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 (set 1, 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 1.0 mm for cadaver femurs in set 1 (leave-one-out test) and 1.4 mm for clinical subjects in set 3. The reconstructed volumetric BMD showed a mean absolute difference of 140 and 185 mg/cm(3) 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.

[1]  A. A. Zadpoor,et al.  Estimation of 3D rotation of femur in 2D hip radiographs. , 2012, Journal of biomechanics.

[2]  Ryo Kurazume,et al.  Patient-specific femoral shape estimation using a parametric model and two 2D fluoroscopic images , 2007 .

[3]  J. Cauley,et al.  Public health impact of osteoporosis. , 2013, The journals of gerontology. Series A, Biological sciences and medical sciences.

[4]  P J Prendergast,et al.  A method to reconstruct patient-specific proximal femur surface models from planar pre-operative radiographs. , 2010, Medical engineering & physics.

[5]  Ryo Kurazume,et al.  3 D reconstruction of a femoral shape using a parametric model and two 2 D fluoroscopic images , 2008 .

[6]  Fred L. Bookstein,et al.  Principal Warps: Thin-Plate Splines and the Decomposition of Deformations , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  J. Jurvelin,et al.  Estimation of 3D shape, internal density and mechanics of proximal femur by combining bone mineral density images with shape and density templates , 2012, Biomechanics and modeling in mechanobiology.

[8]  Alejandro F. Frangi,et al.  3D bone mineral density distribution and shape reconstruction of the proximal femur from a single simulated DXA image: an in vitro study , 2010, Medical Imaging.

[9]  Hanna Isaksson,et al.  Experimental validation of finite element model for proximal composite femur using optical measurements. , 2013, Journal of the mechanical behavior of biomedical materials.

[10]  Mads Nielsen,et al.  Projected Generalized Procrustes Alignment , 2009, IPMI.

[11]  Stéphane Lavallée,et al.  Nonrigid 3-D/2-D Registration of Images Using Statistical Models , 1999, MICCAI.

[12]  J. Pasco,et al.  The population burden of fractures originates in women with osteopenia, not osteoporosis , 2006, Osteoporosis International.

[13]  Christian M. Langton,et al.  Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur. , 2009, Medical engineering & physics.

[14]  A L Jacob,et al.  Volumetric model determination of the tibia based on 2D radiographs using a 2D/3D database. , 2001, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[15]  Claus Christiansen,et al.  Diagnosis of Osteoporosis , 1992, Southern medical journal.

[16]  Ryo Kurazume,et al.  3D reconstruction of a femoral shape using a parametric model and two 2D fluoroscopic images , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[17]  Luis Gracia,et al.  A mechanical model for predicting the probability of osteoporotic hip fractures based in DXA measurements and finite element simulation , 2012, Biomedical engineering online.

[18]  Bostjan Likar,et al.  A review of 3D/2D registration methods for image-guided interventions , 2012, Medical Image Anal..

[19]  W. Hayes,et al.  The effect of impact direction on the structural capacity of the proximal femur during falls , 1996, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[20]  Claus Christiansen,et al.  Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group. , 1994, World Health Organization technical report series.

[21]  David A. Boas,et al.  Tetrahedral mesh generation from volumetric binary and grayscale images , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[22]  Alejandro F. Frangi,et al.  Technical note: comparison between single and multiview simulated DXA configurations for reconstructing the 3D shape and bone mineral density distribution of the proximal femur. , 2012, Medical physics.

[23]  M. Viceconti,et al.  Accuracy of finite element predictions in sideways load configurations for the proximal human femur. , 2012, Journal of Biomechanics.

[24]  J. Kanis,et al.  Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: Synopsis of a WHO report , 1994, Osteoporosis International.

[25]  Leo Joskowicz,et al.  Registration of a CT-like atlas to fluoroscopic X-ray images using intensity correspondences , 2008, International Journal of Computer Assisted Radiology and Surgery.

