SEARCH

SEARCH BY CITATION

Keywords:

  • OSTEOPOROSIS;
  • TRABECULAR MICROARCHITECTURE;
  • MAGNETIC RESONANCE IMAGING;
  • FRACTURE;
  • POSTMENOPAUSAL WOMEN

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

This study compared microscopic magnetic resonance imaging (µMRI) parameters of trabecular microarchitecture between postmenopausal women with and without fracture who have normal or osteopenic bone mineral density (BMD) on dual-energy X-ray absorptiometry (DXA). It included 36 postmenopausal white women 50 years of age and older with normal or osteopenic BMD (T-scores better than −2.5 at the lumbar spine, proximal femur, and one-third radius on DXA). Eighteen women had a history of low-energy fracture, whereas 18 women had no history of fracture and served as an age, race, and ultradistal radius BMD-matched control group. A three-dimensional fast large-angle spin-echo (FLASE) sequence with 137 µm × 137 µm × 400 µm resolution was performed through the nondominant wrist of all 36 women using the same 1.5T scanner. The high-resolution images were used to measure trabecular bone volume fraction, trabecular thickness, surface-to-curve ratio, and erosion index. Wilcoxon signed-rank tests were used to compare differences in BMD and µMRI parameters between postmenopausal women with and without fracture. Post-menopausal women with fracture had significantly lower (p < 0.05) trabecular bone volume fraction and surface-to-curve ratio and significantly higher (p < 0.05) erosion index than postmenopausal women without fracture. There was no significant difference between postmenopausal women with and without fracture in trabecular thickness (p = 0.80) and BMD of the spine (p = 0.21), proximal femur (p = 0.19), one-third radius (p = 0.47), and ultradistal radius (p = 0.90). Postmenopausal women with normal or osteopenic BMD who had a history of low-energy fracture had significantly different (p < 0.05) µMRI parameters than an age, race, and ultradistal radius BMD-matched control group of postmenopausal women with no history of fracture. Our study suggests that µMRI can be used to identify individuals without a DXA-based diagnosis of osteoporosis who have impaired trabecular microarchitecture and thus a heretofore-unappreciated elevated fracture risk. © 2012 American Society for Bone and Mineral Research.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

Osteoporosis is a multifactorial disease of low bone mass and impaired bone microarchitecture that results in decreased bone strength and increased fracture risk.1 The disease becomes extremely common with advancing age with 40% to 50% of women and 25% of men sustaining an osteoporosis-related fracture during their lifetime.2, 3 Currently an estimated 1.5 million fractures occur annually in the United States,4 which produce high morbidity and mortality and cause substantial health-care expenditures.5–9 Whereas the current disability and economic burden associated with osteoporosis is enormous, the future burden will be considerably higher with the increasing age of the population worldwide.10 As such, a pressing need exists to optimally identify those individuals at elevated fracture risk.

The clinical standard for osteoporosis diagnosis is bone mineral density (BMD) measurements obtained using dual-energy X-ray absorptiometry (DXA).11 In fact, the World Health Organization (WHO) T-score-based system classifying individuals as normal, osteopenic, or osteoporotic12 directly applies only to BMD as measured by DXA.11 DXA has proven to be a valuable clinical tool, because it identifies individuals at elevated fracture risk, and subsequent treatment of men and women with low BMD reduces fracture risk.13–17 However, BMD accounts for only 50% to 65% of variations in the mechanical strength of bone.18, 19 Furthermore, large prospective studies have found that fewer than 50% of individuals who sustain low-energy fractures have a diagnosis of osteoporosis based on BMD measurements.20–22 Thus, clinical need exists to identify factors other than BMD that influence bone strength and fracture risk.

Bone strength is the result of bone density and “bone quality,” a complex amalgamation including macroarchitecture and microarchitecture, mineralization, turnover, and damage accumulation. Bone remodeling is a component of normal human physiology that prevents fatigue damage accumulation and contributes to mineral homeostasis.23, 24 Remodeling is carried out by a coupled team of cells, osteoclasts that excavate remodeling lacunae and osteoblasts that produce and mineralize osteoid.25, 26 Ideally, osteoblasts precisely replace the amount of bone resorbed by osteoclasts via a complex coupling process.27 However, with aging, osteoclastic activity exceeds osteoblastic activity, leading to trabecular thinning and perforation and conversion of trabecular plates to rods.28 The resultant microarchitecture deterioration leads to reduced bone strength and increased fracture risk.29

The recognition of impaired trabecular microarchitecture as a risk factor for fracture was originally based on iliac crest biopsy histomorphometry.30–32 However, histomorphometry is invasive and provides imperfect microarchitectural assessment, because histological sections are two-dimensional, and trabecular microarchitecture is inherently three-dimensional and highly anisotropic.33 Noninvasive three-dimensional assessment of trabecular microarchitecture has recently become possible using high-resolution imaging techniques such as peripheral quantitative computed tomography (pQCT) and microscopic magnetic resonance imaging (µMRI). pQCT can acquire images of the peripheral skeleton with voxel sizes as low as 82 µm × 82 µm × 82 µm, with minimal radiation exposure,34 whereas µMRI can acquire images with voxel sizes as low as 137 µm × 137 µm × 225 µm for the wrist35–37 and 234 µm × 234 µm × 1500 µm for the proximal femur.38 The high-resolution images can be used to measure various microarchitectural parameters, including the fractional volume and thickness of trabecular bone and the degree of connectivity of the trabecular network.39–42

