MRI-based assessment of proximal femur strength compared to mechanical testing

Magnetic resonance imaging based finite element modelling of the proximal femur: a short-term in vivo precision study

Proximal femoral fractures are a serious life-threatening injury with high morbidity and mortality. Magnetic resonance (MR) imaging has potential to non-invasively assess proximal femoral bone strength in vivo through usage of finite element (FE) modelling (a technique referred to as MR-FE). To precisely assess bone strength, knowledge of measurement error associated with different MR-FE outcomes is needed. The objective of this study was to characterize the short-term in vivo precision errors of MR-FE outcomes (e.g., stress, strain, failure loads) of the proximal femur for fall and stance loading configurations using 13 participants (5 males and 8 females; median age: 27 years, range: 21-68), each scanned 3 times. MR-FE models were generated, and mean von Mises stress and strain as well as principal stress and strain were calculated for 3 regions of interest. Similarly, we calculated the failure loads to cause 5% of contiguous elements to fail according to the von Mises yield, Brittle Coulomb-Mohr, normal principal, and Hoffman stress and strain criteria. Precision (root-mean squared coefficient of variation) of the MR-FE outcomes ranged from 3.3% to 11.8% for stress and strain-based mechanical outcomes, and 5.8% to 9.0% for failure loads. These results provide evidence that MR-FE outcomes are a promising non-invasive technique for monitoring femoral strength in vivo.

Six-minute, in vivo MRI quantification of proximal femur trabecular bone 3D microstructure

BACKGROUND

Assessment of proximal femur trabecular bone microstructure in vivo by magnetic resonance imaging has recently been validated for acquiring information independent of bone mineral density in osteoporotic patients. However, the requisite signal-to-noise ratio (SNR) and resolution for interrogation of the trabecular microstructure at this anatomical location prolongs the scan duration and renders the imaging protocol clinically infeasible. Parallel imaging and compressed sensing (PICS) techniques can reduce the scan duration of the imaging protocol without substantially compromising image quality. The present work investigates the limits of acceleration for a commonly used PICS technique, ℓ1-ESPIRiT, for the purpose of quantifying measures of trabecular bone microarchitecture. Based on a desired error tolerance, a six-minute, prospectively accelerated variant of the imaging protocol was developed and assessed for intersession reproducibility and agreement with the longer reference scan.

PURPOSE

To investigate the limits of acceleration for MRI-based trabecular bone quantification by parallel imaging and compressed sensing reconstruction, and to develop a prototypical imaging protocol for assessing the proximal femur microstructure in a clinically practical scan time.

METHODS

Healthy participants (n = 11) were scanned by a 3D balanced steady-state free precession (bSSFP) sequence satisfying the Nyquist criterion with a scan duration of about 18 min. The raw data were retrospectively undersampled and reconstructed to mimic various acceleration factors ranging from 2 to 6. Trabecular volumes-of-interest in four major femoral regions (greater trochanter, intertrochanteric region, femoral neck, and femoral head) were analyzed and six relevant measures of trabecular bone microarchitecture (bone volume fraction, surface-to-curve ratio, erosion index, elastic modulus, trabecular thickness, plates-to-rods ratio) were obtained for images of all accelerations. To assess agreement, median percent error and intraclass correlation coefficients (ICCs) were computed using the fully-sampled data as reference. Based on this analysis, a prospectively 3-fold accelerated sequence with a duration of about 6 min was developed and the analysis was repeated.

RESULTS

A prospective acceleration factor of 3 demonstrated comparable performance in reproducibility and absolute agreement to the fully-sampled scan. The median CoV over all image-derived metrics was generally <6 % and ICCs >0.70. Also, measurements from prospectively 3-fold accelerated scans demonstrated in general median percent errors of <7 % and ICCs >0.70.

CONCLUSION

The present work proposes a method to make in vivo quantitative assessment of proximal femur trabecular microstructure with a clinically practical scan duration of about 6 min.

