Fast Trabecular Bone Strength Predictions of HR‐pQCT and Individual Trabeculae Segmentation–Based Plate and Rod Finite Element Model Discriminate Postmenopausal Vertebral Fractures
ABSTRACT Although high‐resolution peripheral quantitative computed tomography (HR‐pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (µFE) prediction of yield strength using a HR‐pQCT voxel model is impractical for clinical use due to i...
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Published in | Journal of bone and mineral research Vol. 28; no. 7; pp. 1666 - 1678 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Oxford University Press
01.07.2013
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Subjects | |
Online Access | Get full text |
ISSN | 0884-0431 1523-4681 1523-4681 |
DOI | 10.1002/jbmr.1919 |
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Abstract | ABSTRACT
Although high‐resolution peripheral quantitative computed tomography (HR‐pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (µFE) prediction of yield strength using a HR‐pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR‐pQCT‐based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using an individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient‐specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR‐pQCT PR model were compared with those of the registered high‐resolution micro–computed tomography (HR‐µCT) voxel model of 19 trabecular subvolumes from human cadaveric tibia samples. Both the Young's modulus and yield strength of HR‐pQCT PR models strongly correlated with those of µCT voxel models (r2 = 0.91 and 0.86). Notably, the HR‐pQCT PR models achieved major reductions in element number (>40‐fold) and computer central processing unit (CPU) time (>1200‐fold). Then, we applied PR model µFE analysis to HR‐pQCT images of 60 postmenopausal women with (n = 30) and without (n = 30) a history of vertebral fracture. HR‐pQCT PR model revealed significantly lower Young's modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for areal bone mineral density (aBMD) T‐score at the ultradistal radius or total hip. In conclusion, we validated a novel HR‐pQCT PR model of human trabecular bone against µCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear µFE prediction of the HR‐pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. |
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AbstractList | Although high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (µFE) prediction of yield strength using a HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using an individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high-resolution micro-computed tomography (HR-µCT) voxel model of 19 trabecular subvolumes from human cadaveric tibia samples. Both the Young's modulus and yield strength of HR-pQCT PR models strongly correlated with those of µCT voxel models (r² = 0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and computer central processing unit (CPU) time (>1200-fold). Then, we applied PR model µFE analysis to HR-pQCT images of 60 postmenopausal women with (n = 30) and without (n = 30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young's modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for areal bone mineral density (aBMD) T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against µCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear µFE prediction of the HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength.Although high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (µFE) prediction of yield strength using a HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using an individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high-resolution micro-computed tomography (HR-µCT) voxel model of 19 trabecular subvolumes from human cadaveric tibia samples. Both the Young's modulus and yield strength of HR-pQCT PR models strongly correlated with those of µCT voxel models (r² = 0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and computer central processing unit (CPU) time (>1200-fold). Then, we applied PR model µFE analysis to HR-pQCT images of 60 postmenopausal women with (n = 30) and without (n = 30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young's modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for areal bone mineral density (aBMD) T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against µCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear µFE prediction of the HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. Although high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (uFE) prediction of yield strength using a HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using an individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high-resolution micro-computed tomography (HR- mu CT) voxel model of 19 trabecular subvolumes from human cadaveric tibia samples. Both the Young's modulus and yield strength of HR-pQCT PR models strongly correlated with those of mu CT voxel models (r super(2) = 0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and computer central processing unit (CPU) time (>1200-fold). Then, we applied PR model uFE analysis to HR-pQCT images of 60 postmenopausal women with (n = 30) and without (n = 30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young's modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for areal bone mineral density (aBMD) T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against mu CT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear mu FE prediction of the HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. Although high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (µFE) prediction of yield strength using a HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using an individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high-resolution