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    <title>IMAGING TISSUE SCAFFOLDS WITH X-RAY PHASE CONTRAST IMAGING</title>
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    <namePart>Doe, Frederick</namePart>
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    <namePart>Brey, Eric</namePart>
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  <abstract>A major challenge in tissue engineering is imaging within scaffolds. Biomaterials commonly used in tissue engineering have similar x-ray absorption properties to native tissue, so they provide poor contrast in radiography. X-ray phase contrast imaging (XPCI) is an imaging modality that measures light/matter interactions other than absorption. By providing insight into these interactions, x-ray phase contrast imaging has the potential to allow imaging of materials used in biomedical applications. In this thesis, a technique for imaging explanted poly(ethylene glycol) (PEG) hydrogels is presented. PEG is a highly biocompatible polymer with widespread use in biomedical applications. Porous PEG hydrogels were synthesized with 100-150 μm pore size through a salt-leaching technique and loaded with fibrin, a natural protein known to stimulate vascularized tissue formation. The hydrogels were formed in the shape of disks and implanted subcutaneously in the backs of rodent animal models for 1, 2 and 3 weeks. The hydrogels and surrounding tissue were harvested at 1, 2, and 3 weeks. After explanation, the hydrogels were placed in formaldehyde and imaged at the National Light Source at Brookhaven National Laboratory using a multiple image radiography (MIR) technique. Five hundred angles were captured of each sample over 180°, and computed tomography was performed. The samples were compared to histological stains to identify specific tissue features that could be identified in the XPCI images. XPCI allowed imaging of hydrogels and identification of interfaces between native tissue and the PEG material. In addition, tissue invasion into the pores of the scaffold could be identified and could be used to quantify the depth of invasion. Muscle tissue could also be seen, and within muscle fibers were visible. With computed tomography, 3D volumes were constructed, enabling analysis throughout the samples.</abstract>
  <note type="provenance">Submitted by Erma Thomas (thomase@iit.edu) on 2015-06-18T17:05:50Z No. of bitstreams: 3 Frederick Doe Thesis.pdf: 20456579 bytes, checksum: 13fc345a4a0940ba4b6ffad056b26875 (MD5) Abstract document.pdf: 48952 bytes, checksum: 1ec230d86e91e0b83a530f3c1777f0bb (MD5) Thesis cover page signed-1.pdf: 25424 bytes, checksum: 4cc8c16ed228af37df79cb32acd038a9 (MD5)</note>
  <note type="provenance">Made available in DSpace on 2015-06-18T17:05:50Z (GMT). No. of bitstreams: 3 Frederick Doe Thesis.pdf: 20456579 bytes, checksum: 13fc345a4a0940ba4b6ffad056b26875 (MD5) Abstract document.pdf: 48952 bytes, checksum: 1ec230d86e91e0b83a530f3c1777f0bb (MD5) Thesis cover page signed-1.pdf: 25424 bytes, checksum: 4cc8c16ed228af37df79cb32acd038a9 (MD5) Previous issue date: 2014-12</note>
  <note type="thesis">M.S. in Biomedical Engineering, December 2014</note>
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    <dateCaptured>2014</dateCaptured>
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  <originInfo>
    <dateCreated keyDate="yes">2014-12</dateCreated>
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  <identifier type="hdl">http://hdl.handle.net/10560/3428</identifier>
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    <namePart>BME / Biomedical Engineering</namePart>
    <affiliation>Illinois Institute of Technology</affiliation>
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