Application of Optical Photothermal Infrared (O-PTIR) Spectroscopy for Assessment of Bone Composition at the Submicron Scale

The molecular basis of bone structure and strength is mineralized collagen fibrils at the submicron scale (∼500 nm). Recent advances in optical photothermal infrared (O-PTIR) spectroscopy allow the investigation of bone composition with unprecedented submicron spatial resolution, which may provide new insights into factors contributing to underlying bone function. Here, we investigated (i) whether O-PTIR-derived spectral parameters correlated to standard attenuated total reflection (ATR) Fourier transform infrared spectroscopy spectral data and (ii) whether O-PTIR-derived spectral parameters, including heterogeneity of tissue, contribute to the prediction of proximal femoral bone stiffness. Analysis of serially demineralized bone powders showed a significant correlation (r = 0.96) between mineral content quantified using ATR and O-PTIR spectroscopy, indicating the validity of this technique in assessing bone mineralization. Using femoral neck sections, the principal component analysis showed that differences between O-PTIR and ATR spectra were primarily attributable to the phosphate ion (PO4) absorbance band, which was typically shifter toward higher wavenumbers in O-PTIR spectra. Additionally, significant correlations were found between hydrogen phosphate (HPO4) content (r = 0.75) and carbonate (CO3) content (r = 0.66) quantified using ATR and O-PTIR spectroscopy, strengthening the validity of this method to assess bone mineral composition. O-PTIR imaging of individual trabeculae at 500 nm pixel resolution illustrated differences in submicron composition in the femoral neck from bones with different stiffness. O-PTIR analysis showed a significant negative correlation (r = -0.71) between bone stiffness and mineral maturity, reflective of newly formed bone being an important contributor to bone function. Finally, partial least squares regression analysis showed that combining multiple O-PTIR parameters (HPO4 content and heterogeneity, collagen integrity, and CO3 content) could significantly predict proximal femoral stiffness (R2 = 0.74, error = 9.7%) more accurately than using ATR parameters. Additionally, we describe new findings in the effects of bone tissue orientation in the O-PTIR spectra. Overall, this study highlights a new application of O-PTIR spectroscopy that may provide new insights into molecular-level factors underlying bone mechanical competence.

The predictive ability of a QCT-FE model of the proximal femoral stiffness under multiple load cases is strongly influenced by experimental uncertainties

Despite significant improvements in terms of the predictive ability of Quantitative Computed Tomography based Finite Element (QCT-FE) models in estimating femoral strength (fracture load and stiffness), no substantial clinical adoption of this method has taken place to date. Narrowing the wide variability of FE results by standardizing the methodology and validation protocols, as well as reducing the uncertainties in the FEA process have been proposed as routes towards improved reliability. The aim of this study was to: First, validate a QCT-FE model of proximal femoral stiffness in multiple stance load cases, and second, using a parametric approach, determine the influence of select experimental and modeling parameters on the predictive ability of our model. Ten fresh frozen human femoral samples were tested in neutral stance, 15° adducted and 15° abducted load cases. Voxel-based linear-elastic QCT-FE models of the samples were generated to predict the models' stiffness values in all load cases. The base FE models were validated against the experimental results using linear regression. Thirty six deviated models were created using the minimum and maximum values of experiment-based "plausible range" for 18 parameters in 4 categories of embedding, loading, material, and segmentation. The predictive ability of the models were compared in terms of the coefficient of determination (R²) of the linear regression between the measured and predicted stiffness values in all load cases. Our model was capable of capturing 90% of the variation in the experimental stiffness of the samples in neutral stance position (R² = 0.9, concordance correlation coefficient (CCC) = 0.93, percent root mean squared error (RMSE%) = 8.4%, slope and intercept not significantly different from unity and zero, respectively). Embedding and loading categories strongly affected the predictive ability of the models with an average percent difference in R² of 4.36% ± 2.77 and 2.96% ± 1.69 for the stance-neutral load case, respectively. The performance of the models were significantly different in adducted and abducted load cases with their R² dropping to 71% and 70%, respectively. Similarly, off-axes load cases were affected by the parameters differently compared to the neutral load case, with the loading parameter category imposing more than 10% difference on their R², larger than all other categories. We also showed that automatically selecting the best performing plausible value for each parameter and each sample would result in a perfectly linear correlation (R²> 0.99) between the "tuned" model's predicted stiffness and experimental results. Based on our results, high sensitivity of the model performance to experimental parameters requires extra diligence in modeling the embedding geometry and the loading angles since these sources of uncertainty could dwarf the effects of material modeling and image processing parameters. The results of this study could help in improving the robustness of the QCT-FE models of proximal femur by limiting the uncertainties in the experimental and modeling steps.

