Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature.
Eur Radiol
; 28(7): 2960-2968, 2018 Jul.
Article
em En
| MEDLINE
| ID: mdl-29404769
ABSTRACT
OBJECTIVES:
To predict ATRX mutation status in patients with lower-grade gliomas using radiomic analysis.METHODS:
Cancer Genome Atlas (TCGA) patients with lower-grade gliomas were randomly allocated into training (n = 63) and validation (n = 32) sets. An independent external-validation set (n = 91) was built based on the Chinese Genome Atlas (CGGA) database. After feature extraction, an ATRX-related signature was constructed. Subsequently, the radiomic signature was combined with a support vector machine to predict ATRX mutation status in training, validation and external-validation sets. Predictive performance was assessed by receiver operating characteristic curve analysis. Correlations between the selected features were also evaluated.RESULTS:
Nine radiomic features were screened as an ATRX-associated radiomic signature of lower-grade gliomas based on the LASSO regression model. All nine radiomic features were texture-associated (e.g. sum average and variance). The predictive efficiencies measured by the area under the curve were 94.0 %, 92.5 % and 72.5 % in the training, validation and external-validation sets, respectively. The overall correlations between the nine radiomic features were low in both TCGA and CGGA databases.CONCLUSIONS:
Using radiomic analysis, we achieved efficient prediction of ATRX genotype in lower-grade gliomas, and our model was effective in two independent databases. KEY POINTS ⢠ATRX in lower-grade gliomas could be predicted using radiomic analysis. ⢠The LASSO regression algorithm and SVM performed well in radiomic analysis. ⢠Nine radiomic features were screened as an ATRX-predictive radiomic signature. ⢠The machine-learning model for ATRX-prediction was validated by an independent database.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Encefálicas
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Imageamento por Ressonância Magnética
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Proteína Nuclear Ligada ao X
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Genótipo
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Glioma
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Mutação
Tipo de estudo:
Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Eur Radiol
Assunto da revista:
RADIOLOGIA
Ano de publicação:
2018
Tipo de documento:
Article
País de afiliação:
China