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Radiogenomic classification of the 1p/19q status in presumed low-grade gliomas

机译:假定的低度神经胶质瘤的1p / 19q状态的放射基因组分类

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1p/19q co-deletion is an important prognostic factor in low grade gliomas. However, determination of the 1p/19q status currently requires a biopsy. To overcome this, we investigate a radiogenomic classification using support vector machines to non-invasively predict the 1p/19q status from multimodal MRI data. Different approaches of predicting this status were compared: a direct approach which predicts the 1p/19q co-deletion status and an indirect approach which predicts the mutation status of 1p and 19q individually and combines these predictions to predict the 1p/19q co-deletion status. Using the indirect approach based on both the T1-weighted and T2-weighted images delivered the best result and resulted in a 95% confidence interval for the sensitivity and specificity of [0.44; 0.89] and [0.70; 1.00] respectively.
机译:1p / 19q共缺失是低度神经胶质瘤的重要预后因素。但是,确定1p / 19q状态目前需要进行活检。为了克服这个问题,我们研究了使用支持向量机从多模式MRI数据无创地预测1p / 19q状态的放射基因组分类。比较了预测该状态的不同方法:预测1p / 19q共缺失状态的直接方法和预测1p和19q突变状态的间接方法,并结合这些预测以预测1p / 19q共缺失状态的间接方法。使用基于T1加权和T2加权图像的间接方法可提供最佳结果,并且敏感性和特异性为[0.44;结果为95%]。 0.89]和[0.70; 1.00]。

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