Automated quantification of three-dimensional organization of fiber-like structures in biological tissues.

Journal: Biomaterials
Published Date: Feb 1, 2017

Abstract

Fiber-like structures are prevalent in biological tissues, yet quantitative approaches to assess their three-dimensional (3D) organization are lacking. We develop 3D directional variance, as a quantitative biomarker of truly 3D fibrillar organization by extending the directional statistics formalism developed for describing circular data distributions (i.e. when 0° and 360° are equivalent) to axial ones (i.e. when 0° and 180° are equivalent). Significant advantages of this analysis include its time efficiency, sensitivity and ability to provide quantitative readouts of organization over different size scales of a given data set. We establish a broad range of applications for this method by characterizing collagen fibers, neuronal axons and fibroblasts in the context of cancer diagnostics, traumatic brain injury and cell-matrix interactions in developing engineered tissues. This method opens possibilities for unraveling in a sensitive, and quantitative manner the organization of essential fiber-like structures in tissues and ultimately its impact on tissue function.

Authors

  • Zhiyi Liu
    Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
  • Dimitra Pouli
    Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Disha Sood
    Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
  • Aswin Sundarakrishnan
    Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
  • Carrie K Hui Mingalone
    Department of Developmental, Molecular and Chemical Biology, Tufts University School of Medicine, Boston, MA, 02111, USA.
  • Lisa M Arendt
    Department of Developmental, Molecular and Chemical Biology, Tufts University School of Medicine, Boston, MA, 02111, USA.
  • Carlo Alonzo
    Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
  • Kyle P Quinn
    Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA; Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR, 72701, USA.
  • Charlotte Kuperwasser
    Department of Developmental, Molecular and Chemical Biology, Tufts University School of Medicine, Boston, MA, 02111, USA.
  • Li Zeng
    Wenzhou Medical University, Wenzhou, China.
  • Thomas Schnelldorfer
    Lahey Hospital & Medical Center, Burlington, MA, 01805, USA.
  • David L Kaplan
    Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
  • Irene Georgakoudi
    Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA. Electronic address: Irene.Georgakoudi@tufts.edu.

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