Emerging Research on Bone Health Using High-Resolution CT and MRI

Systematic measuring cortical thickness in tibiae for bio-mechanical analysis

BACKGROUND AND OBJECTIVE

Measuring the thickness of cortical bone tissue helps diagnose bone diseases or monitor the progress of different treatments. This type of measurement can be performed visually from CAT images by a radiologist or by semi-automatic algorithms from Hounsfield values. This article proposes a mechanism capable of measuring thickness over the entire bone surface, aligning and orienting all the images in the same direction to have comparable references and reduce human intervention to a minimum. The objective is to batch process large numbers of patients' CAT images obtaining thicknesses profiles of their cortical tissue to be used in many applications.

METHODS

Classical morphological and Deep Learning segmentation is used to extract the area of interest, filtering and interpolation to clean the bones and contour detection and Signed Distance Functions to measure the cortical Thickness. The alignment of the set of bones is achieved by detecting their longitudinal direction, and the orientation is performed by computing their principal component of the center of mass slice.

RESULTS

The method processed in an unattended manner 67% of the patients in the first run and 100% in the second run. The difference in the thickness values between the values provided by the algorithm and the measures done by a radiologist was, on average, 0.25 millimetres with a standard deviation of 0.2.

CONCLUSION

Measuring the cortical thickness of a bone would allow us to prepare accurate traumatological surgeries or study their structural properties. Obtaining thickness profiles of an extensive set of patients opens the way for numerous studies to be carried out to find patterns between bone thickness and the patients' medical, social or demographic variables.

Adaptive local thresholding can enhance the accuracy of HR-pQCT-based trabecular bone morphology assessment

High-resolution peripheral quantitative computed tomography (HR-pQCT) devices can scan extremities at bone microstructural level in vivo and are used mainly in research of bone diseases. Two HR-pQCT scanners are commercially available to date: XtremeCT (first generation) and XtremeCT-II (second generation) from Scanco Medical AG (Switzerland). Recently, we have proposed an adaptive local thresholding (AT) technique and showed that it can improve quantification accuracy of bone microstructural parameters, with visually less sharp cone-beam CT (CBCT) images providing a similar accuracy than XtremeCT. The aim of this study was to evaluate whether the AT segmentation technique could enhance the accuracy of HR-pQCT in quantifying bone microstructural images and to assess whether the agreement between XtremeCT and XtremeCT-II could be improved. Nineteen radii were scanned with three scanners from Scanco Medical AG: (1) XtremeCT at 82 μm, (2) XtremeCT-II at 60.7 μm and (3) the small animal microCT scanner VivaCT40 at 19 μm voxel size. The scans were segmented applying two different methods, once following the manufacturer standard technique (ST), and once by means of AT. Three-dimensional (3D) morphological analysis was performed on the trabecular volume of the segmented images using the manufacturer's standard software to calculate bone volume fraction (BV/TV), trabecular thickness (Tb.Th), separation (Tb.Sp) and number (Tb.N). The average accuracy of XtremeCT improved from R² = 0.76 (ST) to 0.85 (AT) and reached the same level of accuracy as XtremeCT-II with ST (R² = 0.86). The largest improvements were obtained for BV/TV and Tb.Th. For XtremeCT-II, mean accuracy improved slightly from R² = 0.86 (ST) to 0.89 (AT). For both segmentations and both scanners, the standard section was quantified slightly more accurate than the subchondral section. The agreement between the scanners was enhanced from R² = 0.89 (ST) to 0.98 (AT). In conclusion, AT can enhance the accuracy of XtremeCT to quantify distal radius bone microstructural parameters close to XtremeCT-II level and increases the agreement between the two HR-pQCT scanners. High-resolution peripheral quantitative computed tomography, segmentation, bone microstructural parameters.