Automated Quantitative Bone Analysis in In Vivo X-ray Micro-Computed Tomography

Effect of micro-CT acquisition parameters and individual analysis on the assessment of bone repair

This study aimed to investigate whether two acquisition parameters, voxel size and filter thickness, used in a micro-computed tomography (micro-CT) scan, together with the examiner's experience, influence the outcome of bone repair analysis in an experimental model. Bone defects were created in rat tibiae and scanned using two voxel sizes of 6- or 12-µm and two aluminum filter thickness of 0.5- or 1-mm. Then, bone volume fraction (BV/TV) and trabecular thickness (Tb.Th) were analyzed twice by two groups of operators: experienced and inexperienced examiners. For BV/TV, no significant differences were found between scanning voxel sizes of 6 and 12 µm for the experienced examiners; however, for the inexperienced examiners, the analysis performed using a 12-µm voxel size resulted in higher BV/TV values (32.4 and 32.9) than those acquired using a 6-µm voxel size (25.4 and 24.8) (p < 0.05). For Tb.Th, no significant differences between the analyses performed by experienced and inexperienced groups were observed when using the 6-µm voxel size. However, inexperienced examiners' analysis revealed higher Tb.Th values when using the 12-µm voxel size compared with 6 µm (0.05 vs. 0.03, p < 0.05). Filter thickness had no influence on the results of any group. In conclusion, voxel size and operator experience affected the measured Tb.Th and BV/TV of a region with new bone formation. Operator experience in micro-CT analysis is more critical for BV/TV than for Tb.Th, whereas voxel size significantly affects Tb.Th evaluation. Operators in the initial phases of research training should be calibrated for bone assessments.

Open-source pipeline for automatic segmentation and microstructural analysis of murine knee subchondral bone

μCT images are commonly analysed to assess changes in bone density and microstructure in preclinical murine models. Several platforms provide automated analysis of bone microstructural parameters from volumetric regions of interest (ROI). However, segmentation of the regions of subchondral bone to create the volumetric ROIs remains a manual and time-consuming task. This study aimed to develop an automated end-to-end pipeline, combining segmentation and microstructural analysis, to evaluate subchondral bone in the mouse proximal knee.

METHODS

A segmented dataset of μCT scans from 62 knees (healthy and arthritic) from 10-week male C57BL/6 mice was used to train a U-Net type architecture to automate segmentation of the subchondral trabecular bone. These segmentations were used in tandem with the original scans as input for microstructural analysis along with thresholded trabecular bone. Manually and U-Net segmented ROIs were fed into two available pipelines for microstructural analysis: the ITKBoneMorphometry library and CTan (SKYSCAN). Outcome parameters were compared between pipelines, including: bone volume (BV), total volume (TV), BV/TV, trabecular number (TbN), trabecular thickness (TbTh), trabecular separation (TbSp), and bone surface density (BSBV).

RESULTS

There was good agreement for all bone measures comparing the manual and U-Net pipelines utilizing ITK (R = 0.88-0.98) and CTAn (R = 0.91-0.98). ITK and CTAn showed good agreement for BV, TV, BV/TV, TbTh and BSBV (R = 0.9-0.98). However, limited agreement was seen between TbN (R = 0.73) and TbSb (R = 0.59) due to methodological differences in how spacing is evaluated. Microstructural parameters generated from manual and automatic segmentations showed high correlation across all measures. Using the CTAn pipeline yielded strong R² values (0.83-0.96) and very strong agreement based on ICC (0.90-0.98). The ITK pipeline yielded similarly high R² values (0.91-0.96, except for TbN (0.77)), and ICC values (0.88-0.98). The automated segmentations yield lower average values for BV, TV and BV/TV (ranging from 14 % to 6.3 %), but differences were not found to be influenced by the mean ROI values.

CONCLUSIONS

This integrated pipeline seamlessly automated both segmentation and quantification of the proximal tibia subchondral bone microstructure. This automated pipeline allows the analysis of large volumes of data, and its open-source nature may enable the standardization of microstructural analysis of trabecular bone across different research groups.

