Literature DB >> 15691732

Intraoperative tumor segmentation and volume measurement in MRI-guided glioma surgery for tumor resection rate control.

Nobuhiko Hata1, Yoshihiro Muragaki, Takashi Inomata, Takashi Maruyama, Hiroshi Iseki, Tomokatsu Hori, Takeyoshi Dohi.   

Abstract

RATIONALE AND
OBJECTIVES: 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.
MATERIALS AND 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.
CONCLUSION: 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.

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Year:  2005        PMID: 15691732     DOI: 10.1016/j.acra.2004.11.009

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  3 in total

1.  Acquisition models in intraoperative positron surface imaging.

Authors:  Frédéric Monge; Dzhoshkun I Shakir; Florence Lejeune; Xavier Morandi; Nassir Navab; Pierre Jannin
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-10-06       Impact factor: 2.924

2.  A neurosurgical navigation system based on intraoperative tumour remnant estimation.

Authors:  Jaesung Hong; Yoshihiro Muragaki; Ryoichi Nakamura; Makoto Hashizume; Hiroshi Iseki
Journal:  J Robot Surg       Date:  2007-02-10

3.  Anatomic compression caused by high-volume convection-enhanced delivery to the brain.

Authors:  Francisco Valles; Massimo S Fiandaca; John Bringas; Peter Dickinson; Richard LeCouteur; Robert Higgins; Mitchel Berger; John Forsayeth; Krystof S Bankiewicz
Journal:  Neurosurgery       Date:  2009-09       Impact factor: 4.654

  3 in total

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