Prediction accuracy of femoral and tibial stress and strain using statistical shape and density model-based finite element models in paediatrics.

Osteoporosis is defined as low bone density, and results in a markedly increased risk of skeletal fractures. It has been estimated that about 40% of all women above 50 years old will suffer from an osteoporotic fracture leading to hospitalization. Current osteoporosis diagnostics is largely based on statistical tools, using epidemiological parameters and bone mineral density (BMD) measured with dual energy X-ray absorptiometry (DXA). However, DXA-based BMD proved to be only a moderate predictor of bone strength. Therefore, novel methods that take into account all mechanical characteristics of the bone and their influence on bone resistance to fracture are advocated. Finite element (FE) models may improve the bone strength prediction accuracy, since they can account for the structural determinants of bone strength, and the variety of external loads acting on the bones during daily life. Several studies have proved that FE models can perform better than BMD as a bone strength predictor. However, these FE models are built from Computed Tomography (CT) datasets, as the 3D bone geometry is required, and take several hours of work by an experienced engineer. Moreover, the radiation dose for the patient is higher for CT than for DXA scan. All these factors contributed to the low impact that FE-based methods have had on the current clinical practice so far. This thesis work aimed at developing accurate and thoroughly validated FE models to enable a more accurate prediction of femoral strength. An accurate estimation of femoral strength could be used as one of the main determinant of a patient’s fracture risk during population screening. In the first part of the thesis, the ex vivo mechanical tests performed on cadaver human femurs are presented. Digital image correlation (DIC), an optical method that allows for a full-field measurement of the displacements over the femur surface, was used to retrieve strains during the test. Then, a subject-specific FE modelling technique able to predict the deformation state and the overall strength of human femurs is presented. The FE models were based on clinical images from 3D CT datasets, and were validated against the measurements collected during the ex vivo mechanical tests. Both the experimental setup with DIC and the FE modelling procedure have been initially tested using composite bones (only the FE part of the composite bone study is presented in this thesis). After that, the method was extended to human cadaver bones. Once validated against experimental strain measurements, the FE modelling procedure could be used to predict bone strength. In the last part of the thesis, the predictive ability of FE models based on the shape and BMD distribution reconstructed from a single DXA image using a statistical shape and appearance model (SSAM, developed outside this thesis) was assessed. The predictions were compared to the experimental measurements, and the obtained accuracy compared to that of CT-based FE models. The results obtained were encouraging. The CT-based FE models were able to predict the deformation state with very good accuracy when compared to thousands of full-field measurements from DIC (normalized root mean square error, NRMSE, below 11%), and, most importantly, could predict the femoral strength with an error below 2%. The performances of SSAM-based FE models were also promising, showing only a slight reduction of the performances when compared to the CT-based approach (NRMSE below 20% for the strain prediction, average strength prediction error of 12%), but with the significant advantage of the models being built from one single conventional DXA image. In conclusion, the concept of a new, accurate and semi-automatic FE modelling procedure aimed at predicting fracture risk on individuals was developed. The performances of CT-based and SSAM-based models were thoroughly compared, and the results support the future translation of SSAM-based FE model built from a single DXA image into the clinics. The developed tool could therefore allow to include a mechanistic information into the fracture risk screening, which may ultimately lead to an increased accuracy in the identification of the subjects at risk.

The objective of this study was to develop a new calibration method that enables calibration of Hounsfield units (HU) to bone mineral densities (BMD) without the use of a calibration phantom for fracture risk prediction of femurs with metastases using CT-based finite element (FE) models. Fifty-seven advanced cancer patients (67 femurs with bone metastases) were CT scanned atop a separate calibration phantom using a standardized protocol. Non-linear isotropic FE models were constructed based on the phantom calibration and on two phantomless calibration methods: the “air-fat-muscle” and “non-patient-specific” calibration. For air-fat-muscle calibration, peaks for air, fat and muscle tissue were extracted from a histogram of the HU in a standardized region of interest including the patient’s right leg and surrounding air. These CT peaks were linearly fitted to reference “BMD” values of the corresponding tissues to obtain a calibration function. For non-patient-specific calibration, an average phantom calibration function was used for all patients. FE failure loads were compared between phantom and phantomless calibrations. There were no differences in failure loads between phantom and air-fat-muscle calibration (p = 0.8), whereas there was a significant difference between phantom and non-patient-specific calibration (p<0.001). Although this study was not designed to investigate this, in four patients who were scanned using an aberrant reconstruction kernel, the effect of the different kernel seemed to be smaller for the air-fat-muscle calibration compared to the non-patient-specific calibration. With the air-fat-muscle calibration, clinical implementation of the FE model as tool for fracture risk assessment will be easier from a practical and financial viewpoint, since FE models can be made using everyday clinical CT scans without the need of concurrent scanning of calibration phantoms.

