Can we improve the prediction of hip fracture by assessing bone structure using shape and appearance modelling?

Copyright 2013 Elsevier B.V., All rights reserved.Peer reviewedPreprin

A shape analysis approach to prediction of bone stiffness using FEXI

The preferred method of assessing the risk of an osteoporosis related fracture is currently a measure of bone mineral density (BMD) by dual energy X-ray absorptiometry (DXA). However, other factors contribute to the overall risk of fracture, including anatomical geometry and the spatial distribution of bone. Finite element analysis can be performed in both two and three dimensions, and predicts the deformation or induced stress when a load is applied to a structure (such as a bone) of defined material composition and shape. The simulation of a mechanical compression test provides a measure of whole bone stiffness (N mm−1). A simulation system was developed to study the sensitivity of BMD, 3D and 2D finite element analysis to variations in geometric parameters of a virtual proximal femur model. This study demonstrated that 3D FE and 2D FE (FEXI) were significantly more sensitive to the anatomical shape and composition of the proximal femur than conventional BMD. The simulation approach helped to analyse and understand how variations in geometric parameters affect the stiffness and hence strength of a bone susceptible to osteoporotic fracture. Originally, the FEXI technique modelled the femur as a thin plate model of an assumed constant depth for finite element analysis (FEA). A better prediction of tissue depth across the bone, based on its geometry, was required to provide a more accurate model for FEA. A shape template was developed for the proximal femur to provide this information for the 3D FE analysis. Geometric morphometric techniques were used to procure and analyse shape information from a set of CT scans of excised human femora. Generalized Procrustes Analysis and Thin Plate Splines were employed to analyse the data and generate a shape template for the proximal femur. 2D Offset and Depth maps generated from the training set data were then combined to model the three-dimensional shape of the bone. The template was used to predict the three-dimensional bone shape from a 2D image of the proximal femur procured through a DXA scan. The error in the predicted 3D shape was measured as the difference in predicted and actual depths at each pixel. The mean error in predicted depths was found to be 1.7mm compared to an average bone depth of 34mm. 3D FEXI analysis on the predicted 3D bone along with 2D FEXI for a stance loading condition and BMD measurement were performed based on 2D radiographic projections of the CT scans and compared to bone stiffness results obtained from finite element analysis of the original 3D CT scans. 3D FEXI provided a significantly higher correlation (R2 = 0.85) with conventional CT derived 3D finite element analysis than achieved with both BMD (R2 = 0.52) and 2D FEXI (R2 = 0.44)

Generation of 3D shape, density, cortical thickness and finite element mesh of proximal femur from a DXA image

Areal bone mineral density (aBMD), as measured by dual-energy X-ray absorptiometry (DXA), predicts hip fracture risk only moderately. Simulation of bone mechanics based on DXA imaging of the proximal femur, may help to improve the prediction accuracy. Therefore, we collected three (1-3) image sets, including CT images and DXA images of 34 proximal cadaver femurs (set1, including 30 males, 4 females), 35 clinical patient CT images of the hip (set 2, including 27 males, 8 females) and both CT and DXA images of clinical patients (set 3, including 12 female patients). All CT images were segmented manually and landmarks were placed on both femurs and pelvises. Two separate statistical appearance models (SAMs) were built using the CT images of the femurs and pelvises in sets 1 and 2, respectively. The 3D shape of the femur was reconstructed from the DXA image by matching the SAMs with the DXA images. The orientation and modes of variation of the SAMs were adjusted to minimize the sum of the absolute differences between the projection of the SAMs and a DXA image. The mesh quality and the location of the SAMs with respect to the manually placed control points on the DXA image were used as additional constraints. Then, finite element (FE) models were built from the reconstructed shapes. Mean point-to-surface distance between the reconstructed shape and CT image was 1.0mm for cadaver femurs in set 1 (leave-one-out test) and 1.4mm for clinical subjects in set 3. The reconstructed volumetric BMD showed a mean absolute difference of 140 and 185mg/cm3 for set 1 and set 3 respectively. The generation of the SAM and the limitation of using only one 2D image were found to be the most significant sources of errors in the shape reconstruction. The noise in the DXA images had only small effect on the accuracy of the shape reconstruction. DXA-based FE simulation was able to explain 85% of the CT-predicted strength of the femur in stance loading. The present method can be used to accurately reconstruct the 3D shape and internal density of the femur from 2D DXA images. This may help to derive new information from clinical DXA images by producing patient-specific FE models for mechanical simulation of femoral bone mechanics