Multiple previous studies have shown that trabecular microarchitectural parameters measured using both pQCT43 and µMRI44–50 are superior to BMD for distinguishing between osteoporotic individuals with and without fracture.44–50 However, no previous study has investigated the ability of these parameters to assess fracture risk in individuals without a DXA-based diagnosis of osteoporosis. Thus, this study was performed to compare µMRI parameters of trabecular microarchitecture between postmenopausal women with and without fracture who have normal or osteopenic bone mineral density.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

Subjects

The prospective study was performed in compliance with HIPAA regulations and with approval from our Institutional Review Board. All subjects signed written consent before participating in the study.

The study included 36 postmenopausal white women 50 years of age and older with normal or osteopenic BMD (T-scores better than −2.5 at the lumbar spine, proximal femur, and one-third radius on DXA). Eighteen women had a history of low-energy fracture, which was defined as a clinically symptomatic fracture occurring with everyday activities, including a fall from standing height or less. Five subjects had ankle fractures, two subjects had rib fractures, six subjects had vertebral body fractures, one subject had a humerus fracture, and four subjects had dominant-side wrist fractures. All fractures were documented either through the medical records or through actual review of the imaging studies. The mean interval between the time the subjects sustained a fracture and the time they were enrolled in the study was 4.8 years, with a range between 0.1 and 17.1 years and a standard deviation of 4.4 years. Eighteen women had no history of low-energy fracture and served as an age, race, and ultradistal radius BMD-matched control group. Age between subjects was matched to within 6 months, and BMD in grams/cm2 at the nondominant ultradistal radius was matched within 5%. Subjects were excluded from the study if they had a history of metabolic bone disease, malignancy, renal failure, use of medications that alter bone turnover, diseases/conditions leading to nondominant arm disuse, and contraindications to µMRI examination.

Subjects were recruited through an Institute on Aging Volunteer Registry at our institution, which was searched for potential eligible volunteers. After phone screening, potential eligible subjects underwent standard spine, proximal femur, and nondominant forearm DXA scans (Lunar iDXA densitometer, GE Healthcare, Madison, WI, USA). Quality-assurance precision data obtained from repeat BMD measurements on 30 postmenopausal women showed a coefficient of variance of 1.2% for the spine, 0.6% for the proximal femur, 2.4% for the distal radius, and 3.9% for the ultradistal radius. DXA images were used to exclude the presence of prior trauma, osteoarthritis, or inflammatory- or crystalline-induced arthritis of the nondominant wrist, which may influence trabecular microarchitecture. A DXA vertebral fracture assessment (VFA) image of the thoracolumbar spine was obtained to document vertebral fracture status to assure that unappreciated vertebral fractures did not exist in subjects in the control group. Blood was drawn to obtain a routine chemistry panel to show the absence of systemic conditions indicative of bone disease. Subjects meeting inclusion/exclusion criteria with a history of low-energy fracture and those determined to be an appropriate match were included in the study.

µMRI examination

All subjects underwent a µMRI examination of the nondominant wrist on the same 1.5T scanner (Signa Hdx, GE Healthcare, Madison, WI, USA) using a specially designed transmit-receive elliptical birdcage coil (Insight MRI, Worcester, MA, USA). All subjects were imaged with their arm positioned at the side and their wrist centered within the coil. The coil was placed in the middle of an immobilizing vacuum bag (VacFixTM, Soule Medical Systems, Inc., Tampa, FL, USA) and attached to the base of a positioning device. The vacuum bag was secured around the arm using Velcro straps and inflated to minimize wrist movement during the µMRI examination.37, 51, 52

All µMRI examinations consisted of a three-dimensional fast large-angle spin-echo (FLASE) sequence. Intermittent navigator echoes were incorporated into the sequence to allow for motion correction. The FLASE sequence was performed using a TR/TE of 80 ms/10 ms, 140° flip angle, 7.0 cm × 5.3 cm field of view, 512 × 384 matrix, 0.4 mm slice thickness, one excitation, 137 µm × 137 µm × 400 µm voxel size, and 12-minute and 30-second scan time. Images were acquired through a 7.0 cm × 5.3 cm × 7.0 cm volumetric slab, which was centered on the distal radius 7 mm proximal to the tip of the epiphyseal line.37, 51, 52

Image analysis

Image analysis was performed by an experienced research technologist from MicroMRI, Inc. (Langhorne, PA, USA) using a previously described semiautomated virtual bone biopsy system.33 Motion-corrected images were generated from the raw data using estimates of patient motion obtained from the navigator echoes.53 A three-dimensional volume-of-interest through the distal radius was selected to exclude areas of artifact but to include as much of the bone marrow space as possible. The volume-of-interest was processed using a bone volume fraction mapping technique to generate noiseless parametric images where each voxel represented the trabecular bone volume fraction (bone volume/trabecular volume).54

