Osteoporosis　is　characterized　by　reduced　bone　strength　predisposing　to　an　increased　risk　of　fracture.　Biomechanical　computed　tomography　(BCT),　predicting　bone　strength　via　CT-based　finite　element　analysis　(FEA),　is　now　clinically　available　in　the　USA　for　diagnosing　osteoporosis　or　assessing　fracture　risk.　How-ever,　it　has　not　been　previously　validated　using　a　cohort　of　only　Chinese　subjects.　Additionally,　the　effect　of　various　modeling　approaches　on　BCT　outcomes　remains　elusive.　To　address　these　issues,　we　performed　DXA　and　QCT　scanning,　compression　testing,　and　BCT　analyses　on　thirteen　vertebrae　derived　from　Chi-nese　donors.　Three　BCT　models　were　created　(voxBCT　and　tetBCT:　voxel-based　and　tetrahedral　element　-based　FE　models　generated　by　a　commercial　software;　matBCT:　tetrahedral　element-based　FE　model　generated　by　a　custom　MATLAB　program).　BCT-computed　outcomes　were　compared　with　experimental　measures　or　between　different　BCT　models.　Results　showed　that,　DXA-measured　areal　bone　mineral　den-sity　(aBMD)　showed　weak　correlations　with　experimentally-measured　vertebral　stiffness　(R-2　=　0.28)　and　strength　(R-2　=　0.34).　Compared　to　DXA-aBMD,　BCT-computed　stiffness　provided　improved　correlations　with　experimentally-measured　stiffness　(voxBCT:　R-2　=　0.82;　tetBCT:　R　2　=　0.77;　matBCT:　R-2　=　0.76)　and　strength　(voxBCT:　R-2　=　0.55;　tetBCT:　R-2　=　0.57;　matBCT:　R-2　=　0.53);　BCT-computed　mechanical　param-eters　(stiffness,　stress　and　strain)　of　the　three　different　models　were　highly　correlated　with　each　other,　with　coefficient　of　determination　(R-2)　values　of　0.89-0.98.　These　results,　based　on　a　cohort　of　Chinese　vertebral　cadavers,　suggest　that　BCT　is　superior　over　aBMD　to　consistently　predict　vertebral　mechanical　characteristics,　regardless　of　the　modeling　approaches　of　choice.　(C)　2021　IPEM.　Published　by　Elsevier　Ltd.　All　rights　reserved.