Assessment of incident spine and hip fractures in women and men using finite element analysis of CT scans

Validation of Biomechanical Computed Tomography for Fracture Risk Classification in Metastatic Hormone-sensitive Prostate Cancer

BACKGROUND

Guidelines recommend dual-energy x-ray absorptiometry (DXA) screening to assess fracture risk and benefit from antiresorptive therapy in men with metastatic hormone-sensitive prostate cancer (mHSPC) on androgen deprivation therapy (ADT). However, <30% of eligible patients undergo DXA screening. Biomechanical computed tomography (BCT) is a radiomic technique that measures bone mineral density (BMD) and bone strength from computed tomography (CT) scans.

OBJECTIVE

To evaluate the (1) correlations between BCT- and DXA-assessed BMD, and (2) associations between BCT-assessed metrics and subsequent fracture.

DESIGN, SETTING, AND PARTICIPANTS

A multicenter retrospective cohort study was conducted among patients with mHSPC between 2013 and 2020 who received CT abdomen/pelvis or positron emission tomography/CT within 48 wk before ADT initiation and during follow-up (48-96 wk after ADT initiation).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

We used univariate logistic regression to assess the associations between BCT measurements and the primary outcomes of subsequent pathologic and nonpathologic fractures.

RESULTS AND LIMITATIONS

Among 91 eligible patients, the median ([interquartile range) age was 67 yr (62-75), 44 (48.4%) were White, and 41 (45.1%) were Black. During the median follow-up of 82 wk, 17 men (18.6%) developed a pathologic and 15 (16.5%) a nonpathologic fracture. BCT- and DXA-assessed femoral-neck BMD T scores were strongly correlated (R2 = 0.93). On baseline CT, lower BCT-assessed BMD (odds ratio [OR] 1.80, 95% confidence interval or CI [1.10, 3.25], p = 0.03) was associated with an increased risk of a pathologic fracture. Lower femoral strength (OR 1.63, 95% CI [0.99, 2.71], p = 0.06) was marginally associated with an increased risk of a pathologic fracture. Neither BMD (OR 1.52, 95% CI [0.95, 2.63], p = 0.11) nor strength (OR 1.14, 95% CI [0.75, 1.80], p = 0.57) was associated with a nonpathologic fracture. BCT identified nine (9.9%) men eligible for antiresorptive therapy, of whom four (44%) were not treated. Limitations include low fracture numbers resulting in lower power to detect fracture associations.

CONCLUSIONS

Among men diagnosed with mHSPC, BCT assessments were strongly correlated with DXA, predicted subsequent pathologic fracture, and identified additional men indicated for antiresorptive therapy.

PATIENT SUMMARY

We assess whether biomechanical computer tomography (BCT) from routine computer tomography (CT) scans can identify fracture risk among patients recently diagnosed with metastatic prostate cancer. We find that BCT and dual-energy x-ray absorptiometry-derived bone mineral density are strongly correlated and that BCT accurately identifies the risk for future fracture. BCT may enable broader fracture risk assessment and facilitate timely interventions to reduce fracture risk in metastatic prostate cancer patients.

Anatomical and biomechanical factors of osteoporotic vertebral fracture and the occurrence of cascade fractures

Osteoporosis weakens the structural strength of bone to such an extent that normal daily activity may exceed the capacity of the vertebra to bear this load. Vertebral fracture and deformity is a hallmark of osteoporosis. The detriment of trabecular bone properties alone cannot explain the occurrence of osteoporotic vertebral fracture. The ability of the spine to bear and resist loads depends on the structural capacity of the vertebrae, but also on loading conditions arising from activities of daily living or low-energy trauma. This review describes the mechanical properties of the vertebral bone, the structural load-bearing capacity of the various elements forming the spine, the neuromuscular control of the trunk, as well as the biomechanics of the loads to which the spine is subjected in relation to the presence of osteoporosis and the risk of vertebral fracture. A better understanding of biomechanical factors may help to explain both the high incidence of osteoporotic vertebral fractures and their mechanism of production. Consideration of these issues may be important in the development of prevention and management strategies.

Osteoporosis treatment prevents hip fracture similarly in both sexes: the FOCUS observational study

Randomized trials have not been performed, and may never be, to determine if osteoporosis treatment prevents hip fracture in men. Addressing that evidence gap, we analyzed data from an observational study of new hip fractures in a large integrated healthcare system to compare the reduction in hip fractures associated with standard-of-care osteoporosis treatment in men versus women. Sampling from 271 389 patients age ≥ 65 who had a hip-containing computed tomography scan during care between 2005-2018, we selected all who subsequently had a first hip fracture (cases) after the CT scan (start of observation) and a sex-matched equal number of randomly selected patients. From those, we analyzed all who tested positive for osteoporosis (DXA-equivalent hip bone mineral density T-score ≤ -2.5, measured from the CT scan using VirtuOst). We defined "treated" as at least six months of any osteoporosis medication by prescription fill data during follow up; "not-treated" was no prescription fill. Sex-specific odds ratios of hip fracture for treated versus not-treated patients were calculated by logistic regression; adjustments included age, BMD T-score, a BMD-treatment interaction, body mass index, race/ethnicity, and seven baseline clinical risk factors. At two-year follow-up, 33.9% of the women (750/2211 patients) and 24.0% of the men (175/728 patients) were treated, primarily with alendronate; 51.3% and 66.3%, respectively, were not-treated; and 721 and 269, respectively, had a first hip fracture since the CT scan. Odds ratio of hip fracture for treated versus not-treated was 0.26 (95% confidence interval: 0.21-0.33) for women and 0.21 (0.13-0.34) for men; the ratio of these odds ratios (men:women) was 0.81 (0.47-1.37), indicating no significant sex effect. Various sensitivity and stratified analyses confirmed these trends, including results at five-year follow-up. Given these results and considering the relevant literature, we conclude that osteoporosis treatment prevents hip fracture similarly in both sexes.

CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis

The use of opportunistic computed tomography (CT) image-based biomarkers may be a low-cost strategy for screening older individuals at high risk for osteoporotic fractures and populations that are not sufficiently targeted. This review aimed to assess the discriminative ability of image-based biomarkers derived from existing clinical routine CT scans for hip, vertebral, and major osteoporotic fracture prediction. A systematic search in PubMed MEDLINE, Embase, Cochrane, and Web of Science was conducted from the earliest indexing date until July 2023. The evaluation of study quality was carried out using a modified Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. The primary outcome of interest was the area under the curve (AUC) and its corresponding 95% confidence intervals (CIs) obtained for four main categories of biomarkers: areal bone mineral density (BMD), image attenuation, volumetric BMD, and finite element (FE)-derived biomarkers. The meta-analyses were performed using random effects models. Sixty-one studies were included in this review, among which 35 were synthesized in a meta-analysis and the remaining articles were qualitatively synthesized. In comparison to the pooled AUC of areal BMD (0.73 [95% CI 0.71-0.75]), the pooled AUC values for predicting osteoporotic fractures for FE-derived parameters (0.77 [95% CI 0.72-0.81]; p < 0.01) and volumetric BMD (0.76 [95% CI 0.71-0.81]; p < 0.01) were significantly higher, but there was no significant difference with the pooled AUC for image attenuation (0.73 [95% CI 0.66-0.79]; p = 0.93). Compared to areal BMD, volumetric BMD and FE-derived parameters may provide a significant improvement in the discrimination of osteoporotic fractures using opportunistic CT assessments.

DXA-based statistical models of shape and intensity outperform aBMD hip fracture prediction: A retrospective study

Areal bone mineral density (aBMD) currently represents the clinical gold standard for hip fracture risk assessment. Nevertheless, it is characterised by a limited prediction accuracy, as about half of the people experiencing a fracture are not classified as at being at risk by aBMD. In the context of a progressively ageing population, the identification of accurate predictive tools would be pivotal to implement preventive actions. In this study, DXA-based statistical models of the proximal femur shape, intensity (i.e., density) and their combination were developed and employed to predict hip fracture on a retrospective cohort of post-menopausal women. Proximal femur shape and pixel-by-pixel aBMD values were extracted from DXA images and partial least square (PLS) algorithm adopted to extract corresponding modes and components. Subsequently, logistic regression models were built employing the first three shape, intensity and shape-intensity PLS components, and their ability to predict hip fracture tested according to a 10-fold cross-validation procedure. The area under the ROC curves (AUC) for the shape, intensity, and shape-intensity-based predictive models were 0.59 (95%CI 0.47-0.69), 0.80 (95%CI 0.70-0.90) and 0.83 (95%CI 0.73-0.90), with the first being significantly lower than the latter two. aBMD yielded an AUC of 0.72 (95%CI 0.59-0.82), found to be significantly lower than the shape-intensity-based predictive model. In conclusion, a methodology to assess hip fracture risk uniquely based on the clinically available imaging technique, DXA, is proposed. Our study results show that hip fracture risk prediction could be enhanced by taking advantage of the full set of information DXA contains.

