Ahmed Wehab, de Graaf Michiel A, Broersen Alexander, Kitslaar Pieter H, Oost Elco, Dijkstra Jouke, Bax Jeroen J, Reiber Johan H C, Scholte Arthur J
Department of Cardiology, Leiden University Medical Center, Albinusdreef 2, Postal zone 2300 RC, 2333 ZA, Leiden, The Netherlands.
Int J Cardiovasc Imaging. 2015 Jan;31(1):151-61. doi: 10.1007/s10554-014-0519-4. Epub 2014 Aug 27.
Potentially, Agatston coronary artery calcium (CAC) score could be calculated on contrast computed tomography coronary angiography (CTA). This will make a separate non-contrast CT scan superfluous. This study aims to assess the performance of a novel fully automatic algorithm to detect and quantify the Agatston CAC score in contrast CTA images. From a clinical registry, 20 patients were randomly selected for each CAC category (i.e. 0, 1-99, 100-399, 400-999, ≥1,000). The Agatston CAC score on non-contrast CT was calculated manually, while the novel algorithm was used to automatically detect and quantify Agatston CAC score in contrast CTA images. The resulting Agatston CAC scores were validated against the non-contrast images. A total of 100 patients (60 ± 11 years, 63 men) were included. The median CAC score on non-contrast CT was 145 (IQR 5-760), whereas the contrast CTA CAC score was 170 (IQR 23-594) (P = 0.004). The automatically computed CAC score showed a high correlation (R = 0.949; P < 0.001) and intra-class correlation (R = 0.863; P < 0.001) with non-contrast CT CAC score. Moreover, agreement within CAC categories was good (κ 0.588). Fully automatic detection of Agatston CAC score on contrast CTA is feasible and showed high correlation with non-contrast CT CAC score. This could imply a radiation dose reduction and time saving by omitting the non-contrast scan.
理论上，阿加斯顿冠状动脉钙化（CAC）评分可通过对比增强计算机断层扫描冠状动脉造影（CTA）来计算。这将使单独的非增强CT扫描变得多余。本研究旨在评估一种新型全自动算法在对比增强CTA图像中检测和量化阿加斯顿CAC评分的性能。从临床登记处中，为每个CAC类别（即0、1 - 99、100 - 399、400 - 999、≥1000）随机选择20例患者。在非增强CT上手动计算阿加斯顿CAC评分，同时使用该新型算法自动检测和量化对比增强CTA图像中的阿加斯顿CAC评分。将所得的阿加斯顿CAC评分与非增强图像进行验证。共纳入100例患者（60±11岁，63例男性）。非增强CT上的CAC评分中位数为145（四分位间距5 - 760），而对比增强CTA的CAC评分为170（四分位间距23 - 594）（P = 0.004）。自动计算的CAC评分与非增强CT的CAC评分显示出高度相关性（R = 0.949；P < 0.001）和组内相关性（R = 0.863；P < 0.001）。此外，在CAC类别内的一致性良好（κ 0.588）。在对比增强CTA上全自动检测阿加斯顿CAC评分是可行的，并且与非增强CT的CAC评分显示出高度相关性。这可能意味着通过省略非增强扫描可减少辐射剂量并节省时间。