The average trabecular thickness on the bone volume fraction maps was measured using a fuzzy distance transform algorithm.55 The bone volume fraction maps then underwent subvoxel processing to improve resolution, which resulted in a voxel size of 69 µm × 69 µm × 103 µm.56 The maps were binarized and skeletonized to produce a model of the trabecular network consisting of surfaces and curves that represented the lower-dimensional counterparts of plates and struts respectively.42 Digital topological analysis was used to classify each voxel within the volume-of-interest into a surface (S), curve (C), or their mutual junction (CC, SC, and SS). Further classification was used to distinguish between voxels located in the interior or edge of the respective curves or surfaces (CI, SI, CE, and SE).35, 57

The topological parameters surface-to-curve ratio and erosion index were calculated to describe the integrity of the trabecular network. The surface-to-curve ratio represented the relative platelike versus rodlike character of the trabecular network and was defined as the sum of all surface-type voxels (SE, SI, SC, SS) divided by the sum of all curve-type voxels (CE, CI, and CC). The erosion index represented the degree of connectivity of the trabecular network and was defined as the sum of all surface-type voxels expected to increase with bone resorption (CI, CE, CC, and SE) divided by the sum of all surface-type voxels expected to decrease with bone resorption (SI, SC, and SS).35, 57

A preliminary pilot study was performed at our institution by MicroMRI, Inc. (Langhorne, PA, USA) to document the precision of the FLASE sequence and virtual bone biopsy system for measuring µMRI parameters. µMRI examinations were performed twice on separate days on 10 healthy volunteers (four male with average age of 27.8 years and six females with an average age of 28.3 years), using the previously described imaging protocol. µMRI parameters of trabecular microarchitecture were measured using the previously described methods. The mean coefficient of variance for repeat measurements was 2.4% for bone volume fraction, 2.1% for trabecular thickness, 6.2% for surface-to-curve ratio, and 4.1% for erosion index, which was similar to values reported at other institutions.37, 58

Statistical analysis

All statistical analysis was performed using the R programming environment (R Development Core Team; Vienna, Austria; Version 2.3.1; 2006; http:/www.R-project.org). Wilcoxon signed-rank tests were used to compare differences between postmenopausal women with and without fracture in age, height, weight, body mass index, BMD measurements (lumbar spine, proximal femur, one-third radius, and ultradistal radius), laboratory values (calcium, phosphate, creatinine, albumen, alkaline phosphatase, and alanine aminotransferase), and µMRI parameters (trabecular bone volume fraction, trabecular thickness, surface-to-curve ratio, and erosion index). For all statistical tests, differences were considered to be statistically significant if the p-value was less than 0.05.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

There was no statistically significant difference (p = 0.13–0.99) between postmenopausal with and without fracture in age, height, weight, body mass index, BMD measurements, and laboratory values (Table 1). However, postmenopausal women with fracture had significantly lower (p < 0.05) trabecular bone volume fraction and surface-to-curve ratio and significantly higher (p < 0.05) erosion index than postmenopausal women without fracture. There was no significant difference (p = 0.80) in trabecular thickness between postmenopausal women with and without fracture (Table 2).

Table 1. Characteristics of Postmenopausal Women With and Without Fracture
CharacteristicMean (SD)Difference Between Groups
Fracture GroupNon-Fracture Group
Age60.9 years (+/− 6.4 years)61.1 years (+/− 6.8 years)p = 0.13
Height65.0 cm (+/− 2.8 cm)64.5 cm (+/− 3.0 cm)p = 0.60
Weight160.4 lbs (+/− 26.2 lbs)147.7 lbs (+/− 23.2 lbs)p = 0.68
Body mass index27.0 kg/m2 (+/− 5.6 kg/m2)25.1 kg/m2 (+/− 4.2 kg/m2)p = 0.26
Lumbar spine BMD1.122 g/cm2 (+/− 0.098 g/cm2)1.169 g/cm2 (+/− 0.128 g/cm2)p = 0.21
Proximal femur BMD0.827 g/cm2 (+/− 0.067 g/cm2)0.865 g/cm2 (+/− 0.095 g/cm2)p = 0.19
One-third radius BMD0.831 g/cm2 (+/− 0.086 g/cm2)0.810 g/cm2 (+/− 0.086 g/cm2)p = 0.17
Ultradistal radius BMD0.376 g/cm2 (+/− 0.059 g/cm2)0.377 g/cm2 (+/− 0.055 g/cm2)p = 0.90
Calcium9.5 mg/dL (+/− 0.4 mg/dL)9.4 mg/dL (+/− 0.4 mg/dL)p = 0.15
Phosphate3.8 mg/dL (+/− 0.6 mg/dL)3.7 mg/dL (+/− 0.4 mg/dL)p = 0.96
Creatinine0.8 mg/dL (+/− 0.1 mg/dL)0.8 mg/dL (+/− 0.1 mg/dL)p = 0.99
Albumen4.3 mg/dL (+/− 0.2 mg/dL)4.4 mg/dL (+/− 0.2 mg/dL)p = 0.63
Alkaline phosphatase74.3 mg/dL (+/− 16.0 mg/dL)79.3 mg/dL (+/− 54.4 mg/dL)p = 0.74
Alanine aminotransferase26.0 mg/dL (+/− 43.5 mg/dL)32.1 mg/dL (+/− 19.7 mg/dL)p = 0.99
Table 2. µMRI Parameters in Postmenopausal Women With and Without Fracture
µMRI ParameterMean (SD)Difference Between Groups
Fracture GroupNonfracture Group
Trabecular bone Volume fraction9.3% (+/− 1.1%)10.2% (+/− 0.9%)p < 0.001
Trabecular thickness85.5 µm (+/− 8.0 µm)85.7 µm (+/− 6.3 µm)p = 0.80
Surface-to-curve ratio5.1 (+/− 1.0)5.9 (+/− 1.0)p = 0.04
Erosion index1.4 (+/− 0.2)1.2 (+/− 0.2)p = 0.03

