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Abstract Background Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn’t been fully investigated for the differentiation and may have the potential to improve it. Methods A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance. Results Higher ADC kurtosis ( P = 0.022), frac kurtosis ( P <0.001),and frac skewness ( P <0.001) were found for glioma, while higher (MTRasym@3.5ppm) 10 ( P = 0.045), frac 10 ( P <0.001),frac 90 ( P = 0.001), frac mean ( P <0.001), and frac entropy ( P <0.001) were observed for SBM. frac kurtosis (OR = 0.431, 95%CI 0.256–0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm) 10 , frac 10 , and frac kurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac 10 and frac kurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25). Conclusions The frac 10 and frac kurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm) 10 helps improving the differentiation specificity.
Su et al. (Fri,) studied this question.
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