Automated 3D trabecular bone structure analysis of the proximal femur--prediction of biomechanical strength by CT and DXA.
CONCLUSIONS
The standard diagnostic technique for assessing osteoporosis is dual X-ray absorptiometry (DXA) measuring bone mass parameters. In this study, a combination of DXA and trabecular structure parameters (acquired by computed tomography [CT]) most accurately predicted the biomechanical strength of the proximal femur and allowed for a better prediction than DXA alone.


BACKGROUND
An automated 3D segmentation algorithm was applied to determine specific structure parameters of the trabecular bone in CT images of the proximal femur. This was done to evaluate the ability of these parameters for predicting biomechanical femoral bone strength in comparison with bone mineral content (BMC) and bone mineral density (BMD) acquired by DXA as standard diagnostic technique.


METHODS
One hundred eighty-seven proximal femur specimens were harvested from formalin-fixed human cadavers. BMC and BMD were determined by DXA. Structure parameters of the trabecular bone (i.e., morphometry, fuzzy logic, Minkowski functionals, and the scaling index method [SIM]) were computed from CT images. Absolute femoral bone strength was assessed with a biomechanical side-impact test measuring failure load (FL). Adjusted FL parameters for appraisal of relative bone strength were calculated by dividing FL by influencing variables such as body height, weight, or femoral head diameter.


RESULTS
The best single parameter predicting FL and adjusted FL parameters was apparent trabecular separation (morphometry) or DXA-derived BMC or BMD with correlations up to r = 0.802. In combination with DXA, structure parameters (most notably the SIM and morphometry) added in linear regression models significant information in predicting FL and all adjusted FL parameters (up to R(adj) = 0.872) and allowed for a significant better prediction than DXA alone.


CONCLUSIONS
A combination of bone mass (DXA) and structure parameters of the trabecular bone (linear and nonlinear, global and local) most accurately predicted absolute and relative femoral bone strength.
Baum
T
T
Institut für Röntgendiagnostik, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 Munich, Germany. thbaum@gmx.de
Carballido-Gamio
J
J
Huber
M B
MB
Müller
D
D
Monetti
R
R
Räth
C
C
Eckstein
F
F
Lochmüller
E M
EM
Majumdar
S
S
Rummeny
E J
EJ
Link
T M
TM
Bauer
J S
JS
D015502:Absorptiometry, Photon / Q000379:methods; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D015519:Bone Density / Q000502:physiology; D005260:Female; D005269:Femur / Q000000981:diagnostic imaging / Q000473:pathology / Q000503:physiopathology*; D005270:Femur Head / Q000000981:diagnostic imaging / Q000503:physiopathology; D005272:Femur Neck / Q000000981:diagnostic imaging / Q000503:physiopathology; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008297:Male; D008875:Middle Aged; D010024:Osteoporosis / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D013314:Stress, Mechanical; D014057:Tomography, X-Ray Computed / Q000379:methods