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

Our study found a significantly lower bone volume fraction in postmenopausal women with fracture when compared with postmenopausal women without fracture. Link and associates compared µMRI parameters of the calcaneus46 and Majumdar and associates compared µMRI parameters of the wrist50 in postmenopausal women with and without hip fracture and also found significantly lower trabecular bone volume fraction in subjects with fracture. In addition, Wehrli and associates found significantly lower trabecular bone volume fraction of the wrist in postmenopausal women with vertebral body fracture when compared with postmenopausal women without fracture.35 However, in those prior studies, a significant difference in BMD between subjects with and without fracture was present, which may have served as a confounding variable in fracture risk assessment.35, 36, 50 In our study, low trabecular bone volume fraction was found to be a risk factor for fracture independent of BMD, because our postmenopausal women with and without fracture had similar BMD measurements at all body sites and were specifically matched for BMD at the ultradistal radius where µMRI parameters were measured.

Our study found a significantly lower surface-to-curve ratio and significantly higher erosion index in postmenopausal women with fracture when compared with postmenopausal women without fracture. Postmenopausal bone loss is characterized by conversion of trabecular plates to rods because of excessive osteoclastic activity eventually leading to plate perforation.59 Differences in topological parameters in our study indicate a more rodlike trabecular network and greater trabecular erosive changes in postmenopausal women with fracture. Wehrli and associates also found significantly lower surface-to-curve ratio and significantly higher erosion index of the wrist in postmenopausal women with vertebral body fracture when compared with postmenopausal women without fracture. However, subjects with and without fracture also showed significant BMD differences, which may have served as a confounding variable in the study.50 A later study by Ladinsky and associates found a significant correlation between surface-to-curve ratio and erosive index of the wrist and vertebral body fracture burden in postmenopausal women, which was independent of vertebral body BMD.48

Our study found no significant difference in trabecular thickness between postmenopausal women with and without fracture. This is consistent with prior work demonstrating that bone loss in postmenopausal women is characterized by trabecular perforation rather than the trabecular thinning, which is more commonly observed in aging men.60, 61 Similarly, Link and associates found no significant difference in trabecular thickness of the calcaneus,46 and Majumdar and associates found no significant difference in trabecular thickness of the wrist50 between postmenopausal women with and without hip fracture. However, Ladinsky and associates found a significant correlation between trabecular thickness of the wrist and vertebral body fracture burden in postmenopausal women, which was independent of vertebral body BMD.48 The difference in the results of our study and the study performed by Landinsky and associates may be partly explained by differences in patient populations. Our study included only postmenopausal women with a T-score better than −2.5 at the lumbar spine, proximal femur, and one-third radius on DXA, whereas the study by Landinsky and associates included only postmenopausal females with a T-score between −1.5 and −3.5 at the lumbar spine and proximal femur.

Our study is the first to investigate the role of trabecular microarchitectural parameters in assessing fracture status exclusively in individuals with normal or osteopenic BMD. All previous studies have shown that parameters of trabecular microarchitecture measured using pQCT43 and µMRI44–45 can distinguish between osteoporotic individuals with and without fracture.44–50 However, individuals with a DXA-based diagnosis of osteoporosis would meet the current U.S. National Osteoporosis Foundation guidelines for receiving pharmacologic therapy to increase BMD and reduce fracture risk regardless of whether their trabecular microarchitecture was normal or abnormal. Our study shows that µMRI can be used as a noninvasive method to identify individuals without a DXA-based diagnosis of osteoporosis who have a heretofore-unappreciated elevated fracture risk. As microarchitectural deterioration profoundly reduces bone strength, it is apparent that clinical application of tools capable of identifying such structural deterioration may enhance targeting of fracture prevention therapy.

