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Evaluating Cellular Migration in Tissue Engineered Scaffolds through an Image Processing Algorithm

Technology #20150055

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Researchers
Robert Tranquillo, PhD
Head of Department, Biomedical Engineering, College of Science and Engineering
External Link (bme.umn.edu)
Fluvio Lobo Fenoglietto
Managed By
Andrew Morrow
Technology Licensing Officer
Publications
Influence of culture conditions and extracellular matrix alignment on human mesenchymal stem cells invasion into decellularized engineered tissues
Journal of Tissue Engineering and Regenerative Medicine, Volume 9, Issue 5, pages 605–618, May 2015

Tissue Engineered Scaffold and Cell Migration Analysis

In the field of Tissue Engineering and Regenerative Medicine, reseeding represents the last step prior to the implantation of the tissue engineered (TE) scaffold. Populating the scaffold with the cells of the patient reduces the risk of immune response and implant rejection. However, the process is limited by the time it takes to reach a cellular density comparable to that of native tissue. While most efforts have been focused towards identifying factors that enhance cell invasion, analytical methods to evaluate the efficacy of these factors have not been developed. The Surface Cell Invasion Analysis (SCIA) software targets this issue by providing an image-based quantitative analysis of cell migration.

Invasion Analysis through Image Processing

The analysis of reseeded TE scaffolds involves sample fixation, sectioning, staining, and imaging. Cross section images of the TE scaffold are the result from which conclusions on the efficacy of the seeding process are drawn. Through the implementation of MATLAB-based image processing functions, SCIA standardizes and automates this analysis. SCIA reduces noise native to the input images, adds physical dimensions to captured features (scaffold surfaces, cells, etc.), erodes and dilates images to eliminate clusters and other artifacts of thresholding, and stores results into labeled structure arrays and Excel sheets for further analysis. Additional functions such as Migration Histogram Analysis (mighist) use the output of SCIA for comparison across sample groups.

BENEFITS AND FEATURES OF SCIA

  • Quantification of Cellular Migration
  • Calculation of Cellular Morphological Parameters
  • Data Visualization
  • Integration of Image Processing Functions and Methodologies in Concert
  • Statistical Treatment/Sample group Comparison

Availability of Surface Cell Invasion Analysis Software

The SCIA software is available for researchers at academic institutions and commercial organizations. Select the appropriate license from the right hand column. The software requires MATLAB R2013b and the MATLAB Image Processing Toolbox.