[26]  J. Gower.  Generalized procrustes analysis , 1975 .

[27]  J. P. Karjalainen,et al.  Multi-site bone ultrasound measurements in elderly women with and without previous hip fractures , 2012, Osteoporosis International.

[28]  A. A. Zadpoor,et al.  Repeatability of digital image correlation for measurement of surface strains in composite long bones. , 2013, Journal of biomechanics.

[29]  Nazli Sarkalkan,et al.  Statistical shape and appearance models for fast and automated estimation of proximal femur fracture load using 2D finite element models. , 2014, Journal of biomechanics.

[30]  W. Skalli,et al.  Three-dimensional X-ray absorptiometry (3D-XA): a method for reconstruction of human bones using a dual X-ray absorptiometry device , 2005, Osteoporosis International.

[31]  P. Zysset,et al.  The role of cortical shell and trabecular fabric in finite element analysis of the human vertebral body. , 2009, Journal of biomechanical engineering.

[32]  G. Holzer,et al.  Hip Fractures and the Contribution of Cortical Versus Trabecular Bone to Femoral Neck Strength , 2009, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[33]  Computer-Assisted Intervention,et al.  Medical Image Computing and Computer-Assisted Intervention – MICCAI’99 , 1999, Lecture Notes in Computer Science.

[34]  J. Keyak,et al.  Generation of a 3D proximal femur shape from a single projection 2D radiographic image , 2009, Osteoporosis International.

[35]  F. Eckstein,et al.  Cortical bone finite element models in the estimation of experimentally measured failure loads in the proximal femur. , 2012, Bone.

[36]  Alejandro F. Frangi,et al.  3D reconstruction of both shape and Bone Mineral Density distribution of the femur from DXA images , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[37]  Laura Caponetti,et al.  3D Bone Reconstruction From Two X-ray Views , 1990, [1990] Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[38]  Alejandro F. Frangi,et al.  Hip fracture discrimination from dual-energy X-ray absorptiometry by statistical model registration. , 2012, Bone.

[39]  H Labelle,et al.  Optimized vertical stereo base radiographic setup for the clinical three-dimensional reconstruction of the human spine. , 1994, Journal of biomechanics.

[40]  Jaimie M. Henderson,et al.  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention , 2006 .

[41]  B. Joe,et al.  Relationship between tetrahedron shape measures , 1994 .

[42]  Timothy F. Cootes,et al.  Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[43]  Andrew H. Gee,et al.  High resolution cortical bone thickness measurement from clinical CT data , 2010, Medical Image Anal..

[44]  Omar Ahmad,et al.  Volumetric DXA (VXA): A new method to extract 3D information from multiple in vivo DXA images , 2010, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[45]  Randall J. Allemang,et al.  THE MODAL ASSURANCE CRITERION–TWENTY YEARS OF USE AND ABUSE , 2003 .

[46]  Hans-Christian Hege,et al.  Fast Generation of Virtual X-ray Images for Reconstruction of 3D Anatomy , 2013, IEEE Transactions on Visualization and Computer Graphics.

[47]  M. Viceconti,et al.  The material mapping strategy influences the accuracy of CT-based finite element models of bones: an evaluation against experimental measurements. , 2007, Medical engineering & physics.

[48]  Timothy F. Cootes,et al.  Active Appearance Models , 1998, ECCV.

[49]  C. Cooper,et al.  Perspective how many women have osteoporosis? , 1992, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[50]  F. Taddei,et al.  To what extent can linear finite element models of human femora predict failure under stance and fall loading configurations? , 2014, Journal of biomechanics.

[51]  Alejandro F. Frangi,et al.  Reconstructing the 3D Shape and Bone Mineral Density Distribution of the Proximal Femur From Dual-Energy X-Ray Absorptiometry , 2011, IEEE Transactions on Medical Imaging.