Our study has several limitations. One limitation was the wide variety of low-energy fractures sustained by our postmenopausal women, which may have resulted in a rather heterogeneous study group. However, this is reflective of the real-life clinical scenario in which individuals with low BMD sustain a variety of low-energy fractures. A second limitation of our study was the suboptimal resolution of the FLASE sequence used to evaluate trabecular microarchitecture. In particular, the 137 µm × 137 µm × 400 µm resolution may have been insufficient to accurately measure trabecular thickness that typically ranges between 100 µm and 150 µm.34 Thus, the inability of our study to detect a significant difference in trabecular thickness between subjects with and without fracture may be partly because of resolution-dependent inaccuracies in the measurement of this microarchitectural parameter. Another limitation of our study was the relatively small number of subjects. Additional studies using a larger number of subjects and perhaps higher resolution imaging techniques should be performed to further compare trabecular microarchitectural parameters between postmenopausal women with and without fracture who do not have a DXA-based diagnosis of osteoporosis. A final limitation of our study was that the µMRI examination was performed only on the nondominant wrist of postmenopausal females. Previous studies have also measured µMRI parameters in the calcaneus,45, 46 tibia,50, 62, 63 and proximal femur.38 It is possible that µMRI parameters measured at these sites may be more useful for distinguishing between subjects with and without fracture than µMRI parameters measured at the wrist.

In conclusion, our study found that postmenopausal women with normal or osteopenic BMD who had a history of low-energy fracture had significantly lower trabecular bone volume fraction and surface-to-curve ratio and significantly higher erosion index than an age, race, and ultradistal radius BMD-matched control group of postmenopausal women with no history of fracture. Our study suggests that µMRI can be used to identify individuals without a DXA-based diagnosis of osteoporosis who have a heretofore-unappreciated elevated fracture risk. In the future, µMRI may potentially enhance targeting of fracture prevention therapy to include individuals with normal or osteopenic BMD who have impaired trabecular microarchitecture. For example, patients without a DEXA-based diagnosis of osteoporosis who have a family history of low-energy fracture or an elevated fracture risk according to the World Health Organization Fracture Risk Assessment Tool (FRAX) could be further evaluated with µMRI. If such individuals were found to have substantial microarchitectural deterioration, it seems logical that pharmacologic therapy could reduce subsequent fracture risk. However, before µMRI can be used as decision-making tool in clinical practice, additional studies are first needed to delineate the population distribution of normal and abnormal µMRI parameters and to determine clinical thresholds at which these parameters are sufficiently abnormal to indicate the need for pharmacologic therapy to reduce fracture risk.

Disclosures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

Author NB serves as a consultant for and receives research support from Amgen, Lilly, Merck, and Tarsa. Author MK was the chief medical officer of MicroMRI, Inc. (Langhorne, PA) during the time the study was conducted. All other authors state that they have no conflicts of interest.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References

We would like to acknowledge MicroMRI, Inc. (Langhorne, PA, USA) for providing the sequence and coil used during the µMRI examination and for performing the complex image analysis needed to measure µMRI parameters of trabecular microarchitecture.

The study was funded by the University of Wisconsin Institute for Clinical and Translational Research and by grant 1UL1RR025011 from the Clinical and Translational Science Award Program of the National Institutes of Health.

