Intelligent Management of Brain Markers for Early Prognosis of the Spatiotemporal Growth of Gliomas

Author

Toumpaniaris, Petros ; Verganelakis, Dimitris ; Spanoudakis, Nikos ; Zervakis, M.

Author_Institution

Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece

fYear

2014

fDate

10-12 Nov. 2014

Firstpage

647

Lastpage

651

Abstract

The diagnosis and treatment of brain gliomas has still many weaknesses and is followed by a high mortality rate and very low life expectancy. Facing towards the tendency for a personalized diagnosis and therapy, any effort should be focused to the spatiotemporal growth of the tumor for the early prognosis and treatment of the gliomas. In the above context, this study aims to analyze the brain markers choline (Cho) and fractional anisotropy (FA) in order to determine whether they are reliable indices of glioma presence in a brain region, before this region is damaged to such an extent that will be visible in the classic magnetic resonance imaging. This study is based on the experimental analysis of Cho from the spectrum of metabolites and FA from the diffusion tensor image, aiming ultimately to the improvement of the diagnosis and thus the therapy and the life expectancy rate of the patients suffering from glioma.

Keywords

biochemistry; biodiffusion; biomechanics; biomedical MRI; brain; data analysis; feature extraction; knowledge based systems; magnetic resonance spectroscopy; medical image processing; molecular biophysics; physiological models; spatiotemporal phenomena; spectral analysis; spectrochemical analysis; tensors; tumours; FA analysis; brain glioma diagnosis; brain glioma treatment; brain marker analysis; brain marker management; brain region damage; choline analysis; diffusion tensor image; early glioma growth prognosis; early glioma treatment; fractional anisotropy analysis; glioma presence index; intelligent management; life expectancy rate; magnetic resonance imaging; metabolite spectrum; personalized diagnosis; personalized therapy; spatiotemporal glioma growth; spatiotemporal tumor growth; Anisotropic magnetoresistance; Diffusion tensor imaging; Image color analysis; Lesions; Prognostics and health management; MRI; brain markers; brain tumor; choline; diffusion tensor; early prognosis; fractional anisotropy; glioma; spatiotemporal diffusion;

fLanguage

English

Publisher

ieee

Conference_Titel

Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on

Conference_Location

Limassol

ISSN

1082-3409

Type

conf

DOI

10.1109/ICTAI.2014.102

Filename

6984538