title: Diffusion tensor analysis of peritumoral edema using lambda chart analysis indicative of the heterogeneity of the microstructure within edema.
abstract: OBJECTIVE
  Histopathological studies indicate that cerebral edema associated with tumors (peritumoral edema) does not represent a single pathophysiological or clinical entity. In this study the authors investigated peritumoral edema by performing lambda chart analysis (LCA), a noninvasive technique that can be used to make visible and analyze apparent water diffusivity in tissues in vivo, and assessed the utility of LCA in differentiating high-grade gliomas from nonglial tumors.
  
  
  METHODS
  The water diffusivity characteristics of peritumoral edema associated with four tumor groups-12 high-grade gliomas, five low-grade gliomas, 11 metastatic tumors, and 15 meningiomas-were assessed in 43 patients by performing magnetic resonance imaging with the aid of a 3-tesla magnetic resonance imaging system. In all tumor groups, peritumoral edema exhibited greater trace values and reduced anisotropy compared with normal white matter. Edema associated with high-grade gliomas had significantly higher trace values than edema associated with the other three tumor groups, although the anisotropic angles of those groups were comparable.
  
  
  CONCLUSIONS
  Lambda chart analysis identified two distinct types of peritumoral edema: edema associated with high-grade gliomas and edema associated with low-grade gliomas or nonglial tumors. The apparent water diffusivity was significantly greater in high-grade gliomas, whereas the anisotropy in these lesions was comparable to that of edema in other tumors. These findings indicated that water movement in areas of edema, predominantly in the extracellular spaces, was less restricted in high-grade gliomas, a phenomenon that likely reflected the destruction of the extracellular matrix ultrastructure by malignant cell infiltration and consequently greater water diffusion. Although preliminary, this study indicates that LCA could be used as a clinical tool for differentiating high-grade gliomas and for evaluating the extent of cellular infiltration.
authors.affiliation: Center for Integrated Human Brain Science, Department of Neurosurgery, Brain Research Institute, University of Niigata, Japan.
authors.forename: Ken-ichi
authors.initials: K
authors.lastname: Morita
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Matsuzawa
authors.forename: Yukihiko
authors.initials: Y
authors.lastname: Fujii
authors.forename: Ryuichi
authors.initials: R
authors.lastname: Tanaka
authors.forename: Ingrid L
authors.initials: IL
authors.lastname: Kwee
authors.forename: Tsutomu
authors.initials: T
authors.lastname: Nakada
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D016880:Anisotropy; D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000145:classification / Q000473:pathology* / Q000556:secondary; D002648:Child; D003196:Computer Graphics; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D005910:Glioma / Q000145:classification / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008432:Mathematical Computing; D008577:Meningeal Neoplasms / Q000473:pathology*; D008579:Meningioma / Q000473:pathology*; D008875:Middle Aged; D011379:Prognosis; D012680:Sensitivity and Specificity