Feasibility of 3.5mm C2 pedicle screws in children: Part II, a computerized tomography analysis

BACKGROUND

There have been no studies with large sample sizes on growth of the pedicle of C2 in children. In the present study we measured the pedicle of C2 through computed tomography (CT) imaging in children aged less than 14 years and evaluated the suitability of the 3.5-mm screw for the pedicle in such children.

METHODS

The study was conducted on CT morphometric images of 420 children in our hospital between June 2018 and June 2020. The width (D1), length (D2), height (D3), inclination angle (α), and tail angle (β) of the C2 pedicle were measured. One-way analysis of variance and Student's t test were used for statistical analyses. The least-square method was used to analyze the curve fitting the trend of anatomical change in the pedicle. The largest degree of goodness of fit determined the best-fitting curve.

RESULTS

The size of the pedicle of C2 increased with age. The median ranges of D1, D2, D3, α, and β were 3.312-5.431 mm, 11.732-23.645 mm, 3.597-8.038 mm, 32.583°-36.640°, and 24.867°-31.567°, respectively. The curves fitting the trends of D1 and D3 were power functions, whereas D2 was fitted by a logarithmic curve. However, no curve fitted α or β.

CONCLUSION

A 3.5-mm screw can be placed in the pedicle of C2 in children aged more than one year. The growth and development trend of this pedicle can provide an anatomical reference for deciding on posterior cervical surgery and for selecting and designing pedicle screws for children.

Guidelines for Micro-Computed Tomography Analysis of Rodent Dentoalveolar Tissues

Micro–computed tomography (μCT) has become essential for analysis of mineralized as well as nonmineralized tissues and is therefore widely applicable in the life sciences. However, lack of standardized approaches and protocols for scanning, analyzing, and reporting data often makes it difficult to understand exactly how analyses were performed, how to interpret results, and if findings can be broadly compared with other models and studies. This problem is compounded in analysis of the dentoalveolar complex by the presence of four distinct mineralized tissues: enamel, dentin, cementum, and alveolar bone. Furthermore, these hard tissues interface with adjacent soft tissues, the dental pulp and periodontal ligament (PDL), making for a complex organ. Drawing on others' and our own experience analyzing rodent dentoalveolar tissues by μCT, we introduce techniques to successfully analyze dentoalveolar tissues with similar or disparate compositions, densities, and morphological characteristics. Our goal is to provide practical guidelines for μCT analysis of rodent dentoalveolar tissues, including approaches to optimize scan parameters (filters, voltage, voxel size, and integration time), reproducibly orient samples, define regions and volumes of interest, segment and subdivide tissues, interpret findings, and report methods and results. We include illustrative examples of analyses performed on genetically engineered mouse models with phenotypes in enamel, dentin, cementum, and alveolar bone. The recommendations are designed to increase transparency and reproducibility, promote best practices, and provide a basic framework to apply μCT analysis to the dentoalveolar complex that can also be extrapolated to a variety of other tissues of the body. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.

Bone and joint enhancement filtering: Application to proximal femur segmentation from uncalibrated computed tomography datasets

Methods for reliable femur segmentation enable the execution of quality retrospective studies and building of robust screening tools for bone and joint disease. An enhance-and-segment pipeline is proposed for proximal femur segmentation from computed tomography datasets. The filter is based on a scale-space model of cortical bone with properties including edge localization, invariance to density calibration, rotation invariance, and stability to noise. The filter is integrated with a graph cut segmentation technique guided through user provided sparse labels for rapid segmentation. Analysis is performed on 20 independent femurs. Rater proximal femur segmentation agreement was 0.21 mm (average surface distance), 0.98 (Dice similarity coefficient), and 2.34 mm (Hausdorff distance). Manual segmentation added considerable variability to measured failure load and volume (CV_RMS > 5%) but not density. The proposed algorithm considerably improved inter-rater reproducibility for all three outcomes (CV_RMS < 0.5%). The algorithm localized the periosteal surface accurately compared to manual segmentation but with a slight bias towards a smaller volume. Hessian-based filtering and graph cut segmentation localizes the periosteal surface of the proximal femur with comparable accuracy and improved precision compared to manual segmentation.

