Abstract
Background
Multi-slice computed tomography (CT) allows noninvasive evaluation of the severity
of coronary calcification. However, there has yet to be a definitive parameter based
on the cross-sectional CT image for predicting the need for rotational atherectomy
(RA). Therefore, we aimed to investigate the mean density of cross-sectional CT images
to predict the need for RA during percutaneous coronary intervention (PCI).
Methods
A total of 154 lesions with moderate to severe calcification detected in coronary
angiography were identified in 126 patients who underwent coronary CT prior to PCI
for stable angina. PCI with RA was performed for 48 lesions, and the remaining 106
were treated without RA. Multi-slice CT was retrospectively evaluated for its ability
to predict the use of RA. We chose the most severely calcified cross-sectional image
for each lesion. The mean density within the outer vessel contour, calcium arc quadrant
of the cross-sectional CT image, calcium length, calcification remodeling index, and
per-lesion coronary artery calcium score was studied.
Results
Receiver-operator characteristic curve analysis revealed 637 Hounsfield units (HU)
(area under the curve = 0.98, 95% confidence interval: 0.97–1.00, p < 0.001) as
the best mean density cutoff value for predicting RA. Multivariate logistic regression
analysis showed that a mean calcium level >637 HU was a strong independent predictor
(odds ratio: 32.8, 95% confidence interval: 7.0–153, p < 0.001) for using RA.
Conclusions
The mean density of the cross-sectional CT image, a simple quantitative parameter,
was the strongest predictor of the need for RA during PCI.
Keywords
Abbreviations:
CAC (coronary artery calcium), CT (computed tomography), HU (Hounsfield unit), IVUS (intravascular ultrasound), MLA (minimum lumen area), MSA (minimum stent area), OCT (optical coherence tomography), PCI (percutaneous coronary intervention), QCA (quantitative coronary angiography), RA (rotational atherectomy), ROC (receiver operator characteristic), WL/WW (window level/window width)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: February 10, 2023
Accepted:
February 1,
2023
Received in revised form:
January 29,
2023
Received:
September 8,
2022
Publication stage
In Press Journal Pre-ProofIdentification
Copyright
© 2023 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
