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Identifying Coronary Artery Calcification on Non-gated Computed Tomography Scans
Published on: August 28, 2018
Quantifying Aortic Valve Calcification using Coronary Computed Tomography Angiography
Abdulrahman M Alqahtani1, Kevin E Boczar2, Vinay Kansal2
1Division of Cardiology, University of Ottawa Heart Institute, Canada; King Fahad Medical City, Riyadh, Saudi Arabia.
Insights
Quantifying aortic valve calcification (AVC) with contrast-enhanced CT angiography (CTA) is feasible. This new method, AVCCorrected, shows good agreement with traditional coronary artery calcification (CAC) scoring.
Area of Science:
- Cardiovascular Imaging
- Radiology
- Medical Diagnostics
Background:
- Aortic valve calcification (AVC) is linked to adverse cardiovascular outcomes and mortality.
- Current quantification methods for AVC may not be optimal.
Purpose of the Study:
- To develop and validate a novel method for quantifying AVC using contrast-enhanced coronary CT angiography (CTA).
- To assess the reliability and agreement of the new AVC quantification method compared to traditional methods.
Main Methods:
- Utilized data from 59 patients undergoing both non-contrast and contrast-enhanced coronary CTA.
- Developed a new AVC quantification method (AVCCTA) using contrast-enhanced CTA, defining a calcium threshold based on aortic attenuation.
- Calculated a correction factor to convert AVCCTA to an AVCCAC equivalent (AVCCorrected).
Main Results:
- Excellent correlation (r=0.982) between AVCCAC and AVCCTA in the derivation cohort.
- Good correlation (ICC=0.939) and agreement (kappa=0.700) between AVCCAC and AVCCorrected in the validation cohort.
- A correction factor (1.868) was established to equate AVCCTA to AVCCAC.
Conclusions:
- Quantification of AVC using contrast-enhanced CTA (AVCCorrected) is feasible and reliable.
- The method demonstrates good agreement with traditional AVC quantification (AVCCAC).
- Further large-scale validation is required to determine if AVCCorrected can replace AVCCAC.
Introduction:
Aortic valve calcification (AVC) has been associated with major adverse cardiovascular events and all-cause mortality. We sought to develop and validate a method to quantify AVC using coronary CT angiography (CTA).
Methods:
Of 59 patients who underwent both non-contrast and contrast enhanced coronary CTA, 25 patients served as the derivation cohort and 34 patients served as the validation cohort. For non-contrast enhanced CT, quantification of AVC was performed using the Agatston method for coronary artery calcification (CAC). For contrast enhanced coronary CTA, a region of interest (ROI) was placed in the ascending aorta and the mean aortic attenuation value (HUAorta) and standard deviation (SD) were measured. Using a calcium threshold of mean HUAorta + 2SD, the AVCCTA was calculated. All other Agatston score parameters (weighting factors and area calculations) remained unchanged.
Results:
In the derivation cohort, the correlation between AVCCAC and AVCCTA was excellent (r = 0.982). Using the line of best fit, a correction factor was calculated enabling the conversion of AVCCTA results to a AVCCAC equivalent (AVCCorrected = 1.868 × AVCCTA). Using this correction in the validation cohort, the correlation and agreement between AVCCAC and AVCCorrected were good (ICC = 0.939; 95% CI: 0.881-0.969; kappa = 0.700; 95% CI: 0.469-0.931).
Conclusion:
The quantification of AVCCorrected using contrast enhanced CTA is feasible using a systematic approach with very good reliability and good agreement with AVCCAC. Larger-scale validation studies are needed to determine whether the use of AVCCAC can be eliminated in favour of AVCCorrected.
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