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

机译:Duchenne肌营养不良犬犬模型评估疾病严重程度:定量MRI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-连接肌障碍,其患肌肌蛋白基因突变引起,后果骨骼和心肌的进步变性。金毛猎犬肌营养不良(GRMD)是一种具有类似效果的DMD的自发X型犬模型。由于高软组织对比图像,优选MRI作为非侵入性方法,以提取对应于生物学特性的信息。我们建议和评估非侵入性的基于MRI成像生物标志物评估采用九只动物的3T和4.7T MRI数据金毛肌营养不良症(GRMD)的严重程度。这些成像生物标志物在定量MRI(QMRI)中使用一阶统计和纹理(由小波评估)。在一个休假的交叉验证框架中,我们使用SVM来区分年轻和旧的GRMD动物。初步结果显示出不同QMRI序列的年轻和旧动物之间的良好差异,并基于不同的特征选择。

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