A Predictive Model of Vertebral Trabecular Anisotropy From Ex Vivo Micro-CT
A Predictive Model of Vertebral Trabecular Anisotropy From Ex Vivo Micro-CT
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DOI：
10.1109/tmi.2014.2387114
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发表时间：
2015-08-01
影响因子：
10.6
通讯作者：
Frangi, Alejandro F.
中科院分区：
文献类型：
--
作者：
Lekadir, Karim;Hoogendoorn, Corne;Frangi, Alejandro F.
脊柱相关疾病是临床医学中最常见的问题之一。对于一些应用，如1)改善脊柱强度的评估，以及2)优化脊柱干预的个性化，基于图像的脊椎生物力学建模有望发挥重要的预测作用。然而，这需要构建特定于学科和全面的计算模型。特别是，他们需要结合关于椎骨各向异性微结构的信息，这在椎骨的生物力学功能中发挥着核心作用。然而，在实践中，脊椎小梁的准确个性化已被证明是困难的，因为其在体内的成像目前是不可行的。因此，本文提出了一种基于体外显微CT图像训练样本的精确预测椎体结构张量的统计方法。据我们所知，这是第一个提出并验证脊椎数据集的预测模型。该方法将特征选择和偏最小二乘回归相结合，根据更容易提取的形状和密度信息，得到预测织物张量的最优潜变量。对20个体外T12椎骨的详细验证表明，该方法对于小梁各向异性个性化的准确性和一致性。
Spine-related disorders are amongst the most frequently encountered problems in clinical medicine. For several applications such as 1) to improve the assessment of the strength of the spine, as well as 2) to optimize the personalization of spinal interventions, image-based biomechanical modeling of the vertebrae is expected to play an important predictive role. However, this requires the construction of computational models that are subject-specific and comprehensive. In particular, they need to incorporate information about the vertebral anisotropic micro-architecture, which plays a central role in the biomechanical function of the vertebrae. In practice, however, accurate personalization of the vertebral trabeculae has proven to be difficult as its imaging in vivo is currently infeasible. Consequently, this paper presents a statistical approach for accurate prediction of the vertebral fabric tensors based on a training sample of ex vivo micro-CT images. To the best of our knowledge, this is the first predictive model proposed and validated for vertebral datasets. The method combines features selection and partial least squares regression in order to derive optimal latent variables for the prediction of the fabric tensors based on the more easily extracted shape and density information. Detailed validation with 20 ex vivo T12 vertebrae demonstrates the accuracy and consistency of the approach for the personalization of trabecular anisotropy.