Grading of Meningioma Tumors Based on Analyzing Tumor Volumetric Histograms Obtained From Conventional Mri and Apparent Diffusion Coefficient Images Publisher



Haghighi Borujeini M¹ ; Farsizaban M^{2, 3} ; Yazdi SR⁴ ; Tolulope Agbele A⁵ ; Ataei G⁶ ; Saber K⁴ ; Hosseini SM⁷ ; Abedifirouzjah R⁸ Show Affiliations
Source: Egyptian Journal of Radiology and Nuclear Medicine Published:2021

Abstract

Background: Our purpose was to evaluate the application of volumetric histogram parameters obtained from conventional MRI and apparent diffusion coefficient (ADC) images for grading the meningioma tumors. Results: Tumor volumetric histograms of preoperative MRI images from 45 patients with the diagnosis of meningioma at different grades were analyzed to find the histogram parameters. Kruskal-Wallis statistical test was used for comparison between the parameters obtained from different grades. Multi-parametric regression analysis was used to find the model and parameters with high predictive value for the classification of meningioma. Mode; standard deviation on post-contrast T1WI, T2-FLAIR, and ADC images; kurtosis on post-contrast T1WI and T2-FLAIR images; mean and several percentile values on ADC; and post-contrast T1WI images showed significant differences among different tumor grades (P < 0.05). The multi-parametric linear regression showed that the ADC histogram parameters model had a higher predictive value, with cutoff values of 0.212 (sensitivity = 79.6%, specificity = 84.3%) and 0.180 (sensitivity = 70.9%, specificity = 80.8%) for differentiating the grade I from II, and grade II from III, respectively. Conclusions: The multi-parametric model of volumetric histogram parameters in some of the conventional MRI series (i.e., post-contrast T1WI and T2-FLAIR images) along with the ADC images are appropriate for predicting the meningioma tumors’ grade. © 2021, The Author(s).