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Title: Face shape analysis in people with epilepsy
Author: Chinthapalli, Vamsi Krishna
ISNI:       0000 0004 7230 2745
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Stereophotogrammetry and dense surface modelling are novel techniques that have been used to study face shape in genetic and neurodevelopmental disorders. In people with epilepsy, it has been recognised that the condition may be associated with underlying structural variants or malformations of cortical development in some cases. Here I recruited 869 people with epilepsy or unaffected relatives and control subjects to study face shape. I sought to explore whether face shape and symmetry, using new metrics for each, could help to predict those people with epilepsy who may have potential underlying genetic or structural causes. My reproducibility studies found that stereophotogrammetry and dense surface modelling were susceptible to error from changes in head position or face expression, but not from camera calibration, image acquisition and image landmarking. The next study found that in people with epilepsy, a measurement of atypical face shape, Face Shape Difference (FSD), was significantly increased in those with pathogenic structural variants compared to those without pathogenic structural variants. The FSD value was used to predict the presence of pathogenic structural variants with a sensitivity of 66- 80% and specificity of 65-78%. Body mass index affects face shape in a partly predictable manner. The effect of body mass index differences was controlled for in a further analysis. I then analysed facial asymmetry and showed that it was increased in people with developmental lesions in the brain but not in people with pathogenic structural variants. A final study showed that stereophotogrammetry, dense surface modelling, FSD and reflected FSD could be used to study a single genetic disorder associated with epilepsy, to find previously unrecognised face shape changes. Stereophotogrammetry and dense surface modelling therefore appear to be promising tools to aid both in discovery of underlying causes for epilepsy and in understanding of such causes in terms of facial development.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available