Rapid Quantification of Microvessels of Three-Dimensional Blood-Brain Barrier Model Using Optical Coherence Tomography and Deep Learning Algorithm.

The blood-brain barrier (BBB) is a selective barrier that controls the transport between the blood and neural tissue features and maintains brain homeostasis to protect the central nervous system (CNS). In vitro models can be useful to understand the role of the BBB in disease and assess the effects of drug delivery. Recently, we reported a 3D BBB model with perfusable microvasculature in a Transwell insert. It replicates several key features of the native BBB, as it showed size-selective permeability of different molecular weights of dextran, activity of the P-glycoprotein efflux pump, and functionality of receptor-mediated transcytosis (RMT), which is the most investigated pathway for the transportation of macromolecules through endothelial cells of the BBB. For quality control and permeability evaluation in commercial use, visualization and quantification of the 3D vascular lumen structures is absolutely crucial. Here, for the first time, we report a rapid, non-invasive optical coherence tomography (OCT)-based approach to quantify the microvessel network in the 3D in vitro BBB model. Briefly, we successfully obtained the 3D OCT images of the BBB model and further processed the images using three strategies: morphological imaging processing (MIP), random forest machine learning using the Trainable Weka Segmentation plugin (RF-TWS), and deep learning using pix2pix cGAN. The performance of these methods was evaluated by comparing their output images with manually selected ground truth images. It suggested that deep learning performed well on object identification of OCT images and its computation results of vessel counts and surface areas were close to the ground truth results. This study not only facilitates the permeability evaluation of the BBB model but also offers a rapid, non-invasive observational and quantitative approach for the increasing number of other 3D in vitro models.

Development of a three-dimensional blood-brain barrier network with opening capillary structures for drug transport screening assays.

The blood-brain barrier (BBB), a selective barrier regulating the active and passive transport of solutes in the extracellular fluid of the central nervous system, prevents the delivery of therapeutics for brain disorders. The BBB is composed of brain microvascular endothelial cells (BMEC), pericytes and astrocytes. Current in vitro BBB models cannot reproduce the human structural complexity of the brain microvasculature, and thus their functions are not enough for drug assessments. In this study, we developed a 3D self-assembled microvascular network formed by BMEC covered by pericytes and astrocyte end feet. It exhibited perfusable microvasculature due to the presence of capillary opening ends on the bottom of the hydrogel. It also demonstrated size-selective permeation of different molecular weights of fluorescent-labeled dextran, as similarly reported for in vivo rodent brain, suggesting the same permeability with actual in vivo brain. The activity of P-glycoprotein efflux pump was confirmed using the substrate Rhodamine 123. Finally, the functionality of the receptor-mediated transcytosis, one of the main routes for drug delivery of large molecules into the brain, could be validated using transferrin receptor (TfR) with confocal imaging, competition assays and permeability assays. Efficient permeability coefficient (Pe) value of transportable anti-TfR antibody (MEM-189) was seven-fold higher than those of isotype antibody (IgG1) and low transportable anti-TfR antibody (13E4), suggesting a higher TfR transport function than previous reports. The BBB model with capillary openings could thus be a valuable tool for the screening of therapeutics that can be transported across the BBB, including those using TfR-mediated transport.