When bone mass fails to predict bone failure

Ott, Susan M.

doi:10.1007/bf01673395

Cited by 86 publications

(45 citation statements)

References 59 publications

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“…Several studies have shown that there is an association between BMD [1, 2, 20, 21] or BMAD [22,23] and risk of fracture. However, only part of the difference in fracture risk is explained by differences in bone mass [24,25]. In addition to bone mass, bone geometry is thought to be an independent risk factor for fracture risk.…”

Section: Discussionmentioning

confidence: 99%

Determinants of Bone Mass and Bone Geometry in Adolescent and Young Adult Women

Kardinaal¹,

Hoorneman²,

Väänänen

et al. 2000

Calcif Tissue Int

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Bone mass and bone geometry are considered to have independent effects on bone strength. The purpose of this study was to obtain data on bone mass and geometry in young female populations and how they are influenced by body size and lifestyle factors. In a cross-sectional, observational study in six European countries, 1116 healthy Caucasian girls aged 11-15 and 526 women aged 20-23 participated. Their radius was scanned at the ultradistal site and at a site approximately 30% of the radius length from the distal end with dual energy X-ray absorptiometry (DXA). The following parameters were assessed from the scans: bone mineral content (BMC), bone mineral density (BMD), cortical wall thickness (CWT), middistal diameter (D), cortical index (CI = 2CWT/D), and the Breaking Bending Resistance Index (BBRI = (D4 - [D-CWT]4)/D). Calcium intake was assessed by 3-day food records and physical activity by questionnaire. Body size parameters were measured by anthropometry. All parameters showed an increasing trend with pubertal stage and age, except for physical activity and calcium intake. BMC and BMD were relatively more dependent on body weight and age at menarche, whereas variation in D and the mechanical index BBRI was better explained by differences in height and grip strength. CI and CWT were relatively independent of variation in body size, whereas BMC and BBRI especially were explained for a substantial proportion (25-33% in the young adults) by body size parameters. Dietary intake of calcium and level of physical activity seem to contribute little to variation in bone parameters.

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Section: Discussionmentioning

confidence: 99%

Determinants of Bone Mass and Bone Geometry in Adolescent and Young Adult Women

Kardinaal¹,

Hoorneman²,

Väänänen

et al. 2000

Calcif Tissue Int

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“…However, from reviews of several case-control trials it is also known that bone mass shows considerable overlap between groups of subjects who are well matched apart from the presence or absence of a vertebral fracture [1][2][3]. This overlap means there are other factors which contribute to the risk of vertebral fracture for a given subject.…”

Section: Introductionmentioning

confidence: 92%

Image-Based Assessment of Spinal Trabecular Bone Structure from High-Resolution CT Images

Gordon

Lang

Augat

et al. 1998

Osteoporosis International

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The goal of this study was to assess whether a high-resolution CT measure of trabecular bone structure can enhance the discrimination between subjects with or without a vertebral fracture and having overall low hip or spine bone mineral density (BMD) by dual-energy X-ray absorptiometry (DXA). Sixty-one women with low BMD by DXA (T-score < -2.5 at hip or spine) were examined. Twenty women had sustained a vertebral fracture. Quantitative CT (QCT) BMD and high-resolution CT spinal scans were performed on a whole-body CT scanner. For the high-resolution images (0.31 mm pixel, 1.5 mm thick slice), trabecular bone was segmented from marrow using an adaptive threshold, region growth and skeletonization step. From the processed image we measured the apparent trabecular bone fraction (BV/TV), apparent trabecular thickness (I.Th) and apparent trabecular spacing (I.Sp). We also assessed the connectivity of the marrow space using region growing to derive a mean (HA) and maximum (HM) hole size. Despite the fact that the study population was preselected to have a low BMD by DXA, QCT BMD was highly associated with (p < 0.005) with fracture status. All structural parameters were correlated (r approximately 0.64 to 0.79) with BMD with p < 0.003 and showed significant differences between the fracture and non-fracture group. However, except for HA, this difference did not remain significant after adjustment for BMD. When BMD and then HA was entered into a paired linear regression model to predict fracture outcome, HA contributed with p = 0.03 and BMD with p = 0.86. ROC analysis was applied and showed that HA, BMD, I.Th and I.Sp discriminated the two groups with areas of 0.76, 0.75, 0.71 and 0.68, respectively. These findings suggest that an assessment of vertebral trabecular structure from high-resolution CT images is useful in discriminating subjects with vertebral fractures and potentially useful for predicting future fractures.

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“…2,3 However, it has been shown that fracture incidence cannot be predicted by BMD alone. [4][5][6] Other factors such as bone microstructural and mechanical properties contribute significantly to fracture risk. [7][8][9] With advances in imaging techniques and computational methods, image-based micro-finite element analysis (μFEA) has become a valuable noninvasive tool for evaluating bone mechanical properties in response to external loads.…”

Section: Introductionmentioning

confidence: 99%

Potential of in vivo MRI‐based nonlinear finite‐element analysis for the assessment of trabecular bone post‐yield properties

et al. 2013

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Purpose: Bone strength is the key factor impacting fracture risk. Assessment of bone strength from high-resolution (HR) images have largely relied on linear micro-finite element analysis (μFEA) even though failure always occurs beyond the yield point, which is outside the linear regime. Nonlinear μFEA may therefore be more informative in predicting failure behavior. However, existing nonlinear models applied to trabecular bone (TB) have largely been confined to micro-computed tomography (μCT) and, more recently, HR peripheral quantitative computed tomography (HR-pQCT) images, and typically have ignored evaluation of the post-yield behavior. The primary purpose of this work was threefold: (1) to provide an improved algorithm and program to assess TB yield as well as post-yield properties; (2) to explore the potential benefits of nonlinear μFEA beyond its linear counterpart; and (3) to assess the feasibility and practicality of performing nonlinear analysis on desktop computers on the basis of micro-magnetic resonance (μMR) images obtained in vivo in patients. Methods: A method for nonlinear μFE modeling of TB yield as well as post-yield behavior has been designed where material nonlinearity is captured by adjusting the tissue modulus iteratively according to the tissue-level effective strain obtained from linear analysis using a computationally optimized algorithm. The software allows for images at in vivo μMRI resolution as input with retention of grayscale information. Associations between axial stiffness estimated from linear analysis and yield as well as post-yield parameters from nonlinear analysis were investigated from in vivo μMR images of the distal tibia (N = 20; ages: 58-84) and radius (N = 20; ages: 50-75). Results: All simulations were completed in 1 h or less for 61 strain levels using a desktop computer (dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM). Although yield stress and ultimate stress correlated strongly (R 2 > 0.95, p < 0.001) with axial stiffness, toughness correlated moderately at the distal tibia (R 2 = 0.81, p < 0.001) and only weakly at the distal radius (R 2 = 0.34, p = 0.007). Further, toughness was found to vary by up to 16% for bone of very similar axial stiffness (<2%). Conclusions:The work demonstrates the practicality of nonlinear μFE simulations at in vivo μMRI resolution, as well as its potential for providing additional information beyond that obtainable from linear analysis. The data suggest that a direct assessment of toughness may provide information not captured by stiffness.

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When bone mass fails to predict bone failure

Cited by 86 publications

References 59 publications

Determinants of Bone Mass and Bone Geometry in Adolescent and Young Adult Women

Determinants of Bone Mass and Bone Geometry in Adolescent and Young Adult Women

Image-Based Assessment of Spinal Trabecular Bone Structure from High-Resolution CT Images

Potential of in vivo MRI‐based nonlinear finite‐element analysis for the assessment of trabecular bone post‐yield properties

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