Prediction of osteoporosis from proximal femoral cortical bone thickness and Hounsfield unit value with clinical significance

Background

Utilizing dual-energy x-ray absorptiometry (DXA) to assess bone mineral density (BMD) was not routine in many clinical scenarios, leading to missed diagnoses of osteoporosis. The objective of this study is to obtain effective parameters from hip computer tomography (CT) to screen patients with osteoporosis and predict their clinical outcomes.

Methods

A total of 375 patients with hip CT scans for intertrochanteric fracture were included. Among them, 56 patients possessed the data of both hip CT scans and DXA and were settled as a training group. The cortical bone thickness (CTh) and Hounsfield unit (HU) values were abstracted from 31 regions of interest (ROIs) of the proximal femur. In the training group, the correlations between these parameters and BMD were investigated, and their diagnostic efficiency of osteoporosis was assessed. Finally, 375 patients were divided into osteoporotic and nonosteoporotic groups based on the optimal cut-off values, and the clinical difference between subgroups was evaluated.

Results

The CTh value of ROI 21 and the HU value of ROI 14 were moderately correlated with the hip BMD [r = 0.475 and 0.445 (p < 0.001), respectively]. The best diagnostic effect could be obtained by defining osteoporosis as CTh value < 3.19 mm in ROI 21 or HU value < 424.97 HU in ROI 14, with accuracies of 0.821 and 0.883, sensitivities of 84% and 76%, and specificities of 71% and 87%, respectively. The clinical outcome of the nonosteoporotic group was better than that of the osteoporotic group regardless of the division criteria.

Conclusion

The CTh and HU values of specific cortex sites in the proximal femur were positively correlated with BMD of DXA at the hip. Thresholds for osteoporosis based on CTh and HU values could be utilized to screen osteoporosis and predict clinical outcomes.

Effect of fall direction on the lower hip fracture risk in athletes with different loading histories: A finite element modeling study in multiple sideways fall configurations

Physical loading makes bones stronger through structural adaptation. Finding effective modes of exercise to improve proximal femur strength has the potential to decrease hip fracture risk. Previous proximal femur finite element (FE) modeling studies have indicated that the loading history comprising impact exercises is associated with substantially higher fracture load. However, those results were limited only to one specified fall direction. It remains thus unclear whether exercise-induced higher fracture load depends on the fall direction. To address this, using magnetic resonance images of proximal femora from 91 female athletes (mean age 24.7 years with >8 years competitive career) and their 20 non-athletic but physically active controls (mean age 23.7 years), proximal femur FE models were created in 12 different sideways fall configurations. The athletes were divided into five groups by typical loading patterns of their sports: high-impact (H-I: 9 triple- and 10 high-jumpers), odd-impact (O-I: 9 soccer and 10 squash players), high-magnitude (H-M: 17 powerlifters), repetitive-impact (R-I: 18 endurance runners), and repetitive non-impact (R-NI: 18 swimmers). Compared to the controls, the FE models showed that the H-I and R-I groups had significantly (p < 0.05) higher fracture loads, 11-17% and 22-28% respectively, in all fall directions while the O-I group had significantly 10-11% higher fracture loads in four fall directions. The H-M and R-NI groups did not show significant benefit in any direction. Also, the analyses of the minimum fall strength (MFS) among these multiple fall configurations confirmed significantly 15%, 11%, and 14% higher MFSs in these impact groups, respectively, compared to the controls. These results suggest that the lower hip fracture risk indicated by higher fracture loads in athletes engaged in high impact or repetitive impact sports is independent of fall direction whereas the lower fracture risk attributed to odd-impact exercise is more modest and specific to the fall direction. Moreover, in concordance with the literature, the present study also confirmed that the fracture risk increases if the impact is imposed on the more posterolateral aspect of the hip. The present results highlight the importance of engaging in the impact exercises to prevent hip fractures and call for retrospective studies to investigate whether specific impact exercise history in adolescence and young adulthood is also associated with lower incidence of hip fractures in later life.

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.

Limit analysis of human proximal femur

A limit analysis numerical approach oriented to predict the peak/collapse load of human proximal femur, under two different loading conditions, is presented. A yield criterion of Tsai-Hu-type, expressed in principal stress space, is used to model the orthotropic bone tissues. A simplified human femur 3D model is envisaged to carry on numerical simulation of in-vitro tests borrowed from the relevant literature and to reproduce their findings. A critical discussion, together with possible future developments, is presented.

