Multi-object and multi-feature models of thumb anatomy for population based morphological assessment

Farrell, Caitlin

Multi-object and multi-feature models of thumb anatomy for population based morphological assessment

Thesis / Dissertation

2024

Publisher

University of Cape Town

Department

Division of Biomedical Engineering

Faculty

Faculty of Health Sciences

Abstract

The trapeziometacarpal (TMC) joint, formed by the junction of the trapezium and first metacarpal (MC1) bones, is highly susceptible to the onset and progression of osteoarthritis (OA). Although various treatment options exist to ease symptoms and slow the progression of OA, the success of these treatments is heavily reliant on the early diagnosis of the disorder. The primary aim of this research was to develop a methodology for the use of computed tomography (CT) imaging in the characterisation of biomechanical risk factors of OA in the TMC joint using data from OA-affected and control subjects. Features related to shape, pose, and intensity in the CT images of the TMC joints from the subjects were correlated to a range of biomechanical risk factors. Multi-object and multi feature-class statistical models of control and OA-affected datasets were created through the development of 3 pipelines – a registration pipeline, a correspondence pipeline, and a model building pipeline. These models were used to compare the ranges of 5 morphological anatomical measures, namely: the distances between the articular surfaces of the bones; the angle of volar beak protrusion; the angle of trapezial inclination; the surface areas of the articular facets; and the radii of curvature. In line with the respective hypotheses, the distance between the articular surfaces and the angle of volar beak protrusion were seen to decrease in OA-affected data whilst the surface areas of the articular facets were seen to increase. Contrary to their respective hypotheses, the angle of trapezial inclination was seen to decrease in OA-affected data and the radii of curvature of the articular facets showed no significant changes in morphology. This suggests certain anatomical measures may be indicative of the onset and progression of TMC OA and provides a range of values typical of both control subjects and OA-affected subjects. A third model representative of the combined OA-affected and control data was developed and used to determine the correlations between the shape and pose, and the shape and intensity feature classes. This indicated a high correlation between both the shape and intensity and the shape and pose feature classes, thus suggesting a correlation between the respective biomechanical risk factors. In summary, the results of this research suggest that a decreased distance between the articular surfaces, an increased articular surface area, and a decrease in the angle of volar beak protrusion may be indicative of the onset and progression of TMC OA. This research is limited by the relatively small size of the datasets used and thus further research is necessary to determine the variation in the trapezial angle of inclination and the change in concavity of the articular surface of the MC1. Moreover, this research serves as an explanation and demonstration of the developed pipelines in the creation of a DMFC-GPM of the TMC joint which can be applied to larger and more diverse datasets in future research to determine the correlations between the respective feature classes.

Keywords

biomedical engineering

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