Background: Chronic allograft vasculopathy (CAV) is a major mechanism of graft failure of transplanted organs in humans. Morphometric analysis of coronary arteries enables the quantitation of CAV in mouse models of heart transplantation. However, conventional histological procedures using single 2-dimensional sections limit the accuracy of CAV quantification. The aim of this study is to improve the accuracy of CAV quantification by reconstructing the murine coronary system in 3-dimensions (3D) and using virtual reconstruction and volumetric analysis to precisely assess neointimal thickness.

Methods: Mouse tissue samples, native heart and transplanted hearts with chronic allograft vasculopathy, were collected and analyzed. Paraffin embedded samples were serially sectioned, stained and digitized using whole slide digital imaging techniques under normal and ultraviolet lighting. Sophisticated software tools were used to generate and manipulate 3D reconstructions of the major coronary arteries and branches.

Results: The 3D reconstruction provides not only accurate measurements but also exact volumetric data of vascular lesions. This virtual coronary arteriography demonstrates that the vasculopathy lesions in this model are localized to the proximal coronary segments. In addition, virtual rotation and volumetric analysis enabled more precise measurements of CAV than single, randomly oriented histologic sections, and offer an improved readout for this important experimental model.

Conclusions: We believe 3D reconstruction of 2D histological slides will provide new insights into pathological mechanisms in which structural abnormalities play a role in the development of a disease. The techniques we describe are applicable to the analysis of arteries, veins, bronchioles and similar sized structures in a variety of tissue types and disease model systems.

Virtual Slides: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/3772457541477230 .

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383204PMC
http://dx.doi.org/10.1186/s13000-015-0248-6DOI Listing

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