AUTHOR=Strobel Hannah A. , Schultz Alex , Moss Sarah M. , Eli Rob , Hoying James B. TITLE=Quantifying Vascular Density in Tissue Engineered Constructs Using Machine Learning JOURNAL=Frontiers in Physiology VOLUME=12 YEAR=2021 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.650714 DOI=10.3389/fphys.2021.650714 ISSN=1664-042X ABSTRACT=

Given the considerable research efforts in understanding and manipulating the vasculature in tissue health and function, making effective measurements of vascular density is critical for a variety of biomedical applications. However, because the vasculature is a heterogeneous collection of vessel segments, arranged in a complex three-dimensional architecture, which is dynamic in form and function, it is difficult to effectively measure. Here, we developed a semi-automated method that leverages machine learning to identify and quantify vascular metrics in an angiogenesis model imaged with different modalities. This software, BioSegment, is designed to make high throughput vascular density measurements of fluorescent or phase contrast images. Furthermore, the rapidity of assessments makes it an ideal tool for incorporation in tissue manufacturing workflows, where engineered tissue constructs may require frequent monitoring, to ensure that vascular growth benchmarks are met.