Experimental and analytical tools for rapid development of digital imaging-based elasto-tomography technology
| dc.contributor.author | Ismail, Hina Muhammad | |
| dc.date.accessioned | 2018-06-01T02:04:22Z | |
| dc.date.available | 2018-06-01T02:04:22Z | |
| dc.date.issued | 2018 | en |
| dc.description.abstract | Breast cancer is the second most common cancer in the world and has the highest cancer mortality rate in women. Presently, 1 of every 4 women carry an increased risk of breast cancer, of which, 6% are below the minimum screening age of 45. Early detection via regular screening not only reduces mortality rates, but also decreases overall treatment expenditure. X-ray mammography is the clinical standard breast cancer screening technique. However, due to significant limitations, such as unacceptable rates of false positive and false negative results, exposure to ionizing radiation, and discomfort and pain due to the compression of the breast it is not recommended for women under 45 years of age. These women also often have denser breast tissues, which further reduce mammography efficacy and diagnostic capability. Digital imaged elasto-tomography (DIET) has been developed to overcome some of the limitations of current techniques and mammography in particular. The digital imaged elasto-tomography (DIET) concept is based on non-invasive, pain-free, vibration based analysis of local tissue stiffness, a form of elastographic reconstruction from actuation motion. This technique enables early detection of breast cancer, as it is not restricted in the ages of women who could utilize it for screening. Thus, combined with effective treatment, it could reduce mortality, particularly for younger women. More specifically, recent analysis showing annual mammography down to 40 years of age would save many more lives than current screening, indicating a system like DIET, safely offering screening to any age, could significantly improve breast cancer mortality. DIET is a novel method and technology, but is not yet at a stage suitable for a large randomised clinical trial. However, its development could be significantly enhanced by a series of tools to improve the speed and repeatability of DIET technology development. Currently, DIET is developed primary by executing pilot clinical testing of human volunteers. This experimental approach is slow, not repeatable as technology progresses and thus not necessarily optima, as well as placing a burden on diagnosed volunteer patients. In particular, repeating trials is not possible, limiting the ability to accurately assess technological changes. The productivity of DIET technology development could thus be enhanced in three main areas: a) development of realistic and accurate tissue mimicking breast phantoms; b) validation of the surface measurement algorithms to quantify their error and thus to quantify the limits of diagnostic algorithms; and c) development of finite element models to accurately mimic breast phantoms to avoid repeated phantom experiments. The first would allow repeatable phantom trials in lieu of relying on volunteers. The second would enable more accurate assessment of errors and their impact on surface motion diagnostics. Equally, it would also allow assessment of whether improvements in sensing or actuation would make a clinical differences. The final, third element would further improve productivity by replacing phantom tests with models to generate “data”. The overall outcome is significantly enhanced development pathways. In this thesis, mechanical properties of three different materials; agar, gelatine, and silicone used to emulate the mechanical behavior of real breast tissue are measured to assess their suitability for use in phantoms in systems assessing tissue mechanics for diagnostics. The stiffness ratio of adipose to tumor between the phantom materials and real human tissues were compared. Hyperelastic parameters of Neo-Hookean, Mooney Rivil, and Ogden models were obtained for the selected silicone material due to its appropriate mechanical properties, reliability, and repeatability. Finally, silicone based three homogenous phantoms of selected material were fabricated with different sizes of tumor. Finite element models of breast shaped phantoms were developed using ABAQUS software. The geometry of the model was constructed with the same dimensions from fabricated phantoms. The mechanical properties were modeled by using the Neo-Hookean hyperelastic material model. Results showed good to strong correlation ranging from 0.7 to 1.0 in all cases with over 90% having a value over 0.9.Overall, the comparison of the DIET experimental data and the FE model data showed good agreement. A single point laser Doppler vibrometer was used to validate the optical flow motion measuring algorithm used in DIET experimental data. Results show excellent validation with errors less than 6 % for healthy phantom, and errors less than 8 % for 10 mm and 20 mm inclusions. Overall results show the optical flow algorithm is validated with relatively small errors compared to a gold-standard, non-contact laser measurement. Finally, because of the validation effectiveness and accuracy of finite element modeling compared to DIET experimental data. Six new phantoms were modeled with different tumor positions. This analysis assess the impact of tumor position on diagnosis of breast cancer using surface motions and basic elastography assumptions, which should further impact and encourage the development of DIET. Overall, all 3 goals are accomplished. The results of this thesis provide means to dramatically speed up development of the DIET system. More generally, they provide significant results to enable elastographic technology development. | en |
| dc.identifier.uri | http://hdl.handle.net/10092/15489 | |
| dc.identifier.uri | http://dx.doi.org/10.26021/1737 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.publisher | University of Canterbury | en |
| dc.rights | All Right Reserved | en |
| dc.rights.uri | https://canterbury.libguides.com/rights/theses | en |
| dc.title | Experimental and analytical tools for rapid development of digital imaging-based elasto-tomography technology | en |
| dc.type | Theses / Dissertations | en |
| thesis.degree.discipline | Mechanical Engineering | |
| thesis.degree.grantor | University of Canterbury | en |
| thesis.degree.level | Doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
| uc.bibnumber | 2658889 | |
| uc.college | Faculty of Engineering | en |