Using physioLens for High-Throughput Airway Physiology and Image Analysis

Airway constriction is a key feature of respiratory diseases such as asthma. However, measuring airway narrowing in precision-cut lung slices (PCLS) can be time-consuming because airway responses can vary significantly within the same lung.

A study by Boucher et al (2024) investigated how the physioLensautomated PCLS solution can simplify airway constriction measurements while helping researchers determine the optimal number of airways needed for reliable results.

The Challenge of Measuring Airway Constriction in PCLS

PCLS models provide a valuable way to study airway physiology and bronchoconstriction ex vivo. However, individual airways can respond very differently to stimuli such as methacholine, ranging from minimal constriction to complete closure.

This variability means that analyzing too few airways may produce unreliable results, while manually measuring large numbers of airways can be labor-intensive and difficult to scale.

Automated PCLS Imaging with physioLens

The physioLens platform automates both experimental intervention and image analysis of airway constriction, enabling researchers to analyze large numbers of airways efficiently.

In the study, PCLS from male BALB/c mice, including mice with experimental asthma, were exposed to methacholine to induce airway constriction. An average of 45 airways per mouse across 32 mice were analyzed automatically.

The study reported a mean maximal airway constriction of 37.4 ± 32.0%, highlighting the substantial variability between individual airways.

How Many Airways Should Be Analyzed?

One of the study’s most useful findings was the identification of an optimal sample size for PCLS airway constriction experiments.

Random sampling simulations showed that approximately:

• 35 airways per mouse were required for a reliable mean maximal constriction
• 16 airways were sufficient for estimating standard deviation
• 29 airways were needed for coefficient of variation

These findings can help researchers design more efficient PCLS airway physiology experiments, balancing data reliability with experimental throughput.

Airway Responsiveness in Experimental Asthma

Although maximum airway constriction did not differ significantly between control and experimental asthma groups, the asthma model showed reduced sensitivity to methacholine, demonstrated by a shift in the concentration-response curve.

These results suggest that asthma-related airway dysfunction may involve differences in airway responsiveness, narrowing heterogeneity, and airway closure, rather than simply an increase in maximum smooth muscle contraction.

Lung Inflation Technique Does Not Affect Results

The researchers also compared two lung inflation approaches: inflation through the trachea and trans-parenchymal inflation using agarose.

Importantly, the inflation technique did not significantly affect airway constriction responses or the effect of experimental asthma on methacholine responsiveness. This supports the robustness of the PCLS approach across different experimental preparation methods.

Advancing High-Throughput Airway Research

The study demonstrates how automated PCLS imaging and airway constriction analysis can improve the efficiency and reproducibility of ex vivo airway research.

By using physioLens to analyze large numbers of airways and establishing appropriate sample sizes, researchers can obtain more reliable measurements while reducing the manual workload associated with traditional image analysis.

This approach could accelerate research into asthma, airway hyperresponsiveness, bronchoconstriction, and other respiratory diseases, while supporting higher-throughput screening of potential therapeutics.