3D-DXA Based Finite Element Modelling for Femur Strength Prediction: Evaluation Against QCT

Osteoporosis is characterised by the loss of bone density resulting in an increased risk of fragility fractures. The clinical gold standard for diagnosing osteoporosis is based on the areal bone mineral density (aBMD) used as a surrogate for bone strength, in combination with clinical risk factors. Finite element (FE) analyses based on quantitative computed tomography (QCT) have been shown to estimate bone strength better than aBMD. However, their application in the osteoporosis clinics is limited due to exposure of patients to increased X-rays radiation dose. Statistical modelling methods (3D-DXA) enabling the estimation of 3D femur shape and volumetric bone density from dual energy X-ray absorptiometry (DXA) scan have been shown to improve osteoporosis management. The current study used 3D-DXA based FE analyses to estimate femur strength from the routine clinical DXA scans and compared its results against 151 QCT based FE analyses, in a clinical cohort of 157 subjects. The linear regression between the femur strength predicted by QCT-FE and 3D-DXA-FE models correlated highly (coefficient of determination R2 = 0.86) with a root mean square error (RMSE) of 397 N. In conclusion, the current study presented a 3D-DXA-FE modelling tool providing accurate femur strength estimates noninvasively, compared to QCT-FE models.

Fully automated CT imaging biomarkers for opportunistic prediction of future hip fractures

OBJECTIVE

Assess automated CT imaging biomarkers in patients who went on to hip fracture, compared with controls.

METHODS

In this retrospective case-control study, 6926 total patients underwent initial abdominal CT over a 20-year interval at one institution. A total of 1308 patients (mean age at initial CT, 70.5 ± 12.0 years; 64.4% female) went on to hip fracture (mean time to fracture, 5.2 years); 5618 were controls (mean age 70.3 ± 12.0 years; 61.2% female; mean follow-up interval 7.6 years). Validated fully automated quantitative CT algorithms for trabecular bone attenuation (at L1), skeletal muscle attenuation (at L3), and subcutaneous adipose tissue area (SAT) (at L3) were applied to all scans. Hazard ratios (HRs) comparing highest to lowest risk quartiles and receiver operating characteristic (ROC) curve analysis including area under the curve (AUC) were derived.

RESULTS

Hip fracture HRs (95% CI) were 3.18 (2.69-3.76) for low trabecular bone HU, 1.50 (1.28-1.75) for low muscle HU, and 2.18 (1.86-2.56) for low SAT. 10-year ROC AUC values for predicting hip fracture were 0.702, 0.603, and 0.603 for these CT-based biomarkers, respectively. Multivariate combinations of these biomarkers further improved predictive value; the 10-year ROC AUC combining bone/muscle/SAT was 0.733, while combining muscle/SAT was 0.686.

CONCLUSION

Opportunistic use of automated CT bone, muscle, and fat measures can identify patients at higher risk for future hip fracture, regardless of the indication for CT imaging.

ADVANCES IN KNOWLEDGE

CT data can be leveraged opportunistically for further patient evaluation, with early intervention as needed. These novel AI tools analyse CT data to determine a patient's future hip fracture risk.

Evaluation of bone-related mechanical properties in female patients with long-term remission of Cushing's syndrome using quantitative computed tomography-based finite element analysis

BACKGROUND

Hypercortisolism in Cushing's syndrome (CS) is associated with bone loss, skeletal fragility, and altered bone quality. No studies evaluated bone geometric and strain-stress values in CS patients after remission thus far.

PATIENTS AND METHODS

Thirty-two women with CS in remission (mean age [±SD] 51 ± 11; body mass index [BMI], 27 ± 4 kg/m2; mean time of remission, 120 ± 90 months) and 32 age-, BMI-, and gonadal status-matched female controls. Quantitative computed tomography (QCT) was used to assess volumetric bone mineral density (vBMD) and buckling ratio, cross-sectional area, and average cortical thickness at the level of the proximal femur. Finite element (FE) models were generated from QCT to calculate strain and stress values (maximum principal strain [MPE], maximum strain energy density [SED], maximum Von Mises [VM], and maximum principal stress [MPS]). Areal BMD (aBMD) and trabecular bone score (TBS) were assessed by dual-energy X-ray absorptiometry (2D DXA).

RESULTS

Trabecular vBMD at total hip and trochanter were lower in CS as compared with controls (P < .05). Average cortical thickness was lower, and buckling ratio was greater in CS vs controls (P < .01). All strain and stress values were higher in CS patients vs controls (P < .05). 2D DXA-derived measures were similar between patients and controls (P > .05). Prior hypercortisolism predicted both VM (β .30, P = .014) and MPS (β .30, P = .015), after adjusting for age, BMI, menopause, delay to diagnosis, and duration of remission.

CONCLUSIONS

Women with prior hypercortisolism have reduced trabecular vBMD and impaired bone geometrical and mechanical properties, which may contribute to an elevated fracture risk despite long-term remission.

Vertebral Fracture Risk Thresholds from Phantom-Less Quantitative Computed Tomography-Based Finite Element Modeling Correlate to Phantom-Based Outcomes

INTRODUCTION

Osteoporosis indicates weakened bones and heightened fracture susceptibility due to diminished bone quality. Dual-energy x-ray absorptiometry is unable to assess bone strength. Volumetric bone mineral density (vBMD) from quantitative computed tomography (QCT) has been used to establish guidelines as equivalent measurements for osteoporosis. QCT-based finite element analysis (FEA) has been implemented using calibration phantoms to establish bone strength thresholds based on the established vBMD. The primary aim was to validate vertebral failure load thresholds using a phantom-less approach with previously established thresholds, advancing a phantom-free approach for fracture risk prediction.

METHODOLOGY

A controlled cohort of 108 subjects (68 females) was used to validate sex-specific vertebral fracture load thresholds for normal, osteopenic, and osteoporotic subjects, obtained using a QCT/FEA-based phantom-less calibration approach and two material equations.

RESULTS

There were strong prediction correlations between the phantom-less and phantom-based methods (R2: 0.95 and 0.97 for males, and R2: 0.96 and 0.98 for females) based on the two equations. Bland Altman plots and paired t-tests showed no significant differences between methods. Predictions for bone strengths and thresholds using the phantom-less method matched those obtained using the phantom calibration and those previously established, with ≤4500 N (fragile) and ≥6000 N (normal) bone strength in females, and ≤6500 N (fragile) and ≥8500 N (normal) bone strength in males.

CONCLUSION

Phantom-less QCT-based FEA can allow for prospective and retrospective studies evaluating incidental vertebral fracture risk along the spine and their association with spine curvature and/or fracture etiology. The findings of this study further supported the application of phantom-less QCT-based FEA modeling to predict vertebral strength, aiding in identifying individuals prone to fractures. This reinforces the rationale for adopting this method as a comprehensive approach in predicting and managing fracture risk.

Validity of evaluating spinal kinetics without participant-specific kinematics

Musculoskeletal models are commonly used to estimate in vivo spinal loads under various loading conditions. Typically, participant-specific measured kinematics (PSMK) are coupled with participant-specific models, but obtaining PSMK data can be costly and infeasible in large studies or clinical practice. Thus, we evaluated two alternative methods to estimate spinal loads without PSMK: 1) ensemble average kinematics (EAK) based on kinematics from all participants; and 2) using separately measured individual kinematics (SMIK) from multiple other participants as inputs, then averaging the resulting loads. This study compares the dynamic spine loading patterns and peak loads in older adults performing five lifting tasks using PSMK, EAK and SMIK. Median root mean square errors of EAK and SMIK methods versus PSMK ranged from 18 to 72% body weight for compressive loads and from 2 to 25% body weight for shear loads, with median cross-correlations ranging from 0.931 to 0.991. The root mean square errors and cross-correlations between repeated PSMK trials fell within similar ranges. Compressive peak loads evaluated by EAK and SMIK were not different than PSMK in 12 of 15 cases, while by comparison repeated PSMK trials were not different in 13 of 15 cases. Overall, the resulting spine loading magnitudes and profiles using EAK or SMIK were not notably different than using a PSMK approach, and differences were not greater than between two PSMK trials. Thus, these findings indicate that these approaches may be used to make reasonable estimates of dynamic spinal loading without direct measurement of participant kinematics.

EMG Validation of a Subject-Specific Thoracolumbar Spine Musculoskeletal Model During Dynamic Activities in Older Adults

Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and for magnitude differences via root-mean-square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that across most of the tasks the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92 ± 0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60 ± 0.20). Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18 ± 0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate subject-specific in vivo muscular activations for these dynamic lifting tasks.

Cortical and Trabecular Bone Deficit in Middle-Aged Men Living with HIV

A significant increase in the risk of hip fracture was observed in middle-aged men living with human immunodeficiency virus (MLWH), almost a decade earlier than those without infection. Data regarding cortical and trabecular bone deficit of hip, an important determinant of bone strength, in MLWH are limited. Quantitative CT was performed in consecutive MLWH aged ≥30 years between November 2017 and October 2018 at Severance Hospital, Seoul, Korea. Volumetric bone mineral density (vBMD) and cortical bone mapping parameters of hip (cortical thickness [CTh], cortical bone vBMD [CBMD], cortical mass surface density [CMSD], endocortical trabecular density [ECTD]) were compared to age-matched and body mass index (BMI)-matched controls (1:2) using a community-based healthy adults cohort. Among 83 MLWH and 166 controls (mean age: 47.2 years; BMI: 23.6 kg/m2 ), MLWH had lower total hip vBMD (280 ± 41 versus 296 ± 41 mg/cm3 ), CMSD (155 versus 160 mg/cm2 ), and ECTD (158 versus 175 mg/cm3 ) than controls that remained robust after adjustment for covariates (adjusted β: total hip vBMD, -18.8; CMSD, -7.3; ECTD, -18.0; p < 0.05 for all). Cortical bone mapping revealed localized deficit of CTh, CBMD, and CMSD in the anterolateral trochanteric region and femoral neck in MLWH compared to controls, with a more extensive ECTD deficit. In MLWH, lower CD4 T-cell count (/100 cells/mm3 decrement) and protease inhibitor (PI)-based regimen (versus non-PI regimen) at the time of antiretroviral treatment initiation were associated with lower total hip vBMD (adjusted β -7.5 for lower CD4 count; -28.3 for PI-based regimen) and CMSD (adjusted β -2.6 for lower CD4 count; -12.7 for PI-based regimen; p < 0.05 for all) after adjustment for covariates including age, BMI, smoking, alcohol use, hepatitis C virus co-infection, tenofovir exposure, and CT scanner types. MLWH had lower hip bone density with cortical and trabecular bone deficit compared to community-dwelling controls. © 2023 American Society for Bone and Mineral Research (ASBMR).

