Abstract Microvascular networks (MVNs) formed via endothelial cell self-assembly in 3D hydrogels have emerged as a widely used platform for modeling vascularized tissues and studying vascular pathophysiology. Conventional MVN systems incorporate supporting fibroblasts and may include biochemical cues such as VEGF, FGF, or S1P, as well as mechanical stimuli like luminal flow, yet the impact of these variables on MVN morphology and function remains incompletely understood. Here, we systematically investigated the effects of fibroblast concentration, fibroblast-conditioned media, angiogenic factors, and luminal flow on the morphology, perfusability, and vessel wall integrity of MVNs cultured in a microfluidic vasculature-on-a-chip. In addition to standard branch-based metrics such as vessel coverage area and diameter, we developed and applied novel void-based morphological parameters that quantify the size, shape, and distribution of vessel-free spaces to capture subtle differences across MVN culture conditions. Our results demonstrate that high fibroblast-to-endothelial cell ratios accelerate MVN formation but promote excessive vessel fusion, while MVNs cultured without fibroblasts—using only conditioned media or soluble factors—exhibited patch-like, non-physiological morphology with reduced branch formation. Direct inclusion of fibroblasts proved essential for promoting the thin, interconnected vascular structures characteristic of in vivo microvasculature and could not be substituted by soluble cues alone. Furthermore, the presence or absence of fibroblasts modulated MVN responsiveness to luminal flow. Overall, our void-based analysis method enabled more sensitive discrimination of MVN morphological features than traditional branch-based metrics and offers a reduced-data, high-content approach suitable for integration with machine learning and AI-assisted image analysis pipelines. This platform provides a new framework for optimizing MVN culture protocols and advancing vascular tissue engineering studies, particularly for the advancement of organ-on-a-chip (OOC) and microphysiological systems.
Shao et al. (Tue,) studied this question.