Opportunistic CT screening predicts individuals at risk of major osteoporotic fracture

Michalski, Andrew S.; Besler, Bryce A.; Burt, Lauren A; Boyd, Steven K.

doi:10.1007/s00198-021-05863-0

Cited by 21 publications

(17 citation statements)

References 43 publications

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“…Previous studies confirmed the superiority of FEA to DXA-aBMD (11) and even QCT-vBMD (12) in both prevalent and incident vertebral fracture prediction (13)(14)(15)(16). Aside from fracture prediction, FEA has a unique value in the opportunistic screening of osteoporosis (7), drug efficacy (17), and postoperative evaluation of internal fixation (18).…”

Section: Introductionmentioning

confidence: 82%

“…We adopted diagnostic categories based on spine QCTtrabecular vBMD measurements as the gold standard since previous FEA studies verified the equivalence of FEA and vBMD osteoporotic fracture predictivity, which is superior to DXA (8,9). Compared to QCT, the FE method takes bone geometry and the contribution of cortical bone to bone strength into consideration and requires no additional imaging hardware and radiation exposure (7). It has a promising future in opportunistic screening for osteoporosis and postoperative implant evaluation (18).…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, although DXA was the most meaningful examination for osteoporosis, more than 60% of patients had never undergone DXA before or after fragility fractures (5). Conversely, accessibility to computed tomography (CT) scans are markedly better (6), and approximately 54.5% of those CT scans are performed at relevant osteoporotic fracture sites (7). In 2015, the International Society of Clinical Densitometry identified the priority of quantitative computed tomography (QCT) for its use in fracture prediction (8), as it simultaneously allows DXA-equivalent femoral aBMD, volumetric BMD (vBMD), and finite element analysis (FEA).…”

Section: Introductionmentioning

confidence: 99%

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Influence of image reconstruction kernel on computed tomography-based finite element analysis in the clinical opportunistic screening of osteoporosis—A preliminary result

Jiang

Jin²,

Ming³

et al. 2023

Front. Endocrinol.

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PurposeThis study aimed to evaluate the difference in vertebral mechanical properties estimated by finite element analysis (FEA) with different computed tomography (CT) reconstruction kernels and evaluate their accuracy in the screening and classification of osteoporosis.MethodsThere were 31 patients enrolled retrospectively from the quantitative CT database of our hospital, uniformly covering the range from osteoporosis to normal. All subjects’ CT raw data were reconstructed both with a smooth standard convolution kernel (B40f) and a sharpening bone convolution kernel (B70f), and FEA was performed on L1 of each subject based on two reconstructed images to obtain vertebral estimated strength and stiffness. The trabecular volumetric bone mineral density (vBMD) of the same vertebral body was also measured. FEA measurements between two kernels and their accuracy for osteoporosis screening were compared.ResultsThe vertebral stiffness and strength measured in FEA-B40f were significantly lower compared with those of FEA-B70f (12.0%, p = 0.000 and 10.7%, p = 0.000, respectively). The correlation coefficient between FEA-B70F and vBMD was slightly higher than that of FEA-B40F in both vertebral strength and stiffness (strength: r2-B40f = 0.21, p = 0.009 vs. r2-B70f = 0.27, p = 0.003; stiffness: r2-B40f = 0.37, p = 0.002 vs. r2-B70f = 0.45, p=0.000). The receiver operator characteristic curve showed little difference in the classification of osteoporosis between FEA-B40f and FEA-B70f.ConclusionTwo kernels both seemed to be applicable to the opportunistic screening of osteoporosis by CT-FEA despite variance in FE-estimated bone strength and bone stiffness. A protocol for CT acquisition and FEA is still required to guarantee the reproducibility of clinical use.

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Section: Introductionmentioning

confidence: 82%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Influence of image reconstruction kernel on computed tomography-based finite element analysis in the clinical opportunistic screening of osteoporosis—A preliminary result

Jiang

Jin²,

Ming³

et al. 2023

Front. Endocrinol.

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“…Small artifacts due to manual segmentation along the axial direction are evident. Additional details on the data can be found in a previous study Michalski et al (2021).…”

Section: Methodsmentioning

confidence: 99%

Local Morphometry of Closed, Implicit Surfaces

Besler,

Kemp,

Michalski

et al. 2021

Preprint

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Anatomical structures such as the hippocampus, liver, and bones can be analyzed as orientable, closed surfaces. This permits the computation of volume, surface area, mean curvature, Gaussian curvature, and the Euler-Poincaré characteristic as well as comparison of these morphometrics between structures of different topology. The structures are commonly represented implicitly in curve evolution problems as the zero level set of an embedding. Practically, binary images of anatomical structures are embedded using a signed distance transform. However, quantization prevents the accurate computation of curvatures, leading to considerable errors in morphometry. This paper presents a fast, simple embedding procedure for accurate local morphometry as the zero crossing of the Gaussian blurred binary image. The proposed method was validated based on the femur and fourth lumbar vertebrae of 50 clinical computed tomography datasets. The results show that the signed distance transform leads to large quantization errors in the computed local curvature. Global validation of morphometry using regression and Bland-Altman analysis revealed that the coefficient of determination for the average mean curvature is improved from 93.8% with the signed distance transform to 100% with the proposed method. For the surface area, the proportional bias is improved from -5.0% for the signed distance transform to +0.6% for the proposed method. The Euler-Poincaré characteristic is improved from unusable in the signed distance transform to 98% accuracy for the proposed method. The proposed method enables an improved local and global evaluation of curvature for purposes of morphometry on closed, implicit surfaces.

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“…Finally, CT and MRI scans can be used in the detection of vertebral fractures, sometimes leading to an opportunistic diagnosis. 54 Fracture risk assessment in men Fracture prediction tools can also be used to predict the risk of fractures and to identify the need for BMD measurement. There are several tools available in clinical practice, the best known ones being Fracture Risk Assessment Tool (FRAX) 55 , Garvan 56 and QFracture.…”

Section: Imaging For Osteoporosis In Menmentioning

confidence: 99%