Researchers have created a set of parameters that can be measured through ultrasound to quantitatively evaluate various physical features of the lungs. They have also shown that these parameters enable accurate diagnosis and evaluation of lung disease severity in animal studies.
Researchers have created a set of parameters that can be measured through ultrasound to quantitatively evaluate various physical features of the lungs. They have also shown that these parameters enable accurate diagnosis and evaluation of lung disease severity in animal studies.
“Diseases can impact the lungs in numerous ways,” explains Marie Muller, co-senior author of a study on this work and an associate professor of mechanical and aerospace engineering at North Carolina State University. “They may alter the lung’s microstructure, change the elasticity of lung tissue, or affect the volume and type of fluids present in the lungs, among other things. Each of these alterations can be quantified through ultrasound. Our objective was to clearly define the parameters for these lung characteristics and to identify the combinations of these parameters that correspond with various lung diseases.”
“To clarify, we’re referring to numerical values for each parameter,” states Muller, who is also part of the Joint Biomedical Engineering Department at NC State and the University of North Carolina at Chapel Hill. “For a single disease with three related parameters, we would have three distinct numbers. Using these numbers in a mathematical formula, we can generate a biomarker score. This score indicates not only the presence of a specific health issue but also its severity.”
The research team generated 60 parameters to assess a broad range of lung characteristics, including alveolar density and fluid levels in the lungs. They also modified existing ultrasound parameters, initially designed for other organs, for application on lung tissue.
They tested all 60 parameters on the lungs of both healthy rats and those with varying degrees of fibrosis or edema. Fibrosis refers to scarring in lung tissue, while edema is characterized by fluid accumulation in the lungs.
“We then applied statistical analysis to figure out which combinations of parameters were linked to specific health conditions and were sensitive enough to gauge the severity of those conditions,” Muller explains.
This analysis revealed that only five parameters were needed to evaluate fibrosis and edema: three for fibrosis and two for edema.
“One of the issues with many diagnostic tools is that they often have to balance sensitivity and specificity,” Muller remarks. “A test that is highly sensitive may reliably detect an issue but can result in many false positives. Conversely, a very specific test rarely reports false positives but might overlook several health issues it should identify or may struggle to evaluate the severity of a particular disease.”
“We are thrilled about this new diagnostic tool because it achieves both high sensitivity and high specificity,” Muller adds. “We can attain this balance due to our use of multiple parameters.”
To evaluate the sensitivity of this new diagnostic tool, the team monitored rats undergoing treatment for fibrosis. As these rats received therapy, the tool was effective in tracking improvements in their lung tissue.
The researchers have also created software for processing data that can work alongside existing ultrasound equipment to acquire the numerical values for each parameter and compute biomarker scores for edema and fibrosis.
“We’ve confirmed that this method performs effectively in a rat model,” Muller states. “The next steps will involve computational simulations, laboratory tests, and further animal model evaluations to ensure that this technique is viable even when ultrasound must penetrate a thicker chest wall. If successful, we’ll aim for clinical trials.”
“Furthermore, since we’ve established 60 parameters — a substantial number — we are hopeful that this method can eventually identify diagnostic biomarkers for a variety of other lung conditions.”
