Wiktorowicz Agata, Wit Adrian, Dziewierz Artur, Rzeszutko Lukasz, Dudek Dariusz, Kleczynski Pawel
Second Department of Cardiology, Jagiellonian University Medical College, Krakow, Poland.
Faculty of Physics and Applied Computer Science, University of Science and Technology, Krakow, Poland.
Minerva Cardioangiol. 2019 Feb;67(1):3-10. doi: 10.23736/S0026-4725.18.04793-X. Epub 2018 Sep 13.
Precise calcium evaluation in the aortic complex may be complicated. We aimed to assess the usefulness of a novel semi-automatic algorithm for multi slice computed tomography-derived (MSCT) quantitative estimation of aortic valve calcifications (AVC) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation (TAVI).
Ten patients with severe AS who underwent TAVI with Edwards Sapien S3 26 mm prosthesis and had a pre-procedural MSCT scan were included. Data on baseline characteristics, procedural and long-term outcomes were collected prospectively. Pre-procedural MSCT data were used for AVC evaluation with 3D modeling (calcium volume, thickness, area, density, and distribution) in a dedicated program.
Mean calcium thickness was 4.6 (3.6-5.8) mm. Median calcium are 333.6 (274.7-386.7) mm2. We found a significant correlation between larger maximal calcium layer thickness and PVL occurrence after TAVI (P=0.039). The radial representation of the calcium distribution allowed to divide aortic valve into 3 zones and to compare each zone to parallel zone on TTE images. In zones with PVL ≥2 mean AVC was higher than in zones with PVL <2 (7354.6±4020.4 pixels vs. 4325.1±1790.6 pixels; P=0.018). Based on ROC analysis, the optimal cut-off value of AVC to predict PVL ≥2 was >6506 pixels with 57.1% sensitivity and 90.5% specificity (AUC 0.762 [95% CI: 0.564 to 0.901], P=0.029).
Multiplane AVC quantitative evaluation provided details on total calcium amount, pattern and distribution in aortic valve. Established AVC parameters allowed better visualization of an operating area and prediction of PVL after TAVI.
主动脉复合体中精确的钙评估可能较为复杂。我们旨在评估一种新型半自动算法在经导管主动脉瓣植入术(TAVI)治疗的严重主动脉瓣狭窄(AS)患者中对多层螺旋计算机断层扫描(MSCT)衍生的主动脉瓣钙化(AVC)进行定量评估的实用性。
纳入10例接受爱德华兹Sapien S3 26mm人工瓣膜TAVI且术前进行了MSCT扫描的严重AS患者。前瞻性收集基线特征、手术及长期结局数据。术前MSCT数据用于在专用程序中通过三维建模(钙体积、厚度、面积、密度和分布)进行AVC评估。
平均钙厚度为4.6(3.6 - 5.8)mm。钙面积中位数为333.6(274.7 - 386.7)mm²。我们发现TAVI后较大的最大钙层厚度与瓣周漏(PVL)发生之间存在显著相关性(P = 0.039)。钙分布的径向表示法可将主动脉瓣分为3个区域,并在经胸超声心动图(TTE)图像上与平行区域进行比较。PVL≥2的区域平均AVC高于PVL<2的区域(7354.6±4020.4像素对4325.1±1790.6像素;P = 0.018)。基于ROC分析,预测PVL≥2的AVC最佳截断值>6506像素,敏感性为57.1%,特异性为90.5%(曲线下面积0.762 [95%CI:0.564至0.901],P = 0.029)。
多平面AVC定量评估提供了主动脉瓣总钙量、模式和分布的详细信息。既定的AVC参数有助于更好地可视化手术区域并预测TAVI后的PVL。