3-D X-Ray-Induced Acoustic Computed Tomography With a Spherical Array: A Simulation Study on Bone Imaging

X-ray-induced acoustic computed tomography (XACT) is a promising imaging modality combining high X-ray absorption contrast with the 3-D propagation advantages provided by high-resolution ultrasound waves. The purpose of this study was to optimize the configuration of a 3-D XACT imaging system for bone imaging. A 280 ultrasonic sensors with peak frequency of 10 MHz was designed to distribute on a spherical surface to optimize the 3-D volumetric imaging capability. We performed both theoretical calculations and simulations of this optimized XACT imaging configuration on a mouse-sized digital phantom containing various X-ray absorption coefficients. Iteration algorithm based on total variation has been used for 3-D XACT image reconstruction. The spatial resolution of imaging was estimated to about [Formula: see text] along both axial and lateral directions. We simulate XACT imaging of bone microstructures using digital phantoms generated from micro-CT images of real biological samples, showing that XACT imaging can provide high-resolution imaging of the mouse paw. Results of this study will greatly enhance the potential of XACT imaging in the evaluation of bone diseases for future clinical use.

Overall Bone Structure as Assessed by Slice-by-Slice Profile

Quantifying the inner structure of bones is central to various analyses dealing with the phenotypic evolution of animals with an ossified skeleton. Computed tomography allows to assess the repartition of bone tissue within an entire skeletal element. Two parameters of importance for such analyses are the global compactness (Cg) and total cross-sectional area (Tt.Ar). However, no open-source, time-efficient methods are available to acquire these parameters for whole bones. A methodology to assess the variation of these parameters along a profile following one of the studied bone’s anatomical axes is also wanting. Here I present an ImageJ macro and associated R script to automatically acquire Cg and Tt.Ar along an axis of the skeletal element of interest using a slice-by-slice approach. No manual segmentation is required and several bones can be present on the analysed scan, as long as the bone of interest is isolated and the largest element on each slice. While some bias might be involved by the automatic acquisition, semi-automatic slice exclusion and correction procedures can be used to efficiently account for it. As a test case, µCT-data was gathered for the mid-lumbar vertebra of over 70 mammals. The two evaluated correction procedures proved to perform equally well, with a slight advantage for the one relying on the exclusion of local outliers. The presented macro allows to efficiently build a dataset concerned with the quantification of bone inner structure. The code being readily available, further improvement of the methodology and adjustment to particular needs can be easily performed.

Ex vivo evaluation of an atherosclerotic human coronary artery via histology and high-resolution hard X-ray tomography

Atherosclerotic arteries exhibit characteristic constrictions and substantial deviations from cylindrical shape. Therefore, determining the artery's cross-section along the centerline is challenging, although high-resolution isotropic three-dimensional data are available. Herein, we apply high-resolution computed tomography in absorption and phase to a plaque-containing human artery post-mortem, through the course of the preparation stages for histology. We identify the impact of paraffin embedding and decalcification on the artery lumen. For automatic extraction of lumen's cross-section along centerline we present a dedicated pipeline. Comparing fixated tissue before and after paraffin embedding gives rise to shape changes with lumen reduction to 50-80%. The histological slicing induces further deformations with respect to tomography. Data acquired after decalcification show debris unintentionally distributed within the vessel preventing the reliable automatic lumen segmentation. Comparing tomography of laboratory- and synchrotron-radiation-based X rays by means of joint histogram analysis leads us to conclude that advanced desktop tomography is capable of quantifying the artery's lumen as an essential input for blood flow simulations. The results indicate that the most reliable lumen quantification is achieved by imaging the non-decalcified specimen fixed in formalin, using phase contrast modality and a dedicated processing pipeline. This study focusses on a methodology to quantitatively evaluate diseased artery segments post-mortem and provides unique structural parameters on the treatment-induced local shrinkage, which will be the basis of future studies on the flow in vessels affected by constrictions.