1. A metric for quantitative evaluation of glioma margin changes in magnetic resonance imaging.
- Author
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Hu, Binwu, Zhang, Zhiqiang, Chen, Suting, Xu, Qiang, and Li, Jianrui
- Subjects
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MAGNETIC resonance imaging , *GLIOMAS , *RECEIVER operating characteristic curves , *RANK correlation (Statistics) , *TUMOR grading - Abstract
Background: Gliomas differ from meningiomas in their margins, most of which are not separated from the surrounding tissue by a distinct interface. Purpose: To characterize the margins of gliomas quantitatively based on the margin sharpness coefficient (MSC) is significant for clinical judgment and invasive analysis of gliomas. Material and Methods: The data for this study used magnetic resonance image (MRI) data from 67 local patients and 15 open patients to quantify the intensity of changes in the glioma margins of the brain using MSC. The accuracy of MSC was assessed by consistency analysis and Bland–Altman test analysis, as well as invasive correlations using receiver operating characteristic (ROC) and Spearman correlation coefficients for subjects. Results: In grading the tumors, the mean MSC values were significantly lower for high-grade gliomas (HGG) than for low-grade gliomas (LGG). The concordance correlation between the measured gradient and the actual gradient was high (HGG: 0.981; LGG: 0.993), and the Bland–Altman mean difference at the 95% confidence interval (HGG: −0.576; LGG: 0.254) and the limits of concordance (HGG: 5.580; LGG: 5.436) indicated no statistical difference. The correlation between MSC and invasion based on the margins of gliomas showed an AUC of 0.903 and 0.911 for HGG and LGG, respectively. The mean Spearman correlation coefficient of the MSC versus the actual distance of invasion was −0.631 in gliomas. Conclusion: The relatively low MSC on the blurred margins and irregular shape of gliomas may help in benign-malignant differentiation and invasion prediction of gliomas and has potential application for clinical judgment. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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