Fig 1.
Segmentation of meningioma with a 3D-reconstructed model using the 3D slicer and estimation of the tumor volume (red box indicates the volume).
(A) an example of a 3D-reconstructed meningioma from one of the study patients and the volume shows about 14.8cc; (B) an example of a 3D-reconstructed meningioma from one of the study patients and the volume shows about 104.1 cc.
Table 1.
Characteristics of patients with convexity and parasagittal meningiomas classified according to peritumoral edema.
Fig 2.
Comparison of meningioma volume between PTBE and non-PTBE groups and determination of the optimal meningioma volume cut-off values for prediction of PTBE in patients with convexity and parasagittal meningiomas.
Boxplots of (A) meningioma volume in all patients and (B) meningioma volume classified by age group according to PTBE. ROC curve to identify the optimal cutoff values of (C) meningioma volume in all patients and (D) meningioma volume classified by age group for prediction of PTBE. PTBE = peritumoral brain edema; ROC = receiver operating characteristic.
Fig 3.
Scatterplot with LOWESS curve and boxplots for assessment of the association between PTBE grade and meningioma volume.
(A) Scatterplot with LOWESS curve showing the association between PTBE grade and meningioma volume in all patients; (B) Scatterplot with LOWESS curve showing the association between PTBE grade and meningioma volume classified by sex; (C) Scatterplot with LOWESS curve showing the association between PTBE grade and meningioma volume classified by age group; (D) Boxplots showing the comparison of meningioma volume between age groups according to PTBE grade. LOWESS = locally weighted scatter plot smoothing; PTBE = peritumoral brain edema.
Table 2.
Univariate and multivariate logistic regression analyses of the association between peritumoral edema and various variables in patients with convexity and parasagittal meningiomas.