title: Fractional anisotropy and tumor cell density of the tumor core show positive correlation in diffusion tensor magnetic resonance imaging of malignant brain tumors.
abstract: A noninvasive technique for assessing tumor tissue characteristics is required to assist preoperative surgical planning for malignant brain tumors. Preoperative information on tumor cell density within a tumor would help better define the target for tumor biopsy, resulting in more accurate diagnosis and grading of malignant brain tumors. One possible source of this information is diffusion tensor imaging (DTI), although to date studies have focused on its ability to delineate white matter fiber tracks by fiber-tracking and to detect tumor infiltration around the tumor and normal white matter interface. However, the use of DTI for providing information on cell density has also been examined, although with the controversial results. In addition the exact relationships between cell density and the two key values that DTI provides, namely fractional anisotropy (FA) and mean diffusivity (MD), still need to be investigated. In the present study we performed a retrospective investigation of tumor cell density and FA and MD values in biopsy cases. We found that FA has a good positive correlation (R=0.75) and MD has a good negative correlation (R=0.70) with tumor cell density within the tumor core. Similar correlation was observed between the Ki-67 labeling index and FA (R=0.71) and MD (R=0.62). Thus, measurement of both FA and MD within the tumor core has a potential to provide detailed information on tumor cell density within the tumor. Although data obtained from DTI should be interpreted carefully and comprehensively with other imaging modalities such as positron emission tomography, DTI seems to be informative for planning the best biopsy target containing the highest cell density.
authors.affiliation: Department of Neurosurgery, Osaka University Gradate School of Medicine, 2-2 Yamadoka, Suita, Osaka 565-0871, Japan. m-kinoshita@nsurg.med.osaka-u.ac.jp
authors.forename: Manabu
authors.initials: M
authors.lastname: Kinoshita
authors.forename: Naoya
authors.initials: N
authors.lastname: Hashimoto
authors.forename: Tetsu
authors.initials: T
authors.lastname: Goto
authors.forename: Naoki
authors.initials: N
authors.lastname: Kagawa
authors.forename: Haruhiko
authors.initials: H
authors.lastname: Kishima
authors.forename: Shuichi
authors.initials: S
authors.lastname: Izumoto
authors.forename: Hisashi
authors.initials: H
authors.lastname: Tanaka
authors.forename: Norihiko
authors.initials: N
authors.lastname: Fujita
authors.forename: Toshiki
authors.initials: T
authors.lastname: Yoshimine
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016880:Anisotropy; D001932:Brain Neoplasms / Q000473:pathology*; D002452:Cell Count / Q000379:methods*; D002648:Child; D002675:Child, Preschool; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic