Format

Send to:

Choose Destination
See comment in PubMed Commons below
AJNR Am J Neuroradiol. 2011 Jan;32(1):67-73. doi: 10.3174/ajnr.A2269. Epub 2010 Nov 4.

Discrimination between metastasis and glioblastoma multiforme based on morphometric analysis of MR images.

Author information

  • 1Institute for Molecules and Materials, Analytical Chemistry Radboud University Nijmegen, Nijmegen, the Netherlands. l.blanchet@science.ru.nl

Abstract

BACKGROUND AND PURPOSE:

Solitary MET and GBM are difficult to distinguish by using MR imaging. Differentiation is useful before any metastatic work-up or biopsy. Our hypothesis was that MET and GBM tumors differ in morphology. Shape analysis was proposed as an indicator for discriminating these 2 types of brain pathologies. The purpose of this study was to evaluate the accuracy of this approach in the discrimination of GBMs and brain METs.

MATERIALS AND METHODS:

The dataset consisted of 33 brain MR imaging sets of untreated patients, of which 18 patients were diagnosed as having a GBM and 15 patients, as having solitary metastatic brain tumor. The MR imaging was segmented by using the K-means algorithm. The resulting set of classes (also called "clusters") represented the variety of tissues observed. A morphology-based approach allowed discrimination of the 2 types of tumors. This approach was validated by a leave-1-patient-out procedure.

RESULTS:

A method was developed for the discrimination of GBMs and solitary METs. Two masses out of 33 were wrongly classified; the overall results were accurate in 93.9% of the observed cases.

CONCLUSIONS:

A semiautomated method based on a morphologic analysis was developed. Its application was found to be useful in the discrimination of GBM from solitary MET.

PMID:
21051512
[PubMed - indexed for MEDLINE]
Free full text
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for HighWire
    Loading ...
    Write to the Help Desk