Determinants of Bone Mass and Bone Geometry in Adolescent and Young Adult Women

Kardinaal, A.F.M.; Hoorneman, G.; Väänänen, Kalervo; Charles, Peder; Andò, Sebastiano; Maggiolini, Marcello; Charzewska, Jadwiga; Rotily, Michel; Deloraine, A.; Heikkinen, Jorma; Juvin, R.; Schaafsma, G.

doi:10.1007/pl00005834

Cited by 38 publications

(28 citation statements)

References 34 publications

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“…Similar findings were previously reported using DXA projection techniques (7), however the associations were much weaker in their study. The observed relationships are expected as it is well established that the skeleton scales with height and weight (38,39). Femoral neck width increasing trend seen with age (r= 0.606; p=0.063) found in our study are consistent with previously reported studies (4,5) which suggesting subperiosteal expansion and cortical thinning with age.…”

Section: Discussionsupporting

confidence: 92%

Method for Cortical Bone Structural Analysis From Magnetic Resonance Images1

Gomberg¹,

Saha²,

Wehrli³

2005

Academic Radiology

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Rationale-Quantitative evaluation of cortical bone architecture as a means to assess bone strength is typically accomplished on the basis of images obtained by dual-energy X-ray absorptiometry (DXA) or computed tomography (CT). Magnetic resonance imaging (MRI) has potential advantages for this task in that it allows imaging in arbitrary scan planes at high spatial resolution. However, several hurdles have to be overcome in order to make this approach practical, including resolution of issues related to nonlinear receive coil sensitivity, variations in marrow composition and the presence periosteal isointense tissues which all complicate segmentation. Objectives-To develop MR acquisition and analysis methods optimized for detection of cortical boundaries in complex geometries such as the femoral neck.Materials and Methods-Cortical boundary detection is achieved by radially tracing intensity profiles that intersect the bone's periosteal and endosteal boundary. The profiles are subsequently normalized to the intensity of the marrow signal, processed with morphologic image operators and binarized. The resulting boundaries are then mapped back onto the spatial image and erroneous boundary points removed. From the detected cortical boundaries cortical cross-sectional area and thickness are computed. The method was evaluated on cortical bone specimens and human volunteers on the basis of high-resolution images acquired at 1.5 Tesla field strength. To assess whether the method is sensitive to detect the expected dependencies of cortical parameters in weight-bearing bone on overall habitus, ten women ages 46-73 years (mean 56 years) underwent the cortical imaging protocol in the proximal femur and the results were compared with DXA BMD parameters of the hip and spine.Results-Reproducibility was on the order of 2%. Double oblique images of the femoral neck in the ten women studied showed cortical cross-sectional area to correlate strongly with height (r = 0.88, p = 0.0008) while cortical diameter versus age approached significance (r = 0.61, p = 0.06). Measurements in specimens of some cortical parameters indicated a resolution dependence. It is to be noted, however, that parameter rank remained constant across all specimens studied. Conclusion-The data suggest the new method to be robust and applicable on standard clinical MR scanners at arbitrary anatomic locations to yield clinically meaningful quantitative results.

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Section: Discussionsupporting

confidence: 92%

Method for Cortical Bone Structural Analysis From Magnetic Resonance Images1

Gomberg¹,

Saha²,

Wehrli³

2005

Academic Radiology

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“…The latter used the same peripheral DXA apparatus we used, but they do not provide detailed information regarding the calculation of medullary area and refer to a patented software option. Our CVs are comparable to those in the literature [17,18].…”

Section: Discussionsupporting

confidence: 87%

“…Correlation coefficients of 0.8 between measured and calculated radial dimensions demonstrate a reasonable accuracy of the procedure we adopted. This procedure for calculating the medullary area is apparently the same as that used by Haapsalo et al [17] and Kardinal et al [18]. The latter used the same peripheral DXA apparatus we used, but they do not provide detailed information regarding the calculation of medullary area and refer to a patented software option.…”

Section: Discussionmentioning

confidence: 95%

Radial Bending Breaking Resistance Derived by Densitometric Evaluation Predicts Femoral Neck Fracture

