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• W2003174799 abstract "Abstract Cortical bone is perforated by an interconnected network of porous canals that facilitate the distribution of neurovascular structures throughout the cortex. This network is an integral component of cortical microstructure and, therefore, undergoes continual change throughout life as the cortex is remodeled. To date, the investigation of cortical microstructure, including the canal network, has largely been limited to the two‐dimensional (2D) realm due to methodological hurdles. Thanks to continuing improvements in scan resolution, micro‐computed tomography (μCT) is the first nondestructive imaging technology capable of resolving cortical canals. Like its application to trabecular bone, μCT provides an efficient means of quantifying aspects of 3D architecture of the canal network. Our aim here is to introduce the use of μCT for this application by providing examples, discussing some of the parameters that can be acquired, and relating these to research applications. Although several parameters developed for the analysis of trabecular microstructure are suitable for the analysis of cortical porosity, the algorithm used to estimate connectivity is not. We adapt existing algorithms based on skeletonization for this task. We believe that 3D analysis of the dimensions and architecture of the canal network will provide novel information relevant to many aspects of bone biology. For example, parameters related to the size, spacing, and volume of the canals may be particularly useful for investigation of the mechanical properties of bone. Alternatively, parameters describing the 3D architecture of the canal network, such as connectivity between the canals, may provide a means of evaluating cumulative remodeling related change. Anat Rec (Part B: New Anat) 274B:169–179, 2003. © 2003 Wiley‐Liss, Inc." @default.
• W2003174799 created "2016-06-24" @default.
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• W2003174799 date "2003-09-01" @default.
• W2003174799 modified "2023-10-11" @default.
• W2003174799 title "Quantitative 3D analysis of the canal network in cortical bone by micro-computed tomography" @default.
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• W2003174799 doi "https://doi.org/10.1002/ar.b.10024" @default.
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