Researchers have developed a new computational way of analysing X-ray images of lungs, which could herald a breakthrough in the diagnosis and assessment of Chronic Obstructive Pulmonary Disease (COPD) and other lung diseases.
A multi-disciplinary team of mathematicians, clinicians, and image specialists has devised a method for numerically describing the complicated three-dimensional structure of the lung using topology - a part of mathematics designed specifically for the study of complex shapes.
Utilizing a combination of computed tomography (CT) scans, high-performance computing and algorithms, the researchers computed numerical characteristics, in three dimensions, of the entire bronchial trees of 64 patients categoriz ed in four different groups: healthy non-smokers, healthy smokers, patients with moderate COPD and patients with mild COPD.
The team analyzed such features as the structure and size of the bronchial tree, the length and direction of its branches and the comparative changes in shape during deep inhalation and full exhalation. They found that, typically, a larger more complex tree indicates better lung function and a smaller distorted tree, poorer lung function.
The researchers found that their novel method was able to accurately distinguish between the different groups of patients, the characteristics of their lung function and the different stages of their condition. It was able to identify charactaristics not detectable to the naked eye.
Furthermore, they hope that repeating this method across a much larger database of images and combining it with other data could lead to the real-world development of a valuable clinical tool for the early diagnosis of conditions like COPD and asthma - providing a more accurate way of identifying the severity of an individual patient's condition.
Lead researcher: "Until now, the severity of lung conditions has been assessed by using a spirometer - a device which measures the force and amount of air a patient can exhale - and two-dimensional CT images, assessed by expert specialists, who have extensive experience of examining and interpreting CT imagery, and using relatively simple measures of lung density and bronchial wall thickness.
"Our study shows that this new method, employing topological data analysis, can complement and expand on established techniques to give a valuable, accurate range of information about the lung function of individuals. Further research is needed, but this could eventually aid decisions about the treatment of patients with serious, or potentially serious, lung conditions."
The paper Lung Topology Characteristics in patients with Chronic Obstructive Pulmonary Disease is published in the journal Scientific Reports.
Computers to analyze x-ray images of lungs
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