An integrated experimental-computational framework to assess the influence of microstructure and material properties on fracture toughness in clinical specimens of human femoral cortical bone

Microstructural and compositional changes that occur due to aging, pathological conditions, or pharmacological treatments alter cortical bone fracture resistance. However, the relative importance of these changes to the fracture resistance of cortical bone has not been quantified in detail. In this technical note, we developed an integrated experimental-computational framework utilizing human femoral cortical bone biopsies to advance the understanding of how fracture resistance of cortical bone is modulated due to modifications in its microstructure and material properties. Four human biopsy samples from individuals with varying fragility fracture history and osteoporosis treatment status were converted to finite element models incorporating specimen-specific material properties and were analyzed using fracture mechanics-based modeling. The results showed that cement line density and osteonal volume had a significant effect on crack volume. The removal of cement lines substantially increased the crack volume in the osteons and interstitial bone, representing straight crack growth, compared to models with cement lines due to the lack of crack deflection in the models without cement lines. Crack volume in the osteons and interstitial bone increased when mean elastic modulus and ultimate strength increased and mean fracture toughness decreased. Crack volume in the osteons and interstitial bone was reduced when material property heterogeneity was incorporated in the models. Although both the microstructure and the heterogeneity of the material properties of the cortical bone independently increased the fracture toughness, the relative contribution of the microstructure was more significant. The integrated experimental-computational framework developed here can identify the most critical microscale features of cortical bone modulated by pathological processes or pharmacological treatments that drive changes in fracture resistance and improve our understanding of the relative influence of microstructure and material properties on fracture resistance of cortical bone.

Biomechanical CT to Assess Bone After Sleeve Gastrectomy in Adolescents With Obesity: A Prospective Longitudinal Study

Sleeve gastrectomy (SG) is effective in treating cardiometabolic complications of obesity but is associated with bone loss. Our aim was to determine the effect of SG on the lumbar spine by biomechanical CT analysis in adolescents/young adults with obesity. We hypothesized that SG would lead to a decrease in strength and bone mineral density (BMD) compared with nonsurgical controls. In a 12-month prospective nonrandomized study, adolescents/young adults with obesity underwent SG (n = 29, 18.0 ± 2.1 years, 23 female) or were followed without surgery (controls, n = 30, 17.95 ± 3.0 years, 22 female). At baseline and 12 months, participants underwent quantitative computed tomography (QCT) of L1 and L2 for biomechanical assessment and MRI of the abdomen and mid-thigh for body composition assessment. Twelve-month changes between groups and within groups were assessed. Analyses were controlled for baseline and 12-month changes in body mass index (BMI) by multivariable analyses. Regression analysis was performed to evaluate the effect of body composition on bone parameters. Our institutional review board (IRB) approved the study, and informed consent/assent was obtained. Participants in the SG group had a higher baseline BMI than controls (p = 0.01) and lost an average of 34.3 ± 13.6 kg 12 months after surgery, whereas weight was unchanged in controls (p < 0.001). There were significant reductions in abdominal adipose tissue and thigh muscle area in the SG group compared with controls (p < 0.001). Bone strength, bending stiffness, and average and trabecular volumetric BMD decreased in the SG group compared with controls (p < 0.001). After controlling for change in BMI, a 12-month reduction in cortical BMD was significant in the SG group compared with controls (p = 0.02). Reductions in strength and trabecular BMD were associated with reductions in BMI, visceral adipose tissue, and muscle (p ≤ 0.03). In conclusion, SG in adolescents decreased strength and volumetric BMD of the lumbar spine compared with nonsurgical controls. These changes were associated with decreases in visceral fat and muscle mass. © 2023 American Society for Bone and Mineral Research (ASBMR).

Finite element analysis of bone mechanical properties using MRI-derived bound and pore water concentration maps

Ultrashort echo time (UTE) MRI techniques can be used to image the concentration of water in bones. Particularly, quantitative MRI imaging of collagen-bound water concentration (Cbw) and pore water concentration (Cpw) in cortical bone have been shown as potential biomarkers for bone fracture risk. To investigate the effect of Cbw and Cpw on the evaluation of bone mechanical properties, MRI-based finite element models of cadaver radii were generated with tissue material properties derived from 3 D maps of Cbw and Cpw measurements. Three-point bending tests were simulated by means of the finite element method to predict bending properties of the bone and the results were compared with those from direct mechanical testing. The study results demonstrate that these MRI-derived measures of Cbw and Cpw improve the prediction of bone mechanical properties in cadaver radii and have the potential to be useful in assessing patient-specific bone fragility risk.

Relationship between trabecular bone score, bone mineral density and vertebral fractures in patients with axial spondyloarthritis

BACKGROUND

In patients with axial spondyloarthritis, vertebral fracture risk is elevated and not always correlated with bone mineral density (BMD). Trabecular bone score (TBS) may offer some advantages in the assessment of vertebral fracture risk in these patients. The primary objective of this study was to compare TBS and BMD between axial spondyloarthritis patients depending on their vertebral fracture status. Secondary objectives were to estimate the prevalence of morphometric vertebral fractures, and to explore factors associated with fracture, as well as the interference of syndesmophytes on BMD and TBS.

METHODS

A cross-sectional study was conducted. Data were collected on demographic and clinical characteristics, lab results, imaging findings and treatment. Statistical analysis was performed using SPSS v.13 statistical software.

RESULTS

Eighty-four patients (60 men and 24 women; mean age of 59 years) were included. Nearly half (47.6%) of them had lumbar syndesmophytes. The rate of morphometric fracture was 11.9%. TBS showed a higher area under the curve (0.89) than total hip, femoral neck and lumbar BMD (0.80, 0.78, and 0.70 respectively) for classifying patients regarding their fracture status. Nonetheless, the differences did not reach statistical significance. Syndesmophytes affected lumbar spine BMD (p < 0.001), but not hip BMD or TBS. Fractures were associated with TBS, total hip BMD, erythrocyte sedimentation rate and C-reactive protein levels.

CONCLUSIONS

We identified decreased TBS and total hip BMD, as well as increased erythrocyte sedimentation rate and C-reactive protein levels as factors associated with morphometric vertebral fractures. Unlike lumbar spine BMD, TBS is not affected by the presence of syndesmophytes.

Prevalence of osteoporosis in older male veterans receiving hip-containing computed tomography scans: opportunistic use of biomechanical computed tomography analysis (BCT)

Osteoporosis care in men is suboptimal due to low rates of testing and treatment. Applying biomechanical computed tomography (BCT) analysis to existing CT scans, we found a high proportion of men with osteoporosis have never been diagnosed or treated. BCT may improve identification of patients at high risk of fracture.

PURPOSE

Osteoporosis care in men is suboptimal due to low rates of DXA testing and treatment. Biomechanical computed tomography analysis (BCT) can be applied "opportunistically" to prior hip-containing CT scans to measure femoral bone strength and hip BMD.

METHODS

In this retrospective, cross-sectional study, we used BCT in male veterans with existing CT scans to investigate the prevalence of osteoporosis, defined by hip BMD (T-score ≤  - 2.5) or fragile bone strength (≤ 3500 N). 577 men, age ≥ 65 with abdominal/pelvic CTs performed in 2017-2019, were randomly selected for BCT analysis. Clinical data were collected via electronic health records and used with the femoral neck BMD T-score from BCT to estimate 10-year hip fracture risks by FRAX.

RESULTS

Prevalence of osteoporosis by BCT increased with age (13.5% age 65-74; 18.2% age 75-84; 34.3% age ≥ 85), with an estimated overall prevalence of 18.3% for men age ≥ 65. In those with osteoporosis (n = 108/577), only 38.0% (41/108) had a prior DXA and 18.6% (7/108) had received osteoporosis pharmacotherapy. Elevated hip fracture risk by FRAX (≥ 3%) did not fully capture those with fragile bone strength. In a multivariate logistic regression model adjusted for age, BMI, race, and CT location, end stage renal disease (odds ratio 7.4; 95% confidence interval 2.3-23.9), COPD (2.2; 1.2-4.0), and high-dose inhaled corticosteroid use (3.7; 1.2-11.8) were associated with increased odds of having osteoporosis by BCT.

CONCLUSION

Opportunistic BCT in male veterans provides an additional avenue to identify patients who are at high risk of fractures.

