A comparison of DXA and CT based methods for estimating the strength of the femoral neck in post-menopausal women.
A comparison of DXA and CT based methods for estimating the strength of the femoral neck in post-menopausal women.
复制标题
DOI:
10.1007/s00198-012-2066-y
复制
发表时间:
2013-04
影响因子:
4
通讯作者:
Cauley, J. A.
中科院分区:
文献类型:
--
作者:
Danielson, M. E.;Beck, T. J.;Karlamangla, A. S.;Greendale, G. A.;Atkinson, E. J.;Lian, Y.;Khaled, A. S.;Keaveny, T. M.;Kopperdahl, D.;Ruppert, K.;Greenspan, S.;Vuga, M.;Cauley, J. A.
Simple 2-dimensional (2D) analyses of bone strength can be done with dual energy x-ray absorptiometry (DXA) data and applied to large data sets. We compared 2D analyses to 3-dimensional (3D) finite element analyses (FEA) based on quantitative computed tomography (QCT) data. 213 women participating in the Study of Women’s Health across the Nation (SWAN) received hip DXA and QCT scans. DXA BMD and femoral neck diameter and axis length were used to estimate geometry for composite bending (BSI) and compressive strength (CSI) indices. These and comparable indices computed by Hip Structure Analysis (HSA) on the same DXA data were compared to indices using QCT geometry. Simple 2D engineering simulations of a fall impacting on the greater trochanter were generated using HSA and QCT femoral neck geometry; these estimates were benchmarked to a 3D FEA of fall impact. DXA-derived CSI and BSI computed from BMD and by HSA correlated well with each other (R= 0.92 and 0.70) and with QCT-derived indices (R= 0.83–0.85 and 0.65–0.72). The 2D strength estimate using HSA geometry correlated well with that from QCT (R=0.76) and with the 3D FEA estimate (R=0.56). Femoral neck geometry computed by HSA from DXA data corresponds well enough to that from QCT for an analysis of load stress in the larger SWAN data set. Geometry derived from BMD data performed nearly as well. Proximal femur breaking strength estimated from 2D DXA data is not as well correlated with that derived by a 3D FEA using QCT data.
登录
查看更多内容
影响因子:
6.2
作者:
Orwoll, Eric S.;Marshall, Lynn M.;Keaveny, Tony M.
通讯作者:
Keaveny, Tony M.
影响因子:
2.4
作者:
Keyak, JH;Rossi, SA;Skinner, HB
通讯作者:
Skinner, HB
影响因子:
6.2
作者:
Burge, Russel;Dawson-Hughes, Bess;Tosteson, Anna
通讯作者:
Tosteson, Anna
影响因子:
6.7
作者:
BECK, TJ;RUFF, CB;RAO, GU
通讯作者:
RAO, GU
影响因子:
56.9
作者:
CARTER, DR;HAYES, WC
通讯作者:
HAYES, WC