Departments of Biomedical Sciences and Medicine, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute,116N Robertson Blvd, Suite 400, Los Angeles, CA 90048, USA.
1st Department of Cardiology, Medical University of Warsaw, Banacha 1A, 02-097 Warsaw, Poland.
Eur Heart J Cardiovasc Imaging. 2021 May 10;22(6):626-635. doi: 10.1093/ehjci/jeaa304.
We aimed to investigate the role of aortic valve tissue composition from quantitative cardiac computed tomography angiography (CTA) in patients with severe aortic stenosis (AS) for the differentiation of disease subtypes and prognostication after transcatheter aortic valve implantation (TAVI).
Our study included 447 consecutive AS patients from six high-volume centres reporting to a prospective nationwide registry of TAVI procedures (POL-TAVI), who underwent cardiac CTA before TAVI, and 224 matched controls with normal aortic valves. Components of aortic valve tissue were identified using semi-automated software as calcific and non-calcific. Volumes of each tissue component and composition [(tissue component volume/total tissue volume) × 100%] were quantified. Relationship of aortic valve composition with clinical outcomes post-TAVI was evaluated using Valve Academic Research Consortium (VARC)-2 definitions.High-gradient (HG) AS patients had significantly higher aortic tissue volume compared to low-flow low-gradient (LFLG)-AS (1672.7 vs. 1395.3 mm3, P < 0.001) as well as controls (509.9 mm3, P < 0.001), but increased non-calcific tissue was observed in LFLG compared to HG patients (1063.6 vs. 860.2 mm3, P < 0.001). Predictive value of aortic valve calcium score [area under the curve (AUC) 0.989, 95% confidence interval (CI): 0.981-0.996] for severe AS was improved after addition of non-calcific tissue volume (AUC 0.995, 95% CI: 0.991-0.999, P = 0.011). In the multivariable analysis of clinical and quantitative computed tomography parameters of aortic valve tissue, non-calcific tissue volume [odds ratio (OR) 5.2, 95% CI 1.8-15.4, P = 0.003] and history of stroke (OR 2.6, 95% CI 1.1-6.5, P = 0.037) were independent predictors of 30-day major adverse cardiovascular event (MACE).
Quantitative CTA assessment of aortic valve tissue volume and composition can improve detection of severe AS, differentiation between HG and LFLG-AS in patients referred for TAVI as well as prediction of 30-day MACEs post-TAVI, over the current clinical standard.
我们旨在通过定量心脏计算机断层血管造影术(CTA)研究严重主动脉瓣狭窄(AS)患者主动脉瓣组织成分在区分疾病亚型和经导管主动脉瓣植入术(TAVI)后的预后中的作用。
我们的研究纳入了来自六个大容量中心的 447 名连续的接受 TAVI 治疗的 AS 患者,他们在 TAVI 前接受了心脏 CTA 检查,并纳入了 224 名匹配的正常主动脉瓣患者作为对照。使用半自动软件识别主动脉瓣组织中的钙化和非钙化成分。量化每个组织成分的体积和组成[(组织成分体积/总组织体积)×100%]。使用 Valve Academic Research Consortium(VARC)-2 定义评估主动脉瓣成分与 TAVI 后临床结果的关系。与低流量低梯度(LFLG)-AS 患者(1672.7 毫米 3,P<0.001)和对照组(509.9 毫米 3,P<0.001)相比,高梯度(HG)AS 患者的主动脉组织体积明显更高,但与 HG 患者相比,LFLG 患者的非钙化组织增加(1063.6 毫米 3,P<0.001)。主动脉瓣钙评分的预测价值[曲线下面积(AUC)0.989,95%置信区间(CI):0.981-0.996]在添加非钙化组织体积后得到改善(AUC 0.995,95%CI:0.991-0.999,P=0.011)。在主动脉瓣组织的临床和定量 CT 参数的多变量分析中,非钙化组织体积[比值比(OR)5.2,95%CI 1.8-15.4,P=0.003]和卒中史(OR 2.6,95%CI 1.1-6.5,P=0.037)是 30 天主要不良心血管事件(MACE)的独立预测因子。
定量 CTA 评估主动脉瓣组织体积和组成可以提高对严重 AS 的检出率,区分接受 TAVI 治疗的患者中的 HG 和 LFLG-AS,并预测 TAVI 后 30 天的 MACE,优于当前的临床标准。