Bone Diagnostics

Structural Dynamics Analysis for the early Detection of Bone Loss

Trabecular bone tissue changes significantly during the aging process from a strong interconnected

network to a weak structure. While bone density scanners can accurately determine bone mass, they

are not able to explain more than 30% of the variation in mechanical properties. Structural

dynamics represents a direct and physical measurement of the biomechanical properties of bone.

Osteoporosis afflicts about 200 million people worldwide; and osteoporotic fractures are in the millions annually in the US alone and cost tens of billions of dollars. Characterization of bone quality in osteoporotic patients is important with respect to monitoring treatment efficacy, though currently quite limited. While some technical hurdles in developing a noninvasive diagnostic tool using low frequency vibration have been overcome, changes in the frequency response signal of bone have not been investigated at the various bone organizational levels. Our principal hypothesis is that the vibrational modes of bone tissue change significantly with the deterioration of bone micro-architecture and that these modes can be captured by noninvasive sensors.

Structural Dynamics can Detect Fractures Earlier than X-Ray

Bone integrity testing on the spinous process can reveal tissue damage within the anterior

vertebral body. We developed a technique that utilizes low-frequency vibration to detect

loss of bone integrity. When compared to the gold standard, our technique outperformed

the traditional X-Ray technique in every single case.

The diagnostic tools for clinicians to detect vertebral body fractures are limited to radiation technologies1, such as Xray and CT. The objective is to identify shape changes that reflect bone tissue failure. Because this method is subjective, only crude changes of 15% and more in vertebral height can be detected2. From in-vitro laboratory experiments it is know that the ultimate load is reached at deformations much less than 5%, and is generally detected before any shape changes are visible in radiographic images3. Acoustic vibration is a promising technique to detect changes in material integrity and quality. The overall goal of this study was to investigate the use of acoustic vibration to detect spinal fractures.

In all twelve samples, changes in the tissue dynamic response were more sensitive than the load cell reading (gold standard). Both, the load cell reading and the dynamic tissue response were more sensitive than the Xray technique taken at each load increment. In this study, acoustic vibration indicated bony fractures earlier than the load cell or the X-rays. Clearly, further studies are needed to quantify damage severity with changes in dynamic signal before any diagnostic can be made.

Fundamental Changes in Stress  Backbone of Trabecular Tissue

The more bone mass is lost during the aging process, the less efficient a bone network

becomes in bearing mechanical load. Mirco-fractures and micro-cracks prevent

an even load transfer across these regions, resulting in a reduced number of

stress backbones that allow load transfer along the loading axis.

Aging induces several types of architectural changes in trabecular bone including thinning, increased levels of anisotropy, and perforation. It has been determined, on the basis of analysis of mathematical models, that reduction in fracture load caused by perforation is significantly higher than those due to equivalent levels of thinning or anisotropy. The analysis has also provided an expression which relates the fractional reduction of strength t to the fraction of elements n that have been removed from a network. Further, it was proposed that the ratio G of the elastic constant of a sample and its linear response at resonance can be used as a surrogate for t. Experimental validation of these predictions requires following architectural changes in a given sample of trabecular bone; techniques to study such changes using microcomputed tomography are only beginning to be available. In the present study, we use anatomically accurate computer models constructed from digitized images of bone samples for the purpose. Images of healthy bone are subjected to successive levels of synthetic degradation via surface erosion. Computer models constructed from these images are used to calculate their fracture load and other mechanical properties. Results from these computations are shown to be consistent with predictions derived from the analysis of mathematical models. Although the form of t(n) is known, parameters in the expression are expected to be sample-specific, and hence n is not a reliable predictor of strength. We provide an example to demonstrate this. In contrast, analysis of model networks shows that the linear part of t(G) depends only on the structure of trabecular bone. Computations on models constructed from samples of iliac crest trabecular bone are shown to be in agreement with this assertion. Since G can be computed from a vibrational assessment of bone, we argue that the latter can be used to introduce new surrogates for bone strength and hence diagnostic tools for osteoporosis.

Kinematic Analysis of the Temporomandibular Joint

Despite the differences in size and shape of mandibles and head size of our population, there seems

to be common motion pattern within the healthy temporomandibular joint. The motion indicates a

mostly progressive rotation during mouth opening with an additional translation of the condyle with

respect to the fossa at the later stage (>75% of mouth opening). While the rotational pattern

does not deviate much between health and ADD patients, the translational component does.

The objectives of the current study were to develop an algorithm for the separation of complex mandibular motion into translational and rotational motion and to use this algorithm in a study to determine motion characteristics of subjects without diagnosed pathology of the temporomandibular joint. The motion of the mandible was measured using an optical tracking system which recorded the motion of reflective marker spheres connected to mouthpieces worn by ten subjects. The data was analyzed using an algorithm which separated translational motion from rotational motion. A normal mandibular motion pathway was obtained. The mean opening angle for the population was 23.53¬ƒ (SD = 2.86¬ƒ). The mean translational value was measured at 1.24cm (SD = 0.13 cm). A combination of rotational opening with translation occurred only after about 80% of the opening was exceeded. The resulting motion patterns showed primarily rotational motion in the first phase of opening, a combination of translation and rotation in the next phase. From the results, it is believed that rotational motion is the primary mode of the joint, with translation serving to extend the range of opening. Additionally, a trend of late translational opening amongst the population implies that a normal pattern of opening exists for joint motion in the temporomandibular joint. Jaw motion was consistent between subjects tested, which allows for standardization of the normal joint path.

Body Area Network for Intra-Skeletal Communication

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