Personalised Lower Limb Bone Models in a Paediatric Population

Statistical shape model for the pelvis, femur, and tibia/fibula of children aged 4-18 years. The dataset consisted of 333 CT scans. From PCA weights, partial least squares regression can be used to predict bone shapes using demographic inputs such as age, height, and weight. The shape model predicted bone geometry with root mean squared error (RMSE) of 2.91±0.99mm in the pelvis, 2.01±0.62mm in the femur, and 1.85±0.54mm in the tibia/fibula. <br/><br/>This project includes the following software/data packages: <br/> <ul> <li> <a href="https://simtk.org/frs?group_id=2210#pack_2314">Lower_limb_bone_pred </a> : Predict lower limb bones in a paediatric population using demographic and linear bone measurements. </li> <li> <a href="https://simtk.org/frs?group_id=2210#pack_2402">Paediatric bone measurements </a> : Data from the paper:Carman, L., Besier, T., Stott, N. S., & Choisne, J. (2023). Sex differences in linear bone measurements occur following puberty but do not influence femoral or tibial torsion. Scientific Reports, 13(1), 11733. https://doi.org/10.1038/s41598-023-38783-6Contains clinical bone measurements of a typically developed paediatric population aged 4 to 18 years taken from 333 CT scans. </li> </ul>

针对4至18岁儿童骨盆、股骨及胫腓骨的统计形状模型。该数据集包含333份CT扫描图像。通过主成分分析（PCA）权重，可利用部分最小二乘回归（PLSR）技术，基于年龄、身高和体重等人口统计学输入预测骨骼形状。该形状模型在骨盆、股骨及胫腓骨的预测中，分别实现了2.91±0.99毫米、2.01±0.62毫米和1.85±0.54毫米的均方根误差（RMSE）。本课题涉及以下软件/数据包：

<ul>
<li><a href="https://simtk.org/frs?group_id=2210#pack_2314">Lower_limb_bone_pred</a>：利用人口统计学和线性骨骼测量值，在儿童人群中预测下肢骨骼。</li>
<li><a href="https://simtk.org/frs?group_id=2210#pack_2402">Paediatric bone measurements</a>：源于论文：Carman, L.，Besier, T.，Stott, N. S.，& Choisne, J. (2023). Puberty-induced sex differences in linear bone measurements and their non-influence on femoral or tibial torsion. Scientific Reports, 13(1), 11733. https://doi.org/10.1038/s41598-023-38783-6，包含从333份CT扫描中提取的典型发育儿童人群（4至18岁）的临床骨骼测量数据。</li>
</ul>