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Revealing the metabolic profile of brain tumors for diagnosis purposes

Zervakis Michalis, G.J.Postma, Buydens, Lutgarde, M.G. Kounelakis

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URIhttp://purl.tuc.gr/dl/dias/29862FB5-7222-4A52-AAE1-820F88FB4FA8-
Αναγνωριστικόhttps://doi.org/10.1109/IEMBS.2009.5334984-
Γλώσσαen-
Μέγεθος4 pagesen
ΤίτλοςRevealing the metabolic profile of brain tumors for diagnosis purposesen
ΔημιουργόςZervakis Michalisen
ΔημιουργόςΖερβακης Μιχαληςel
Δημιουργός G.J.Postmaen
ΔημιουργόςBuydens, Lutgardeen
ΔημιουργόςM.G. Kounelakis en
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠερίληψηThe metabolic behavior of complex brain tumors, like gliomas and meningiomas, with respect to their type and grade was investigated in this paper. Towards this direction the smallest set of the most representative metabolic markers for each brain tumor type was identified, using ratios of peak areas of well established metabolites, from 1H-MRSI (proton magnetic resonance spectroscopy imaging) data of 24 patients and 4 healthy volunteers. A feature selection method that embeds Fisher's filter criterion into a wrapper selection scheme was applied; support vector machine (SVM) and least squares-SVM (LS-SVM) classifiers were used to evaluate the ratio markers classification significance. The area under the receiver operating characteristic curve (AUROC) was adopted to evaluate the classification significance. It is found that the NAA/CHO, CHO/S, MI/S ratios can be used to discriminate gliomas and meningiomas from Healthy tissue with AUROC greater than 0.98. Ratios CHO/S, CRE/S, MI/S, LAC/CRE, ALA/CRE, ALA/S and LIPS/CRE can identify type and grade differences in gliomas giving AUROC greater than 0.98 apart from the scheme of gliomas grade II vs grade III where 0.84 was recorded due to high heterogeneity. Finally NAA/CRE, NAA/S, CHO/S, MI/S and ALA/S manage to discriminate gliomas from meningiomas providing AUROC exceeding 0.90.en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-23-
Ημερομηνία Δημοσίευσης2009-
Θεματική ΚατηγορίαMedicineen
Βιβλιογραφική ΑναφοράM.G. Kounelakis, M.E. Zervakis, G.J. Postma, L.M.C. Buydens, A. Heerschap, "Revealing the metabolic profile of brain tumors for diagnosis purposes," in 2009 Annual Intern. Conf. of the IEEE Eng. in Medicine and Biol. Society, EMBC ,pp.35 - 38.doi:10.1109/IEMBS.2009.5334984en

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