Biodynamic imaging is an emerging 3D optical imaging technology that probes up to 1 mm deep inside three-dimensional living tissue using short-coherence dynamic light scattering to measure the intracellular motions of cells inside their natural microenvironments. Biodynamic imaging is label-free and non-invasive. The information content of biodynamic imaging is captured through tissue dynamics spectroscopy that displays the changes in the Doppler signatures from intracellular constituents in response to applied compounds. The affected dynamic intracellular mechanisms include organelle transport, membrane undulations, cytoskeletal restructuring, strain at cellular adhesions, cytokinesis, mitosis, exo- and endo-cytosis among others. The development of 3D high-content assays such as biodynamic profiling can become a critical new tool for assessing efficacy of drugs and the suitability of specific types of tissue growth for drug discovery and development. The use of biodynamic profiling to predict clinical outcome of living biopsies to cancer therapeutics can be developed into a phenotypic companion diagnostic, as well as a new tool for therapy selection in personalized medicine. This invited talk will present an overview of the optical, physical and physiological processes involved in biodynamic imaging. Several different biodynamic imaging modalities include motility contrast imaging (MCI), tissue-dynamics spectroscopy (TDS) and tissue-dynamics imaging (TDI). A wide range of potential applications will be described that include process monitoring for 3D tissue culture, drug discovery and development, cancer therapy selection, embryo assessment for in-vitro fertilization and artificial reproductive technologies, among others.
David D. Nolte, "Biodynamic Doppler imaging of subcellular motion inside 3D living tissue culture and biopsies
(Conference Presentation)," Proc. SPIE 9725, Frontiers in Biological Detection: From Nanosensors to Systems VIII, 972505 (Presented at SPIE BiOS: February 14, 2016; Published: 27 April 2016); https://doi.org/10.1117/12.2211170.4848770203001.
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