Name
Abstract | ||
|---|---|---|
Although magnetic resonance spectroscopy (MRS) methods of 1.5Tesla (T) and 3T have been widely applied during the last decade for noninvasive diagnostic purposes, only a few studies have been reported on the value of the information extracted in brain cancer discrimination. The purpose of this study is threefold. First, to show that the diagnostic value of the information extracted from two different MRS scanners of 1.5T and 3T is significantly influenced in terms of brain gliomas discrimination. Second, to statistically evaluate the discriminative potential of publicly known metabolic ratio markers, obtained from these two types of scanners in classifying low-, intermediate-, and high-grade gliomas. Finally, to examine the diagnostic value of new metabolic ratios in the discrimination of complex glioma cases where the diagnosis is both challenging and critical. Our analysis has shown that although the information extracted from 3T MRS scanner is expected to provide better brain gliomas discrimination; some factors like the features selected, the pulse-sequence parameters, and the spectroscopic data acquisition methods can influence the discrimination efficiency. Finally, it is shown that apart from the bibliographical known, new metabolic ratio features such as N-acetyl aspartate/S, Choline/S, Creatine/S , and myo-Inositol/S play significant role in gliomas grade discrimination. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TITB.2011.2131146 | IEEE Transactions on Information Technology in Biomedicine |
Keywords | Field | DocType |
magnetic resonance spectroscopy,feature extraction,magnetic resonance imaging,support vector machines,cancer,support vector machine,magnetic resonance image,data acquisition,indexing terms,information extraction,feature selection,data mining | Nuclear medicine,Brain gliomas,Data mining,Pattern recognition,Glioma,Artificial intelligence,Medicine,Discriminative model,Magnetic resonance imaging | Journal |
Volume | Issue | ISSN |
15 | 4 | 1089-7771 |
Citations | PageRank | References |
1 | 0.41 | 3 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michail M. Kounelakis | 1 | 1 | 0.41 |
| Ioannis N. Dimou | 2 | 6 | 1.20 |
| Michalis Zervakis | 3 | 199 | 21.30 |
| Ioannis Tsougos | 4 | 10 | 2.67 |
| E. E. Tsolaki | 5 | 1 | 0.41 |
| Evanthia Kousi | 6 | 10 | 1.31 |
| Eftychia E. Kapsalaki | 7 | 10 | 1.99 |
| Kyriaki Theodorou | 8 | 10 | 1.65 |