Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.584117
Title: Abdominal Aortic Aneurysm detection by common femoral artery Doppler ultrasound waveform analysis
Author: Wells, Catherine E.
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2007
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Abstract:
Abdominal Aortic Aneurysm (AAA) is a serious, life threatening condition. AAAs are often asymptomatic and many remain silent until rupture. If detected early, the condition can be monitored and electively repaired relatively safely. Arterial disease is readily and routinely assessed using Doppler ultrasound. The effect of occlusive arterial disease on Doppler waveforms is well documented and the disease state of the aorto-iliac segment can be estimated by examination of the common femoral artery (CFA) waveform. Theoretically, aneurysmal disease should alter the blood flow pattern due to the localised increase in vessel diameter. It has been noted during routine clinical examinations of CFA Doppler waveforms, that when certain features were observed, an AAA was often present. Reported studies examining lower limb Doppler waveforms and flows through aneurysm models support these observations. The main aim of this research study was to determine if and how the Doppler waveform of the CFA is changed in the presence AAA and to utilise these changes for the early diagnosis of AAA. The interpretation of Doppler waveforms for the assessment of vascular disease requires a high level of skill and training and still remains subjective. An automated, objective detection method to detect AAA by analysis of the CFA Doppler waveform was achieved by implementing a MATLAB software based computer program to perform CFA waveform feature based analysis and determine whether or not an AAA is present. The second aim of the study was to predict the AAA size and presence of ILT using the program results. For patients with no significant atherosclerotic disease, automated MATLAB based CFA waveform analysis provided 100% sensitivity and 73.3% specificity for AAA detection. Additional waveform features set up by atherosclerotic disease made it more difficult to separate the AAA and normal patients with significant atherosclerotic disease. It was not possible to adequately predict the physical characteristics of using the AAA detection program. In conclusion, feature analysis of the CFA Doppler waveform may provide a promising, alternative method for AAA detection. AAA characterisation may be possible using different analysis methods.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.584117  DOI: Not available
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