Using mathematics to assess lung function


Researchers at the University of Southampton have developed a new digital way of analysing X-ray images of lungs that could herald a breakthrough in diagnosing Chronic Obstructive Pulmonary Disease (COPD) and other lung diseases.

The team devised a method for numerically describing the three-dimensional structure of the lung using topology – a mathematical technique to study complex shapes. By combining CT scans, high-performance computing and algorithms, they computed the three-dimensional numerical characteristics of the entire bronchial trees in 64 patients from four groups: healthy non-smokers, healthy smokers, patients with mild COPD and patients with moderate COPD.

Understanding COPD

COPD is a complex lung condition involving the airways (bronchi) and the lung tissue (alveoli) which results in a progressive loss of lung function.

It affects more than 200 million people worldwide, who are often middle-aged or older adults and mainly those who have had significant exposure to cigarette smoke. It is the fourth leading cause of death worldwide.

The team analysed 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.

It was found that, typically, a larger more complex tree indicates better lung function and a smaller distorted tree indicates poorer lung function.

The method accurately distinguished between the different groups of patients, the characteristics of their lung function and the different stages of their condition and was also able to identify characteristics not detectable to the naked eye.

Changing practice

The team hopes that repeating this method across a 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 and monitoring of conditions like COPD and asthma. This would provide a more accurate way of identifying the severity of an individual patient’s condition.

“This method is a major advance in our ability to study the structural abnormalities of COPD, a complex disease that affects so many people and, sadly, results in significant morbidity and mortality” explained Professor of Medicine of the NIHR Southampton Biomedical Research Centre, Ratko Djukanović.

“The image analysis method is the first to apply the field of topology in lung diseases, and one of only a handful of studies of this kind in medicine. Southampton is a great place for collaborative research of this kind, so we’re looking forward to developing this method for use in routine clinical care.”

Lead researcher in this collaboration between mathematicians and clinical scientists and Professor in Mathematics, Jacek Brodzki said “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 standard, two-dimensional CT images.” “The images are assessed by experienced specialists in examining and interpreting CT imagery, using relatively simple measures of lung density and bronchial wall thickness.”

“Our study shows that this new method can expand on established techniques to give an accurate range of information about the lung function of individuals. This could eventually aid decisions about the treatment of patients with serious lung conditions.”

Posted on Monday 25 June 2018