Wiktorowicz Agata, Wit Adrian, Malinowski Krzysztof Piotr, Dziewierz Artur, Rzeszutko Lukasz, Dudek Dariusz, Kleczynski Pawel
Jagiellonian University Medical College, Faculty of Medicine, Institute of Cardiology, 2 Department of Cardiology, 30-688, Krakow, Poland.
Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059 Krakow, Poland.
Quant Imaging Med Surg. 2021 Feb;11(2):652-664. doi: 10.21037/qims-20-669.
Paravalvular leak (PVL) is one of the most common complications of transcatheter aortic valve replacement (TAVR) and affects short- and long-term outcomes. The aim of this study was to identify the computed tomography (CT) imaging biomarkers that allow PVL after TAVR to be predicted.
Patients were included who had severe aortic valve stenosis, had undergone TAVR with a self-expanding valve, and had undergone a pre-procedural CT scan. Data on baseline characteristics, procedural and long-term outcomes were collected retrospectively. We used MATLAB software with a self-developed algorithm for CT scan analysis and found parameters that quantified aortic valve calcifications (AVC) in detail.
Fifty patients were included. The identified CT-derived parameters included AVC size, volume, thickness and density, as well as calcium radial distribution. The volume of the largest calcium block, calcium perimeter and calcium size (assessed by Feret's diameter) showed a strong association with PVL occurrence after TAVR (P=0.012, P=0.001 and P=0.045, respectively). The prognostic model showed that a 10 mm increase in the local AVC amount in each valve section was associated with a 9.8% (95% CI: 2-18%; P=0.019) increase in the risk of PVL occurrence in the corresponding area after TAVR. ROC analysis revealed that the cut-off point of the AVC area was 96.5 mm in the polar coordinate system presentation. Kaplan-Meier curves showed worse PVL-free survival in patients with more than 96.5 mm of calcium area (P=0.013; log-rank).
Quantitative AVC assessment for PVL prediction may play an important role in screening before TAVR. In future, the use of quantitative AVC assessment as an imaging biomarker in TAVR candidates and the creation and extension of an online database containing quantitative AVC parameters may help to identify high PVL risk patients.
瓣周漏（PVL）是经导管主动脉瓣置换术（TAVR）最常见的并发症之一，影响短期和长期预后。本研究的目的是确定能够预测TAVR术后PVL的计算机断层扫描（CT）成像生物标志物。
纳入患有严重主动脉瓣狭窄、接受了自膨胀瓣膜TAVR且术前进行了CT扫描的患者。回顾性收集基线特征、手术及长期预后数据。我们使用带有自行开发算法的MATLAB软件进行CT扫描分析，发现了可详细量化主动脉瓣钙化（AVC）的参数。
纳入50例患者。确定的CT衍生参数包括AVC大小、体积、厚度和密度，以及钙的径向分布。最大钙块体积、钙周长和钙大小（通过费雷特直径评估）与TAVR术后PVL的发生密切相关（分别为P = 0.012、P = 0.001和P = 0.045）。预后模型显示，每个瓣膜节段局部AVC量增加l0 mm与TAVR术后相应区域PVL发生风险增加9.8%（95%CI：2 - 18%；P = 0.019）相关。ROC分析显示，在极坐标系表示中，AVC面积的截断点为96.5 mm。Kaplan - Meier曲线显示，钙面积超过96.5 mm的患者无PVL生存期较差（P = 0.013；对数秩检验）。
用于预测PVL的定量AVC评估可能在TAVR术前筛查中发挥重要作用。未来，将定量AVC评估用作TAVR候选者的成像生物标志物，以及创建和扩展包含定量AVC参数的在线数据库，可能有助于识别PVL高风险患者。
