Table 1.
Compiled data of lung tissue stiffness reported in literature using different testing methods.
Fig 1.
Methods used to quantify lung modulus.
Lungs from 12 animals were tested using multiple methods. For each method, an example force-displacement or force-time curve is shown for a typical tissue sample, as well as an inset image of the tissue sample being actively tested. (a) Cavitation rheology uses a small needle inserted into an intact tissue, wherein a sensor measures the pressure required to cavitate a bubble within a tissue. This cavitation pressure was then input into a model to find a tissue compliance and an effective modulus. (b) SAOS requires defined, excised samples and applies shear across a range of oscillatory frequencies, resulting in a dynamic modulus, storage modulus (G’), and loss modulus (G”), which can be related to the Young’s modulus via the Poisson’s ratio (ν). (c) Micro-indentation requires excised samples with defined thicknesses and applies small compressive forces, results in a force-displacement curve, the slope of which resulted in a Young’s modulus. (d) Uniaxial testing applies tension to a prepared, excised sample, resulting in a stress-strain curve, the slope of which relays a Young’s modulus. Due to the heterogeneity of the ECM in structure and composition, lung tissue has two different regimes: an initial toe region, and a steeper, sloped region. (e) Compiled data of Young’s modulus measurements on lung tissue using cavitation rheology, SAOS rheometry, micro-indentation, and uniaxial tension with number of samples used for each testing method.
Fig 2.
Mechanical properties of fresh vs. frozen tissue using micro-indentation.
Fresh lung samples were tested using micro-indentation and then frozen using either (a) Liquid Nitrogen (LN2), (b) OCT medium with LN2, or (c) slowly frozen to -80°C, and subsequently re-tested. Samples marked with * are statistically significantly different after freezing, compared to the original fresh tissue specimen, (p<0.05) as found using a Student’s t-test. Error bars are shown in only one directly for clear visualization of the data.
Fig 3.
SAOS and micro-indentation moduli do not depend on testing order.
The Young’s modulus measured with micro-indentation before (left of dashed line) or after (right) SAOS did not affect the measured sample modulus. SAOS samples could be tested once (N = 1), while micro-indentation samples were indented multiple times (N = 3) to obtain the mean and standard deviation.
Fig 4.
Lung tissue modulus temperature dependence as measured by SAOS.
(a) A lung sample was subjected to a strain sweep from 0.01% to 100% at both 25°C and 37°C. Multiple runs were conducted on the same sample to construct the plot. (b) A sample of lung tissue was tested at 25°C and 37°C to determine the effect on temperature variation. No statistically significant differences were noted in the storage modulus (G’) or loss modulus (G”) as a function of temperature.
Fig 5.
Comparison of Young’s modulus of lung tissue and baseline hydrogel across different mechanical testing techniques.
(a) The Young’s modulus of the parenchymal region of the lungs were determined by each method described: cavitation rheology (blue), micro-indentation (red), SAOS (green) and uniaxial tension (purple). Each data point represents averaged data across samples using the method indicated for a single lung lobe. Lobes within sets of lungs were paired to generate up to four data points per lung set (sample number). For cavitation rheology, two data points for each lung sample represent measurements on both lobes on the same day. Statistical analysis (two-tailed Student’s t-test) inferred non-significant difference between measurements using different methods (p>0.05). (b) The Young’s modulus of a 4 vol% PEGDMA/HEMA hydrogel was determined by cavitation rheology (blue), and micro-indentation (red). Each data point represents averaged data across several different hydrogel samples (N = 14 for cavitation, N = 11 for indentation).