Authors' Roles: Study design: RK, MT, MK, and NB. Study conduct: RK, MT, DK, and NB. Data collection: RK, MT, DK, and NB. Data analysis: RK, MT, AMDR, and NB. Data interpretation: RK, MT, MK, and NB. Drafting manuscript: RK. Revising manuscript: all authors. Approval of final manuscript: all authors. Data analysis: RK, MT, and NB take responsibility for the integrity of the data analysis.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgements
  9. References
  • 1
    Anonymous. Osteoporosis prevention, diagnosis and therapy. NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis and Therapy. JAMA. 2001; 285: 78595.
  • 2
    Chrischilles EA, Butler CD, Davis CS, Wallace RB. A model of lifetime osteoporosis impact. Arch Intern Med. 1991; 151: 202632.
  • 3
    Nguyen TV, Eisman JA, Kelly PJ, Sambrook PN. Risk factors for osteoporotic fractures in elderly men. Am J Epidemiol. 1996; 144(3): 25563.
  • 4
    U.S. Department of Health and Human Services. Bone Health and Osteoporosis: A Report of the Surgeon General. Rockville, MD: U.S. Department of Health and Human Services, Office of the Surgeon General, 2004.
  • 5
    Ray NF, Chan JK, Thamer M, Melton LJI. Medical expenditures for the treatment of osteoporotic fractures in the United States in 1995: report from the National Osteoporosis Foundation. J Bone Miner Res. 1997; 12: 2435.
  • 6
    Gold DT. The nonskeletal consequences of osteoporotic fractures. Psychologic and social outcomes. Rheum Dis Clin North Am. 2001; 27: 25562.
  • 7
    Adachi JD, Ioannidis G, Pickard L, Berger C, Prior JC, Joseph L, et al. The association between osteoporotic fractures and health-related quality of life as measured by the Health Utilities Index in the Canadian Multicentre Osteoporosis Study (CaMos). Osteoporos Int. 2003; 14: 895904.
  • 8
    Lips P, van Schoor NM. Quality of life in patients with osteoporosis. Osteoporos Int. 2005; 16: 44755.
  • 9
    Tosteson ANA, Hammond CS. Quality-of-life assessment in osteoporosis. Pharmacoeconomics. 2002; 20: 289303.
  • 10
    Burge R, Dawson-Hughes B, Solomon DH, Wong JB, King A, Tosteson A. Incidence and economic burden of osteoporosis-related fractures in the United States, 2005-2025. J Bone Miner Res. 2007; 22: 46575.
  • 11
    Hans PDD, Downs RW, Duboeuf F, Greenspan S, Jankowski L, Kiebzak GM, Petak SM. Skeletal sites for osteoporosis diagnosis: The 2005 ISCD Official Positions. J Clin Densitom. 2006; 9: 1521.
  • 12
    WHO Study Group. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. WHO technical report series. 1994; 843: 1129.
  • 13
    Liberman UA, Weiss SR, Broll J, Minne HW, Quan H, Bell NH, Rodriguez-Portales J, Downs RW, Dequaker J, Favus M. Effect of oral alendronate on bone mineral density and the incidence of fractures in postmenopausal osteoporosis. The Alendronate Phase III Osteoporosis Treatment Study Group. N Engl J Med. 1995; 333(22): 143743.
  • 14
    Harris ST, Watts NB, Genant HK, McKeever CD, Hangartner T, Keller M, Chesnut CH, Brown J, Eriksen EF, Hoseyni MS, Axelrod DW, Miller PD. Effects of risedronate treatment on vertebral and nonvertebral fractures in women with postmenopausal osteoporosis. JAMA. 1999; 282: 134452.
  • 15
    Neer RM, Arnaud CD, Zanchetta JR, Prince R, Gaich GA, Reginster JY, Hodsman AB, Eriksen EF, Ish-Shalom S, Genant HK, Wang O, Mitlak BH. Effect of parathyroid hormone (1-34) on fractures and bone mineral density in postmenopausal women with osteoporosis. N Engl J Med. 2001; 344(19): 143441.
  • 16
    Ettinger B, Black DM, Mitlak BH, Knickerbocker RK, Nickelsen T, Genant HK, Christiansen C, Delmas PD, Zanchetta JR, Stakkestad J, Gluer CC, Krueger K, Cohen FJ, Eckert S, Ensrud KE, Avioli LV, Lips P, Cummings SR. Reduction of vertebral fracture risk in postmenopausal women with osteoporosis treated with raloxifene. JAMA. 1999; 282: 63745.
  • 17
    Black DM, Delmas PD, Eastell R, Reid IR, Boonen S, Cauley JA, Cosman F, Lakatos P, Leung PC, Man Z, Mautalen C, Mesenbrink P, Hu H, Caminis J, Tong K, Rosario-Jansen T, Krasnow J, Hue TF, Sellmeyer D, Eriksen EF, Cummings SR. Once-yearly zoledronic acid for treatment of postmenopausal osteoporosis. N Engl J Med. 2007; 356: 180922.
  • 18
    Gordon CL, Webber CE, Nicholson PS. Relation between image-based assessment of distal radius trabecular structure and compressive strength. Can Assoc Radiol J. 1998; 49(6): 3907.
  • 19
    Siffert RS, Luo GM, Cowin SC, Kaufman JJ. Dynamic relationships of trabecular bone density, architecture, and strength in a computational model of osteopenia. Bone. 1996; 18(2): 197206.
  • 20
    Schuit SCE, van der Klift M, Weel AEAM, de Laet CEDH, Burger H, Seeman E, Hofman A, Uitterlinden AG, van Leeuwen JP, Pols HA. Fracture incidence and association with bone mineral density in elderly men and women: the Rotterdam study. Bone. 2004; 34: 195202.
