Micro‐CT based quantification of non‐mineralized tissue on cultured hydroxyapatite scaffolds

Abstract

An improved method to determine material volumes from microcomputed tomography (micro-CT) data is presented. In particular, the method can account for materials with significantly overlapping peaks and small volumes. The example case is a hydroxyapatite scaffold cultured with osteoprogenitor cells. The histogram obtained from the micro-CT data is decomposed into a Gaussian attenuation distribution for each material in the sample, including scaffold, pore and surface tissue, and background. This is done by creating a training set of attenuation data to find initial parameters and then using a nonlinear curve fit, which produced R(2) values greater than 0.998. To determine the material volumes, the curves that simulated each material are integrated, allowing small volume fractions to be accurately quantified. Thresholds for visualizing the samples are chosen based on volume fractions of the Gaussian curves. Additionally, the use of dual-material regions helps accurately visualize tissue on the scaffold, which is otherwise difficult because of the large volume fraction of scaffold. Finally, the curve integration method is compared with Bayesian estimation and intersection thresholding methods. The pore tissue is not represented at all by the Bayesian estimation, and the intersection thresholding method is less accurate than the curve integration method.

Three-Dimensional Characterization of Tissue-Engineered Constructs by Contrast-Enhanced Nanofocus Computed Tomography

“…10,13 The latter approach, without the use of a contrast agent, has also been used for static or bioreactor in vitro cultures, 16,18,19 showing distinct contrast differences between the mineralized matrix and scaffold. Phase-contrast imaging [24][25][26] or micro-CT combined with osmium tetroxide as a contrast agent 28 has shown its potential to assess nonmineralized ECM in an in vitro engineered TE construct. However, the limited availability of synchrotron radiation or CT systems allowing phase-contrast imaging, the toxicity of osmium tetroxide, and the high cost associated with its disposal, all hamper their use as routine quality control for TE constructs.…”

“…On the other hand, by using the more routinely available desktop micro-CT in a standard absorption mode, without the use of a contrast agent, it has not been possible yet to visualize an in vitro produced nonmineralized ECM in 3D scaffolds. 24,27 To address this limitation, osmium tetroxide, 28 a well-known X-ray opaque staining, has been used to visualize cells in 3D constructs. This stain is, however, toxic to cells and thus cannot be used for noninvasive quality control of ECM growth in the TE construct.…”

3D imaging of tissue integration with porous biomaterials

“…This approach works well for detection of mineralized ECM formed within low attenuating materials such as polymeric scaffolds. However, more sophisticated segmentation algorithms may be needed to separate multiple materials with overlapping density distributions [13]. For example, it is difficult to isolate small volumes of bone formed on the surface of hydroxyapatite or other bioceramic material scaffolds.…”

The curve integration method is comparable to manual segmentation for the analysis of bone/scaffold composites using micro‐CT

“…This article compares the curve integration17 method to manual segmentation in order to validate the former. The curve integration method was derived from a segmentation method called supervised classification and has been used to evaluate tissue engineering scaffolds cultured in vitro 17.…”

“…This article compares the curve integration17 method to manual segmentation in order to validate the former. The curve integration method was derived from a segmentation method called supervised classification and has been used to evaluate tissue engineering scaffolds cultured in vitro 17. Supervised classification18–20 has most commonly been used to label land patterns from satellite or aerial photographs in the field of remote sensing 21.…”