|dc.identifier.citation||Roberts. W. 2013. Assessment of Coronary Artery Disease by Computed Tomography. Queen Mary University of London.||en_US
Computed Tomography Coronary
Angiography (CTCA)is a technique for imaging
coronary arteries with increasing indications in clinical cardiology.
1.Develop a heart rate (HR) lowering regime for CTCA and to measure its association
with image quality.
2.Examine the diagnostic accuracy of 64 slice CTCA (CTCA64) in patients with known
coronary artery disease (CAD).
3.Examine the diagnostic accuracy of CTCA64 for assessment of stent restenosis
4.Demonstrate utility of CTCA as an
endpoint in assessment of novel
diagnostic biomarkers of CAD.
I developed a HR reducing strategy using metoprolol and assessed its effectiveness for
improving CTCA64 image quality.
The diagnostic value of CTCA in patients with suspected angina was evaluated by
comparison with invasive coronary angiography.
The diagnostic value of CTCA for quantifying stent restenosis was evaluated by
comparison with intravascular ultrasound.
The utility of CTCA for evaluating the diagnostic value of B-type natriuretic peptide (BNP) and high sensitivity cardiac troponin I (hs- TnI) was evaluated by blood sampling in patients with suspected angina
who subsequently underwent CTCA.
1.In 121 patients undergoing CTCA, 75 required rate control. This was achieved (rate ≤60 bpm) in 83% using a systematic regimen of oral and IV metoprolol (n=71) or
verapamil (n=4). I demonstrated a significant relation between HR reduction and
graded image quality (p<0.001).
2.80 patients underwent CTCA64 and invasive coronary angiography. 724 coronary
arterial segments were available for analysis. The sensitivity and specificity of CTCA for significant luminal stenosis was 83.3% (95% CI 67.1-92.5%) and 96.7% (95% CI 95.1-97.9%), respectively, but the
positive predictive value was only 63.5% (95% CI 50.4-75.3%).
3.80 patients with 125 stented segments underwent CTCA64 and invasive coronary
angiography. Additional intravascular ult
rasound (IVUS) examination of stented
segments was performed in 48 patients.
Using IVUS as the gold-standard for stent
restenosis, CTCA and invasive coronary angiography had comparable diagnostic
specificities for binary stent restenosis: 82.7% (95% confidence intervals 69.7-
91.84%)and 78.9% (95% confidence intervals 65.3-88.9%), respectively. Sensitivities were
lower, particularly the sensitivity of CTCA which was only 11.8% (95% confidence intervals 1.5-36.4%) compared with 58.8% (95% confidence intervals 32.9-81.6%) for
invasive coronary angiography.
4. In 93 patients with suspected angina CTCA64 provided a useful endpoint for
assessing the diagnostic value of novel
circulating biomarkers. BNP levels were higher in the 13 patients shown to have significant (≥50% stenosis) coronary artery disease compared with patients who had unobstructed coronary arteries (18.08pg/ml
(IQR 22) vs 9.14pg/ml (IQR 12.62), p=0.024) and increased significantly with exercise,
particularly in the group with anatomic coronary artery disease (2.73 ± 5.69 pg/ml vs
1.27±3.29 pg/ml, p=0.16). Conversely I found no association between hs-TnI and the
presence of CAD.
Image quality of CTCA64 is enhanced by heart rate reduction below 60 bpm which can
be achieved safely by a regimen of oral and intravenous metoprolol. Although CTCA64
is a useful non-invasive method for diagnosis of coronary artery disease,
it has a low positive predictive value for identifying severe (≥50%) luminal stenosis
which limits its clinical value. Its
value for assessment of stent restenosis is
even more limited but it finds useful application as an endpoint for diagnostic evaluation of novel biomarkers, allowing confirmation of an association between
circulating BNP levels and stable coronary artery disease||en_US
|dc.description.sponsorship||Barts and London charitable trust; Siemens; The Hospital of St John and St Elizabeth||en_US
|dc.publisher||Queen Mary University of London||en_US
|dc.subject||Coronary artery disease||en_US
|dc.title||Assessment of Coronary Artery Disease by Computed Tomography||en_US
|dc.rights.holder||The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author||