  • 21
    Siris ES, Chen YT, Abbott TA, Barrett-Connor E, Miller PD, Wehren LE, Berger ML. Bone mineral density thresholds for pharmacological intervention to prevent fractures. Arch Intern Med. 2004; 164: 110812.
  • 22
    Stone KL, Seeley DG, Lui LY, Cauley JA, Ensrud KE, Browner W, Nevitt MC, Cummings SR. BMD at multiple sites and risk of fracture of multiple types: Long-term results from the study of osteoporotic fractures. J Bone Miner Res. 2003; 18: 194754.
  • 23
    Parfitt AM. Bone remodeling: Relationship to the amount and structure of bone, and the pathogenesis and prevention of fractures. In: Riggs BL, Melton LJ, editors. Osteoporosis: Etiology, Diagnosis, and Management. New York: Raven Press; 1988. p. 4594.
  • 24
    Heaney RP. Pathophysiology of osteoporosis. Endocrinol Metab Clin North Am. 1998; 27: 25565.
  • 25
    Parfitt AM. Osteonal and hemi-osteonal remodeling: The spatial and temporal framework for signal traffic in adult human bone. J Cell Biochem. 1994; 55: 27386.
  • 26
    Parfitt AM. Skeletal heterogeneity and the purposes of bone remodeling: Implications for the understanding of osteoporosis. In: Marcus R, Feldman D, Kelsey J, editors. Osteoporosis. San Diego, CA: Academic Press; 1996. p. 31529.
  • 27
    Rodan GA. Coupling of bone resorption and formation during bone remodeling. In: Marcus R, Feldman D, Kelsey J, editors. Osteoporosis. San Diego, CA: Academic Press; 1996. p. 28999.
  • 28
    Hildebrand T, Laib A, Muller R, Dequeker J, Ruegsegger P. Direct three-dimensional morphometric analysis of human cancellous bone: microstructural data from spine, femur, iliac crest, and calcaneus. J Bone Miner Res. 1999; 14(7): 116774.
  • 29
    Van der Linden JC, Weinans H. Effects of microarchitecture on bone strength. Current Osteoporosis Reports. 2007; 5: 5661.
  • 30
    Kleerekoper M, Villanueva AR, Stanciu J, Rao DS, Parfitt AM. The role of three-dimensional trabecular microstructure in the pathogenesis of vertebral compression fractures. Calcif Tissue Int. 1985; 37(6): 5947.
  • 31
    Moore RJ, Durbridge TC, McNeil PJ, Parkinson IH, Need AG, Vernon-Roberts B. Trabecular spacing in post-menopausal Australian women with and without vertebral fractures. Aust N Z J Med. 1992; 22(3): 26973.
  • 32
    Aaron JE, Shore PA, Shore RC, Beneton M, Kanis JA. Trabecular architecture in women and men of similar bone mass with and without vertebral fracture: II. Three-dimensional histology. Bone. 2000; 27(2): 27782.
  • 33
    Wehrli FW. Structural and functional assessment of trabecular and cortical bone by micro magnetic resonance imaging. J Magn Reson Imaging. 2007; 25(2): 390409.
  • 34
    Krug R, Carballido-Gamio J, Burghardt AJ, Kazakia G, Hyun BH, Jobke B, Banerjee S, Huber M, Link TM, Majumdar S. Assessment of trabecular bone structure comparing magnetic resonance imaging at 3 Tesla with high-resolution peripheral quantitative computed tomography ex vivo and in vivo. Osteoporos Int. 2008; 19(5): 65361.
  • 35
    Wehrli FW, Gomberg BR, Saha PK, Song HK, Hwang SN, Snyder PJ. Digital topological analysis of in vivo magnetic resonance microimages of trabecular bone reveals structural implications of osteoporosis. J Bone Miner Res. 2001; 16(8): 152031.
  • 36
    Wehrli FW, Hwang SN, Ma J, Song HK, Ford JC, Haddad JG. Cancellous bone volume and structure in the forearm: noninvasive assessment with MR microimaging and image processing. Radiology. 1998; 206(2): 34757.
  • 37
    Lam SC, Wald MJ, Rajapakse CS, Liu Y, Saha PK, Wehrli FW. Performance of the MRI-based virtual bone biopsy in the distal radius: Serial reproducibility and reliability of structural and mechanical parameters in women representative of osteoporosis study populations. Bone. 2011; 49(4): 895903.
  • 38
    Krug R, Banerjee S, Han ET, Newitt DC, Link TM, Majumdar S. Feasibility of in vivo structural analysis of high-resolution magnetic resonance images of the proximal femur. Osteoporos Int. 2005; 16(11): 130714.
  • 39
    Feldkamp LA, Goldstein SA, Parfitt AM, Jesion G, Kleerekoper M. The direct examination of three-dimensional bone architecture in vitro by computed tomography. J Bone Miner Res. 1989; 4(1): 311.
  • 40
    Kuhn JL, Goldstein SA, Feldkamp LA, Goulet RW, Jesion G. Evaluation of a microcomputed tomography system to study trabecular bone structure. J Orthop Res. 1990; 8(6): 83342.
  • 41
    Laib A, Beuf O, Issever A, Newitt DC, Majumdar S. Direct measures of trabecular bone architecture from MR images. Adv Exp Med Biol. 2001; 496: 3746.
  • 42
    Gomberg BR, Saha PK, Song HK, Hwang SN, Wehrli FW. Topological analysis of trabecular bone MR images. IEEE Trans Med Imaging. 2000; 19(3): 16674.
  • 43
