New Technology Offers Potential for Faster, More Accurate CF Diagnosis
A new technology could enable faster and more accurate cystic fibrosis (CF) diagnoses by non-invasively tracking the movement of air through even the fine structures of the lungs at high-resolution.
A study done in mice showed this technology, called X-ray velocimetry (XV), could pinpoint localized areas of abnormal airflow in a lung, as often seen in CF patients.
The study, “Quantification of muco-obstructive lung disease variability in mice via laboratory X-ray velocimetry,” was published in the journal Nature Scientific Reports.
The new technology, developed by researchers at Monash University in Australia, measures how different layers of tissue diffract or absorb X-rays as they pass through the body. Capturing these images at high speed over the course of a patient’s breathing cycle provides information about both lung structure and function.
These measurements enable precise assessments of the expansion of even very small lung tissues, which makes it possible to pinpoint the origin of any functional change.
To test XV in living animals, researchers used a mouse model of CF called beta-ENaC mice.
The team was able to clearly see reduced lung expansion and the locations where mucus buildup had obstructed airflow in the beta-ENaC mice, as compared to healthy littermates. These imaging results were confirmed by extracting lungs and sectioning them into thin slices, in which the mucus blockages could be seen directly.
Researchers also observed a generally lower lung volume in the beta-ENaC mice, as compared to their healthy littermates, consistent with the symptoms of the disease.
According to the team, a useful byproduct of XV’s heightened sensitivity is that it provides a quantitative way of classifying CF cases. Based on the presence and pattern of airflow obstructions, the researchers could assign different cases as “healthy,” “heterogenous,” or “clustered.”
Healthy lungs expanded in a uniform manner, consistent with both lungs being clear and unobstructed. Heterogenous disease was defined when CF-like obstructions occurred relatively evenly throughout the lungs. Cases were classified as clustered disease when lungs became partially obstructed with mucus, showing poor ventilation and trapped air in the obstructed regions.
“In this study we present two developments in XV analysis. Firstly, we show the ability of laboratory-based XV to detect the patchy nature of CF-like disease in affected mice. Secondly, we present a technique for numerical quantification of that disease, which can delineate between two major modes of disease symptoms [heterogeneous disease and clustered disease],” Freda Werdiger, PhD, the study’s lead author, said in a press release.
Understanding the differences between different types of CF can have important implications for treatment and outcomes.
“To effectively diagnose, monitor and treat respiratory disease, clinicians should be able to accurately assess the spatial distribution of airflow across the fine structure of the lung. This capability would enable any decline or improvement in health to be located and measured, allowing improved treatment options to be designed,” Werdiger said.
Overall, “the success of XV lies in its ability to draw reliable and meaningful quantitative measures, and this study shows how this can be accomplished. These methods allow analyses to be applied in a straightforward fashion and with minimal manual processing,” Werdiger added.
The team believes this technology can be applied to large data sets in order to assess lung function changes and “to develop a robust numerical model for CF lung disease.”
“The combination of X-ray velocimetry and progressive automation of the data analysis is an important step in the development of more sophisticated methods of lung function testing, and should assist research internationally to improve the health and lives of people with cystic fibrosis, and a range of other lung diseases,” researchers wrote.
XV technology was developed and commercialized by 4DMedical, led by CEO and former Monash University researcher Andreas Fouras. The U.S. Food and Drug Administration recently approved this technology for all respiratory indications in adults.