Abstract
More accurate techniques to estimate fracture risk could help reduce the burden of fractures in postmenopausal women. Although micro-finite element (μFE) simulations allow a direct assessment of bone mechanical performance, in this first clinical study we investigated whether the additional information obtained using geometrically and materially nonlinear μFE simulations allows a better discrimination between fracture cases and controls. We used patient data and high-resolution peripheral quantitative computed tomography (HRpQCT) measurements from our previous clinical study on fracture risk, which compared 100 postmenopausal women with a distal forearm fracture to 105 controls. Analyzing these data with the nonlinear μFE simulations, the odds ratio (OR) for the factor-of-risk (yield load divided by the expected fall load) was marginally higher (1.99; 95% confidence interval [CI], 1.41-2.77) than for the factor-of-risk computed from linear μFE (1.89; 95% CI, 1.37-2.69). The yield load and the energy absorbed up to the yield point as computed from nonlinear μFE were highly correlated with the initial stiffness (R2 = 0.97 and 0.94, respectively) and could therefore be derived from linear simulations with little loss in precision. However, yield deformation was not related to any other measurement performed and was itself a good predictor of fracture risk (OR, 1.89; 95% CI, 1.39-2.63). Moreover, a combined risk score integrating information on relative bone strength (yield load-based factor-of-risk), bone ductility (yield deformation), and the structural integrity of the bone under critical loads (cortical plastic volume) improved the separation of cases and controls by one-third (OR, 2.66; 95% CI, 1.84-4.02). We therefore conclude that nonlinear μFE simulations provide important additional information on the risk of distal forearm fractures not accessible from linear μFE nor from other techniques assessing bone microstructure, density, or mass.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2601-2608 |
| Number of pages | 8 |
| Journal | Journal of Bone and Mineral Research |
| Volume | 28 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2013 |
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Keywords
- bone microstructure
- Distal forearm fracture
- high-resolution peripheral quantitative computed tomography
- nonlinear micro-finite element analysis
- risk assessment
ASJC Scopus subject areas
- Orthopedics and Sports Medicine
- Endocrinology, Diabetes and Metabolism
Cite this
Improved fracture risk assessment based on nonlinear micro-finite element simulations from HRpQCT images at the distal radius. / Christen, David; Melton, L. Joseph; Zwahlen, Alexander; Amin, Shreyasee; Khosla, Sundeep; Müller, Ralph.
In: Journal of Bone and Mineral Research, Vol. 28, No. 12, 12.2013, p. 2601-2608.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Improved fracture risk assessment based on nonlinear micro-finite element simulations from HRpQCT images at the distal radius
AU - Christen, David
AU - Melton, L. Joseph
AU - Zwahlen, Alexander
AU - Amin, Shreyasee
AU - Khosla, Sundeep
AU - Müller, Ralph
PY - 2013/12
Y1 - 2013/12
N2 - More accurate techniques to estimate fracture risk could help reduce the burden of fractures in postmenopausal women. Although micro-finite element (μFE) simulations allow a direct assessment of bone mechanical performance, in this first clinical study we investigated whether the additional information obtained using geometrically and materially nonlinear μFE simulations allows a better discrimination between fracture cases and controls. We used patient data and high-resolution peripheral quantitative computed tomography (HRpQCT) measurements from our previous clinical study on fracture risk, which compared 100 postmenopausal women with a distal forearm fracture to 105 controls. Analyzing these data with the nonlinear μFE simulations, the odds ratio (OR) for the factor-of-risk (yield load divided by the expected fall load) was marginally higher (1.99; 95% confidence interval [CI], 1.41-2.77) than for the factor-of-risk computed from linear μFE (1.89; 95% CI, 1.37-2.69). The yield load and the energy absorbed up to the yield point as computed from nonlinear μFE were highly correlated with the initial stiffness (R2 = 0.97 and 0.94, respectively) and could therefore be derived from linear simulations with little loss in precision. However, yield deformation was not related to any other measurement performed and was itself a good predictor of fracture risk (OR, 1.89; 95% CI, 1.39-2.63). Moreover, a combined risk score integrating information on relative bone strength (yield load-based factor-of-risk), bone ductility (yield deformation), and the structural integrity of the bone under critical loads (cortical plastic volume) improved the separation of cases and controls by one-third (OR, 2.66; 95% CI, 1.84-4.02). We therefore conclude that nonlinear μFE simulations provide important additional information on the risk of distal forearm fractures not accessible from linear μFE nor from other techniques assessing bone microstructure, density, or mass.
AB - More accurate techniques to estimate fracture risk could help reduce the burden of fractures in postmenopausal women. Although micro-finite element (μFE) simulations allow a direct assessment of bone mechanical performance, in this first clinical study we investigated whether the additional information obtained using geometrically and materially nonlinear μFE simulations allows a better discrimination between fracture cases and controls. We used patient data and high-resolution peripheral quantitative computed tomography (HRpQCT) measurements from our previous clinical study on fracture risk, which compared 100 postmenopausal women with a distal forearm fracture to 105 controls. Analyzing these data with the nonlinear μFE simulations, the odds ratio (OR) for the factor-of-risk (yield load divided by the expected fall load) was marginally higher (1.99; 95% confidence interval [CI], 1.41-2.77) than for the factor-of-risk computed from linear μFE (1.89; 95% CI, 1.37-2.69). The yield load and the energy absorbed up to the yield point as computed from nonlinear μFE were highly correlated with the initial stiffness (R2 = 0.97 and 0.94, respectively) and could therefore be derived from linear simulations with little loss in precision. However, yield deformation was not related to any other measurement performed and was itself a good predictor of fracture risk (OR, 1.89; 95% CI, 1.39-2.63). Moreover, a combined risk score integrating information on relative bone strength (yield load-based factor-of-risk), bone ductility (yield deformation), and the structural integrity of the bone under critical loads (cortical plastic volume) improved the separation of cases and controls by one-third (OR, 2.66; 95% CI, 1.84-4.02). We therefore conclude that nonlinear μFE simulations provide important additional information on the risk of distal forearm fractures not accessible from linear μFE nor from other techniques assessing bone microstructure, density, or mass.
KW - bone microstructure
KW - Distal forearm fracture
KW - high-resolution peripheral quantitative computed tomography
KW - nonlinear micro-finite element analysis
KW - risk assessment
UR - http://www.scopus.com/inward/record.url?scp=84888059970&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84888059970&partnerID=8YFLogxK
U2 - 10.1002/jbmr.1996
DO - 10.1002/jbmr.1996
M3 - Article
C2 - 23703921
AN - SCOPUS:84888059970
VL - 28
SP - 2601
EP - 2608
JO - Journal of Bone and Mineral Research
JF - Journal of Bone and Mineral Research
SN - 0884-0431
IS - 12
ER -