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.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Research Project (R01)
Project #
5R01AR054439-04
Application #
8265330
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Lester, Gayle E
Project Start
2009-06-18
Project End
2014-05-31
Budget Start
2012-06-01
Budget End
2014-05-31
Support Year
4
Fiscal Year
2012
Total Cost
$309,876
Indirect Cost
$96,228
Name
University of Iowa
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52242
Saha, Punam K; Basu, Subhadip; Hoffman, Eric A (2016) Multiscale Opening of Conjoined Fuzzy Objects: Theory and Applications. IEEE Trans Fuzzy Syst 24:1121-1133
Chen, Cheng; Jin, Dakai; Liu, Yinxiao et al. (2016) Trabecular bone characterization on the continuum of plates and rods using in vivo MR imaging and volumetric topological analysis. Phys Med Biol 61:N478-N496
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
Li, Cheng; Jin, Dakai; Chen, Cheng et al. (2015) Automated cortical bone segmentation for multirow-detector CT imaging with validation and application to human studies. Med Phys 42:4553-65
Saha, Punam K; Liu, Yinxiao; Chen, Cheng et al. (2015) Characterization of trabecular bone plate-rod microarchitecture using multirow detector CT and the tensor scale: Algorithms, validation, and applications to pilot human studies. Med Phys 42:5410-25
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
Li, Cheng; Jin, Dakai; Burns, Trudy L et al. (2013) A New Algorithm for Cortical Bone Segmentation with Its Validation and Applications to In Vivo Imaging. Proc Int Conf Image Anal Process 8157:349-358
Liu, Yinxiao; Jin, Dakai; Saha, Punam K (2013) A NEW ALGORITHM FOR TRABECULAR BONE THICKNESS COMPUTATION AT LOW RESOLUTION ACHIEVED UNDER IN VIVO CONDITION. Proc IEEE Int Symp Biomed Imaging 2013:390-393
Jin, Dakai; Liu, Yinxiao; Saha, Punam K (2013) Application of fuzzy skeletonization ot quantitatively assess trabecular bone micro-architecture. Conf Proc IEEE Eng Med Biol Soc 2013:3682-5

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