0000000000376255
AUTHOR
Jan Luts
Differentiation between Brain Metastasis and Glioblastoma using MRI and two-dimensional Turbo Spectroscopic Imaging data
In this paper we propose a novel technique to differentiate brain metastases from high-grade gliomas, which represent the most aggressive and common brain lesions. In spite of the significant progresses achieved in the field of MRI in the last decades, the differentiation between these two types of tumors is still a challenge as they show a similar appearance on MRI images, but require a completely different therapeutic treatment. Here, we show that such a differentiation is actually possible and can be obtained by making use of MRI as well as of two-dimensional Turbo Spectroscopic Imaging (2D-TSI) information. Specifically, the proposed technique consists of three steps: we first detect th…
Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI
Brain metastases and glioblastoma multiforme are the most aggressive and common brain tumours in adults and they require a different clinical management. Anatomical magnetic resonance imaging (MRI) or clinical history, cannot always clearly distinguish between them. This study describes and verifies the use of magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging (MRSI) in combination with MRI for differential diagnosis of glioblastomas and metastases. Feature selection methods are applied to the magnetic resonance (MR) spectra of 121 patients and relevant features are detected. Different classification methods are used to distinguish glioblastoma multiforme and…
On the Implementation of HealthAgents: Agent-Based Brain Tumour Diagnosis
This paper introduces HealthAgents, an EC-funded research project to improve the classification of brain tumours through multi-agent decision support over a secure and distributed network of local databases or Data Marts. HealthAgents will not only develop new pattern recognition methods for distributed classification and analysis of in vivo MRS and ex vivo/in vitro HRMAS and DNA data, but also define a method to assess the quality and usability of a new candidate local database containing a set of new cases, based on a compatibility score. Using its Multi-Agent architecture, HealthAgents intends to apply cutting-edge agent technology to the Biomedical field and develop the HealthAgents net…
Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy
[EN] Automatic brain tumor classification by MRS has been under development for more than a decade. Nonetheless, to our knowledge, there are no published evaluations of predictive models with unseen cases that are subsequently acquired in different centers. The multicenter eTUMOUR project (2004-2009), which builds upon previous expertise from the INTERPRET project (2000-2002) has allowed such an evaluation to take place. A total of 253 pairwise classifiers for glioblastoma, meningioma, metastasis, and low-grade glial diagnosis were inferred based on 211 SV short TE INTERPRET MR spectra obtained at 1.5 T (PRESS or STEAM, 20-32 ms) and automatically pre-processed. Afterwards, the classifiers …