Increased risks of vertebral fracture and reoperation in primary spinal fusion patients who test positive for osteoporosis by Biomechanical Computed Tomography analysis

BACKGROUND CONTEXT

While osteoporosis is a risk factor for adverse outcomes in spinal fusion patients, diagnosing osteoporosis reliably in this population has been challenging due to degenerative changes and spinal deformities. Addressing that challenge, biomechanical computed tomography analysis (BCT) is a CT-based diagnostic test for osteoporosis that measures both bone mineral density and bone strength (using finite element analysis) at the spine; CT scans taken for spinal evaluation or previous care can be repurposed for the analysis.

PURPOSE

Assess the effectiveness of BCT for preoperatively identifying spinal fusion patients with osteoporosis who are at high risk of reoperation or vertebral fracture.

STUDY DESIGN

Observational cohort study in a multi-center integrated managed care system using existing data from patient medical records and imaging archives.

PATIENT SAMPLE

We studied a randomly sampled subset of all adult patients who had any type of primary thoracic (T4 or below) or lumbar fusion between 2005 and 2018. For inclusion, patients with accessible study data needed a preop CT scan without intravenous contrast that contained images (before any instrumentation) of the upper instrumented vertebral level.

OUTCOME MEASURES

Reoperation for any reason (primary outcome) or a newly documented vertebral fracture (secondary outcome) occurring up to 5 years after the primary surgery.

METHODS

All study data were extracted using available coded information and CT scans from the medical records. BCT was performed at a centralized lab blinded to the clinical outcomes; patients could test positive for osteoporosis based on either low values of bone strength (vertebral strength ≤ 4,500 N women or 6,500 N men) and/or bone mineral density (vertebral trabecular bone mineral density ≤ 80 mg/cm³ both sexes). Cox proportional hazard ratios were adjusted by age, presence of obesity, and whether the fusion was long (four or more levels fused) or short (3 or fewer levels fused); Kaplan-Meier survival was compared by the log rank test. This project was funded by NIH (R44AR064613) and all physician co-authors and author 1 received salary support from their respective departments. Author 6 is employed by, and author 1 has equity in and consults for, the company that provides the BCT test; the other authors declare no conflicts of interest.

RESULTS

For the 469 patients analyzed (298 women, 171 men), median follow-up time was 44.4 months, 11.1% had a reoperation (median time 14.5 months), and 7.7% had a vertebral fracture (median time 2.0 months). Overall, 25.8% of patients tested positive for osteoporosis and no patients under age 50 tested positive. Compared to patients without osteoporosis, those testing positive were at almost five-fold higher risk for vertebral fracture (adjusted hazard ratio 4.7, 95% confidence interval = 2.2-9.7; p<.0001 Kaplan-Meier survival). Of those positive-testing patients, those who tested positive concurrently for low values of both bone strength and bone mineral density (12.6% of patients overall) were at almost four-fold higher risk for reoperation (3.7, 1.9-7.2; Kaplan-Meier survival p<.0001); the remaining positive-testing patients (those who tested positive for low values of either bone strength or bone mineral density but not both) were not at significantly higher risk for reoperation (1.6, 0.7-3.7) but were for vertebral fracture (4.3, 1.9-10.2). For both clinical outcomes, risk remained high for patients who underwent short or long fusion.

CONCLUSION

In a real-world clinical setting, BCT was effective in identifying primary spinal fusion patients aged 50 or older with osteoporosis who were at elevated risks of reoperation and vertebral fracture.

Opportunistic Screening Techniques for Analysis of CT Scans

PURPOSE OF REVIEW

Opportunistic screening is a combination of techniques to identify subjects of high risk for osteoporotic fracture using routine clinical CT scans prescribed for diagnoses unrelated to osteoporosis. The two main components are automated detection of vertebral fractures and measurement of bone mineral density (BMD) in CT scans, in which a phantom for calibration of CT to BMD values is not used. This review describes the particular challenges of opportunistic screening and provides an overview and comparison of current techniques used for opportunistic screening. The review further outlines the performance of opportunistic screening.

RECENT FINDINGS

A wide range of technologies for the automatic detection of vertebral fractures have been developed and successfully validated. Most of them are based on artificial intelligence algorithms. The automated differentiation of osteoporotic from traumatic fractures and vertebral deformities unrelated to osteoporosis, the grading of vertebral fracture severity, and the detection of mild vertebral fractures is still problematic. The accuracy of automated fracture detection compared to classical radiological semi-quantitative Genant scoring is about 80%. Accuracy errors of alternative BMD calibration methods compared to simultaneous phantom-based calibration used in standard quantitative CT (QCT) range from below 5% to about 10%. The impact of contrast agents, frequently administered in clinical CT on the determination of BMD and on fracture risk determination is still controversial. Opportunistic screening, the identification of vertebral fracture and the measurement of BMD using clinical routine CT scans, is feasible but corresponding techniques still need to be integrated into the clinical workflow and further validated with respect to the prediction of fracture risk.

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

PURPOSE

This 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.

METHODS

There 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.

RESULTS

The 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: r ²-B40f = 0.21, p = 0.009 vs. r ²-B70f = 0.27, p = 0.003; stiffness: r ²-B40f = 0.37, p = 0.002 vs. r ²-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.

CONCLUSION

Two 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.

Prediction of femoral strength of elderly men based on quantitative computed tomography images using machine learning

Hip fracture is the most common complication of osteoporosis, and its major contributor is compromised femoral strength. This study aimed to develop practical machine learning models based on clinical quantitative computed tomography (QCT) images for predicting proximal femoral strength. Eighty subjects with entire QCT data of the right hip region were randomly selected from the full MrOS cohorts, and their proximal femoral strengths were calculated by QCT-based finite element analysis (QCT/FEA). A total of 50 parameters of each femur were extracted from QCT images as the candidate predictors of femoral strength, including grayscale distribution, regional cortical bone mapping (CBM) measurements, and geometric parameters. These parameters were simplified by using feature selection and dimensionality reduction. Support vector regression (SVR) was used as the machine learning algorithm to develop the prediction models, and the performance of each SVR model was quantified by the mean squared error (MSE), the coefficient of determination (R² ), the mean bias, and the SD of bias. For feature selection, the best prediction performance of SVR models was achieved by integrating the grayscale value of 30% percentile and specific regional CBM measurements (MSE ≤ 0.016, R² ≥ 0.93); and for dimensionality reduction, the best prediction performance of SVR models was achieved by extracting principal components with eigenvalues greater than 1.0 (MSE ≤ 0.014, R² ≥ 0.93). The femoral strengths predicted from the well-trained SVR models were in good agreement with those derived from QCT/FEA. This study provided effective machine learning models for femoral strength prediction, and they may have great potential in clinical bone health assessments.

2D-3D reconstruction of the proximal femur from DXA scans: Evaluation of the 3D-Shaper software

Introduction: Osteoporosis is currently diagnosed based on areal bone mineral density (aBMD) computed from 2D DXA scans. However, aBMD is a limited surrogate for femoral strength since it does not account for 3D bone geometry and density distribution. QCT scans combined with finite element (FE) analysis can deliver improved femoral strength predictions. However, non-negligible radiation dose and high costs prevent a systematic usage of this technique for screening purposes. As an alternative, the 3D-Shaper software (3D-Shaper Medical, Spain) reconstructs the 3D shape and density distribution of the femur from 2D DXA scans. This approach could deliver a more accurate estimation of femoral strength than aBMD by using FE analysis on the reconstructed 3D DXA. Methods: Here we present the first independent evaluation of the software, using a dataset of 77 ex vivo femora. We extend a prior evaluation by including the density distribution differences, the spatial correlation of density values and an FE analysis. Yet, cortical thickness is left out of this evaluation, since the cortex is not resolved in our FE models. Results: We found an average surface distance of 1.16 mm between 3D DXA and QCT images, which shows a good reconstruction of the bone geometry. Although BMD values obtained from 3D DXA and QCT correlated well (r ² = 0.92), the 3D DXA BMD were systematically lower. The average BMD difference amounted to 64 mg/cm³, more than one-third of the 3D DXA BMD. Furthermore, the low correlation (r ² = 0.48) between density values of both images indicates a limited reconstruction of the 3D density distribution. FE results were in good agreement between QCT and 3D DXA images, with a high coefficient of determination (r ² = 0.88). However, this correlation was not statistically different from a direct prediction by aBMD. Moreover, we found differences in the fracture patterns between the two image types. QCT-based FE analysis resulted mostly in femoral neck fractures and 3D DXA-based FE in subcapital or pertrochanteric fractures. Discussion: In conclusion, 3D-Shaper generates an altered BMD distribution compared to QCT but, after careful density calibration, shows an interesting potential for deriving a standardized femoral strength from a DXA scan.

Biomechanical CT-computed bone strength predicts the risk of subsequent vertebral fracture

Following primary fractures and percutaneous kyphoplasty (PKP), patients have a high risk of incurring a subsequent vertebral fracture (SVF). Given that SVF is a consequence of mechanical deterioration of the vertebra, we sought to examine whether vertebral strength derived from QCT-based finite element analysis (i.e., BCT) can predict the risk of SVF. Sixty-six patients who underwent PKP were categorized into two groups: control or non-SVF group (age: 70 ± 7 years; n = 40) and SVF group (age: 69 ± 8 years; n = 26). BCT was performed on L4 or L3 vertebrae to noninvasively measure vertebral strength. Vertebral strength was also estimated based upon the geometry and material properties of the vertebra. Additionally, trabecular volumetric bone mineral density (vBMD) and L1 Hounsfield unit (HU) were measured. t-Test, χ² test or Mann Whitney U test were used to compare differences in these parameters between the two groups. The predictive abilities of BCT strength and other measured parameters were evaluated using the receiver operating characteristic (ROC) analysis. Results showed no significant difference in either vBMD or L1 HU between the control and SVF groups (p > 0.05), whereas BCT-computed and estimated vertebral strength values were significantly reduced by 33 % and 24 % for the SVF group relative to the non-SVF group, respectively. ROC curve indicated that BCT strength had the largest area under the curve, compared to other parameters. These results suggest that BCT-computed vertebral strength may serve as a surrogate for assessing risk of SVF.

