Digital chest x-rays using radiomics

Dataset wherein a unique sliding window segmentation method was developed to eliminate the difficult and time-consuming task of accurate Pulmonary tuberculosis (PTB) disease segmentation from planar images. It was applied as a secondary segmentation, superimposed on a primary automatic lung segmentation, that divided the entire lung region into uniform windows that overlapped while sliding over the  chest x-ray (CXR) in both image dimensions. When radiomic features were extracted from each sliding window, it allowed the distribution of the features across the lung region to be evaluated.
Three different outcomes were achieved when radiomic feature extraction was applied to chest x-rays using the sliding window segmentation. Firstly a model was developed that can automatically differentiate normal CXR from CXR with PTB cavities, which could improve the accuracy of CXR reporting currently regaining prominence as a high-volume screening tool. Secondly, signature parameter maps that showed a strong correlation to the lung pathology were constructed. This might be valuable as a quantitative supplementary indicator in the management of PTB disease and further increase the acceptance of CXR as a tool for assessing the Tuberculosis (TB) response in medical research and clinical practice. Finally, a radiomics score was constructed that was able to quantify the change in the disease characteristics as seen from digital CXR of patients diagnosed with PTB. This radiomic score analysis of serial x-rays taken while patients receive TB therapy has the potential to be a quantitative monitoring tool of response to therapy. Radiomics was therefore successfully applied in this study to quantify the characteristics of PTB from chest x-rays.

本数据集采用了一种独特的滑动窗口分割方法，旨在消除从平面图像中精确分割肺结核（PTB）疾病这一复杂且耗时的工作。该方法作为辅助分割技术，叠加在初级自动肺部分割之上，将整个肺区域划分为均匀的滑动窗口，在胸片（CXR）的图像维度上滑动。通过对每个滑动窗口提取的放射组学特征进行分析，可评估特征在肺区域内的分布情况。
当使用滑动窗口分割对胸片进行放射组学特征提取时，实现了三种不同的结果。首先，开发了一个模型，能够自动区分正常胸片与具有PTB空洞的胸片，这有望提高当前作为高容量筛查工具的胸片报告的准确性。其次，构建了与肺病理学具有强相关性的特征参数图，这可能在肺结核疾病管理中作为一种定量辅助指标，并进一步增加将胸片作为评估结核病（TB）反应在医学研究和临床实践中的工具的接受度。最后，构建了一个放射组学评分，能够量化肺结核患者从数字胸片中观察到的疾病特征的变化。分析患者在接受结核病治疗期间拍摄的连续X光片，该放射组学评分分析有望成为治疗反应的定量监测工具。因此，本研究成功将放射组学应用于量化胸片中肺结核的特征。