Computed tomography (CT)-based finite element (FE) models may improve the current osteoporosis diagnostics and prediction of fracture risk by providing an estimate for femoral strength. However, the need for a CT scan, as opposed to the conventional use of dual-energy X-ray absorptiometry (DXA) for osteoporosis diagnostics, is considered a major obstacle. The 3D shape and bone mineral density (BMD) distribution of a femur can be reconstructed using a statistical shape and appearance model (SSAM) and the DXA image of the femur. Then, the reconstructed shape and BMD could be used to build FE models to predict bone strength. Since high accuracy is needed in all steps of the analysis, this study aimed at evaluating the ability of a 3D FE model built from one 2D DXA image to predict the strains and fracture load of human femora. Three cadaver femora were retrieved, for which experimental measurements from ex vivo mechanical tests were available. FE models were built using the SSAM-based reconstructions: using only the SSAM-reconstructed shape, only the SSAM-reconstructed BMD distribution, and the full SSAM-based reconstruction (including both shape and BMD distribution). When compared with experimental data, the SSAM-based models predicted accurately principal strains (coefficient of determination >0.83, normalized root-mean-square error <16%) and femoral strength (standard error of the estimate 1215 N). These results were only slightly inferior to those obtained with CT-based FE models, but with the considerable advantage of the models being built from DXA images. In summary, the results support the feasibility of SSAM-based models as a practical tool to introduce FE-based bone strength estimation in the current fracture risk diagnostics.

Predicting rupture locations of ascending aortic aneurysms using CT-based finite element models

Removals of cephalomedullary nails (CMNs) after healed pertrochanteric femur fractures are sometimes requested by patients or medically indicated due to pain or screw cut-out. However, CMN removal carries a high risk of secondary femoral neck fracture, even in the absence of trauma. Consequently, decisions on nail removal and establishing a safe post-operative loading regimen can be challenging. This study investigated if finite element (FE) models can pre-operatively predict femoral strength after CMN removal to support these clinical decisions. Nine proximal femora of body donors who were treated with a CMN during their lifetime were included. Computed tomography (CT) scans were acquired with the CMN still in place, followed by virtual implant removal using image processing. Based on this scan, non-linear voxel-based FE models were created and femoral strength was predicted for a one-legged stance configuration. For validation, the CMNs were physically removed and femoral strength was assessed in a material testing machine. The FE models predicted the femoral strength accurately relative to the experiments (R2 = 0.94, CCC = 0.97). In conclusion, CT-based FE models demonstrate potential to predict femoral strength after CMN removal pre-operatively. This could help patients and clinicians to make an informed decision on implant removal and permissible post-operative weight-bearing.

Cortical bone finite element models in the estimation of experimentally measured failure loads in the proximal femur

Accuracy of specimen-specific nonlinear finite element analysis for evaluation of distal radius strength in cadaver material

Predicting strength of femora with metastatic lesions from single 2D radiographic projections using convolutional neural networks.

Validation of 3D finite element models from simulated DXA images for biofidelic simulations of sideways fall impact to the hip.

Finite element and experimental models of cemented hip joint reconstructions can produce similar bone and cement strains in pre-clinical tests

Denosumab treatment is associated with decreased cortical porosity and increased bone density and strength at the proximal humerus of ovariectomized cynomolgus monkeys.

In vivo study of a computed tomography (CT)-based nonlinear finite element model (FEM). To establish an FEM with the optimum element size to assess the vertebral strength by comparing analyzed data with those obtained from mechanical testing in vitro, and then to assess the second lumbar (L2) vertebral strength in vivo. FEM has been reported to predict vertebral strength in vitro, but has not been used clinically. Comparison among the 3 models with a different element size of 1 mm, 2 mm, and 3 mm was performed to determine which model achieved the most accurate prediction. Vertebral strength was assessed in 78 elderly Japanese women using an FEM with the optimum element size. The optimum element size was 2 mm. The L2 vertebral strength obtained with the FEM was 2154 +/- 685 N, and the model could detect preexisting vertebral fracture better than measurement of bone mineral density. The FEM could assess vertebral strength in vivo.