The role of opportunistic quantitative computed tomography in the evaluation of bone disease and risk of fracture in thalassemia major

OBJECTIVE

Dual-energy X-ray absorptiometry (DXA) remains the cornerstone for osteoporosis evaluation in Thalassemia major. However, several drawbacks have been observed in this unique setting. We sought to determine the correlation between quantitative CT (QCT) and DXA-derived parameters; secondarily, we aimed to investigate the role of the two techniques in predicting the risk of fracture.

METHODS

We retrospectively included patients with β-thalassemia major who had undergone both lumbar and femoral DXA examinations, and CT scans including the lumbar spine, performed for disparate diagnostic issues, within 4 months from the DXA. CT data were examined employing a phantom-less QCT method for bone mineral density (BMD) assessment. We also retrieved any spontaneous or fragility fractures occurring from 1 year before up to 5 years after the date of DXA scans.

RESULTS

The 43 patients were included. QCT measures were significantly higher than those determined by DXA. The gap between QCT and DXA values was strongly associated with patient age. The most powerful predictive variable for risk of fracture was the ACR classification based on volumetric BMD obtained by QCT.

CONCLUSIONS

DXA provided more negative measures than those determined by QCT. However, QCT seemed to evaluate thalassaemic osteopathy better than DXA, since volumetric BMD was a stronger predictor of fracture.

A Review of CT-Based Fracture Risk Assessment with Finite Element Modeling and Machine Learning

PURPOSE OF REVIEW

We reviewed advances over the past 3 years in assessment of fracture risk based on CT scans, considering methods that use finite element models, machine learning, or a combination of both.

RECENT FINDINGS

Several studies have demonstrated that CT-based assessment of fracture risk, using finite element modeling or biomarkers derived from machine learning, is equivalent to currently used clinical tools. Phantomless calibration of CT scans for bone mineral density enables accurate measurements from routinely taken scans. This opportunistic use of CT scans for fracture risk assessment is facilitated by high-quality automated segmentation with deep learning, enabling workflows that do not require user intervention. Modeling of more realistic and diverse loading conditions, as well as improved modeling of fracture mechanisms, has shown promise to enhance our understanding of fracture processes and improve the assessment of fracture risk beyond the performance of current clinical tools. CT-based screening for fracture risk is effective and, by analyzing scans that were taken for other indications, could be used to expand the pool of people screened, therefore improving fracture prevention. Finite element modeling and machine learning both provide valuable tools for fracture risk assessment. Future approaches should focus on including more loading-related aspects of fracture risk.

The application of artificial intelligence in spine surgery

Due to its obvious advantages in processing big data and image information, the combination of artificial intelligence and medical care may profoundly change medical practice and promote the gradual transition from traditional clinical care to precision medicine mode. In this artical, we reviewed the relevant literatures and found that artificial intelligence was widely used in spine surgery. The application scenarios included etiology, diagnosis, treatment, postoperative prognosis and decision support systems of spinal diseases. The shift to artificial intelligence model in medicine constantly improved the level of doctors' diagnosis and treatment and the development of orthopedics.

Evaluation of Load-To-Strength Ratios in Metastatic Vertebrae and Comparison With Age- and Sex-Matched Healthy Individuals

Vertebrae containing osteolytic and osteosclerotic bone metastases undergo pathologic vertebral fracture (PVF) when the lesioned vertebrae fail to carry daily loads. We hypothesize that task-specific spinal loading patterns amplify the risk of PVF, with a higher degree of risk in osteolytic than in osteosclerotic vertebrae. To test this hypothesis, we obtained clinical CT images of 11 cadaveric spines with bone metastases, estimated the individual vertebral strength from the CT data, and created spine-specific musculoskeletal models from the CT data. We established a musculoskeletal model for each spine to compute vertebral loading for natural standing, natural standing + weights, forward flexion + weights, and lateral bending + weights and derived the individual vertebral load-to-strength ratio (LSR). For each activity, we compared the metastatic spines' predicted LSRs with the normative LSRs generated from a population-based sample of 250 men and women of comparable ages. Bone metastases classification significantly affected the CT-estimated vertebral strength (Kruskal-Wallis, p < 0.0001). Post-test analysis showed that the estimated vertebral strength of osteosclerotic and mixed metastases vertebrae was significantly higher than that of osteolytic vertebrae (p = 0.0016 and p = 0.0003) or vertebrae without radiographic evidence of bone metastasis (p = 0.0010 and p = 0.0003). Compared with the median (50%) LSRs of the normative dataset, osteolytic vertebrae had higher median (50%) LSRs under natural standing (p = 0.0375), natural standing + weights (p = 0.0118), and lateral bending + weights (p = 0.0111). Surprisingly, vertebrae showing minimal radiographic evidence of bone metastasis presented significantly higher median (50%) LSRs under natural standing (p < 0.0001) and lateral bending + weights (p = 0.0009) than the normative dataset. Osteosclerotic vertebrae had lower median (50%) LSRs under natural standing (p < 0.0001), natural standing + weights (p = 0.0005), forward flexion + weights (p < 0.0001), and lateral bending + weights (p = 0.0002), a trend shared by vertebrae with mixed lesions. This study is the first to apply musculoskeletal modeling to estimate individual vertebral loading in pathologic spines and highlights the role of task-specific loading in augmenting PVF risk associated with specific bone metastatic types. Our finding of high LSRs in vertebrae without radiologically observed bone metastasis highlights that patients with metastatic spine disease could be at an increased risk of vertebral fractures even at levels where lesions have not been identified radiologically.

Patient-Specific Finite Element Modeling of the Whole Lumbar Spine Using Clinical Routine Multi-Detector Computed Tomography (MDCT) Data-A Pilot Study

(1) Background: To study the feasibility of developing finite element (FE) models of the whole lumbar spine using clinical routine multi-detector computed tomography (MDCT) scans to predict failure load (FL) and range of motion (ROM) parameters. (2) Methods: MDCT scans of 12 subjects (6 healthy controls (HC), mean age ± standard deviation (SD): 62.16 ± 10.24 years, and 6 osteoporotic patients (OP), mean age ± SD: 65.83 ± 11.19 years) were included in the current study. Comprehensive FE models of the lumbar spine (5 vertebrae + 4 intervertebral discs (IVDs) + ligaments) were generated (L1−L5) and simulated. The coefficients of correlation (ρ) were calculated to investigate the relationship between FE-based FL and ROM parameters and bone mineral density (BMD) values of L1−L3 derived from MDCT (BMDQCT-L1-3). Finally, Mann−Whitney U tests were performed to analyze differences in FL and ROM parameters between HC and OP cohorts. (3) Results: Mean FE-based FL value of the HC cohort was significantly higher than that of the OP cohort (1471.50 ± 275.69 N (HC) vs. 763.33 ± 166.70 N (OP), p < 0.01). A strong correlation of 0.8 (p < 0.01) was observed between FE-based FL and BMDQCT-L1-L3 values. However, no significant differences were observed between ROM parameters of HC and OP cohorts (p = 0.69 for flexion; p = 0.69 for extension; p = 0.47 for lateral bending; p = 0.13 for twisting). In addition, no statistically significant correlations were observed between ROM parameters and BMDQCT- L1-3. (4) Conclusions: Clinical routine MDCT data can be used for patient-specific FE modeling of the whole lumbar spine. ROM parameters do not seem to be significantly altered between HC and OP. In contrast, FE-derived FL may help identify patients with increased osteoporotic fracture risk in the future.

