DocumentCode :
51617
Title :
A Robust Algorithm for Thickness Computation at Low Resolution and Its Application to In Vivo Trabecular Bone CT Imaging
Author :
Yinxiao Liu ; Dakai Jin ; Cheng Li ; Janz, Kathleen F. ; Burns, Trudy L. ; Torner, James C. ; Levy, Steven M. ; Saha, Prabir K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
Volume :
61
Issue :
7
fYear :
2014
fDate :
Jul-14
Firstpage :
2057
Lastpage :
2069
Abstract :
Adult bone diseases, especially osteoporosis, lead to increased risk of fracture which in turn is associated with substantial morbidity, mortality, and financial costs. Clinically, osteoporosis is defined by low bone mineral density; however, increasing evidence suggests that the microarchitectural quality of trabecular bone (TB) is an important determinant of bone strength and fracture risk. Accurate measures of TB thickness and marrow spacing is of significant interest for early diagnosis of osteoporosis or treatment effects. Here, we present a new robust algorithm for computing TB thickness and marrow spacing at a low resolution achievable in vivo. The method uses a star-line tracing technique that effectively deals with partial voluming effects of in vivo imaging with voxel size comparable to TB thickness. Also, the method avoids the problem of digitization associated with conventional algorithms based on sampling distance transform along skeletons. Accuracy of the method was examined using computer-generated phantom images, while the robustness of the method was evaluated on human ankle specimens in terms of stability across a wide range of voxel sizes, repeat scan reproducibility under in vivo conditions, and correlation between thickness values computed at ex vivo and in vivo imaging resolutions. Also, the sensitivity of the method was examined by evaluating its ability to predict the bone strength of cadaveric specimens. Finally, the method was evaluated in a human study involving 40 healthy young-adult volunteers (age: 19-21 years; 20 males and 20 females) and ten athletes (age: 19- 21 years; six males and four females). Across a wide range of voxel sizes, the new method is significantly more accurate and robust as compared to conventional methods. Both TB thickness and marrow spacing measures computed using the new method demonstrated strong associations (R2 ∈ [0.83, 0.87]) with bone strength. Also, the TB thickness and marrow spacing m- asures allowed discrimination between male and female volunteers (p ∈ [0.01, 0.04]) as well as between athletes and nonathletes (p ∈ [0.005, 0.03]).
Keywords :
biomechanics; bone; computerised tomography; diseases; fracture toughness; image resolution; image sampling; medical image processing; phantoms; sensitivity; transforms; TB thickness; adult bone diseases; age 19 yr to 21 yr; athletes; bone strength; cadaveric specimens; computer-generated phantom images; diagnosis; ex vivo imaging resolutions; fracture risk; human ankle specimens; in vivo imaging resolutions; in vivo trabecular bone computerised tomography imaging; low bone mineral density; low resolution robust thickness computation algorithm; marrow spacing; microarchitectural quality; mortality; osteoporosis; sampling distance transform; sensitivity; skeletons; star-line tracing technique; substantial morbidity; treatment effects; voxel size; Bones; Computed tomography; Image resolution; In vivo; Robustness; Thickness measurement; Bone biomechanics; marrow spacing; multirow detector computed tomography (CT); star-line tracing; trabecular bone (TB) thickness;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2014.2313564
Filename :
6778077
Link To Document :
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