title: Magnetic resonance imaging based volume estimation of ovarian tumours: use of a segmentation and 3D reformation software.
abstract: The application of a new segmentation software, Anatomatic in the evaluation of volumetric measurements of ovarian tumours and the new Medimag three-dimensional (3D) software in the evaluation of 3D image representation of ovarian tumours with 1.5 T magnetic resonance imaging (MRI) is described. Our goal was to compare MRI based volumetry with operative findings at laparotomy for six consecutive patients with suspected ovarian tumours. Volumetric analysis and three dimensional image reconstructions of the tumours were obtained. At laparotomy, the tumour sizes were measured in situ, and the volumes were calculated. Using Anatomatic, reproducible tumour volumes were achieved with ease and within a reasonably fast time in patients with ovarian tumours without ascites. Medimag helped achieve realistic 3D representations of the tumours. For the four solitary tumours segmentation based volumetry and laparotomy findings agreed in three cases. In one patient with an oval shaped tumour, the segmented volume was double as compared to that estimated at laparotomy. Of the two patients with multiple tumours, both patients had significant ascites, and volumetry misinterpreted the fluid as tumour cyst fluid and markedly overestimated the tumour size. In conclusion, the MRI based segmentation volumetry and 3D image reconstructions are rapid, and reproducible methods of measuring ovarian tumours in patients without significant ascites.
authors.affiliation: Department of Diagnostic Radiology, Tampere University Hospital, Tampere, Finland. prasun@koti.tpo.fi
authors.forename: P
authors.initials: P
authors.lastname: Dastidar
authors.forename: J
authors.initials: J
authors.lastname: Mäenpää
authors.forename: T
authors.initials: T
authors.lastname: Heinonen
authors.forename: T
authors.initials: T
authors.lastname: Kuoppala
authors.forename: M
authors.initials: M
authors.lastname: Van Meer
authors.forename: R
authors.initials: R
authors.lastname: Punnonen
authors.forename: E
authors.initials: E
authors.lastname: Laasonen
mesh_terms: D000328:Adult; D000368:Aged; D001201:Ascites / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000706:statistics & numerical data; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000473:pathology*; D015203:Reproducibility of Results; D012984:Software