Circulating serum microRNAs including senescent miR-31-5p are associated with incident fragility fractures in older postmenopausal women with type 2 diabetes mellitus

Fragility fractures are an important hallmark of aging and an increasingly recognized complication of Type 2 diabetes (T2D). T2D individuals have been found to exhibit an increased fracture risk despite elevated bone mineral density (BMD) by dual x-ray absorptiometry (DXA). However, BMD and FRAX-scores tend to underestimate fracture risk in T2D. New, reliable biomarkers are therefore needed. MicroRNAs (miRNAs) are secreted into the circulation from cells of various tissues proportional to local disease severity. Serum miRNA-classifiers were recently found to discriminate T2D women with and without prevalent fragility fractures with high specificity and sensitivity (AUC > 0.90). However, the association of circulating miRNAs with incident fractures in T2D has not been examined yet. In 168 T2D postmenopausal women in the AGES-Reykjavik cohort, miRNAs were extracted from baseline serum and a panel of 10 circulating miRNAs known to be involved in diabetic bone disease and aging was quantified by qPCR and Ct-values extracted. Unadjusted and adjusted Cox proportional hazard models assessed the associations between serum miRNAs and incident fragility fracture. Additionally, Receiver operating curve (ROC) analyses were performed. Of the included 168 T2D postmenopausal women who were on average 77.2 ± 5.6 years old, 70 experienced at least one incident fragility fracture during the mean follow-up of 5.8 ± 2.7 years. We found that 3 serum miRNAs were significantly associated with incident diabetic fragility fracture: while low expression of miR-19b-1-5p was associated with significantly lower risk of incident fragility fracture (HR 0.84 (95% CI: 0.71-0.99, p = 0.0323)), low expression of miR-203a and miR-31-5p was each significantly associated with a higher risk of incident fragility fracture per unit increase in Ct-value (miR-203a: HR 1.29 (95% CI: 1.12-1.49), p = 0.0004, miR-31-5p HR 1.27 (95% CI: 1.06-1.52), p = 0.009). Hazard ratios of the latter two miRNAs remained significant after adjustments for age, body mass index (BMI), areal bone mineral density (aBMD), clinical FRAX or FRAXaBMD. Women with miR-203a and miR-31-5p serum levels in the lowest expression quartiles exhibited a 2.4-3.4-fold larger fracture risk than women with miR-31-5p and miR-203a serum expressions in the highest expression quartile (0.002 ≤ p ≤ 0.039). Women with both miR-203a and miR-31-5p serum levels below the median had a significantly increased fracture risk (Unadjusted HR 3.26 (95% CI: 1.57-6.78, p = 0.001) compared to those with both expression levels above the median, stable to adjustments. We next built a diabetic fragility signature consisting of the 3 miRNAs that showed the largest associations with incident fracture (miR-203a, miR-31-5p, miR-19b-1-5p). This 3-miRNA signature showed with an AUC of 0.722 comparable diagnostic accuracy in identifying incident fractures to any of the clinical parameters such as aBMD, Clinical FRAX or FRAXaBMD alone. When the 3 miRNAs were combined with aBMD, this combined 4-feature signature performed with an AUC of 0.756 (95% CI: 0.680, 0.823) significantly better than aBMD alone (AUC 0.666, 95% CI: 0.585, 0.741) (p = 0.009). Our data indicate that specific serum microRNAs including senescent miR-31-5p are associated with incident fragility fracture in older diabetic women and can significantly improve fracture risk prediction in diabetics when combined with aBMD measurements of the femoral neck.

Finite element derived femoral strength is a better predictor of hip fracture risk than aBMD in the AGES Reykjavik study cohort

Hip fractures associated with a high economic burden, loss of independence, and a high rate of post-fracture mortality, are a major health concern for modern societies. Areal bone mineral density is the current clinical metric of choice when assessing an individual's future risk of fracture. However, this metric has been shown to lack sensitivity and specificity in the targeted selection of individuals for preventive interventions. Although femoral strength derived from computed tomography based finite element models has been proposed as an alternative based on its superior femoral strength prediction ex vivo, such predictions have only shown marginal or no improvement for assessing hip fracture risk. This study compares finite element derived femoral strength to aBMD as a metric for hip fracture risk assessment in subjects (N = 601) from the AGES Reykjavik Study cohort and analyses the dependence of femoral strength predictions and classification accuracy on the material model and femoral loading alignment. We found hip fracture classification based on finite element derived femoral strength to be significantly improved compared to aBMD. Finite element models with non-linear material models performed better at classifying hip fractures compared to finite element models with linear material models and loading alignments with low internal rotation and adduction, which do not correspond to weak femur alignments, were found to be most suitable for hip fracture classification.

Fracture risk assessment in diabetes mellitus

Growing evidence suggests that diabetes mellitus is associated with an increased risk of fracture. Bone intrinsic factors (such as accumulation of glycation end products, low bone turnover, and bone microstructural changes) and extrinsic factors (such as hypoglycemia caused by treatment, diabetes peripheral neuropathy, muscle weakness, visual impairment, and some hypoglycemic agents affecting bone metabolism) probably contribute to damage of bone strength and the increased risk of fragility fracture. Traditionally, bone mineral density (BMD) measured by dual x-ray absorptiometry (DXA) is considered to be the gold standard for assessing osteoporosis. However, it cannot fully capture the changes in bone strength and often underestimates the risk of fracture in diabetes. The fracture risk assessment tool is easy to operate, giving it a certain edge in assessing fracture risk in diabetes. However, some parameters need to be regulated or replaced to improve the sensitivity of the tool. Trabecular bone score, a noninvasive tool, indirectly evaluates bone microstructure by analyzing the texture sparsity of trabecular bone, which is based on the pixel gray level of DXA. Trabecular bone score combined with BMD can effectively improve the prediction ability of fracture risk. Quantitative computed tomography is another noninvasive examination of bone microstructure. High-resolution peripheral quantitative computed tomography can measure volume bone mineral density. Quantitative computed tomography combined with microstructure finite element analysis can evaluate the mechanical properties of bones. Considering the invasive nature, the use of microindentation and histomorphometry is limited in clinical settings. Some studies found that the changes in bone turnover markers in diabetes might be associated with fracture risk, but further studies are needed to confirm this. This review focused on summarizing the current development of these assessment tools in diabetes so as to provide references for clinical practice. Moreover, these tools can reduce the occurrence of fragility fractures in diabetes through early detection and intervention.

Differences in Hip Geometry Between Female Subjects With and Without Acute Hip Fracture: A Cross-Sectional Case-Control Study

BACKGROUND AND PURPOSE

Although it is widely recognized that hip BMD is reduced in patients with hip fracture, the differences in geometrical parameters such as cortical volume and thickness between subjects with and without hip fracture are less well known.

MATERIALS AND METHODS

Five hundred and sixty two community-dwelling elderly women with hip CT scans were included in this cross-sectional study, of whom 236 had an acute hip fracture. 326 age matched women without hip fracture served as controls. MIAF-Femur software was used for the measurement of the intact contralateral femur in patients with hip fracture and the left femur of the controls. Integral and cortical volumes (Vols) of the total hip (TH), femoral head (FH), femoral neck (FN), trochanter (TR) and intertrochanter (IT) were analyzed. In the FH and FN the volumes were further subdivided into superior anterior (SA) and posterior (SP) as well as inferior anterior (IA) and posterior (IP) quadrants. Cortical thickness (CortThick) was determined for all sub volumes of interest (VOIs) listed above.

RESULTS

The average age of the control and fracture groups was 71.7 and 72.0 years, respectively. The fracture patients had significantly lower CortThick and Vol of all VOIs except for TRVol. In the fracture patients, cortical thickness and volume at the FN were significantly lower in all quadrants except for cortical volume of quadrant SA (p= 0.635). Hip fracture patients had smaller integral FN volume and cross-sectional area (CSA) before and after adjustment of age, height and weight. With respect to hip fracture discrimination, cortical volume performed poorer than cortical thickness across the whole proximal femur. The ratio of Cort/TrabMass (RCTM), a measure of the internal distribution of bone, performed better than cortical thickness in discriminating hip fracture risk. The highest area under curve (AUC) value of 0.805 was obtained for the model that included THCortThick, FHVol, THRCTM and FNCSA.

CONCLUSION

There were substantial differences in total and cortical volume as well as cortical thickness between fractured and unfractured women across the proximal femur. A combination of geometric variables resulted in similar discrimination power for hip fracture risk as aBMD.

Finite Element Assessment of Bone Fragility from Clinical Images

PURPOSE OF REVIEW

We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open.

RECENT FINDINGS

CT-to-FE is useful in longitudinal treatment evaluation and groups discrimination. In metastatic lesions, CT-to-FE strength alone accurately predicts impending femoral fractures. In osteoporosis, strength from CT-to-FE or DXA-to-FE predicts incident fractures similarly to DXA-aBMD. Coupling loads and strength (possibly in dynamic models) may improve prediction. One promising MRI-to-FE workflow may now be tested on clinical data. Evidence of artificial intelligence usefulness is appearing. CT-to-FE is already clinical in opportunistic CT screening for osteoporosis, and risk of metastasis-related impending fractures. Short-term keys to improve image-to-FE in osteoporosis may be coupling FE with fall risk estimates, pool FE results with other parameters through robust artificial intelligence approaches, and increase reproducibility and cross-validation of models. Modeling bone modifications over time and bone fracture mechanics are still open issues.

Density and mechanical properties of vertebral trabecular bone-A review

Being able to predict the mechanical properties of vertebrae in patients with osteoporosis and other relevant pathologies is essential to prevent fractures and to develop the most favorable fracture treatments. Furthermore, a reliable prediction is important for developing more patient- and pathology-specific biomaterials. A plethora of studies correlating bone density to mechanical properties has been reported; however, the results are variable, due to a variety of factors, including anatomical site and methodological differences. The aim of this study was to provide a comprehensive literature review on density and mechanical properties of human vertebral trabecular bone as well as relationships found between these properties. A literature search was performed to include studies, which investigated mechanical properties and bone density of trabecular bone. Only studies on vertebral trabecular bone tissue, reporting bone density or mechanical properties, were kept. A large variation in reported vertebral trabecular bone densities, mechanical properties, and relationships between the two was found, as exemplified by values varying between 0.09 and 0.35 g/cm3 for the wet apparent density and from 0.1 to 976 MPa for the elastic modulus. The differences were found to reflect variations in experimental and analytical processes that had been used, including testing protocol and specimen geometry. The variability in the data decreased in studies where bone tissue testing occurred in a standardized manner (eg, the reported differences in average elastic modulus decreased from 400% to 10%). It is important to take this variability into account when analyzing the predictions found in the literature, for example, to calculate fracture risk, and it is recommended to use the models suggested in the present review to reduce data variability.