Thoracolumbar kyphosis (TLK) secondary to Scheuermann's disease often leads to low back pain, which may be related to altered biomechanical properties of the spine. However, There is a lack of biomechanical studies in the literature that comprehensively evaluate tissue-level stresses and strains in the thoracolumbar spine affected by Scheuermann's kyphosis, particularly during functional motions such as forward flexion. This study analyzed biomechanical changes during forward flexion in TLK patients using musculoskeletal dynamics and finite element modeling. Twenty TLK patients and twenty healthy individuals were recruited. Kinematic data (joint angles), kinetic data (joint reaction forces and moments), and electromyographic (EMG) data were collected at different bending angles using Vicon 3D motion capture and surface electromyography. Physiologic motions captured from in vivo experiment was simulated using OpenSim, with inverse dynamics and optimization used to calculate vertebral joint angles, muscle forces, and intervertebral reaction forces, serving as boundary conditions for ANSYS finite element models. Subject-specific finite element models for both groups were constructed in ANSYS using computed tomography (CT) DICOM files. The CT-based finite element models were used to compute von Mises stress distributions-a mechanical parameter indicating combined tissue stress and potential risk of overload-in the vertebral body, intervertebral discs, and articular cartilage at different forward flexion angles under the applied loadig conditions. At different forward bending angles, TLK patients exhibited high stress distribution in the L1-S1 segment vertebral articular processes. Compared with healthy individuals, the stress distribution in the S1 segment was uneven, with peak stress reaching up to to 2.8 times higher (180% increase) than that of healthy individuals. TLK patients exhibit stress concentration in the annulus fibrosus region of the intervertebral disc, while the stress distribution in the nucleus pulposus region is relatively uniform. The peak stress in the intervertebral disc during different movements can be up to 2.33 times higher (133% increase) than in healthy individuals. In TLK patients, stress concentration was observed in the articular cartilage of all segments except for the L5/S1 segment. The peak stress in the articular cartilage during different movements was up to 12.02 times higher (1,102% increase) than in healthy individuals. These results suggest that TLK patients experience elevated and uneven spinal tissue stress during forward flexion, which may contribute to increased risk of degeneration and back pain.

Theoretical Efficacy of Preventive Measures for Pathologic Fracture After Surgical Removal of Mandibular Lesions Based on a Three-Dimensional Finite Element Analysis

Life expectancy continuously increases but our society faces age-related conditions. Among musculoskeletal diseases, osteoporosis associated with risk of vertebral fracture and degenerative intervertebral disc (IVD) are painful pathologies responsible for tremendous healthcare costs. Hence, reliable diagnostic tools are necessary to plan a treatment or follow up its efficacy. Yet, radiographic and MRI techniques, respectively clinical standards for evaluation of bone strength and IVD degeneration, are unspecific and not objective. Increasingly used in biomedical engineering, CT-based finite element (FE) models constitute the state-of-art for vertebral strength prediction. However, as non-invasive biomechanical evaluation and personalised FE models of the IVD are not available, rigid boundary conditions (BCs) are applied on the FE models to avoid uncertainties of disc degeneration that might bias the predictions. Moreover, considering the impact of low back pain, the biomechanical status of the IVD is needed as a criterion for early disc degeneration. Thus, the first FE study focuses on two rigid BCs applied on the vertebral bodies during compression test of cadaver vertebral bodies, vertebral sections and PMMA embedding. The second FE study highlights the large influence of the intervertebral disc’s compliance on the vertebral strength, damage distribution and its initiation. The third study introduces a new protocol for normalisation of the IVD stiffness in compression, torsion and bending using MRI-based data to account for its morphology. In the last study, a new criterion (Otsu threshold) for disc degeneration based on quantitative MRI data (axial T2 map) is proposed. The results show that vertebral strength and damage distribution computed with rigid BCs are identical. Yet, large discrepancies in strength and damage localisation were observed when the vertebral bodies were loaded via IVDs. The normalisation protocol attenuated the effect of geometry on the IVD stiffnesses without complete suppression. Finally, the Otsu threshold computed in the posterior part of annulus fibrosus was related to the disc biomechanics and meet objectivity and simplicity required for a clinical application. In conclusion, the stiffness normalisation protocol necessary for consistent IVD comparisons and the relation found between degeneration, mechanical response of the IVD and Otsu threshold lead the way for non-invasive evaluation biomechanical status of the IVD. As the FE prediction of vertebral strength is largely influenced by the IVD conditions, this data could also improve the future FE models of osteoporotic vertebra.