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The value of texture analysis in peritumoral edema of differentiating diagnosis between glioblastoma and primary brain lymphoma
To evaluate the value of texture analysis of routine MRI image in peritumoral edema of differentiating diagnosis between glioblastoma (GBM) and primary brain lymphoma (PBL). The MRI imaging data of 22 patients with glioblastoma and 21 patients with PBL who were hospitalized in our hospital from Janu...
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Published in: | British journal of neurosurgery 2023-10, Vol.ahead-of-print (ahead-of-print), p.1-4 |
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Main Authors: | , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | To evaluate the value of texture analysis of routine MRI image in peritumoral edema of differentiating diagnosis between glioblastoma (GBM) and primary brain lymphoma (PBL).
The MRI imaging data of 22 patients with glioblastoma and 21 patients with PBL who were hospitalized in our hospital from January 2010 to October 2018 were selected. All the patients were pathologically diagnosed as glioblastoma or PBL, and MRI plain scan and enhanced examination were performed before operation. FireVoxel software was used to delineate the region of interest (ROI) on the most obvious level of peritumoral edema based on T1WI enhancement. Texture parameters were extracted and compared between glioblastoma and PBL.
In the glioblastoma group, the inhomogeneity, kurtosis and entropy texture parameters were statistically different from those in the PBL group. The entropy parameter area under the curve (AUC) (0.903) was significantly better than the kurtosis parameter AUC (0.859) and the inhomogeneity parameter AUC (0.729). When the entropy parameter Cut-off point = 3.883, the sensitivity, specificity and accuracy of glioblastoma and PBL were 85.7, 86.4 and 86.0%, respectively, by differential diagnosis.
Texture analysis of tumor peritumoral edema provided quantifiable information, which might be a new method for differentiating glioblastoma from PBL. |
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ISSN: | 0268-8697 1360-046X |
DOI: | 10.1080/02688697.2020.1856783 |