Lu Qiyang, Lin Weiyuan, Zhang Ruichen, Chen Rui, Wei Xiaoyu, Li Tingyu, Du Zhicheng, Xie Zhaofeng, Yu Zhuliang, Xie Xinzhou, Liu Hui
College of Automation Science and Technology, South China University of Technology, Guangzhou, China.
Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Front Neuroinform. 2020 Dec 9;14:613666. doi: 10.3389/fninf.2020.613666. eCollection 2020.
The clinical diagnosis of aorta coarctation (CoA) constitutes a challenge, which is usually tackled by applying the peak systolic pressure gradient (PSPG) method. Recent advances in computational fluid dynamics (CFD) have suggested that multi-detector computed tomography angiography (MDCTA)-based CFD can serve as a non-invasive PSPG measurement. The aim of this study was to validate a new CFD method that does not require any medical examination data other than MDCTA images for the diagnosis of CoA. Our study included 65 pediatric patients (38 with CoA, and 27 without CoA). All patients underwent cardiac catheterization to confirm if they were suffering from CoA or any other congenital heart disease (CHD). A series of boundary conditions were specified and the simulated results were combined to obtain a stenosis pressure-flow curve. Subsequently, we built a prediction model and evaluated its predictive performance by considering the AUC of the ROC by 5-fold cross-validation. The proposed MDCTA-based CFD method exhibited a good predictive performance in both the training and test sets (average AUC: 0.948 vs. 0.958; average accuracies: 0.881 vs. 0.877). It also had a higher predictive accuracy compared with the non-invasive criteria presented in the European Society of Cardiology (ESC) guidelines (average accuracies: 0.877 vs. 0.539). The new non-invasive CFD-based method presented in this work is a promising approach for the accurate diagnosis of CoA, and will likely benefit clinical decision-making.
主动脉缩窄（CoA）的临床诊断具有挑战性，通常采用收缩压峰值梯度（PSPG）法来解决。计算流体动力学（CFD）的最新进展表明，基于多排螺旋计算机断层血管造影（MDCTA）的CFD可作为一种无创PSPG测量方法。本研究的目的是验证一种新的CFD方法，该方法除MDCTA图像外不需要任何医学检查数据即可诊断CoA。我们的研究纳入了65例儿科患者（38例CoA患者和27例非CoA患者）。所有患者均接受心导管检查以确认是否患有CoA或任何其他先天性心脏病（CHD）。指定了一系列边界条件，并将模拟结果相结合以获得狭窄压力-流量曲线。随后，我们建立了一个预测模型，并通过5折交叉验证考虑ROC的AUC来评估其预测性能。所提出的基于MDCTA的CFD方法在训练集和测试集中均表现出良好的预测性能（平均AUC：0.948对0.958；平均准确率：0.881对0.877）。与欧洲心脏病学会（ESC）指南中提出的无创标准相比，它也具有更高的预测准确率（平均准确率：0.877对0.539）。本文提出的基于CFD的新型无创方法是一种准确诊断CoA的有前景的方法，可能会有益于临床决策。