Gatti

Sartori

Braga

et al. 2001

Osteoporosis International

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Bone mineral density (BMD) measurement by hip dual-energy X-ray absorptiometry (DXA) is considered the best predictor of osteoporotic fracture risk. BMD takes into account only in part the bone cross-sectional area that is an important determinant of both bone compression strength and of bending breaking resistance. From DXA measurements of proximal radius (Osteoplan, NIM, Verona, Italy) we obtained the projected outer diameter (D) and the mean diameter of the medulla (d), by an algorithm based on the assumption of a constant cortical volumetric density of 1050 g/cm3. The algorithm was validated by the good correlation found (r = 0.8) between calculated d and that actually measured by peripheral quantitative tomography (pQCT; XCT 960, Stratec, Unitrem, Italy) at the same radial site. The D and d values were used to calculate a bending breaking resistance index (BBRI) that is a component of the cross-sectional moment of inertia. The BBRI measured in 5460 women aged 35-89 years, was stable up to the age of 65-70 years and rapidly declined thereafter by 0.7% per year. This profile appears to be due to the fact that the increase in medullary area is compensated in terms of mechanical resistance by enlargement of cross-sectional area. In 68 women with either previous femoral neck (n = 41) or pertrochanteric fracture (n = 27) DXA measurements at proximal and ultradistal radius, lumbar spine and femoral neck were obtained together with the evaluation of proximal radius BBRI. The diagnostic accuracy of BBRI was somewhat comparable to that of spine and femoral neck BMD and significantly superior to that of ultradistal and proximal radius BMD, from which it was derived. Despite the obvious limitation of the cross-sectional nature of this study, our results indicate that a simple re-elaboration of the data obtained by peripheral radial densitometry may achieve diagnostic accuracy for hip fracture risk assessment only marginally lower than that of the direct measure of the BMD of the femoral neck. They also give additional support to the view that bone geometry, particularly for compact skeletal segments, is a determinant of its strength at least as important as bone density.

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“…In the present study, different determinants of bone density, mass and growth were measured using survey radiographs in different breeds of growing dogs with both normal and osteopenic bones. Similar studies have been done in human beings; one such study was undertaken to obtain data on bone mass and geometry in adolescent and young adult woman to see the effects of these determinants on bone strength (Kardinaal et al 2000). Another study in cattle suffering from Calcinosis was also documented by measuring cortical index in metacarpus (Feussener 1977).…”

Section: Discussionmentioning

confidence: 96%

Determinants of bone mass, density and growth in growing dogs with normal and osteopenic bones

et al. 2008

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Survey radiographs of all the growing dogs aged up to 6 months, which were presented to the IVRI polyclinics during the 10 year period were screened to study the determinants of bone mass, density and growth. On the basis of clinical history and radiographic evaluation of long bones, the cases were categorizes as normal or osteopenic. The relative cortical density (RCD), cortical index (CI), diameter of bone at the distal metaphysis (DDFM) and the width of the growth plate (WFGP) were determined by taking the femur as a model bone in German shepherd, Doberman and Spitz breeds of dogs at different age groups. The results showed that RCD was the least in 0-2 month old normal growing dogs in all the breeds. As the age advanced up to 6 months the RCD increased 20-25% and at 6 months, Spitz and Doberman showed significant increase (P<0.05) in the RCD. In osteopenic bones, RCD remained less (25-50%) than that of normal animals at all age groups, and at 2-6 months of age, RCD in osteopenic bones was significantly lesser than in normal animals in GSD and Spitz breeds. The CI was also the least at 0-2 months of age in normal dogs. The CI increased about 50% at 4-6 months of age in GSD and Spitz. Whereas in Dob., there was no appreciable change in the CI at different age groups, and at 2-6 months it was significantly (P<0.05) lesser than that of Spitz. In osteopenic bones, the CI was 25-75% lesser than that of normal animals at different age groups, and at 4-6 months there was significant difference (P<0.05) between the normal and osteopenic bones in GSD and Spitz. The DDFM was the least in 0-2 month old normal growing dogs, and as the age advanced, it increased 10-20% up to 6 months. However, no significant difference in the DDFM was seen between breeds and also between the normal and osteopenic bones at different age groups. In normal animals, the WFGP was the highest in the early age, subsequently it reduced 50-75% and at the 4-6 months there was a significant decrease (P<0.05) in all breeds of dogs. And at the 4-6 months, there was significant (P<0.05) difference in the WFGP between breeds, it was the least in Spitz and maximum in Dob., suggesting faster growth plate closure in Spitz than in GSD and Dob. breeds. In osteopenic bones, WFGP was generally more than in normal animals, and at 4-6 months (about 3-5 times more) there was significant difference (p<0.05) between the normal and osteopenic bones in all breeds, indicating that physeal closure may be delayed in osteopenic bones. The results indicate that among different breeds Doberman breed has the least bone mass and may be more prone to osteopenia; whereas Spitz has the strongest bone.

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Determinants of Bone Mass and Bone Geometry in Adolescent and Young Adult Women

Cited by 38 publications

References 34 publications

Method for Cortical Bone Structural Analysis From Magnetic Resonance Images1

Method for Cortical Bone Structural Analysis From Magnetic Resonance Images1

Radial Bending Breaking Resistance Derived by Densitometric Evaluation Predicts Femoral Neck Fracture

Determinants of bone mass, density and growth in growing dogs with normal and osteopenic bones

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