TY - JOUR
T1 - Hip load capacity and yield load in men and women of all ages
AU - Keyak, J. H.
AU - Kaneko, T. S.
AU - Khosla, S.
AU - Amin, S.
AU - Atkinson, E. J.
AU - Lang, T. F.
AU - Sibonga, J. D.
N1 - Funding Information:
This work was supported by National Institutes of Health , USA R01AR46197 , R01AR060700 , R01AR064140 , AR-27065 and M01 RR00585 and by NASA Johnson Space Center , USA contracts NNJ04HC7SA , NNJ04HF78G , NNJ12HC91P and NNJ15HP23P . This study was made possible by the Rochester Epidemiology Project. We thank Dr. Vilmundur Gudnason (Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland) for the opportunity to include data from the AGES cohort. The Age, Gene/Environment Susceptibility Reykjavik Study was funded by NIH contract N01-AG-12100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament) and was approved by the Icelandic National Bioethics Committee (VSN: 00-063) and the Data Protection Authority. The authors appreciate the assistance of Donald J. Roth, Ph.D. of the NASA Glenn Research Center, Cleveland, OH who wrote software to convert the Mayo Cohort CT scans from 2-mm to 3-mm-thick slices. The researchers are indebted to the participants in Rochester, MN, USA and Reykjavik, Iceland for their willingness to participate in these studies.
Funding Information:
This work was supported by National Institutes of Health, USA R01AR46197, R01AR060700, R01AR064140, AR-27065 and M01 RR00585 and by NASA Johnson Space Center, USA contracts NNJ04HC7SA, NNJ04HF78G, NNJ12HC91P and NNJ15HP23P. This study was made possible by the Rochester Epidemiology Project. We thank Dr. Vilmundur Gudnason (Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland) for the opportunity to include data from the AGES cohort. The Age, Gene/Environment Susceptibility Reykjavik Study was funded by NIH contract N01-AG-12100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament) and was approved by the Icelandic National Bioethics Committee (VSN: 00-063) and the Data Protection Authority. The authors appreciate the assistance of Donald J. Roth, Ph.D. of the NASA Glenn Research Center, Cleveland, OH who wrote software to convert the Mayo Cohort CT scans from 2-mm to 3-mm-thick slices. The researchers are indebted to the participants in Rochester, MN, USA and Reykjavik, Iceland for their willingness to participate in these studies.
Publisher Copyright:
© 2020 Elsevier Inc.
PY - 2020/8
Y1 - 2020/8
N2 - Quantitative computed tomography (QCT) based finite element (FE) models can compute subject-specific proximal femoral strengths, or fracture loads, that are associated with hip fracture risk. These fracture loads are more strongly associated with measured fracture loads than are DXA and QCT measures and are predictive of hip fracture independently of DXA bone mineral density (BMD). However, interpreting FE-computed fracture loads of younger subjects for the purpose of evaluating hip fracture risk in old age is challenging due to limited reference data. The goal of this study was to address this issue by providing reference data for male and female adult subjects of all ages. QCT-based FE models of the left proximal femur of 216 women and 181 men, age 27 to 90 years, from a cohort of Rochester, MN residents were used to compute proximal femoral load capacities, i.e. the maximum loads that can be supported, in single-limb stance and posterolateral fall loading (Stance_LC and Fall_LC, respectively) [US Patent No. 9,245,069] and yield load under fall loading (Fall_yield). To relate these measures to information about hip fracture, the CT scanner and calibration phantom were cross-calibrated with those from our previous prospective study of hip fracture in older fracture and control subjects, the Age Gene/Environment Susceptibility (AGES) Reykjavik cohort. We then plotted Stance_LC, Fall_LC and Fall_yield versus age for the two cohorts on the same graphs. Thus, proximal femoral strengths in individuals above 70 years of age can be assessed through direct comparison with the FE data from the AGES cohort which were analyzed using identical methods. To evaluate younger individuals, reductions in Stance_LC, Fall_LC and Fall_yield from the time of evaluation to age 70 years can be cautiously estimated from the average yearly cross-sectional decreases found in this study (108 N, 19.4 N and 14.4 N, respectively, in men and 120 N, 19.4 N and 21.6 N, respectively, in women), and the projected fracture loads can be compared with data from the AGES cohort. Although we did not set specific thresholds for identifying individuals at risk of hip fracture, these data provide some guidance and may be used to help establish diagnostic criteria in future. Additionally, given that these data were nearly entirely from Caucasian subjects, future research involving subjects of other races/ethnicities is necessary.
AB - Quantitative computed tomography (QCT) based finite element (FE) models can compute subject-specific proximal femoral strengths, or fracture loads, that are associated with hip fracture risk. These fracture loads are more strongly associated with measured fracture loads than are DXA and QCT measures and are predictive of hip fracture independently of DXA bone mineral density (BMD). However, interpreting FE-computed fracture loads of younger subjects for the purpose of evaluating hip fracture risk in old age is challenging due to limited reference data. The goal of this study was to address this issue by providing reference data for male and female adult subjects of all ages. QCT-based FE models of the left proximal femur of 216 women and 181 men, age 27 to 90 years, from a cohort of Rochester, MN residents were used to compute proximal femoral load capacities, i.e. the maximum loads that can be supported, in single-limb stance and posterolateral fall loading (Stance_LC and Fall_LC, respectively) [US Patent No. 9,245,069] and yield load under fall loading (Fall_yield). To relate these measures to information about hip fracture, the CT scanner and calibration phantom were cross-calibrated with those from our previous prospective study of hip fracture in older fracture and control subjects, the Age Gene/Environment Susceptibility (AGES) Reykjavik cohort. We then plotted Stance_LC, Fall_LC and Fall_yield versus age for the two cohorts on the same graphs. Thus, proximal femoral strengths in individuals above 70 years of age can be assessed through direct comparison with the FE data from the AGES cohort which were analyzed using identical methods. To evaluate younger individuals, reductions in Stance_LC, Fall_LC and Fall_yield from the time of evaluation to age 70 years can be cautiously estimated from the average yearly cross-sectional decreases found in this study (108 N, 19.4 N and 14.4 N, respectively, in men and 120 N, 19.4 N and 21.6 N, respectively, in women), and the projected fracture loads can be compared with data from the AGES cohort. Although we did not set specific thresholds for identifying individuals at risk of hip fracture, these data provide some guidance and may be used to help establish diagnostic criteria in future. Additionally, given that these data were nearly entirely from Caucasian subjects, future research involving subjects of other races/ethnicities is necessary.
KW - Bone strength
KW - Femur
KW - Finite element analysis
KW - Hip fracture
KW - Osteoporosis
KW - Quantitative computed tomography
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U2 - 10.1016/j.bone.2020.115321
DO - 10.1016/j.bone.2020.115321
M3 - Article
C2 - 32184195
AN - SCOPUS:85085034254
SN - 8756-3282
VL - 137
JO - Bone
JF - Bone
M1 - 115321
ER -