Histogram analysis in predicting the grade and histological subtype of meningiomas based on diffusion kurtosis imaging

Objectives Presurgical grading is particularly important for selecting the best therapeutic strategy for meningioma patients. Therefore, our study is to investigate the value of histogram analysis of diffusion kurtosis imaging (DKI) maps in the differentiation of grades and histological subtypes of meningiomas.Methods A total of 172 patients with histopathologically proven meningiomas underwent preoperative magnetic resonance imaging (MRI) and were classified into low-grade and high-grade groups. Mean Kurtosis (MK), fractional anisotropy (FA), mean diffusivity (MD) histograms were generated based on solid components of the whole tumour. The following parameters of each histogram were obtained：10th， 25th， 75th, and 90th percentiles, mean，median，maximum，minimum，and kurtosis, skewness, and variance. Comparisons of different grades and subtypes were made by Mann-Whitney U test，Kruskal-Wallis tests, ROC curves analysis, and multiple logistic regression.Results Significantly higher maximum, Skewness, and variance of MD, mean, median, maximum, variance, 10th, 25th, 75th, and 90th percentile of MK were found in high-grade than low-grade meningiomas (all P<0.05). DKI histogram parameters differentiated 7 of 10 pairs of subtype pairs (atypical versus meningothelial/ fibrous/transitional/angiomatous meningiomas; angiomatous versus fibrous/transitional meningioma; fibrous versus meningothelial meningiomas). The 90th percentile of MK yielded the highest AUC of 0.870 and was the only independent indicators for grading meningiomas.Conclusion The histogram analysis of DKI is useful for differentiating meningioma grades and subtypes. The 90th percentile of MK may serve as an optimal parameter for predicting the grade of meningiomas.