Despite advances in imaging, image-based vascular systems biology has remained challenging because blood vessel data is often available only from a single modality or at a given spatial scale, and cross-modality data are difficult to integrate. Therefore, there is an exigent need for a multimodality pipeline that enables ex vivo vascular imaging with MRI, CT and optical microscopy of the same sample, while permitting imaging with complementary contrast mechanisms from the whole-organ to endothelial cell spatial scales. To achieve this, we developed ‘VascuViz’ – an easy-to-use method for simultaneous 3D imaging and visualization of the vascular microenvironment using MRI, CT and optical microscopy in the same intact, unsectioned tissue. The VascuViz workflow permits multimodal imaging with a single labeling step using commercial reagents and is compatible with diverse tissue types and protocols. VascuViz’s interdisciplinary utility in conjunction with novel data visualization approaches opens up new vistas in image-based vascular systems biology.
The usability of many high-throughput lab-on-a-chip devices in point-of-care applications is currently limited by the manual data acquisition and analysis process, which are labor intensive and time consuming. Based on our original design in the biochemical reactions, we proposed here a universal approach to perform automatic, fast, and robust analysis for high-throughput array-based microfluidic immunoassays. Inspired by two-dimensional (2D) barcodes, we incorporated asymmetric function patterns into a microfluidic array. These function patterns provide quantitative information on the characteristic dimensions of the microfluidic array, as well as mark its orientation and origin of coordinates. We used a computer program to perform automatic analysis for a high-throughput antigen/antibody interaction experiment in 10 s, which was more than 500 times faster than conventional manual processing. Our method is broadly applicable to many other microchannel-based immunoassays. V C 2013 AIP Publishing LLC. [http://dx
Vascularization is a crucial step during musculoskeletal tissue regeneration via bioengineered constructs or grafts. Functional vasculature provides oxygen and nutrients to the graft microenvironment, facilitates wound healing, enhances graft integration with host tissue, and ensures the long-term survival of regenerating tissue. Therefore, imaging de novo vascularization (i.e. angiogenesis), changes in microvascular morphology and the establishment and maintenance of perfusion within the graft site (i.e. vascular microenvironment or VME) can provide essential insights into engraftment, wound healing, as well as inform the design of tissue engineering (TE) constructs. In this review, we focus on state-of-the-art imaging approaches for monitoring the VME in craniofacial TE applications, as well as future advances in this field. We describe how cutting-edge in vivo and ex vivo imaging methods can yield invaluable information regarding VME parameters that can help characterize the effectiveness of different TE constructs, and iteratively inform their design for enhanced craniofacial bone regeneration. Finally, we explicate how the integration of novel TE constructs, preclinical model systems, imaging techniques and systems biology approaches could usher an era of "image-based tissue engineering".
Angiogenesis is a key factor in bone healing that allows the delivery of oxygen, nutrients, inflammatory and bone precursor cells to the defect site. It induces dramatic structural and functional remodeling of the vasculature during the first 4 weeks of bone healing. Although recent advances in optical imaging have elucidated the in vivo relationship between angiogenesis and osteogenesis in a calvarial defect model, these efforts were mostly limited to structural imaging of the vasculature and bone. Therefore, to better characterize changes in vascular function (i.e. blood flow, oxygenation, etc.) during the bone healing cascade we developed a multicontrast optical imaging framework to assess in vivo changes in microvascular architecture using intrinsic optical signal (IOS) imaging; changes in blood flow with laser speckle contrast (LSC) imaging; and bone formation with bright‐field imaging at high spatial (5 µm) and temporal (200 ms) resolutions. With this system we acquired multicontrast images from 10 animals with calvarial defects every 2 days, over 4 weeks (Fig. 1a, d). The bone and vasculature were then digitally segmented from the bright‐field and IOS images for quantitative analysis (Fig. 1b, c). We also euthanized an animal each week for assessing 3D changes in bone volume and vascular architecture using an ex vivo, high‐resolution (10 µm) CT imaging workflow we recently developed called VascuViz (Fig. 2a, b, d). Using this framework, we demonstrated that angiogenic remodeling within the bone defect microenvironment was most robust from post injury day (D) 4 to D10, during which blood vessel length, volume and density all showed significant increase (Fig. 2c). The blood flow exhibited a sudden increase at D6 when angiogenesis started, and the angiogenic vessels were most perfused at D12 (Fig. 1d). These vascular changes peaked by the end of week 2 and plateaued during the next 2 weeks which were correlated with a large increase in bone volume during the first 2 weeks and smaller increase during the last 2 weeks (Fig. 2e). These results indicate that both structural and functional changes of the microvascular system strongly correlate with bone growth during the early stages of bone healing. Next, we plan to include additional indices of vascular function such as vessel maturity and intravascular oxygenation, as well as image‐based hemodynamic models to further characterize the role of the vascular microenvironment during osteogenesis. We believe that this novel imaging framework for characterizing the defect microenvironment can be utilized to inform the design of novel tissue engineering (TE) constructs for craniofacial bone regeneration. Collectively, these advances herald a new era of “image‐based TE”.
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