Quantitative Assessment of Bone Quality using Image Guided Failure Analysis

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Abstract

Bone quality influences bone strength with important consequences for osteoporosis, fracture risk and dental implant success. Whilst imaging that is capable of capturing bone structure in 3D is becoming more common, quantitative clinical measures of bone quality rely on bone quantity, not structure. If bone quality could be more accurately measured, and the influence of bone architecture better understood, strength may be better predicted.This thesis presents methods for making structural comparisons between successive micro-CT images of loaded bone and explores the limitations of these. I present a novel method to detect where damage occurs in loaded rat vertebrae based on multiscale rigid registration and difference measures. Together these methods represent a quantitative approach to image guided failure analysis.Time-lapsed micro-CT images of 14 successively loaded rat vertebrae were acquired and damaged regions found using these. Using a random forest classifier I tested whether the damaged regions could be predicted by several commonly used structural measures (bone area and volume), three-dimensional texture measures (co-occurrence matrices and fractal dimension) and a more novel type of architectural measure (based on the structure tensor). A combination of parameters was able to predict damage regions with specificities in the range 70-90% and sensitivities of 60-70%.Using ovariectomised rats as a model of osteoporosis I have performed a pilot experiment to investigate how changes in bone quality might effect our results. The wider applicability of my methods are demonstrated by applying them to dental cone beam images of healthy and osteoporotic patients.

Layman's Abstract

The inside of bones are a complex latticework that makes the bone strong and light. Osteoporosis reduces not only the amount of bone but also the shape of this structure. Currently the diagnosis of osteoporosis relies only on the reduction in the amount of bone and ignores the changes in this structure. In laboratory studies, researchers measure features of this structure such as surface area, thickness and shape.Many studies have looked at the relationship between bone structure and osteoporosis but we want to look at the relationship between bone structure and strength so that clinicians will eventually be able to predict a bone's strength from its radiographic image. This may help predict osteoporosis or increase the success of dental implants.To do this we have taken images of rat vertebrae under compression using micro-CT, a method which allows us to see the bone structure in detail. Using rat vertebrae allows us to examine bone structure in more detail than is possible in humans or living animals and gives us the ability to test the strength of the bone under controlled conditions. This allows us to determine which architectural features on an image makes a bone weak and prone to fracture.We present a novel computer based method to detect where in these bones the damage occurs. We have performed experiments to determine whether various measurements of the structure are able to predict where this damage occurs. We were able to predict 60-70% of damaged, and 70-90% of undamaged, locations correctly.We performed further experiments using ovariectomised rats to simulate osteoporosis to determine how these methods might apply to osteoporotic bone. We have also applied our methods to dental-CBCT images, an advanced imaging method that enables dentists to see the structure of bone in the jaw.

Keyword(s)

Bone Quality; Image Guided Failure Analysis; Micro-CT; Osteoporosis; Trabecular Architecture Measures

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