[52]  Z. Yosibash,et al.  Patient-specific Finite-element Analyses of the Proximal Femur with Orthotropic Material Properties Validated , 2022 .

[53]  David Larsson,et al.  Assessment of Transverse Isotropy in Clinical-Level CT Images of Trabecular Bone Using the Gradient Structure Tensor , 2014, Annals of Biomedical Engineering.

[54]  Timo Jämsä,et al.  A novel methodology for generating 3D finite element models of the hip from 2D radiographs. , 2014, Journal of biomechanics.

[55]  Alejandro F. Frangi,et al.  3D reconstruction of the lumbar vertebrae from anteroposterior and lateral dual-energy X-ray absorptiometry , 2013, Medical Image Anal..

[56]  Leo Joskowicz,et al.  Effective Intensity-Based 2D/3D Rigid Registration between Fluoroscopic X-Ray and CT , 2003, MICCAI.

[57]  Andrew H. Gee,et al.  Imaging the femoral cortex: Thickness, density and mass from clinical CT , 2012, Medical Image Anal..

[58]  Sydney Lou Bonnick,et al.  HSA: beyond BMD with DXA. , 2007, Bone.

[59]  J. Jurvelin,et al.  Assessment of the 3-D shape and mechanics of the proximal femur using a shape template and a bone mineral density image , 2011, Biomechanics and modeling in mechanobiology.

[60]  David Mitton,et al.  3D Evaluation of the acetabular coverage assessed by biplanar X-rays or single anteroposterior X-ray compared with CT-scan , 2008, Computer methods in biomechanics and biomedical engineering.

[61]  S. Goldstein,et al.  Femoral strength is better predicted by finite element models than QCT and DXA. , 1999, Journal of biomechanics.

[62]  Ryo Kurazume,et al.  In-vivo experiments of 3 D femoral shape estimation using two 2 D fluoroscopic images , 2007 .

[63]  Marco Viceconti,et al.  Evaluation of the generality and accuracy of a new mesh morphing procedure for the human femur. , 2011, Medical engineering & physics.

[64]  J. Kanis,et al.  Diagnosis of osteoporosis and assessment of fracture risk , 2002, The Lancet.

[65]  Thomas M Link,et al.  osteoporosis imaging : State of the Art and Advanced Imaging 1 , 2022 .

[66]  F. Eckstein,et al.  Ct-based finite element models can be used to estimate experimentally measured failure loads in the proximal femur. , 2012, Bone.

[67]  Yunhua Luo,et al.  Precision study of DXA‐based patient‐specific finite element modeling for assessing hip fracture risk , 2013, International journal for numerical methods in biomedical engineering.

[68]  O. Johnell,et al.  Requirements for DXA for the management of osteoporosis in Europe , 2005, Osteoporosis International.

[69]  R. Eastell,et al.  Use of DXA‐based finite element analysis of the proximal femur in a longitudinal study of hip fracture , 2013, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[70]  Randall J. Allemang,et al.  A Correlation Coefficient for Modal Vector Analysis , 1982 .

[71]  Alberto Leardini,et al.  Multimod Data Manager: A tool for data fusion , 2007, Comput. Methods Programs Biomed..

[72]  Guoyan Zheng,et al.  Statistical Deformable Model-Based Reconstruction of a Patient-Specific Surface Model from Single Standard X-ray Radiograph , 2009, CAIP.

[73]  L. Joseph Melton,et al.  Perspective how many women have osteoporosis? , 1992, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[74]  Alejandro F. Frangi,et al.  A Statistical Model of Shape and Bone Mineral Density Distribution of the Proximal Femur for Fracture Risk Assessment , 2011, MICCAI.

[75]  T. Keaveny,et al.  Trabecular bone modulus-density relationships depend on anatomic site. , 2003, Journal of biomechanics.

[76]  Bernhard Preim,et al.  Comparison of Fundamental Mesh Smoothing Algorithms for Medical Surface Models , 2006, SimVis.