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Method Article
* These authors contributed equally
Micro-computed tomography (µCT) is a non-destructive imaging tool that is instrumental in assessing bone structure in preclinical studies, however there is a lack of consensus on µCT procedures for analyzing the bone healing callus. This study provides a step-by-step µCT protocol that allows the monitoring of fracture healing.
Micro-computed tomography (µCT) is the most common imaging modality to characterize the three-dimensional (3D) morphology of bone and newly formed bone during fracture healing in translational science investigations. Studies of long bone fracture healing in rodents typically involve secondary healing and the formation of a mineralized callus. The shape of the callus formed and the density of the newly formed bone may vary substantially between timepoints and treatments. Whereas standard methodologies for quantifying parameters of intact cortical and trabecular bone are widely used and embedded in commercially available software, there is a lack of consensus on procedures for analyzing the healing callus. The purpose of this work is to describe a standardized protocol that quantitates bone volume fraction and callus mineral density in the healing callus. The protocol describes different parameters that should be considered during imaging and analysis, including sample alignment during imaging, the size of the volume of interest, and the number of slices that are contoured to define the callus.
Micro-computed tomography (µCT) imaging has been widely used in preclinical bone research, providing noninvasive, high-resolution images to evaluate the microstructure of bones1,2,3,4,5. µCT involves a large number of X-ray images, obtained from a rotating sample or by using a rotating X-ray source and detector. Algorithms are used to reconstruct 3D volumetric data in the form of a stack of image slices. Clinical CT is the gold standard for 3D imaging of human bones, and µCT is a commonly used technique for evaluating bone healing efficiency in experimental animals1,2,3,4,6,7. Mineralized bone has excellent contrast to X-ray, while soft tissues have relatively poor contrast unless a contrast agent is used. In the assessment of fracture healing, µCT generates images that provide detailed information about the 3D structure and density of the mineralized callus. In vivo µCT scanning can also be used for longitudinal, time-course assessment of fracture healing.
The quantification of intact cortical and trabecular bone using µCT is generally well-established and standardized8. Although preclinical studies use a variety of quantification methodologies to analyze fracture healing9,10,11, a detailed protocol of µCT image analysis for callus quantification has not been published yet.Therefore, the aim of this study is to provide a detailed step-by-step protocol for µCT imaging and analysis of bone healing callus.
The following protocol was developed to characterize long-bone healing callus harvested from euthanized mice. However, most of the steps can be applied to rats and also used for in vivo scanning of fractured bones. The protocol describes a particular µCT system and specific image processing, analysis, and visualization software (see Table of Materials), yet the methodology is generally applicable to other scanners and software. The protocol was approved by the Institutional Animal Care and Use Committee of The Pennsylvania State University College of Medicine. Mice used in this study were 16-week-old, male C57BL/6J mice (average weight 31.45 ± 3.2 g).
1. Tissue harvesting and preservation
NOTE: Use a suitable murine fracture model. For this study, the mid-diaphyseal open tibial fracture model was used according to the standard protocol described in12,13.
2. µCT scanning
Figure 1: Structure of the customized scanning fixture. (A) Images of the scanning fixture (top), showing the six sample slots, and the HA phantom (bottom). (B) Images showing the long-bone sample (top) and the HA phantom (bottom) placed in the dedicated slots. (C) Images showing the scanning fixture placed in a 20 mm syringe. Please click here to view a larger version of this figure.
3. Image segmentation
NOTE: Raw images are automatically reconstructed to image sequence data.
Figure 2: Image segmentation. (A) An image showing six samples within one scan. (B) Image cropping to isolate individual samples. (C) Digital alignment to correct a misaligned longitudinal axis (yellow dotted line). (D) Definition of the VOI and callus center plane. Please click here to view a larger version of this figure.
4. Image analysis
Figure 3: Segmentation of the callus outer boundary. (A) A contour of the outer boundary of the callus (red line). (B) Contours at slices sampled across the VOI (red slices). (C) A 3D callus label created by interpolation (red volume). (D) A cross-section of the callus label shown in C (including cortical bone). Please click here to view a larger version of this figure.
Figure 4: Segmentation of the cortical bone. (A) A contour of the periosteal surface of the cortex (green line). (B) Contours at slices sampled across the VOI (green slices). (C) A 3D label of the cortical bone (containing the medullary cavity; green) and the callus (red) created from interpolated labels of the periosteal cortex and the callus. (D) A cross-section of the callus (red) and the cortical bone (containing the intramedullary cavity; green). Please click here to view a larger version of this figure.
Figure 5: Conversion of gray-scale units to BMD. (A) Contours of the HA cylinder at the first and the last slices (red circles). (B) 3D interpolated HA cylinders (left) and cross-sections (right). Brown: highest HA density; blue: second highest HA density; violet: third highest HA density; green: fourth highest HA density. Please click here to view a larger version of this figure.
Figure 6: Segmentation of the mineralized callus. (A) The mineralized callus (≥250 mgHA/ccm) is shown in blue, the rest of the callus (<250 mgHA/ccm) is shown in red, and the space corresponding to the original bone is shown in green. (B) A 3D view of each isolated label. Please click here to view a larger version of this figure.
To monitor bone formation during fracture healing, a mid-diaphyseal open tibial fracture was induced in adult, male C75BL/6J mice. The fracture was stabilized using an intramedullary nail, an established model of secondary healing13. Callus tissues were harvested at days 14, 21, and 28 post-fracture12. These timepoints represent different phases of healing. Endochondral bone formation during secondary bone healing proceeds via initial formation of a fibro-cartilagi...
The purpose of this study is to describe a detailed protocol for µCT analysis with the goal of accurate quantification of the 3D mineralized callus structure, which is often fundamental in bone and fracture healing studies. The protocol utilizes a general-purpose state-of-the-art 3D image analysis software platform which facilitates image visualization, segmentation/labelling, and measurements ranging from simple to complex.
The most time-consuming task in the protocol is semi-automated s...
The authors have no conflicts of interest to disclose.
This work was supported by National Institutes of Health (NIH) R01 DK121327 to R.A.E and R01 AR071968 to F.K.
Name | Company | Catalog Number | Comments |
10% neutral buffered formalin | Fisher chemical | SF100-20 | Used for bone tissue fixation |
Avizo | Thermo Scientific | Image processing and analysis software | |
Hydroxyapatite phantom | Micro-CT HA D4.5, QRM | QRM-70128 | |
Image Processing Language | Scanco | Used to convert raw images to DICOM images | |
Micro-Mosquito Straight Hemostatic Forceps | Medline | Used to remove the intramedullary pin | |
Microsoft Excel | Microsoft | Spreadsheet software | |
Scanco mCT system (vivaCT 40) | Scanco | Used for µCT imaging |
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