Development of computerised scoring system for Chiari-like malformation associated pain and syringomyelia.

这项新研究的目的是建立在我们目前的合作工作的基础上，调查具体的研究问题，即什么，以及在多大程度上，外部构象特征与有问题的内部形态(例如深止口，短口吻，圆顶头，前面向大？眼眶浅，耳朵低)。这将通过以下目标来解决：为CKCS中的CM和SM建立了基于机器学习的回归模型。之前我们在二维中线矢状面MRI上使用了分类模型。我们将把这个模型扩展到从高分辨率三维（3D）磁化制备的梯度回波快速采集（MPRAGE）和CT确定的特征的3D分析。2.开发ML图像评估模型，从诊断mri和CT预测和评分CM-P和SM-S的风险。使用相关分析来了解与繁殖相关的相关特征（短口吻、圆前额、深度、宽睑孔）的外部组合如何与有问题的内部形态相关联。3.将模型扩展到其他短头犬品种，包括吉娃娃和格里芬布鲁塞洛斯。

The aim of this new study is to build on the our current collaborative work to investigate the specific research question of what, andwhat degree of, external conformational features are associated with problematic internal morphology (e.g. deep stop,short muzzle, domed head, forward facing oelarge? eyes in shallow orbits and low set ears). This will be addressedvia the following objectives: 1.Develop a Machine learning-based regression model for CM and SM in the CKCS.Previously we used a classifying model on 2D midline sagittal MRI. We will expand this model to a 3D analysis of featuresdetermined from high-resolution three-dimensional (3D) magnetization-prepared rapid acquisition with gradient echo(MPRAGE) and CT. 2.Develop a ML image assessment model to predict and score risk of CM-P and SM-S from diagnosticMRI and CT. Use Correlated Correlation Analysis to understand how combinations of correlated breeding-related features(short muzzle, domed forehead, depth of stop, wide palpebral apertures) externally correlate with problematic internalmorphology. 3.Expand the model to other brachycephalic breeds including the Chihuahua and Griffon Bruxellois.