Trabecular bone (TB) is a complex quasi-random network of interconnected struts and plates. TB constantly remodels to adapt dynamically to the stresses to which it is subjected (Wolff's Law). In osteoporosis, this dynamic equilibrium between bone formation and resorption is perturbed, leading to bone loss and structural deterioration, both increasing fracture risk. Most osteoporotic fractures occur at sites rich in TB (vertebrae, radius, proximal femur). Bone's mechanical competence can only be partly explained by variations in bone mineral density (BMD), which led to the notion of bone quality, chief among which is architecture as a determinant of TB strength. Recent advances in CT and MRI now allow imaging of TB in vivo. However, the limited SNR precludes voxel sizes much smaller than TB thickness (100-150?m), therefore resulting in images that are inherently fuzzy. Therefore, most conventional histomorphometric approaches to TB structure assessment are not applicable to in vivo resolution regime. This proposal introduces a new morphometric index called tensor scale (t-scale) to measure quality of TB micro architecture via in vivo imaging and designs experimental plans to evaluate reproducibility and sensitivity of t-scale-based TB architectural measures. Also, we will examine their strengths to detect TB architectural changes in response to disease or treatment progression. The fundamental principle of t-scale is to fit an ellipsoid to a local structure. The unique property of t-scale is that the ellipsoid's shape, orientation and size simultaneously determine the topology (plates vs rods), orientation and scale of trabeculae. Our major goals in this project are - (1) to develop the methodology for computing t-scale-based architectural measures from TB images, (2) to evaluate the sensitivity and reproducibility of t-scale-based measures, (3) to examine t-scale measures'ability to predict experimental biomechanical parameters of TB specimens and (4) to examine the sensitivity of t-scale measures to detect the effects of osteoporotic TB loss and antiresorptive treatment via in vivo MRI. The proposed method will (1) obviate the need for binarization, (2) characterize topology, orientation and scale without the need for skeletonization and (3) detect early TB architectural changes in response to treatment or disease progression. The central hypothesis is that the new parameters are more sensitive to detecting remodeling effects and more reproducible than conventional measures. Sensitivity and reproducibility of the new method will be evaluated using synthetic TB networks, micro-CT and ex vivo MR imaging of TB cores from cadaveric distal radii along with experimental biomechanical data, MR images of intact specimens and of human subjects, and finally, patient data from clinical studies previously funded by the NIH. Our objective is to apply t-scale based analysis methods to longitudinal and cross-sectional imaging studies for assessing bone quality.

Public Health Relevance

PROJECTIVE NARATIVE This project will develop an advanced technology for trabecular bone (TB) quality assessment via in vivo imaging which will enable early detection of TB micro-architectural changes in response to treatment or bone disease including osteoporosis. Osteoporosis is a major public health threat and in the U.S. only, 10 million individuals (eight million are women and two million are men) are estimated to already have the disease and almost 34 million more are estimated to have low bone mass, placing them at increased risk for osteoporosis. The technology proposed in the project will be helpful to diagnose patients at early stage of the disease and routinely monitor their disease status or effects of therapeutic treatments.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Research Project (R01)
Project #
Application #
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Lester, Gayle E
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Iowa
Schools of Medicine
Iowa City
United States
Zip Code
Zhang, Ning; Magland, Jeremy F; Song, Hee Kwon et al. (2015) Registration-based autofocusing technique for automatic correction of motion artifacts in time-series studies of high-resolution bone MRI. J Magn Reson Imaging 41:954-63
Liu, Yinxiao; Jin, Dakai; Li, Cheng et al. (2014) A robust algorithm for thickness computation at low resolution and its application to in vivo trabecular bone CT imaging. IEEE Trans Biomed Eng 61:2057-69
Zhang, Ning; Magland, Jeremy F; Rajapakse, Chamith S et al. (2013) Assessment of trabecular bone yield and post-yield behavior from high-resolution MRI-based nonlinear finite element analysis at the distal radius of premenopausal and postmenopausal women susceptible to osteoporosis. Acad Radiol 20:1584-91
Liu, Yinxiao; Liang, Guoyuan; Saha, Punam K (2012) A new multi-object image thresholding method based on correlation between object class uncertainty and intensity gradient. Med Phys 39:514-32
Xu, Ziyue; Sonka, Milan; Saha, Punam K (2011) Improved tensor scale computation with application to medical image interpolation. Comput Med Imaging Graph 35:64-80
Lam, Shing Chun Benny; Wald, Michael J; Rajapakse, Chamith S et al. (2011) 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 49:895-903
Saha, Punam K; Xu, Yan; Duan, Hong et al. (2010) Volumetric topological analysis: a novel approach for trabecular bone classification on the continuum between plates and rods. IEEE Trans Med Imaging 29:1821-38