OBJECTIVE: Oligodendroglial tumors form an uncommon, but distinct, subgroup of gliomas with longer survival, better treatment response, and characteristic genetic alterations. Noninvasive grading of oligodendroglial tumors using functional and metabolic magnetic resonance imaging may be helpful in guiding the treatment approach and predicting malignant transformation of these tumors. We used perfusion-weighted magnetic resonance imaging and proton magnetic resonance spectroscopic imaging (MRSI) to predict the oligodendroglioma grade. METHODS: Twenty-four patients with pathologically confirmed oligodendrogliomas underwent dynamic contrast-enhanced perfusion-weighted magnetic resonance imaging and/or proton MRSI before surgery. We assessed the ability of tumor contrast enhancement, normalized cerebral blood volume, normalized choline, and the presence of either lactate or lipid metabolites to correctly predict the World Health Organization tumor grade. The accuracy of tumor grading using each method was also compared. RESULTS: Tumor contrast enhancement (P = 0.069) and normalized cerebral blood volume (P = 0.181) were not significantly different between low and high-grade oligodendrogliomas. The MRSI measurement of normalized choline was significantly higher in high-grade (2.82 +/- 0.64) than in low-grade (1.62 +/- 0.46) oligodendrogliomas (P < 0.001), and the presence of lactate or lipid metabolites also correctly predicted high-grade tumors (P = 0.014). The maximum accuracy of contrast enhancement, normalized cerebral blood volume, normalized choline, and lactate or lipid metabolites in grading oligodendroglioma was 71, 83, 90, and 85%, respectively. CONCLUSION: MRSI measurements are more accurate than perfusion-weighted magnetic resonance imaging or conventional contrast enhancement in differentiating oligodendroglial tumor grade. In these inherently vascular tumors, metabolic measurements of mitosis and necrosis may be better than measures of neovascularity in presurgical grading.
OBJECTIVE:Oligodendroglial tumors form an uncommon, but distinct, subgroup of gliomas with longer survival, better treatment response, and characteristic genetic alterations. Noninvasive grading of oligodendroglial tumors using functional and metabolic magnetic resonance imaging may be helpful in guiding the treatment approach and predicting malignant transformation of these tumors. We used perfusion-weighted magnetic resonance imaging and proton magnetic resonance spectroscopic imaging (MRSI) to predict the oligodendroglioma grade. METHODS: Twenty-four patients with pathologically confirmed oligodendrogliomas underwent dynamic contrast-enhanced perfusion-weighted magnetic resonance imaging and/or proton MRSI before surgery. We assessed the ability of tumor contrast enhancement, normalized cerebral blood volume, normalized choline, and the presence of either lactate or lipid metabolites to correctly predict the World Health Organization tumor grade. The accuracy of tumor grading using each method was also compared. RESULTS:Tumor contrast enhancement (P = 0.069) and normalized cerebral blood volume (P = 0.181) were not significantly different between low and high-grade oligodendrogliomas. The MRSI measurement of normalized choline was significantly higher in high-grade (2.82 +/- 0.64) than in low-grade (1.62 +/- 0.46) oligodendrogliomas (P < 0.001), and the presence of lactate or lipid metabolites also correctly predicted high-grade tumors (P = 0.014). The maximum accuracy of contrast enhancement, normalized cerebral blood volume, normalized choline, and lactate or lipid metabolites in grading oligodendroglioma was 71, 83, 90, and 85%, respectively. CONCLUSION: MRSI measurements are more accurate than perfusion-weighted magnetic resonance imaging or conventional contrast enhancement in differentiating oligodendroglial tumor grade. In these inherently vascular tumors, metabolic measurements of mitosis and necrosis may be better than measures of neovascularity in presurgical grading.
Authors: Maaike J Vos; Johannes Berkhof; Otto S Hoekstra; Ingeborg Bosma; Eefje M Sizoo; Jan J Heimans; Jaap C Reijneveld; Esther Sanchez; Frank J Lagerwaard; Jan Buter; David P Noske; Tjeerd J Postma Journal: Neuroradiology Date: 2011-07-14 Impact factor: 2.804
Authors: A Romano; M C Rossi Espagnet; L F Calabria; V Coppola; L Figà Talamanca; V Cipriani; G Minniti; A Pierallini; L M Fantozzi; A Bozzao Journal: Radiol Med Date: 2011-09-02 Impact factor: 3.469
Authors: L Khalid; M Carone; N Dumrongpisutikul; J Intrapiromkul; D Bonekamp; P B Barker; D M Yousem Journal: AJNR Am J Neuroradiol Date: 2012-01-19 Impact factor: 3.825
Authors: S Fellah; D Caudal; A M De Paula; P Dory-Lautrec; D Figarella-Branger; O Chinot; P Metellus; P J Cozzone; S Confort-Gouny; B Ghattas; V Callot; N Girard Journal: AJNR Am J Neuroradiol Date: 2012-12-06 Impact factor: 3.825
Authors: Gurpreet S Kapoor; Timothy A Gocke; Sanjeev Chawla; Robert G Whitmore; Ali Nabavizadeh; Jaroslaw Krejza; Joanna Lopinto; Justin Plaum; Eileen Maloney-Wilensky; Harish Poptani; Elias R Melhem; Kevin D Judy; Donald M O'Rourke Journal: J Neurooncol Date: 2009-04-09 Impact factor: 4.130