New Imaging Algorithm Offers Key Insights Into Cystic Fibrosis Diagnosis, Treatment

Ana Pamplona, PhD avatar

by Ana Pamplona, PhD |

Share this article:

Share article via email

SpirometryA recent study entitled “Stochastic Tracking of Infection in a CF Lung” presents a new algorithm that improves recorded imaging results for examining the lungs of Cystic Fibrosis patients by providing information at a microscopic level of the infection site. This study was published on PlosOne by Dr. Sara Zarei from the Computational Science Research Center at San Diego State University, along with colleagues.

Chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF) induces chronic lung inflammation, causing airflow limitation and the scarring of lung tissues. The inflammatory response induced in the airways leads to the recruitment of large amount of neutrophils, and there is also an excess production of mucus that impairs the flow of air in and out of the lungs.

In cystic fibrosis, the scarring induced by inflammatory cytokines that ultimately contribute to the remodeling of a CF lung is primarily due to the contact between the lung lining and the mucus biofilm, which also plays a role in remodeling the lung of the CF patient. In this study, the research team hypothesized that accumulation of mucus is the primary driver of damage to the lung, and following its progression is vital for a better diagnosis and treatment of CF.

[adrotate group=”1″]

There are clinical tests for the global measurement of airflow obstruction and restriction such as Spirometry that offee spirometric indicators such as the forced expiratory volume in one second (FEV) and forced vital capacity (FVC), which measures the volume of air that can be powerfully blown out after a full inspiration movement. However, these tests do not provide detailed information about the specific site of mucus obstruction. Additional information can be obtained by the repeated imaging of the lungs of CF patients, which is normally done by chest x-ray and computed tomography (CT). This is an optimal morphological evaluation of changes to a CF lung, but the exposure to ionizing radiation is a serious impediment. Thus, magnetic resonance imaging (MRI) currently seems to be the appropriate method for lung imaging for a CF patient.

Magnetic resonance imaging (MRI) was introduced in 1987 as an imaging technique for use in patients with CF. There are many MRI methods for analyzing the thoracic cavity, however, despite the clarity and precision of MRI images, they do not give information on smaller airways at the microscopic level. For this reason, the exact site of infection cannot be obtained solely from the analysis of an MRI.

The main goal of this study was to supply the clinicians with an algorithm that enables following the site and progression of mucus in the lungs of CF patients using imaging tools. Thus, the new approach will help doctors visualize the effect of mucus progression on lung function and associate it with the current stage of the disease. The models will allow doctors to quantitatively follow CF patients’ responses to various therapies and prescribe the adequate treatment.  Importantly, these models may play a crucial role in future Cystic Fibrosis treatments.