Skeleton geometry, physical activity and proximal femur bone mass distribution in 8-12 year old children

Doutoramento em Motricidade Humana, especialidade em Actividade Física e SaúdeIn the context of bone health promotion, the aim of this Ph.D dissertation was to analyze potential explanatory factors of the effects of physical activity and of bone geometry on bone mass distribution at the proximal femur in 8-12 year old children. Four studies were undertaken to compare the bone mineral density (BMD) between: (a) the sub-regions of the proximal femur – the neck and its superolateral and inferomedial aspects, the trochanter and the intertrochanter; (b) sexes, concerning the associations/effects of non-targeted physical activity and bone geometry. Sex and regional specific effects of non-targeted physical activity on bone mass distribution at the proximal femur in children were observed. The geometry of the pelvis and the proximal femur, namely the pelvis width and the abductor lever arm, emerged as predictors of bone mass distribution at the proximal femur, therefore as explanatory factors of both the regional and the sex specific patterns. These geometric features might mediate the physical activity effects on bone mineralization at the proximal femur, as long as, when they are considered, the power of physical activity to explain the distribution of bone mass at this skeletal site seems limited.Resumo : No contexto da promoção da saúde óssea, o objetivo desta dissertação de doutoramento foi analisar potenciais fatores explicativos dos efeitos da atividade física habitual e da geometria óssea na distribuição da massa óssea do fémur proximal, em crianças de 8-12 anos de idade. Para o efeito foram realizados quatro estudos comparando a densidade mineral óssea (DMO) entre: (a) as diversas sub-regiões do fémur proximal - o colo do fémur e os seus aspetos supero-lateral e infero-medial, o grande trocanter e a sub-região intertrocantérica; (b) os sexos, relativamente às associações/efeitos da atividade física habitual e da geometria óssea. Foram observadas associações/efeitos da atividade física habitual na massa óssea do fémur proximal diferenciados quanto ao sexo e sub-região. A geometria da pélvis e do femur proximal, nomeadamente a largura da pélvis e o braço de momento de força dos abdutores, surgiram como preditores da distribuição de massa óssea no fémur proximal e consequentemente como fatores explicativos de diferenciação da distribuição de massa óssea de acordo com o sexo e sub-região. Estas caraterísticas geométricas poderão mediar os efeitos da atividade física na mineralização do femur proximal uma vez que quando consideradas parecem limitar a capacidade explicativa da atividade física na distribuição de massa óssea no fémur proximal.FCT - Fundação para a Ciência e a Tecnologi

Combining shape and intensity dxa-based statistical approaches for osteoporotic HIP fracture risk assessment

5noAiming to improve osteoporotic hip fracture risk detection, factors other than the largely adopted Bone Mineral Density (BMD) have been investigated as potential risk predictors. In particular Hip Structural Analysis (HSA)-derived parameters accounting for femur geometry, extracted from Dual-energy X-ray Absorptiometry (DXA) images, have been largely considered as geometric risk factors. However, HSA-derived parameters represent discrete and cross-correlated quantities, unable to describe proximal femur geometry as a whole and tightly related to BMD. Focusing on a post-menopausal cohort (N = 28), in this study statistical models of bone shape and BMD distribution have been developed to investigate their possible role in fracture risk. Due to unavailable retrospective patient-specific fracture risk information, here a surrogate fracture risk based on 3D computer simulations has been employed for the statistical framework construction. When considered separately, BMD distribution performed better than shape in explaining the surrogate fracture risk variability for the analysed cohort. However, the combination of BMD and femur shape quantities in a unique statistical model yielded better results. In detail, the first shape-intensity combined mode identified using a Partial Least Square (PLS) algorithm was able to explain 70% of the surrogate fracture risk variability, thus suggesting that a more effective patients stratification can be obtained applying a shape-intensity combination approach, compared to T-score. The findings of this study strongly advocate future research on the role of a combined shape-BMD statistical framework in fracture risk determination.partially_openembargoed_20211027Aldieri A.; Terzini M.; Audenino A.L.; Bignardi C.; Morbiducci U.Aldieri, A.; Terzini, M.; Audenino, A. L.; Bignardi, C.; Morbiducci, U

