Summary Estimating bone strength aids in osteoporotic fracture risk assessment. Bone strength is usually calculated with a high-resolution CT; however, this modality has limited clinical utility. We demonstrated that clinical photon-counting CT can also be used for bone strength quantification, which facilitates the use of this information in clinical decision-making. Purpose Quantification of bone strength and microarchitecture at the distal radius with high-resolution peripheral quantitative computed tomography (HR-pQCT) can predict osteoporotic fracture risk independently of dual-energy X-ray absorptiometry. Photon-counting CT (PCCT) is a novel imaging technique with larger fields of view, shorter acquisition times, and similar resolution when compared to HR-pQCT. This study aimed to compare the stiffness and strength of the distal radius computed from PCCT and HR-pQCT images. Methods We evaluated a 10.2 mm section of the distal radius from eight cadaveric forearms scanned with PCCT and HR-pQCT at 0.11 mm and 0.061 mm voxel size, respectively. All CT images were converted to voxel-based linear finite element models. Two material models were used: a segmentation-based model with a fixed Young’s modulus of 10 GPa for bone elements, and a density-based model where Young’s modulus was assigned on a voxel-by-voxel basis, based on its gray value. Poisson’s ratio was set to 0.3 for all elements. Axial compression at 1% apparent strain was applied to quantify stiffness; strength was quantified with the Pistoia criterion. In addition, load sharing between cortical and trabecular bone was quantified. Results We found strong correlations between PCCT and HR-pQCT-derived bone stiffness, strength, and cortical and trabecular proportion for segmentation-based models (R2 > 0.911; p < 2e-4). Correlation and agreement were higher for density-based models (R2 > 0.977; p < 4e-6). Conclusion We demonstrated that PCCT can estimate bone strength with high accuracy and agreement when compared to HR-pQCT. These findings highlight PCCT’s potential in assessing fracture risk in osteoporosis. At the same time, PCCT’s large field of view enables broader usage, at sites different from peripheral limbs.

Bone stiffness and strength at the distal radius can be determined using photon-counting CT

期刊论文
发表日期：

2025年3月21日

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Jilmen Quintiens,
Elena Paravisi,
Piyush Uniyal,
G. Harry van Lenthe

摘要

Summary

Estimating bone strength aids in osteoporotic fracture risk assessment. Bone strength is usually calculated with a high-resolution CT; however, this modality has limited clinical utility. We demonstrated that clinical photon-counting CT can also be used for bone strength quantification, which facilitates the use of this information in clinical decision-making.

Purpose

Quantification of bone strength and microarchitecture at the distal radius with high-resolution peripheral quantitative computed tomography (HR-pQCT) can predict osteoporotic fracture risk independently of dual-energy X-ray absorptiometry. Photon-counting CT (PCCT) is a novel imaging technique with larger fields of view, shorter acquisition times, and similar resolution when compared to HR-pQCT. This study aimed to compare the stiffness and strength of the distal radius computed from PCCT and HR-pQCT images.

Methods

We evaluated a 10.2 mm section of the distal radius from eight cadaveric forearms scanned with PCCT and HR-pQCT at 0.11 mm and 0.061 mm voxel size, respectively. All CT images were converted to voxel-based linear finite element models. Two material models were used: a segmentation-based model with a fixed Young’s modulus of 10 GPa for bone elements, and a density-based model where Young’s modulus was assigned on a voxel-by-voxel basis, based on its gray value. Poisson’s ratio was set to 0.3 for all elements. Axial compression at 1% apparent strain was applied to quantify stiffness; strength was quantified with the Pistoia criterion. In addition, load sharing between cortical and trabecular bone was quantified.

Results

We found strong correlations between PCCT and HR-pQCT-derived bone stiffness, strength, and cortical and trabecular proportion for segmentation-based models (R² > 0.911; p < 2e-4). Correlation and agreement were higher for density-based models (R² > 0.977; p < 4e-6).

Conclusion

We demonstrated that PCCT can estimate bone strength with high accuracy and agreement when compared to HR-pQCT. These findings highlight PCCT’s potential in assessing fracture risk in osteoporosis. At the same time, PCCT’s large field of view enables broader usage, at sites different from peripheral limbs.