title: Rapid and Accurate MRI Segmentation of Peritumoral Brain Edema in Meningiomas.
abstract: OBJECTIVE
  The extent of peritumoral brain edema (PTBE) in meningiomas commonly affects the clinical outcome. Despite its importance, edema volume is usually highly inaccurately approximated to a spheroid shape. We tested the accuracy and the reproducibility of semiautomatic lesion management software for the analysis of PTBE in a homogeneous case series of surgically confirmed intracranial meningiomas.
  
  
  METHODS
  PTBE volume was calculated on magnetic resonance images in 50 patients with intracranial meningiomas using commercial lesion management software (Vue PACS Livewire, Carestream, Rochester, NY, USA). Inter and intraobserver agreement evaluation and a comparison between manual volume calculation, the semiautomatic software and spheroid approximation were performed in 22 randomly selected patients.
  
  
  RESULTS
  The calculation of edema volume was possible in all cases irrespective of the extent of the signal changes. The median time for each calculation was 3 min. Interobserver and intraobserver agreement confirmed the reproducibility of the method. Comparison with standard (fully manual) calculation confirmed the accuracy of this software.
  
  
  CONCLUSIONS
  Our study showed a high level of reproducibility of this semiautomatic computational method for peritumoral brain edema. It is rapid and easy to use after relatively short training and is suitable for implementation in clinical practice.
authors.affiliation: Department of Neuroscience, Section of Neurosurgery, Uppsala University, Akademiska Sjukhuset, ing 85, 2 tr, 751 85, Uppsala, Sweden. francesco.latinimd@gmail.com.
authors.forename: F
authors.initials: F
authors.lastname: Latini
authors.affiliation: Department of Surgical sciences, Section of Radiology, Uppsala University, Uppsala, Sweden.
authors.forename: E-M
authors.initials: EM
authors.lastname: Larsson
authors.affiliation: Department of Neuroscience, Section of Neurosurgery, Uppsala University, Akademiska Sjukhuset, ing 85, 2 tr, 751 85, Uppsala, Sweden.
authors.forename: M
authors.initials: M
authors.lastname: Ryttlefors
mesh_terms: D000293:Adolescent; D000328:Adult; D001929:Brain Edema / Q000000981:diagnostic imaging* / Q000473:pathology; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D000069550:Machine Learning; D008297:Male; D008577:Meningeal Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008579:Meningioma / Q000000981:diagnostic imaging* / Q000473:pathology; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Meningiomas; Peritumoral brain edema; Semiautomatic segmentation