PDF(Pubmed)
Abstract：
Coronary artery calcification is a significant predictor of cardiovascular disease, with current detection methods like Agatston scoring having limitations in sensitivity. This study aimed to evaluate the effectiveness of a novel CAC quantification method using dual-energy material decomposition, particularly its ability to detect low-density calcium and microcalcifications. A simulation study was conducted comparing the dual-energy material decomposition technique against the established Agatston scoring method and the newer volume fraction calcium mass technique. Detection accuracy and calcium mass measurement were the primary evaluation metrics. The dual-energy material decomposition technique demonstrated fewer false negatives than both Agatston scoring and volume fraction calcium mass, indicating higher sensitivity. In low-density phantom measurements, material decomposition resulted in only 7.41% false-negative (CAC = 0) measurements compared to 83.95% for Agatston scoring. For high-density phantoms, false negatives were removed (0.0%) compared to 20.99% in Agatston scoring. The dual-energy material decomposition technique presents a more sensitive and reliable method for CAC quantification.
摘要：
冠状动脉钙化是心血管疾病的重要预测因子,目前的检测方法如Agatston评分在灵敏度上有局限性。本研究旨在评估使用双能材料分解的新型CAC量化方法的有效性，特别是其检测低密度钙和微钙化的能力。进行了模拟研究，将双能材料分解技术与已建立的Agatston评分方法和较新的体积分数钙质量技术进行了比较。检测准确性和钙质量测量是主要评估指标。双能材料分解技术显示出比Agatston评分和体积分数钙质量都少的假阴性，表明灵敏度更高。在低密度体模测量中，材料分解仅导致7.41%的假阴性(CAC=0),而Agatston评分为83.95%.对于高密度幻影，消除了假阴性(0.0%),而Agatston评分为20.99%.双能材料分解技术为CAC定量提供了一种更灵敏、更可靠的方法。
