Automated quantification of three-dimensional organization of fiber-like structures in biological tissues. (February 2017)

• Record Type: Journal Article
• Authors: Liu, Zhiyi; Pouli, Dimitra; Sood, Disha; Sundarakrishnan, Aswin; Hui Mingalone, Carrie K.; Arendt, Lisa M.; Alonzo, Carlo; Quinn, Kyle P.; Kuperwasser, Charlotte; Zeng, Li; Schnelldorfer, Thomas; Kaplan, David L.; Georgakoudi, Irene
• Is Part Of: Biomaterials. Volume 116(2017)
• Page Start: 34
• Page End: 47
• Publication Date: 2017-02
• Subjects: Three-dimensional organization -- Collagen fiber -- Neuronal axon -- Cancer -- Traumatic brain injury -- Multi-photon microscopy; Biomedical materials -- Periodicals; Biocompatible Materials -- Periodicals; Biomatériaux -- Périodiques; 610.28
• DOI: 10.1016/j.biomaterials.2016.11.041
• Languages: English
• ISSNs: 0142-9612

Abstract

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.