Adaptive quantification and longitudinal analysis of pulmonary emphysema with a hidden Markov measure field model.
Adaptive quantification and longitudinal analysis of pulmonary emphysema with a hidden Markov measure field model.
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DOI：
10.1109/tmi.2014.2317520
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发表时间：
2014-07
影响因子：
10.6
通讯作者：
Laine AF
中科院分区：
文献类型：
--
作者：
Hame Y;Angelini ED;Hoffman EA;Barr RG;Laine AF
肺气肿的程度通常通过计算低于预定义衰减阈值的体素的比例面积从CT图像估计。然而，这种方法的可靠性受到影响肺部CT强度分布的几个因素的限制。这项工作提出了一种新的方法，肺气肿量化，参数化建模的基础上的强度分布在肺和隐马尔可夫测量场模型分割肺气肿区域。该框架适应于图像的特征，以确保在不同的CT成像协议和由于诸如吸气水平的因素引起的实质强度分布的差异下肺气肿的稳健量化。与标准方法相比，本模型涉及大量的参数，其中大部分可以从数据中估计，以处理肺部CT扫描中遇到的变异性。该方法用于量化87名受试者的肺气肿，并使用不同的成像协议在8年内重复进行CT扫描。大约每年采集一次扫描，数据集共包括365次扫描。结果表明，所提出的方法产生的肺气肿估计有很高的主题内的相关值。通过降低对成像协议变化的敏感性，该方法提供了比标准方法更稳健的估计。此外，所产生的肺气肿划定承诺肺气肿的程度和进展，可能推进疾病亚型的区域分析的巨大优势。
The extent of pulmonary emphysema is commonly estimated from CT images by computing the proportional area of voxels below a predefined attenuation threshold. However, the reliability of this approach is limited by several factors that affect the CT intensity distributions in the lung. This work presents a novel method for emphysema quantification, based on parametric modeling of intensity distributions in the lung and a hidden Markov measure field model to segment emphysematous regions. The framework adapts to the characteristics of an image to ensure a robust quantification of emphysema under varying CT imaging protocols and differences in parenchymal intensity distributions due to factors such as inspiration level. Compared to standard approaches, the present model involves a larger number of parameters, most of which can be estimated from data, to handle the variability encountered in lung CT scans. The method was used to quantify emphysema on a cohort of 87 subjects, with repeated CT scans acquired over a time period of 8 years using different imaging protocols. The scans were acquired approximately annually, and the data set included a total of 365 scans. The results show that the emphysema estimates produced by the proposed method have very high intra-subject correlation values. By reducing sensitivity to changes in imaging protocol, the method provides a more robust estimate than standard approaches. In addition, the generated emphysema delineations promise great advantages for regional analysis of emphysema extent and progression, possibly advancing disease subtyping.