micro-computed tomography (HR-µCT) voxel model of 19 trabecular subvolumes from human cadaveric tibia samples. Both the Young's modulus and yield strength of HR-pQCT PR models strongly correlated with those of µCT voxel models (r² = 0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and computer central processing unit (CPU) time (>1200-fold). Then, we applied PR model µFE analysis to HR-pQCT images of 60 postmenopausal women with (n = 30) and without (n = 30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young's modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for areal bone mineral density (aBMD) T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against µCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear µFE prediction of the HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. ABSTRACT Although high‐resolution peripheral quantitative computed tomography (HR‐pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (µFE) prediction of yield strength using a HR‐pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR‐pQCT‐based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using an individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient‐specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR‐pQCT PR model were compared with those of the registered high‐resolution micro–computed tomography (HR‐µCT) voxel model of 19 trabecular subvolumes from human cadaveric tibia samples. Both the Young's modulus and yield strength of HR‐pQCT PR models strongly correlated with those of µCT voxel models (r2 = 0.91 and 0.86). Notably, the HR‐pQCT PR models achieved major reductions in element number (>40‐fold) and computer central processing unit (CPU) time (>1200‐fold). Then, we applied PR model µFE analysis to HR‐pQCT images of 60 postmenopausal women with (n = 30) and without (n = 30) a history of vertebral fracture. HR‐pQCT PR model revealed significantly lower Young's modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for areal bone mineral density (aBMD) T‐score at the ultradistal radius or total hip. In conclusion, we validated a novel HR‐pQCT PR model of human trabecular bone against µCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear µFE prediction of the HR‐pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. Although high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (µFE) prediction of yield strength using a HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using an individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high-resolution micro-computed tomography (HR-µCT) voxel model of 19 trabecular subvolumes from human cadaveric tibia samples. Both the Young's modulus and yield strength of HR-pQCT PR models strongly correlated with those of µCT voxel models (r2=0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and computer central processing unit (CPU) time (>1200-fold). Then, we applied PR model µFE analysis to HR-pQCT images of 60 postmenopausal women with (n=30) and without (n=30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young's modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for areal bone mineral density (aBMD) T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against µCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear µFE prediction of the HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. [PUBLICATION ABSTRACT] |
Author | Zhou, Bin Wang, Ji Stein, Emily Shane, Elizabeth Shi, Xiutao Adams, Mark Guo, X Edward Liu, X Sherry |
Author_xml | – sequence: 1 givenname: X Sherry surname: Liu fullname: Liu, X Sherry organization: University of Pennsylvania – sequence: 2 givenname: Ji surname: Wang fullname: Wang, Ji organization: Columbia University – sequence: 3 givenname: Bin surname: Zhou fullname: Zhou, Bin organization: Columbia University – sequence: 4 givenname: Emily surname: Stein fullname: Stein, Emily organization: Columbia University – sequence: 5 givenname: Xiutao surname: Shi fullname: Shi, Xiutao organization: Columbia University – sequence: 6 givenname: Mark surname: Adams fullname: Adams, Mark organization: Columbia University – sequence: 7 givenname: Elizabeth surname: Shane fullname: Shane, Elizabeth organization: Columbia University – sequence: 8 givenname: X Edward surname: Guo fullname: Guo, X Edward organization: Columbia University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/23456922$$D View this record in MEDLINE/PubMed |
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Although high‐resolution peripheral quantitative computed tomography (HR‐pQCT) has advanced clinical assessment of trabecular bone microstructure,... Although high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear... |
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SubjectTerms | Aged Aged, 80 and over Elastic Modulus Female Finite Element Analysis FINITE ELEMENT MODEL HIGH‐RESOLUTION PERIPHERAL QUANTITATIVE COMPUTED TOMOGRAPHY Humans INDIVIDUAL TRABECULAE SEGMENTATION Male Middle Aged Models, Biological Postmenopause - metabolism Radius - diagnostic imaging Radius - metabolism Spinal Fractures - diagnostic imaging Spinal Fractures - metabolism Spine - diagnostic imaging Spine - metabolism Tibia - diagnostic imaging Tibia - metabolism Tomography, X-Ray Computed - methods TRABECULAR MICROARCHITECTURE TRABECULAR PLATE AND ROD |
Title | Fast Trabecular Bone Strength Predictions of HR‐pQCT and Individual Trabeculae Segmentation–Based Plate and Rod Finite Element Model Discriminate Postmenopausal Vertebral Fractures |
URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fjbmr.1919 https://www.ncbi.nlm.nih.gov/pubmed/23456922 https://www.proquest.com/docview/1368738474 https://www.proquest.com/docview/1370123381 https://www.proquest.com/docview/1412504595 |
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