Decoding DENSE Heart Displacements

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dc.contributor.advisor Nash, Martyn
dc.contributor.advisor Wang, Vicky Harpur, George 2021-08-18T01:07:54Z 2021-08-18T01:07:54Z 2020 en
dc.description Full Text is available to authenticated members of The University of Auckland only. en
dc.description.abstract Heart failure (HF) is the leading cause of mortality in the western world. There is an urgent need for more personalised and improved diagnosis, prognosis, and clinical management of heart disease. Current diagnosis techniques of HF are limited in terms of their accuracy and the specificity of the information they provide. Research has shown the importance of regional myocardial function measures such as strain and torsion in early identification of dysfunction. Recent advances in magnetic resonance imaging (MRI) have seen the development of the Displacement Encoding with Stimulated Echoes (DENSE) technique, allowing high resolution measurements of regional intramyocardial motion by encoding tissue displacements in the images. This has motivated the need for fast and accurate image analysis tools that can estimate strain measures and be implemented in the clinical setting. This thesis presents a novel framework for the estimation of 3D strain fields from cine DENSE images. 3D kinematic free-form deformation (FFD) modelling methods were used to generate full 3D cylindrical strain fields for a mid-ventricular ring of myocardial tissue to provide information about regional intramyocardial tissue function. The FFD framework was developed and validated with synthetic cine DENSE images generated using a computational phantom subject to cardiac-like deformations. For this, a new deformation model was presented, expressed in cylindrical polar coordinates, that involved non-zero values for all 6 components of strain. Modelling and imaging recommendations were made through in-depth error analysis. It was found that partial volume effects had the most significant effect, particularly on radial strain estimates. Finally, the application to in vivo cine DENSE images acquired from a cardiac patient was shown. The resulting FFD framework strains showed good agreement with strains derived from the existing 2D image analysis tool, DENSEanalysis. Further investigation is required to improve the accuracy of image acquisition and the FFD framework to ensure the generation of reliable patient-specific models that are ready for use in the clinical environment.
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof Masters Thesis - University of Auckland en
dc.relation.isreferencedby UoA en
dc.rights Restricted Item. Full Text is available to authenticated members of The University of Auckland only. en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
dc.rights.uri en
dc.title Decoding DENSE Heart Displacements
dc.type Thesis en Engineering in Bioengineering The University of Auckland en Masters en 2021-06-15T06:13:02Z
dc.rights.holder Copyright: the author en

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