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Assessment of disease severity in a Canine Model of Duchenne Muscular Dystrophy: Classification of Quantitative MRI

机译:杜兴氏肌营养不良犬模型中疾病严重程度的评估:定量MRI的分类

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Duchenne muscular dystrophy (DMD) is a fatal X-linked muscle disorder caused by mutations in the dystrophin gene with a consequence of progressive degeneration of skeletal and cardiac muscle. Golden retriever muscular dystrophy (GRMD) is a spontaneous X-linked canine model of DMD with similar effects. Due to high soft-tissue contrast images, MRI is preferred as a non-invasive method to extract information corresponding to biological characteristics. We propose and evaluate non-invasive MRI-based imaging biomarkers to assess the severity of golden retriever muscular dystrophy (GRMD) using 3T and 4.7T MRI data of nine animals. These imaging biomarkers use first order statistics and texture (assessed by wavelets) in quantitative MRI (qMRI). In a leave-one-sample-out cross-validation framework, we use SVM to differentiate between young and old GRMD animals. The preliminary results show good differentiation between young and old animals for different qMRI sequences and based on a different selection of features.
机译:Duchenne肌营养不良症(DMD)是一种致命的X链肌病,由肌营养不良蛋白基因突变引起,骨骼肌和心肌进行性变性。金毛猎犬肌肉营养不良(GRMD)是DMD的自发X连锁犬模型,具有相似的作用。由于高的软组织对比度图像,MRI优选作为一种非侵入性方法来提取与生物学特征相对应的信息。我们提出和评估基于9种动物的3T和4.7T MRI数据的基于MRI的非侵入性成像生物标记物,以评估金毛猎犬肌肉营养不良(GRMD)的严重性。这些成像生物标记物在定量MRI(qMRI)中使用一阶统计量和纹理(通过小波评估)。在留一样的交叉验证框架中,我们使用SVM区分年老的GRMD动物。初步结果显示,对于不同的qMRI序列,以及基于不同的特征选择,幼小的动物和老年的动物之间存在良好的区分。

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