摘要
目的探索第二代冠状动脉追踪冻结(SSF2)技术,结合深度学习图像重建算法在较高心率患者冠状动脉CT血管成像(CCTA)中的应用价值。方法回顾性纳入心率≥70次/min行CCTA检查的患者62例,CT扫描管电压为100 kV。采用双盲法对冠状动脉的图像质量进行主观评价,分为常规图像(A组)、SSF1图像(B组)和SSF2图像(C组)。结果三组图像质量评分和优秀率比较显示RCA、PDA、LAD、D、LCX、OM、PLB、RI差异均有统计学意义(P<0.05)。冠状动脉的评分为(2.85±0.72)(A组)、(3.38±0.61)(B组)、(3.86±0.34)(C组)。冠状动脉的优秀率为15.19%(A组)、44.39%(B组)、86.42%(C组)。可诊断率比较显示RCA、PDA、D、LCX、OM、PLB、RI差异有统计学意义(P<0.05),而LAD可诊断率差异无统计学意义(χ^(2)=4.01,P=0.135)。结论采用SSF2技术结合深度学习图像重建算法可以进一步提高较高心率患者CCTA图像质量。
Objective To explore the application value of the second generation of snapshot freeze(SSF2)combined with deep learning image reconstruction algorithm in coronary CT angiography(CCTA)in patients with high heart rate.Methods A total of 62 patients with heart rate≥70 times/min who underwent CCTA examination were retrospectively included,and the tube voltage was 100 kV.The image quality of coronary artery was evaluated subjectively by double-blind method,which was divided into conventional images(group A),SSF1 images(group B),and SSF2 images(group C).Results The comparison of image quality scores and excellent rates among the three groups showed that RCA,PDA,LAD,D,LCX,OM,PLB and RI were significantly different(P<0.05).Coronary artery scores were(2.85±0.72)(group A),(3.38±0.61)(group B),and(3.86±0.34)(group C).The excellence rate of coronary artery was 15.19%(group A),44.39%(group B),86.42%(group C)respectively.The comparison of diagnosable rates showed that RCA,PDA,D,LCX,OM,PLB and RI were statistically significant(P<0.05),and LAD was not statistically significant(χ^(2)=4.01,P=0.135).Conclusions SSF2 technology combined with deep learning image reconstruction algorithm can further improve CCTA image quality in patients with high heart rate.
作者
张秀芳
罗春材
ZHANG Xiufang;LUO Chuncai(Department of Radiology,the Second Medical Center of PLA General Hospital,Beijing 100853,China;Department of Radiology,the First Medical Center of PLA General Hospital,Beijing 100853,China)
出处
《武警医学》
CAS
2024年第10期847-852,共6页
Medical Journal of the Chinese People's Armed Police Force
作者简介
张秀芳,本科学历,技师;通讯作者:罗春材,E-mail:luochuncai2@126.com
