Cardiac magnetic resonance (CMR) imaging is the gold standard imaging technique for assessment of ventricular dimensions and function. CMR also allows assessment of ventricular deformation but this requires additional imaging sequences and time consuming post processing which has limited its widespread use. A novel CMR analysis software package, ‘feature tracking’ (Tom Tec, Germany) can measure ventricular deformation directly from cine CMR images. This thesis seeks to further our understanding of the feasibility of feature tracking to assess myocardial deformation and volumetric measures. Chapter 3 validates normal ranges for deformation parameters and compares values against traditional tagging measures. The work identifies global circumferential strain measures as being the most reproducible. In chapters 4 and 5, feature tracking values for left and right ventricular strain are compared with echocardiography derived speckle tracking indices of deformation. For left ventricular (LV) parameters, circumferential and longitudinal strain are most consistent and for the right ventricular (RV) measures, assessment of free wall strain using feature tracking shows promise and with modifications in algorithms is likely to further improve in the future. Chapter 6 assesses the ability of feature tracking to measure diastolic function. The results show that radial diastolic velocities and longitudinal diastolic strain rates can predict diastolic dysfunction (as diagnosed by echocardiography) with acceptable levels of sensitivity and specificity, particularly when used in combination. 11 The use of feature tracking to provide automated measures of ventricular volumes, mass and ejection fraction is assessed in chapter 7. Feature tracking in this context shows acceptable correlation but poor absolute agreement with manual contouring and further adjustments to algorithms is necessary to improve its accuracy. This work offers insights into the use of feature tracking for the assessment of ventricular deformation parameters. It is a technique with advantages over CMR tagging methods and given the speed of post processing has the potential to become the CMR preferred assessment for strain quantification in the future.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:655184 |
| Date | January 2014 |
| Creators | Augustine, Daniel |
| Publisher | Queen Mary, University of London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://qmro.qmul.ac.uk/xmlui/handle/123456789/7872 |
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