Romosozumab improves lumbar spine bone mass and bone strength parameters relative to alendronate in postmenopausal women: results from the Active-Controlled Fracture Study in Postmenopausal Women With Osteoporosis at High Risk (ARCH) trial

The Active-Controlled Fracture Study in Postmenopausal Women With Osteoporosis at High Risk (ARCH) trial (NCT01631214; https://clinicaltrials.gov/ct2/show/NCT01631214) showed that romosozumab for 1 year followed by alendronate led to larger areal bone mineral density (aBMD) gains and superior fracture risk reduction versus alendronate alone. aBMD correlates with bone strength but does not capture all determinants of bone strength that might be differentially affected by various osteoporosis therapeutic agents. We therefore used quantitative computed tomography (QCT) and finite element analysis (FEA) to assess changes in lumbar spine volumetric bone mineral density (vBMD), bone volume, bone mineral content (BMC), and bone strength with romosozumab versus alendronate in a subset of ARCH patients. In ARCH, 4093 postmenopausal women with severe osteoporosis received monthly romosozumab 210 mg sc or weekly oral alendronate 70 mg for 12 months, followed by open-label weekly oral alendronate 70 mg for ≥12 months. Of these, 90 (49 romosozumab, 41 alendronate) enrolled in the QCT/FEA imaging substudy. QCT scans at baseline and at months 6, 12, and 24 were assessed to determine changes in integral (total), cortical, and trabecular lumbar spine vBMD and corresponding bone strength by FEA. Additional outcomes assessed include changes in aBMD, bone volume, and BMC. Romosozumab caused greater gains in lumbar spine integral, cortical, and trabecular vBMD and BMC than alendronate at months 6 and 12, with the greater gains maintained upon transition to alendronate through month 24. These improvements were accompanied by significantly greater increases in FEA bone strength (p < 0.001 at all time points). Most newly formed bone was accrued in the cortical compartment, with romosozumab showing larger absolute BMC gains than alendronate (p < 0.001 at all time points). In conclusion, romosozumab significantly improved bone mass and bone strength parameters at the lumbar spine compared with alendronate. These results are consistent with greater vertebral fracture risk reduction observed with romosozumab versus alendronate in ARCH and provide insights into structural determinants of this differential treatment effect. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

MDCT-Based Finite Element Analysis for the Prediction of Functional Spine Unit Strength-An In Vitro Study

(1) Objective: This study aimed to analyze the effect of ligaments on the strength of functional spine unit (FSU) assessed by finite element (FE) analysis of anatomical models developed from multi-detector computed tomography (MDCT) data. (2) Methods: MDCT scans for cadaveric specimens were acquired from 16 donors (7 males, mean age of 84.29 ± 6.06 years and 9 females, mean age of 81.00 ± 11.52 years). Two sets of FSU models (three vertebrae + two disks), one with and another without (w/o) ligaments, were generated. The vertebrae were segmented semi-automatically, intervertebral disks (IVD) were generated manually, and ligaments were modeled based on the anatomical location. FE-predicted failure loads of FSU models (with and w/o ligaments) were compared with the experimental failure loads obtained from the uniaxial biomechanical test of specimens. (3) Results: The mean and standard deviation of the experimental failure load of FSU specimens was 3513 ± 1029 N, whereas of FE-based failure loads were 2942 ± 943 N and 2537 ± 929 N for FSU models with ligaments and without ligament attachments, respectively. A good correlation (ρ = 0.79, and ρ = 0.75) was observed between the experimental and FE-based failure loads for the FSU model with and with ligaments, respectively. (4) Conclusions: The FE-based FSU model can be used to determine bone strength, and the ligaments seem to have an effect on the model accuracy for the failure load calculation; further studies are needed to understand the contribution of ligaments.

Assessment of Intravertebral Mechanical Strains and Cancellous Bone Texture Under Load Using a Clinically Available Digital Tomosynthesis Modality

Vertebral fractures are the most common osteoporotic fractures, but clinical means for assessment of vertebral bone integrity are limited in accuracy, as they typically use surrogate measures that are indirectly related to mechanics. The objective of this study was to examine the extent to which intravertebral strain distributions and changes in cancellous bone texture generated by a load of physiological magnitude can be characterized using a clinically available imaging modality. We hypothesized that digital tomosynthesis-based digital volume correlation (DTS-DVC) and image texture-based metrics of cancellous bone microstructure can detect development of mechanical strains under load. Isolated cadaveric T11 vertebrae and L2-L4 vertebral segments were DTS imaged in a nonloaded state and under physiological load levels. Axial strain, maximum principal strain, maximum compressive and tensile principal strains, and von Mises equivalent strain were calculated using the DVC technique. The change in textural parameters (line fraction deviation, anisotropy, and fractal parameters) under load was calculated within the cancellous centrum. The effect of load on measured strains and texture variables was tested using mixed model analysis of variance, and relationships of strain and texture variables with donor age, bone density parameters, and bone size were examined using regression models. Magnitudes and heterogeneity of intravertebral strain measures correlated with applied loading and were significantly different from background noise. Image texture parameters were found to change with applied loading, but these changes were not observed in the second experiment testing L2-L4 segments. DTS-DVC-derived strains correlated with age more strongly than did bone mineral density (BMD) for T11.

Update on bone health: the International Menopause Society White Paper 2021

Osteoporosis and associated fractures present a major challenge in improving global health outcomes. Key clinical aspects are the definition of osteoporosis and associated fractures, fracture risk prediction, stratification of risk of fracture, intervention thresholds and the most appropriate intervention based on integration of aforementioned. Correct understanding and application of these concepts are essential to stem the increasing tide of fragility fractures associated with an aging population. The role of muscle strength and function, sarcopenia, and the newly emerging concept of osteosarcopenia in maintaining bone health are discussed in detail.

Assessing hip fracture risk in type-2 diabetic patients using CT-based autonomous finite element methods : a feasibility study

AIMS

Type 2 diabetes mellitus (T2DM) impairs bone strength and is a significant risk factor for hip fracture, yet currently there is no reliable tool to assess this risk. Most risk stratification methods rely on bone mineral density, which is not impaired by diabetes, rendering current tests ineffective. CT-based finite element analysis (CTFEA) calculates the mechanical response of bone to load and uses the yield strain, which is reduced in T2DM patients, to measure bone strength. The purpose of this feasibility study was to examine whether CTFEA could be used to assess the hip fracture risk for T2DM patients.

METHODS

A retrospective cohort study was undertaken using autonomous CTFEA performed on existing abdominal or pelvic CT data comparing two groups of T2DM patients: a study group of 27 patients who had sustained a hip fracture within the year following the CT scan and a control group of 24 patients who did not have a hip fracture within one year. The main outcome of the CTFEA is a novel measure of hip bone strength termed the Hip Strength Score (HSS).

RESULTS

The HSS was significantly lower in the study group (1.76 (SD 0.46)) than in the control group (2.31 (SD 0.74); p = 0.002). A multivariate model showed the odds of having a hip fracture were 17 times greater in patients who had an HSS ≤ 2.2. The CTFEA has a sensitivity of 89%, a specificity of 76%, and an area under the curve of 0.90.

CONCLUSION

This preliminary study demonstrates the feasibility of using a CTFEA-based bone strength parameter to assess hip fracture risk in a population of T2DM patients. Cite this article: Bone Joint J 2021;103-B(9):1497-1504.

The usefulness of trabecular bone score in patients with ankylosing spondylitis

BACKGROUNDS/AIMS

This study was performed to reveal the usefulness of the trabecular bone score (TBS) in assessing bone strength in patients with ankylosing spondylitis (AS) in comparison with dual-energy X-ray absorptiometry (DXA) methods.

METHODS

A total of 215 AS patients (75.8% male) were enrolled from a single university hospital in Korea. Demographic and clinical information were assessed. Patients completed X-rays of the cervical and lumbar spine (L-spine), and spinal ankyloses were quantified using the modified Stoke AS Spine Score (mSASSS). Hip, anteroposterior and lateral L-spine bone mineral density (BMD) and TBS were assessed by DXA methods. Clinical characteristics and bone strength measurement results were compared between male and female AS patients. The accuracy of each bone strength evaluation method in predicting Fracture Risk Assessment Tool (FRAX) scores indicating moderate or higher fracture risk was compared by receiver operating characteristic curves in patients aged ≥ 40 years. Correlations between each bone strength measurement method and mSASSS were examined.

RESULTS

Male patients showed higher mSASSS and less prevalent peripheral joint involvement compared to female patients (p < 0.05). TBS, hip BMD, and L-spine lateral BMD showed comparably high areas under the curve (AUCs) for predicting FRAX-major osteoporotic fractures (MOF) ≥ 10% (AUC ranged 0.72 to 0.76). TBS negatively correlated with mSASSS in both male and female patients (p < 0.01).

CONCLUSION

TBS could predict the risk of MOF and is not influenced by spinal osteoproliferation in AS patients, even in those with advanced spinal changes.

