Nondestructive Mechanical Characterization of Bioengineered Tissues by Digital Holography

ACS Biomater Sci Eng. 2025 Jan 15. doi: 10.1021/acsbiomaterials.4c01503. Online ahead of print.

Abstract

Mechanical properties of engineered connective tissues are critical for their success, yet modern sensors that measure physical qualities of tissues for quality control are invasive and destructive. The goal of this work was to develop a noncontact, nondestructive method to measure mechanical attributes of engineered skin substitutes during production without disturbing the sterile culture packaging. We optimized a digital holographic vibrometry (DHV) system to measure the mechanical behavior of Apligraf living cellular skin substitute through the clear packaging in multiple conditions: resting on solid agar as when the tissue is shipped, on liquid media in which it is grown, and freely suspended in air as occurs when the media is removed for feeding. We utilized full-field measurement to assess the complete surface deformation pattern to compare with vibration theory and found the patterns observed in air showed the closest behavior to theory. To simulate the effects of the actual culture dish geometry and the trilayer composition of the tissue on the porous membrane support, we employed finite element (FE) analysis. To simulate changes in thickness and stiffness that may occur with manufacturing process variations, we dried samples over time and observed measurable increases in the fundamental mode frequency which could be predicted by altering the thickness of the tissue layers in the FE model. However, quantitative estimates of the engineered tissue stiffness based on vibration theory are unrealistically high due to the signal being dominated by the stiff underlying membrane on which the tissue is cultured. Thus, although DHV is not able to specifically quantify the thickness or modulus or identify small spot defects, it has the potential to be used assess the overall properties of a tissue in-line and noninvasively for quality control.

Keywords: 3D deep learning classification; digital holography; manufacturing; mechanical testing; tissue engineering; vibration.