Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/53207
Type: Artigo de periódico
Title: Manual and semi-automatic quantification of in vivo H-1-MRS data for the classification of human primary brain tumors
Author: Cuellar-Baena, S
Morais, LMTS
Cendes, F
Faria, AV
Castellano, G
Abstract: In vivo proton magnetic resonance spectroscopy (H-1-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, H-1-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of H-1-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel H-1-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that H-1-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.
Subject: Proton magnetic resonance spectroscopy
Brain tumors
AMARES
Tumor classification
Country: Brasil
Editor: Assoc Bras Divulg Cientifica
Rights: aberto
Date Issue: 2011
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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