Sumei Wang1, Sungheon Kim2, Yu
Zhang1, Lu Wang1, Edward B. Lee3, Peter Syre4,
John Y. K. Lee4, Harish Poptani1, Elias R. Melhem1
1Radiology, University of
Pennsylvania, Philadelphia, PA, United States; 2Radiology, New
York University School of Medicine, New York, NY, United States; 3Pathology
& Laboratory Medicine, University of Pennsylvania, Philadelphia, PA,
United States; 4Neurosurgery, University of Pennsylvania,
Philadelphia, PA, United States
The purpose of this study is to determine whether DTI metrics along with histogram analysis can help in grading and subtyping of meningiomas. Forty-five meningiomas underwent DTI studies. Logistic regression analysis indicated that mean of eigenvalue skewness (SK), kurtosis of FA, skewness of SK and kurtosis of SK comprised the best model to differentiate atypical from typical meningiomas. Mean of CL, CP, CS and skewness of CP comprised the best predictor to differentiate fibroblastic from other subtype meningiomas. Significantly increased mean FA, CP, LI and decreased CS were observed in fibroblastic subtypes compared with both atypical and other subtype meningiomas.