Use of a dentin bonding agent for the fixation of strain gauges on bone

Capturing deformation of bone using strain gauges is still a common approach in biomechanics. So far, the bone surfaces had to be sanded and cleaned using various solvents prior to attaching the sensors using cyanoacrylate. This work proposes a novel approach employing common bonding procedures to enamel and dentin as used in restorative dentistry. Bovine ribs were obtained and osteotomies were created following clinical protocols for dental implant insertion. A unidirectional strain gauge was attached to the outer surface of the bone specimens using the steps of acid etching with phosphoric acid, application of a three-bottle dentin adhesive and light curing. Emerging strains were then captured during implant insertion as well as during static loading of the implants in a universal testing machine. The method described here allowed for the reliable fixation of strain gauges on unaltered bone surfaces. Both, compressive and tensile strains emerging in the surrounding of the dental implants could be captured.

Biomechanical models: key considerations in study design

This manuscript summarizes presentations of a symposium on key considerations in design of biomechanical models at the 2019 Basic Science Focus Forum of the Orthopaedic Trauma Association. The first section outlines the most important characteristics of a high-quality biomechanical study. The second section considers choices associated with designing experiments using finite element modeling versus synthetic bones versus human specimens. The third section discusses appropriate selection of experimental protocols and finite element analyses. The fourth section considers the pros and cons of use of biomechanical research for implant design. Finally, the fifth section examines how results from biomechanical studies can be used when clinical evidence is lacking or contradictory. When taken together, these presentations emphasize the critical importance of biomechanical research and the need to carefully consider and optimize models when designing a biomechanical study.

Assessing underlying bone quality in spine surgery patients: a narrative review of dual-energy X-ray absorptiometry (DXA) and alternatives

Poor bone quality and low bone mineral density (BMD) have been previously tied to higher rates of postoperative mechanical complications in patients undergoing spinal fusion. These include higher rates of proximal junctional kyphosis, screw pullout, pseudoarthrosis, and interbody subsidence. For these reasons, accurate preoperative assessment of a patient's underlying bone quality is paramount for all elective procedures. Dual-energy X-ray absorptiometry (DXA) is currently considered to be the gold standard for assessing BMD. However, a growing body of research has suggested that in vivo assessments of BMD using DXA are inaccurate and have, at best, moderate correlations to postoperative mechanical complications. Consequently, there have been investigations into using alternative methods for assessing in vivo bone quality, including using computed tomography (CT) and magnetic resonance imaging (MRI) volumes that are commonly obtained as part of surgical evaluation. Here we review the data regarding the accuracy of DXA for the evaluation of spine bone quality and describe the alternative imaging modalities currently under investigation.

MRI-derived porosity index is associated with whole-bone stiffness and mineral density in human cadaveric femora

Ultrashort echo time (UTE) magnetic resonance imaging (MRI) measures proton signals in cortical bone from two distinct water pools, bound water, or water that is tightly bound to bone matrix, and pore water, or water that is freely moving in the pore spaces in bone. By isolating the signal contribution from the pore water pool, UTE biomarkers can directly quantify cortical bone porosity in vivo. The Porosity Index (PI) is one non-invasive, clinically viable UTE-derived technique that has shown strong associations in the tibia with μCT porosity and other UTE measures of bone water. However, the efficacy of the PI biomarker has never been examined in the proximal femur, which is the site of the most catastrophic osteoporotic fractures. Additionally, the loads experienced during a sideways fall are complex and the femoral neck is difficult to image with UTE, so the usefulness of the PI in the femur was unknown. Therefore, the aim of this study was to examine the relationships between the PI measure in the proximal cortical shaft of human cadaveric femora specimens compared to (1) QCT-derived bone mineral density (BMD) and (2) whole bone stiffness obtained from mechanical testing mimicking a sideways fall. Fifteen fresh, frozen whole cadaveric femora specimens (age 72.1 ± 15.0 years old, 10 male, 5 female) were scanned on a clinical 3-T MRI using a dual-echo UTE sequence. Specimens were then scanned on a clinical CT scanner to measure volumetric BMD (vBMD) and then non-destructively mechanically tested in a sideways fall configuration. The PI in the cortical shaft demonstrated strong correlations with bone stiffness (r = -0.82, P = 0.0014), CT-derived vBMD (r = -0.64, P = 0.0149), and with average cortical thickness (r = -0.60, P = 0.0180). Furthermore, a hierarchical regression showed that PI was a strong predictor of bone stiffness which was independent of the other parameters. The findings from this study validate the MRI-derived porosity index as a useful measure of whole-bone mechanical integrity and stiffness.

