Dong Linan, Li Jun, Jian Wushuai, Zhang Lu, Wu Mingshu, Shi Hongli, Luo Shuqian
Department of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
Biomed Eng Online. 2014 Jun 21;13:82. doi: 10.1186/1475-925X-13-82.
Chronic obstructive pulmonary disease (COPD) is one of the leading causes of morbidity and mortality worldwide, and emphysema is a common component of COPD. Currently, it is very difficult to detect early stage emphysema using conventional radiographic imaging without contrast agents, because the change in X-ray attenuation is not detectable with absorption-based radiography. Compared with the absorption-based CT, phase contrast imaging has more advantages in soft tissue imaging, because of its high spatial resolution and contrast.
In this article, we used diffraction enhanced imaging (DEI) method to get the images of early stage emphysematous and healthy samples, then extract X-ray absorption, refraction, and ultra-small-angle X-ray scattering (USAXS) information from DEI images using multiple image radiography (MIR). We combined the absorption image with the USAXS image by a scatter plot. The critical threshold in the scatter plot was calibrated using the linear discriminant function in the pattern recognition.
USAXS image was sensitive to the change of tissue micro-structure, it could show the lesions which were invisible in the absorption image. Combined with the absorption-based image, the USAXS information enabled better discrimination between healthy and emphysematous lung tissue in a mouse model. The false-color images demonstrated that our method was capable of classifying healthy and emphysematous tissues.
Here we present USAXS images of early stage emphysematous and healthy samples, where the dependence of the USAXS signal on micro-structures of biomedical samples leads to improved diagnosis of emphysema in lung radiographs.
慢性阻塞性肺疾病（COPD）是全球发病和死亡的主要原因之一，肺气肿是COPD的常见组成部分。目前，使用无造影剂的传统放射成像很难检测早期肺气肿，因为基于吸收的放射成像无法检测到X射线衰减的变化。与基于吸收的CT相比，相衬成像在软组织成像方面具有更多优势，因为它具有高空间分辨率和对比度。
在本文中，我们使用衍射增强成像（DEI）方法获取早期肺气肿和健康样本的图像，然后使用多图像射线照相法（MIR）从DEI图像中提取X射线吸收、折射和超小角X射线散射（USAXS）信息。我们通过散点图将吸收图像与USAXS图像相结合。使用模式识别中的线性判别函数校准散点图中的临界阈值。
USAXS图像对组织微观结构的变化敏感，它可以显示吸收图像中不可见的病变。结合基于吸收的图像，USAXS信息能够更好地区分小鼠模型中健康和肺气肿的肺组织。伪彩色图像表明我们的方法能够对健康组织和肺气肿组织进行分类。
在这里，我们展示了早期肺气肿和健康样本的USAXS图像，其中USAXS信号对生物医学样本微观结构的依赖性导致肺部X光片中肺气肿的诊断得到改善。
