Use this URL to cite or link to this record in EThOS:
Title: Image-based detection of neuro-facial differences in foetal alcohol spectrum disorders
Author: Suttie, Michael Francis John
ISNI:       0000 0004 7231 9408
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Prenatal exposure to alcohol remains as one of the leading, yet preventable, causes of birth defects and neurodevelopmental disorders in the Western world. Over the past 50 years, since the first documented report on the impact of in utero alcohol exposure, a broad spectrum of associated effects have been recognised. Foetal alcohol spectrum disorders is the collective term encompassing a range of diagnostic classifications that can be identified. At the most severe end of this spectrum are foetal alcohol syndrome (FAS), recognisable by a characteristic set of facial features, growth delay, neurocognitive deficit, and behavioural impairments. Criteria for either of these diagnostic categories typically requires at least two ‘cardinal’ facial features: short palpebral fissure length; thin upper lip-vermillion; and, a smooth philtrum. Methods for identifying these features typically rely on subjective observation. This subjectivity means that accuracy of diagnosis is reliant on the skill and experience of the clinician. However, the main clinical challenges arise when an individual presents with confirmed or suspected prenatal alcohol exposure, but without the facial criteria required for FAS diagnoses. These individuals make up the vast majority of the affected population, and clinical recognition can be extremely challenging. Identification and recognition of facial features associated with prenatal alcohol exposure remain a key area of study. This thesis establishes a novel perspective on the issue of subjective clinical assessment and recognition using 3D face and brain shape analysis. We utilise data from 3D facial imaging, MRI brain images and neurocognitive measures to assess subtle facial differences, face-brain associations and the relationships between face, brain and cognition. Development of innovative techniques and methodologies have allowed us to develop a set of analysis tools applicable to craniofacial assessment, and potentially contribute to the analysis of other facially affected conditions in both clinical and research environments.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available