title: Intraoperative tumor segmentation and volume measurement in MRI-guided glioma surgery for tumor resection rate control.
abstract: OBJECTIVE
  Gross-total surgery under intraoperative magnetic resonance imaging (MRI) is a promising method of glioma removal. The purpose of this article is intraoperative measurement of resected tumor volume in MRI-guided glioma surgery using semiautomatic image segmentation to unbiased resection rate control.
  
  
  METHODS
  A newly developed software program based on a fuzzy connectedness (FC) segmentation algorithm was used to achieve fast and semiautomatic tumor segmentation and tumor volume measurement. The program was validated by retrospective study of eight glioma cases and then applied to seven glioma cases. All clinical cases underwent actual MRI-guided surgery using 0.3-T open magnets.
  
  
  RESULTS
  The volume of the tumor before resection ranged from 10.1 to 206.7 mL. A comparison of the results of manual segmentation with those of the semiautomatic FC-based segmentation gave an average dice similarity coefficient of 0.80 and an average match of 76%. Volume measurement combined with a developed software program enabled quantitative monitoring of tumor removal, which was critical in the near-total resection of glioma in MRI-guided surgery.
  
  
  CONCLUSIONS
  The FC-based tumor segmentation method can be used for intraoperative tumor segmentation and volume measurement in MRI-guided glioma surgery using 0.3-T open magnets. This method is useful for objective resection rate monitoring, which may ultimately minimize the amount of residual tumor in glioma surgery.
authors.affiliation: Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. noby@atre.t.u-tokyo.ac.jp
authors.forename: Nobuhiko
authors.initials: N
authors.lastname: Hata
authors.forename: Yoshihiro
authors.initials: Y
authors.lastname: Muragaki
authors.forename: Takashi
authors.initials: T
authors.lastname: Inomata
authors.forename: Takashi
authors.initials: T
authors.lastname: Maruyama
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Iseki
authors.forename: Tomokatsu
authors.initials: T
authors.lastname: Hori
authors.forename: Takeyoshi
authors.initials: T
authors.lastname: Dohi
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D001932:Brain Neoplasms / Q000473:pathology / Q000601:surgery*; D005240:Feasibility Studies; D005260:Female; D017143:Fuzzy Logic; D005910:Glioma / Q000473:pathology / Q000601:surgery*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007430:Intraoperative Care; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D018365:Neoplasm, Residual; D015642:Radiology, Interventional; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012984:Software; D025321:Surgery, Computer-Assisted