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The University of Southampton
Mathematical Sciences

How the power of mathematics can help assess lung function

Researchers at the University of Southampton 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, including those of viral origin.

A multi-disciplinary team of mathematicians, clinicians, and image specialists, from three University of Southampton Faculties, 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. Topology allows to classify and visualise complicated structures and it also provides numerical characteristics for their comparison.

Research challenge

Using 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 categorised in four different groups: healthy non-smokers, healthy smokers, patients with moderate COPD and patients with mild COPD.

COPD is a complex lung condition that involves, to various degrees, the airways (bronchi) and the lung tissue (alveoli); this results in a progressive loss of lung function. It affects more than 200 million people worldwide –middle-aged or older adults, mainly those who have had significant exposure to cigarette smoke. It is the third leading cause of death worldwide.

The team analysed 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 characteristics not detectable to the naked eye. This methodology could be adapted the analysis of X-rays and CT scans of patients with viral infections, for example, those with suspected Covid-19 infection.

For more information visit the Scientific Reports.

Visit the Centre for Geometry, Topology, and Applications

Staff MemberPrimary Position
Jacek Brodzki Professor of Pure Mathematics, Deputy Head of School (Research)
Ratko Djukanovic Professor of Medicine, Director of the Southampton NIHR Respiratory Biomedical Research Unit,Director of the NIHR Southampton Centre for Biomedical Research
Michael Bennett Senior research scientist
Joy Conway Researcher in the fields of inhaled aerosols and lung imaging
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