Noninvasive assessment of human jawbone using ultrasonic guided waves.
The problem of detecting defects in jawbones is an important problem. Existing methods based on Xrays are invasive and constrain the achievable image quality. They also may carry known risks of cancer generation or may be limited in accurate diagnosis scope. This work is motivated by the lack of current imaging modalities to accurately predict the mechanical properties and defects in jawbone. Ultrasonic guided waves are sensitive to changes in microstructural properties and thus have been widely used for noninvasive material characterization. Using these waves may provide means for early diagnosis of marrow ischemic disorders via detecting focal osteoporotic marrow defect, chronic nonsuppurative osteomyelitis, and cavitations in the mandible (jawbone). Guided waves propagating along the mandibles may exhibit dispersion behavior that depends on material properties, geometry, and embedded cavities. In this work, we present the first study in the theoretical and experimental analysis of guided wave propagation in jawbone. Semianalytical, finite-element (SAFE) method is used to analyze dispersion behavior of guided waves propagating in human mandibles. The geometry of the cross section is obtained by segmenting the computed tomography (CT) images of the jawbone. The cross section of the mandible is divided in two regions representing the cortical and trabecular bones. Each region is modeled as a linear Hookean material. The material properties for both regions are adopted from the literature. The experimental setup for the guided waves experiment is described. The results from both numerical analysis and guided waves experiment exhibit variations in the group velocity of the first arrival signal and in the dispersion behavior of healthy and defected mandibles. These results shall provide a means to noninvasively characterize the jawbone and accurately assess the bone mechanical properties. Our study is not aimed at characterizing the bone density in human mandibles. Rather, it is aimed to assess bone mechanical properties and defects that cannot be diagnosed by X-ray or other imaging modalities. This work may pave the way to the development of inexpensive noninvasive devices to detect small defects in human mandibles.
Mahmoud
Ahmed
A
West Virginia University, Morgantown, WV 26506, USA.
Cortes
Daniel
D
Abaza
Ayman
A
Ammar
Hany
H
Hazey
Mike
M
Ngan
Peter
P
Crout
Richard
R
Mukdadi
Osama
O
D000465:Algorithms; D003198:Computer Simulation; D003720:Densitometry / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007568:Jaw / Q000000981:diagnostic imaging*; D007571:Jaw Diseases / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D008954:Models, Biological; D012542:Scattering, Radiation; D014463:Ultrasonography / Q000379:methods*