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A Fully Automated Approach to Quantitatively Determine Thickness of Tissue-Engineered Cell Sheets

Abstract

Sheet-based tissue engineering is an innovative field that has provided the scientific community with new tissue-engineered products such as skin, cornea, heart valves, and vascular grafts. As this area of tissue engineering progresses toward clinical implementation, quality control becomes more and more important. Imaging methods advertise themselves because of their high resolution and good tissue-fluid contrast. We present and compare two methods, one based on a custom-designed automatized large-area confocal scanner that uses backscattered light for image formation, and one based on optical coherence tomography (OCT). In both modalities, additional image processing is used to extract sheet thickness and density information and to create a quantitative tissue thickness map in a fully automated fashion. In test objects (glass of known thickness and scattering samples) and engineered tissue sheets with artificially introduced defects we found high agreement between the two methods in the measurement of thickness and the visual representation of the defects. Both the OCT and the confocal scanner were able to provide high-detail images visually consistent to those obtained with brightfield microscopy. Both OCT and large-area confocal scanning in combination with specialized image processing algorithms promise to provide information on tissue homogeneity, density, and the presence of potential defects in tissue sheets in an unsupervised fashion and thus help establish new quality control methods in sheet-based tissue engineering.

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Acknowledgments

We gratefully acknowledge support from the Juergen Manchot Foundation (Duesseldorf, Germany) and from the National Institutes of Health, Grant R21 HL081308. We thank Dr. Nicolas L’Heureux (Cytograft Tissue Engineering, Novato, CA, USA) for providing us with the tissue samples. We also thank the anonymous reviewers for valuable comments and discussion.

Author information Authors and Affiliations
  1. Department of Biological Engineering, University of Missouri, Columbia, MO, 65211, USA

    Jeffrey T. LaCroix

  2. Driftmier Engineering Center, Faculty of Engineering, University of Georgia, Athens, GA, 30602, USA

    Jinjun Xia & Mark A. Haidekker

Authors
  1. Jeffrey T. LaCroix
  2. Jinjun Xia
  3. Mark A. Haidekker
Corresponding author

Correspondence to Mark A. Haidekker.

Additional information

Jeffrey T. LaCroix and Jinjun Xia share credit for first authorship.

About this article Cite this article

LaCroix, J.T., Xia, J. & Haidekker, M.A. A Fully Automated Approach to Quantitatively Determine Thickness of Tissue-Engineered Cell Sheets. Ann Biomed Eng 37, 1348–1357 (2009). https://doi.org/10.1007/s10439-009-9694-1

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