Identification of hip fracture patients from radiographs using Fourier analysis of the trabecular structure: a cross-sectional study

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Femoral Strength Prediction using Finite Element Models : Validation of models based on CT and reconstructed DXA images against full-field strain measurements

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

Active Shape Modeling of the Hip in the Prediction of Incident Hip Fracture

The objective of this study was to evaluate right proximal femur shape as a risk factor for incident hip fracture using active shape modeling (ASM). A nested case-control study of white women 65 years of age and older enrolled in the Study of Osteoporotic Fractures (SOF) was performed. Subjects (n = 168) were randomly selected from study participants who experienced hip fracture during the follow-up period (mean 8.3 years). Controls (n = 231) had no fracture during follow-up. Subjects with baseline radiographic hip osteoarthritis were excluded. ASM of digitized right hip radiographs generated 10 independent modes of variation in proximal femur shape that together accounted for 95% of the variance in proximal femur shape. The association of ASM modes with incident hip fracture was analyzed by logistic regression. Together, the 10 ASM modes demonstrated good discrimination of incident hip fracture. In models controlling for age and body mass index (BMI), the area under receiver operating characteristic (AUROC) curve for hip shape was 0.813, 95% confidence interval (CI) 0.771–0.854 compared with models containing femoral neck bone mineral density (AUROC = 0.675, 95% CI 0.620–0.730), intertrochanteric bone mineral density (AUROC = 0.645, 95% CI 0.589–0.701), femoral neck length (AUROC = 0.631, 95% CI 0.573–0.690), or femoral neck width (AUROC = 0.633, 95% CI 0.574–0.691). The accuracy of fracture discrimination was improved by combining ASM modes with femoral neck bone mineral density (AUROC = 0.835, 95% CI 0.795–0.875) or with intertrochanteric bone mineral density (AUROC = 0.834, 95% CI 0.794–0.875). Hips with positive standard deviations of ASM mode 4 had the highest risk of incident hip fracture (odds ratio = 2.48, 95% CI 1.68–3.31, p < .001). We conclude that variations in the relative size of the femoral head and neck are important determinants of incident hip fracture. The addition of hip shape to fracture-prediction tools may improve the risk assessment for osteoporotic hip fractures. © 2011 American Society for Bone and Mineral Research

In silico methods to evaluate Fracture Risk and Bone Mineral Density changes in patients undergoing Total Hip Replacement

La sostituzione totale d’anca è uno degli interventi chirurgici con le più alte percentuali di successo. Esistono due varianti di protesi d’anca che differiscono in base al metodo di ancoraggio all’osso: cementate (fissaggio tramite cemento osseo) e non cementate (fissaggio tramite forzamento). Ad oggi, i chirurghi non hanno indicazioni quantitative di supporto per la scelta fra le due tipologie di impianto, decidendo solo in base alla loro esperienza. Due delle problematiche che interessano le protesi non cementate sono la possibilità di frattura intra-operatoria durante l’inserimento forzato e il riassorbimento osseo nel periodo di tempo successivo all’intervento. A partire da rilevazioni densitometriche effettuate su immagini da TC di pazienti sottoposti a protesi d’anca non cementata, sono stati sviluppati due metodi: 1) per la valutazione del rischio di frattura intra-operatorio tramite analisi agli elementi finiti; 2) per la valutazione della variazione di densità minerale ossea (tridimensionalmente attorno alla protesi) dopo un anno dall’operazione. Un campione di 5 pazienti è stato selezionato per testare le procedure. Ciascuno dei pazienti è stato scansionato tramite TC in tre momenti differenti: una acquisita prima dell’operazione (pre-op), le altre due acquisite 24 ore (post 24h) e 1 anno dopo l’operazione (post 1y). I risultati ottenuti hanno confermato la fattibilità di entrambi i metodi, riuscendo inoltre a distinguere e a quantificare delle differenze fra i vari pazienti. La fattibilità di entrambe le metodologie suggerisce la loro possibilità di impiego in ambito clinico: 1) conoscere la stima del rischio di frattura intra-operatorio può servire come strumento di guida per il chirurgo nella scelta dell’impianto protesico ottimale; 2) conoscere la variazione di densità minerale ossea dopo un anno dall’operazione può essere utilizzato come strumento di monitoraggio post-operatorio del paziente