冠状动脉追踪冻结技术在回顾性心电门控下改善CTCA图像质量

Improving CTCA Iimage Quality by Using Snapshot Freeze Technique under Prospective and Retrospective ECG-gating

目的:评估冠状动脉追踪冻结技术(snapshot freeze,SSF)在回顾性心电门控下对CT冠状动脉图像质量的价值。方法:选取30例疑似冠心病患者进行回顾性心电门控扫描,比较标准算法(standard,STD)重建和SSF重建两种方法的图像质量和可判读性。所获图像由两位医师判读,分别按每一冠状动脉节段、每支冠状动脉及每例冠状动脉进行评分,按Likert 5分制为标准。结果:45%期相SSF算法重建图像可判读性按例[g0.0%(24/30)vs 53.3%(16/30),P=0.039],按分支[90.0%(81/90)vs 71.1%(64/90),P=0.000],和按节段[98.1%(413/421)vs 90.7%(382/421),P=0.000]均高于标准算法图像;75%期SSF算法重建图像可判读性按分支[70.0%(63/90)vs 55.6%(50/90),P=0.02]和按节段[82.7%(348/421)vs 78.4%(330/421),P=0.018]比较高于标准算法重建图像,SSF算法45%和75%期相图像质量按例数(2.8±1.0±2.1±1.2,P=0.012)(2.1±1.2 vs1.6±1.0,P=0.026),按分支(3.0±0.9 vs2.4±1.0,P=0.000)(2.6±1.2vs2.2±1.2,P=0.000)和按节段(3.3±0.9vs 2.9±1.0,P=0.000)(2.9±1.2vs2.7±1.1,P=0.000)比较均明显高于标准算法。结论:冠状动脉追踪冻结技术能明显提高后门控冠状动脉CT图像质量及可判读性,其中对45%期相重建的右冠状动脉图像质量改善作用最为明显。

Purpose： To assess the effect of snapshot freeze motion correction algorithm on image quality of CCTA. Methods： Thirty consecutive patients underwent CCTA with retrospective ECG-gating. Image quality and interpretability were compared between standard （STD） and snapshot freeze （SSF） reconstructions algorithms by using Likert 5-points score, which were interpreted by two experienced radiologists. Results： The CCTA images reconstructed by SSF algorithm showed higher interpretability than that by STD algorithm on per-patient [80.0%（24/30） vs 53.3%（16/30）, P=0.039], per-artery [90.0%（81/90） vs 71.1%（64/90）, P=0.000], and per-segment levels [98.1%（413/421） vs 90.7%（382/421）, P=0.000] of 45% R-R interval images. The CCTA images reconstructed by SSF algorithm showed higher interpretability than that by STD algorithm on per-artery [70.0%（63/90） vs 55.6%（50/90）, P=0.02] and per-segment levels [82.7% （348/421） vs 78.4%（330/421）, P=0.018]. Image quality of the CCTA images reconstructed by SSF algorithm were higher than that by STD algorithm on per-patient （2.8± 1.0 vs 2.1 ± 1.2, P=0.013） （2.1±1.2 vs 1.6±1.0, P =0.026）, per-artery （3.0±0.9 vs 2.4±1.0, P=0.000） （2.6±1.2 vs 2.2±1.2,P=0.000） and persegment levels （3.3＋0.9 vs 2.9±1.0, P=0.000） （2.9±1.2 vs 2.7±1.1, P=0.000） of 45% and 75% R-R interval images. Conclusion： SSF algorithm can be used to improve the image quality and interpretability of CCTA with retrospective ECG-gating. Especially, the image quality of RCA by using the 45% R-R interval as the central phase with retrospective ECG-gating can be improved obviously.