Opportunistic diagnosis of osteoporosis, fragile bone strength and vertebral fractures from routine CT scans; a review of approved technology systems and pathways to implementation

Osteoporosis causes bones to become weak, porous and fracture more easily. While a vertebral fracture is the archetypal fracture of osteoporosis, it is also the most difficult to diagnose clinically. Patients often suffer further spine or other fractures, deformity, height loss and pain before diagnosis. There were an estimated 520,000 fragility fractures in the United Kingdom (UK) in 2017 (costing £4.5 billion), a figure set to increase 30% by 2030. One way to improve both vertebral fracture identification and the diagnosis of osteoporosis is to assess a patient's spine or hips during routine computed tomography (CT) scans. Patients attend routine CT for diagnosis and monitoring of various medical conditions, but the skeleton can be overlooked as radiologists concentrate on the primary reason for scanning. More than half a million CT scans done each year in the National Health Service (NHS) could potentially be screened for osteoporosis (increasing 5% annually). If CT-based screening became embedded in practice, then the technique could have a positive clinical impact in the identification of fragility fracture and/or low bone density. Several companies have developed software methods to diagnose osteoporosis/fragile bone strength and/or identify vertebral fractures in CT datasets, using various methods that include image processing, computational modelling, artificial intelligence and biomechanical engineering concepts. Technology to evaluate Hounsfield units is used to calculate bone density, but not necessarily bone strength. In this rapid evidence review, we summarise the current literature underpinning approved technologies for opportunistic screening of routine CT images to identify fractures, bone density or strength information. We highlight how other new software technologies have become embedded in NHS clinical practice (having overcome barriers to implementation) and highlight how the novel osteoporosis technologies could follow suit. We define the key unanswered questions where further research is needed to enable the adoption of these technologies for maximal patient benefit.

On challenges in clinical assessment of hip fracture risk using image-based biomechanical modelling: a critical review

INTRODUCTION

Hip fracture is a common health risk among elderly people, due to the prevalence of osteoporosis and accidental fall in the population. Accurate assessment of fracture risk is a crucial step for clinicians to consider patient-by-patient optimal treatments for effective prevention of fractures. Image-based biomechanical modeling has shown promising progress in assessment of fracture risk, and there is still a great possibility for improvement. The purpose of this paper is to identify key issues that need be addressed to improve image-based biomechanical modeling.

MATERIALS AND METHODS

We critically examined issues in consideration and determination of the four biomechanical variables, i.e., risk of fall, fall-induced impact force, bone geometry and bone material quality, which are essential for prediction of hip fracture risk. We closely inspected: limitations introduced by assumptions that are adopted in existing models; deficiencies in methods for construction of biomechanical models, especially for determination of bone material properties from bone images; problems caused by separate use of the variables in clinical study of hip fracture risk; availability of clinical information that are required for validation of biomechanical models.

RESULTS AND CONCLUSIONS

A number of critical issues and gaps were identified. Strategies for effectively addressing the issues were discussed.

Prediction of incident vertebral fractures in routine MDCT: Comparison of global texture features, 3D finite element parameters and volumetric BMD

PURPOSE

In this case-control study, we evaluated different quantitative parameters derived from routine multi-detector computed tomography (MDCT) scans with respect to their ability to predict incident osteoporotic vertebral fractures of the thoracolumbar spine.

METHODS

16 patients who received baseline and follow-up contrast-enhanced MDCT and were diagnosed with an incident osteoporotic vertebral fracture at follow-up, and 16 age-, sex-, and follow-up-time-matched controls were included in the study. Vertebrae were labelled and segmented using a fully automated pipeline. Volumetric bone mineral density (vBMD), finite element analysis (FEA)-based failure load (FL) and failure displacement (FD), as well as 24 texture features were extracted from L1 - L3 and averaged. Odds ratios (OR) with 95% confidence intervals (CI), expressed per standard deviation decrease, receiver operating characteristic (ROC) area under the curve (AUC), as well as logistic regression models, including all analyzed parameters as independent variables, were used to assess the prediction of incident vertebral fractures.

RESULTS

The texture feature Correlation (AUC = 0.754, p = 0.014; OR = 2.76, CI = 1.16-6.58) and vBMD (AUC = 0.750, p = 0.016; OR = 2.67, CI = 1.12-6.37) classified incident vertebral fractures best, while the best FEA-based parameter FL showed an AUC = 0.719 (p = 0.035). Correlation was the only significant predictor of incident fractures in the logistic regression analysis of all parameters (p = 0.022).

CONCLUSION

MDCT-derived FEA parameters and texture features, averaged from L1 - L3, showed only a moderate, but no statistically significant improvement of incident vertebral fracture prediction beyond BMD, supporting the hypothesis that vertebral-specific parameters may be superior for fracture risk assessment.

Alterations to the gut microbiome impair bone tissue strength in aged mice

Whole bone strength and resistance to fracture are determined by a combination of bone quantity and bone quality - key factors in determining risk for osteoporosis and age-related fractures. Recent preclinical studies have shown that alterations to the gut microbiome can influence bone quantity as well as bone tissue quality. Prior work on the gut microbiome and bone has been limited to young animals, and it is unknown if the gut microbiome can alter bone tissue strength in aged animals. Here we ask if alterations to the constituents of the gut microbiome influence bone strength in older mice (12-24 months of age). Male C57BL/6J mice raised on a standard chow diet until 12 months of age were assigned to one of three diets: high glycemic, low glycemic, or low glycemic diet containing antibiotics (ampicillin and neomycin) to modify the constituents of the gut microbiome. The group fed the low glycemic diet containing antibiotics showed reductions in whole bone strength that could not be explained by geometry, indicating reduced bone tissue strength (p < 0.007). The high glycemic diet group had larger bone cross-sectional area and moment of inertia and a corresponding greater bone strength as compared to the low glycemic groups, however tissue strength did not noticeably differ from that of the low glycemic group. These findings demonstrate that modifying the gut microbiome in aged mice can alter bone tissue quality.

Experimental testing and biomechanical CT analysis of Chinese cadaveric vertebrae with different modeling approaches

Osteoporosis is characterized by reduced bone strength predisposing to an increased risk of fracture. Biomechanical computed tomography (BCT), predicting bone strength via CT-based finite element analysis (FEA), is now clinically available in the USA for diagnosing osteoporosis or assessing fracture risk. However, it has not been previously validated using a cohort of only Chinese subjects. Additionally, the effect of various modeling approaches on BCT outcomes remains elusive. To address these issues, we performed DXA and QCT scanning, compression testing, and BCT analyses on thirteen vertebrae derived from Chinese donors. Three BCT models were created (voxBCT and tetBCT: voxel-based and tetrahedral element-based FE models generated by a commercial software; matBCT: tetrahedral element-based FE model generated by a custom MATLAB program). BCT-computed outcomes were compared with experimental measures or between different BCT models. Results showed that, DXA-measured areal bone mineral density (aBMD) showed weak correlations with experimentally-measured vertebral stiffness (R² = 0.28) and strength (R² = 0.34). Compared to DXA-aBMD, BCT-computed stiffness provided improved correlations with experimentally-measured stiffness (voxBCT: R² = 0.82; tetBCT: R² = 0.77; matBCT: R² = 0.76) and strength (voxBCT: R² = 0.55; tetBCT: R² = 0.57; matBCT: R² = 0.53); BCT-computed mechanical parameters (stiffness, stress and strain) of the three different models were highly correlated with each other, with coefficient of determination (R²) values of 0.89-0.98. These results, based on a cohort of Chinese vertebral cadavers, suggest that BCT is superior over aBMD to consistently predict vertebral mechanical characteristics, regardless of the modeling approaches of choice.

Patterns of Load-to-Strength Ratios Along the Spine in a Population-Based Cohort to Evaluate the Contribution of Spinal Loading to Vertebral Fractures

Vertebral fractures (VFx) are common among older adults. Epidemiological studies report high occurrence of VFx at mid-thoracic and thoracolumbar regions of the spine; however, reasons for this observation remain poorly understood. Prior reports of high ratios of spinal loading to vertebral strength in the thoracolumbar region suggest a possible biomechanical explanation. However, no studies have evaluated load-to-strength ratios (LSRs) throughout the spine for a large number of activities in a sizeable cohort. Thus, we performed a cross-sectional study in a sample of adult men and women from a population-based cohort to: 1) determine which activities cause the largest vertebral LSRs, and 2) examine patterns of LSRs along the spine for these high-load activities. We used subject-specific musculoskeletal models of the trunk to determine vertebral compressive loads for 109 activities in 250 individuals (aged 41 to 90 years, 50% women) from the Framingham Heart Study. Vertebral compressive strengths from T₄ to L₄ were calculated from computed tomography-based vertebral size and bone density measurements. We determined which activities caused maximum LSRs at each of these spinal levels. We identified nine activities that accounted for >95% of the maximum LSRs overall and at least 89.6% at each spinal level. The activity with the highest LSR varied by spinal level, and three distinct spinal regions could be identified by the activity producing maximum LSRs: lateral bending with a weight in one hand (upper thoracic), holding weights with elbows flexed (lower thoracic), and forward flexion with weight (lumbar). This study highlights the need to consider a range of lifting, holding, and non-symmetric activities when evaluating vertebral LSRs. Moreover, we identified key activities that produce higher loading in multiple regions of the spine. These results provide the first guidance on what activities to consider when evaluating vertebral load-to-strength ratios in future studies, including those examining dynamic motions and the biomechanics of VFx. © 2020 American Society for Bone and Mineral Research (ASBMR).