The Achilles tendon is the largest tendon in the human body, which elastically stores and releases energy to facilitate walking and running. Tendons can suffer from a range of pathologies, most notably that of complete rupture, which affects athletes, physically active workers and the aged. There is a growing demand for in vivo methods of objectively measuring tendon health for aiding diagnosis, monitoring therapy and for assessment of new treatments. Knowledge of the changes in mechanical properties during the healing process is also limited and new methods to accurately and consistently estimate these could provide insights into the healing process and guide future research efforts. This thesis presents the development and use of 2D ultrasound elastography, a quantitative strain estimation imaging technique, as a tool to measure changes in the tensile mechanical properties of the Achilles tendon. This technique performs frame-to-frame block matching of image texture to track motion in an ultrasound signal sequence and create a strain estimation field from the spatial derivative of the motion. Elastography in the image-lateral direction of sagittal plane scans is of particular interest as this is in line with the longitudinal axis of the tendon, but presents extra accuracy issues from out of plane motion and lower image spatial resolution. Tendon rupture also presents unique problems to image acquisition and analysis- patient pain and safety are important considerations and disruption of the ultrasound texture can make 2D motion tracking more difficult. A new 2D elastography block matching algorithm, named `AutoQual', was developed to enable accurate tracking of motion in the image-lateral direction and reduce the impact of artefacts and errors common with damaged Achilles tendons image sequences. It was shown to outperform a multiscale block matching method when tested using ultrasound sequences from in vivo and gelatine phantom experiments. The input parameters of this algorithm were then optimised using the phantom data for benchmarking. The AutoQual algorithm was then used to analyse ultrasound sequences from a 24-week longitudinal study of 21 subjects with ruptured Achilles tendons to assess lateral, axial and principal strains during controlled passive motion of the foot or axial palpation of the ultrasound probe. Lateral and principal strains from controlled dorsiflexion were shown to be more repeatable and more sensitive to change than axial strains with manual palpation. This experience with lateral strain imaging from ruptured Achilles tendons gave an increased knowledge of the strain imaging artefacts and features that can occur. These are described in detail in order that they may be further mitigated in quantitative analysis by optimising acquisition protocols, further amendment of the block tracking algorithm, or exclusion of erroneous areas when selecting regions of interest. Regularisation is a potential solution to some common artefacts such as discontinuities from poor tracking in shadow regions. Regularisation of the lateral displacement fields is investigated using 2D bicubic smoothing splines. The regularisation parameters used are shown to have minimal effect on quantitative analysis and can aid visual clarity or reduce artefacts within certain settings. However, regularisation was also shown to cause large errors when parameters were set more aggressively. Finally, it is identified that cumulative lateral strain measurement of the Achilles and other tendons is feasible but that future work is needed to further improve the quality of force and cross sectional area measurements in order to infer mechanical properties accurately. Repeatable high force motion protocols also need to be developed to measure healthy tendons and to ensure comparable results between different patients and research groups.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:669715 |
| Date | January 2014 |
| Creators | Brown, Phillip G. M. |
| Contributors | Noble, J. Alison ; Thompson, Mark S. |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:e2d0a97e-d557-4b5a-869a-36cbd33b9994 |
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