    Sornay-Rendu E, Boutroy S, Munoz F, Delmas PD. Alterations of cortical and trabecular architecture are associated with fractures in postmenopausal women, partially independent of decreased BMD measured by DXA: the OFELY study. J Bone Miner Res. 2007; 22(3): 42533.
  • 44
    Majumdar S, Genant HK, Grampp S, Newitt DC, Truong VH, Lin JC, Mathur A. Correlation of trabecular bone structure with age, bone mineral density, and osteoporotic status: in vivo studies in the distal radius using high resolution magnetic resonance imaging. J Bone Miner Res. 1997; 12(1): 1118.
  • 45
    Boutry N, Cortet B, Dubois P, Marchandise X, Cotten A. Trabecular bone structure of the calcaneus: preliminary in vivo MR imaging assessment in men with osteoporosis. Radiology. 2003; 227(3): 70817.
  • 46
    Link TM, Majumdar S, Augat P, Lin JC, Newitt D, Lu Y, Lane NE, Genant HK. In vivo high resolution MRI of the calcaneus: differences in trabecular structure in osteoporosis patients. J Bone Miner Res. 1998; 13(7): 117582.
  • 47
    Cortet B, Boutry N, Dubois P, Bourel P, Cotten A, Marchandise X. In vivo comparison between computed tomography and magnetic resonance image analysis of the distal radius in the assessment of osteoporosis. J Clin Densitom. 2000; 3(1): 1526.
  • 48
    Ladinsky GA, Vasilic B, Popescu AM, Wald M, Zemel BS, Snyder PJ, Loh L, Song HK, Saha PK, Wright AC, Wehrli FW. Trabecular structure quantified with the MRI-based virtual bone biopsy in postmenopausal women contributes to vertebral deformity burden independent of areal vertebral BMD. J Bone Miner Res. 2008; 23(1): 6474.
  • 49
    Patel PV, Eckstein F, Carballido-Gamio J, Phan C, Matsuura M, Lochmuller EM, Majumdar S, Link TM. Fuzzy logic structure analysis of trabecular bone of the calcaneus to estimate proximal femur fracture load and discriminate subjects with and without vertebral fractures using high-resolution magnetic resonance imaging at 1.5 T and 3 T. Calcif Tissue Int. 2007; 81(4): 294304.
  • 50
    Majumdar S, Link TM, Augat P, Lin JC, Newitt D, Lane NE, Genant HK. Trabecular bone architecture in the distal radius using magnetic resonance imaging in subjects with fractures of the proximal femur. Magnetic Resonance Science Center and Osteoporosis and Arthritis Research Group. Osteoporos Int. 1999; 10(3): 2319.
  • 51
    Techawiboonwong A, Song HK, Magland JF, Saha PK, Wehrli FW. Implications of pulse sequence in structural imaging of trabecular bone. J Magn Reson Imaging. 2005; 22(5): 64755.
  • 52
    Magland JF, Wald MJ, Wehrli FW. Spin-echo micro-MRI of trabecular bone using improved 3D fast large-angle spin-echo (FLASE). Magn Reson Med. 2009; 61(5): 111421.
  • 53
    Song HK, Wehrli FW. In vivo micro-imaging using alternating navigator echoes with applications to cancellous bone structural analysis. Magn Reson Med. 1999; 41(5): 94753.
  • 54
    Hwang S, Wehrli F. Estimating voxel volume fractions of trabecular bone on the basis of magnetic resonance images acquired in vivo. Int J Imaging Syst Technol. 1999; 10: 18698.
  • 55
    Saha PK, Wehrli FW. Measurement of trabecular bone thickness in the limited resolution regime of in vivo MRI by fuzzy distance transform. IEEE Trans Med Imaging. 2004; 23(1): 5362.
  • 56
    Hwang SN, Wehrli FW. Subvoxel processing: a method for reducing partial volume blurring with application to in vivo MR images of trabecular bone. Magn Reson Med. 2002; 47(5): 94857.
  • 57
    Gomberg BR, Saha PK, Song HK, Hwang SN, Wehrli FW. Three-dimensional digital topolgical analysis of trabecular bone. Adv Exp Med Biol. 2001; 496: 5765.
  • 58
    Gomberg BR, Wehrli FW, Vasilic B, Weening RH, Saha PK, Song HK, Wright AC. Reproducibility and error sources of micro-MRI-based trabecular bone structural parameters of the distal radius and tibia. Bone. 2004; 35(1): 26676.
  • 59
    Parfitt AM. Implications of architecture for the pathogenesis and prevention of vertebral fracture. Bone. 1992; 13( Suppl 2): S417.
  • 60
    Duan Y, Turner CH, Kim BT, Seeman E. Sexual dimorphism in vertebral fragility is more the result of gender differences in age-related bone gain than bone loss. J Bone Miner Res. 2001; 16(12): 226775.
  • 61
    Aaron JE, Makins NB, Sagreiya K. The microanatomy of trabecular bone loss in normal aging men and women. Clin Orthop Relat Res. 1987; 215: 26071.
  • 62
    Benito M, Gomberg B, Wehrli FW, Weening RH, Zemel B, Wright AC, Song HK, Cucchiara A, Snyder PJ. Deterioration of trabecular architecture in hypogonadal men. J Clin Endocrinol Metab. 2003; 88(4): 1497502.
  • 63
    Wehrli FW, Leonard MB, Saha PK, Gomberg BR. Quantitative high-resolution magnetic resonance imaging reveals structural implications of renal osteodystrophy on trabecular and cortical bone. J Magn Reson Imaging. 2004; 20(1): 839.