 72.0%, and 0.905. The sensitivity, specificity, and AUC of the multivariate logistic regression model established with two principal components extracted by PCA, were 87.5%, 88.0%, and 0.913, respectively. Conclusions: Texture feature parameters based on CE-T1W could effectively distinguish orbital lymphoma from orbital inflammatory pseudotumor, among which, GLNU had the highest diagnostic efficiency. |
| keywords:texture analysis run-length matrix magnetic resonance imaging lymphoma inflammatory pseudotumor |
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