title: Role of diffusion tensor imaging in differentiating subtypes of meningiomas.
abstract: OBJECTIVE
  Meningiomas are the most common extraaxial intracranial type of tumor, and their management and prognosis depend on their grade and histology. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are two new imaging techniques that have proved helpful in elucidating the microarchitecture of brain tumors. The aim of the present study was to assess the role of diffusion and diffusion tensor metrics in the identification and classification of meningioma grades and subtypes.
  
  
  METHODS
  A total of 21 consecutive patients with meningioma were included in this retrospective study, of whom 16 had benign meningiomas (three fibroblastic, 11 transitional/mixed, two meningothelial) and five had atypical meningiomas. Tumor mean diffusivity (Dav), fractional anisotropy (FA), linear anisotropy (CL), planar anisotropy (CP), spherical anisotropy (CS) and eigenvalues (e1, e2, e3) were measured in all cases, and differences in diffusion tensor metrics between atypical, fibroblastic and other benign (transitional, meningothelial) meningiomas were statistically analyzed using the Mann-Whitney test.
  
  
  RESULTS
  No statistically significant differences were found among the mean Dav values for atypical, fibroblastic and other benign meningiomas. Both atypical and fibroblastic meningiomas showed significantly higher mean FA values and lower mean CS values compared with other meningiomas (P<0.01), but no statistically significant difference in these values between each other. Atypical meningiomas showed higher CL values compared with fibroblastic and other benign meningiomas but, again, the difference was not statistically significant. Both atypical and fibroblastic meningiomas showed statistically significantly higher CP values and lower e3 values compared with transitional meningiomas (P<0.01).
  
  
  CONCLUSIONS
  These results suggest that diffusion tensor metrics may be helpful in the differentiation of atypical, fibroblastic and other benign meningiomas.
authors.affiliation: Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical sciences and Technology, Trivandrum 695011, India.
authors.forename: M
authors.initials: M
authors.lastname: Jolapara
authors.forename: C
authors.initials: C
authors.lastname: Kesavadas
authors.forename: V V
authors.initials: VV
authors.lastname: Radhakrishnan
authors.forename: B
authors.initials: B
authors.lastname: Thomas
authors.forename: A K
authors.initials: AK
authors.lastname: Gupta
authors.forename: N
authors.initials: N
authors.lastname: Bodhey
authors.forename: S
authors.initials: S
authors.lastname: Patro
authors.forename: J
authors.initials: J
authors.lastname: Saini
authors.forename: U
authors.initials: U
authors.lastname: George
authors.forename: P S
authors.initials: PS
authors.lastname: Sarma
mesh_terms: D000328:Adult; D000368:Aged; D016880:Anisotropy; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008577:Meningeal Neoplasms / Q000145:classification / Q000473:pathology*; D008579:Meningioma / Q000145:classification / Q000473:pathology*; D008875:Middle Aged; D012189:Retrospective Studies; D018709:Statistics, Nonparametric