Bone microarchitecture in patients undergoing parathyroidectomy for management of secondary hyperparathyroidism

Background

Secondary hyperparathyroidism (SHPT) in patients with chronic kidney disease (CKD) leads to complex bone disease, affecting both trabecular and cortical bone, and increased fracture risk. Optimal assessment of bone in patients with CKD is yet to be determined. High-resolution magnetic resonance imaging (MRI) can provide three-dimensional assessment of bone microarchitecture, as well as determination of mechanical strength with finite element analysis (FEA).

Methods

We conducted a single-centre, cross-sectional study to determine bone microarchitecture with MRI in CKD patients with SHPT undergoing parathyroidectomy. Within two weeks of surgery, MRI was performed at the distal tibia and biochemical markers of SHPT (parathyroid hormone [PTH] and alkaline phosphatase [ALP]) were collected. Trabecular and cortical topological parameters as well as bone mechanical competence using FEA were assessed. Correlation of MRI findings of bone was made with biochemical markers.

Results

Twenty patients with CKD (15 male, 5 female) underwent MRI at the time of parathyroidectomy (16 on dialysis, 3 with functioning kidney transplant, one pre-dialysis with CKD stage 5). Median PTH at the time of surgery was 138.5 pmol/L [39.6–186.7 pmol/L]. MRI parameters in patients were consistent with trabecular deterioration, with erosion index (EI) 1.01 ± 0.3, and trabecular bone volume (BV/TV) 10.8 ± 2.9%, as well as poor trabecular network integrity with surface-to-curve ratio (S/C) 5.4 ± 2.3. There was also evidence of reduced cortical thickness, with CTh 2.698 ± 0.630 mm, and FEA demonstrated overall poor bone mechanical strength with mean elastic modulus of 2.07 ± 0.44.

Conclusion

Patients with severe SHPT requiring parathyroidectomy have evidence of significant changes in bone microarchitecture with trabecular deterioration, low trabecular and cortical bone volume, and reduced mechanical competence of bone.

MRI-Based Quantitative Osteoporosis Imaging at the Spine and Femur

Osteoporosis is a systemic skeletal disease with a high prevalence worldwide, characterized by low bone mass and microarchitectural deterioration, predisposing an individual to fragility fractures. Dual-energy X-ray absorptiometry (DXA) has been the clinical reference standard for diagnosing osteoporosis and for assessing fracture risk for decades. However, other imaging modalities are of increasing importance to investigate the etiology, treatment, and fracture risk. The purpose of this work is to review the available literature on quantitative magnetic resonance imaging (MRI) methods and related findings in osteoporosis at the spine and proximal femur as the clinically most important fracture sites. Trabecular bone microstructure analysis at the proximal femur based on high-resolution MRI allows for a better prediction of osteoporotic fracture risk than DXA-based bone mineral density (BMD) alone. In the 1990s, T₂ * mapping was shown to correlate with the density and orientation of the trabecular bone. Recently, quantitative susceptibility mapping (QSM), which overcomes some of the limitations of T₂ * mapping, has been applied for trabecular bone quantifications at the spine, whereas ultrashort echo time (UTE) imaging provides valuable surrogate markers of cortical bone quantity and quality. Magnetic resonance spectroscopy (MRS) and chemical shift encoding-based water-fat MRI (CSE-MRI) enable the quantitative assessment of the nonmineralized bone compartment through extraction of the bone marrow fat fraction (BMFF). Furthermore, CSE-MRI allows for the differentiation of osteoporotic vs. pathologic fractures, which is of high clinical relevance. Lastly, advanced postprocessing and image analysis tools, particularly considering statistical parametric mapping and region-specific BMFF distributions, have high potential to further improve MRI-based fracture risk assessments at the spine and hip. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 2.