West China Biomedical Big Data Centre, West China Hospital, Sichuan University, China; Department of Applied Mechanics, Sichuan University, China.
Department of Vascular Surgery, West China Hospital, Sichuan University, China.
Eur J Vasc Endovasc Surg. 2022 Aug-Sep;64(2-3):155-164. doi: 10.1016/j.ejvs.2022.05.027. Epub 2022 May 20.
This study aimed to derive a novel classification of blood flow pattern in abdominal aortic aneurysms (AAA) based on computational fluid dynamics (CFDs), and to determine the predictive value of flow patterns in AAA rupture.
This was an age and sex matched case control study. Cases were identified as patients who underwent emergency endovascular or open repair due to ruptured or AAA at risk of impending rupture. Controls were age and sex matched with patients with an AAA who were asymptomatic and had a confirmed unruptured AAA from computed tomography angiography images from the same period. Classification of blood flow pattern (type I: non-helical main flow channel with multiple vortices; type II: non-helical main flow channel with single vortices; and type III, helical main flow channel with helical vortices) and haemodynamic parameters (areas of low wall shear stress [A], aneurysm pressure drop [Δ pressure], etc) were derived from CFD analyses. Multivariable regression was used to determine independent AAA rupture risk factors. The incremental discriminant and reclassification abilities for AAA rupture were compared among different models.
Fifty-three ruptured and 53 intact AAA patients were included. Ruptured AAA showed a higher prevalence of type III flow pattern than intact AAA (60.4% vs. 15.1%; p < .001). Type III flow pattern was associated with a significantly increased risk of aneurysm rupture (odds ratio 10.22, 95% confidence interval 3.43 - 30.49). Among all predicting models, the combination of AAA diameter, haemodynamic parameters (A or Δ pressure), and flow pattern showed highest discriminant abilities in both the overall population (c-index = 0.862) and subgroup patients with AAAs < 55 mm (c-index = 0.972). Compared with AAA diameter, adding the flow pattern could significantly improve the reclassification abilities in both the overall population (net reclassification index [NRI] = 0.321; p < .001) and the subgroup of AAAs < 55 mm (NRI = 0.732; p < .001).
Type III flow pattern was associated with a significantly increased risk of AAA rupture. The integration of blood flow pattern may improve the identification of high risk aneurysms in both overall population and in those with AAAs < 55 mm.
本研究旨在基于计算流体动力学(CFD)建立一种新的腹主动脉瘤(AAA)血流模式分类,并确定血流模式在 AAA 破裂中的预测价值。
这是一项年龄和性别匹配的病例对照研究。病例组为因破裂或即将破裂而接受急诊血管内或开放修复的患者。对照组为同期 CT 血管造影图像证实为无症状且 AAA 未破裂的患者,与病例组年龄和性别匹配。血流模式(I 型:无螺旋主流通道伴多个涡流;II 型:无螺旋主流通道伴单个涡流;III 型:螺旋主流通道伴螺旋涡流)和血流动力学参数(低壁切应力区[A]、AAA 压降[Δ压力]等)通过 CFD 分析得出。采用多变量回归确定 AAA 破裂的独立危险因素。比较不同模型对 AAA 破裂的增量判别和重新分类能力。
共纳入 53 例破裂和 53 例完整的 AAA 患者。破裂的 AAA 比完整的 AAA 更常见 III 型血流模式(60.4%比 15.1%;p<0.001)。III 型血流模式与 AAA 破裂的风险显著增加相关(优势比 10.22,95%置信区间 3.43-30.49)。在所有预测模型中,AAA 直径、血流动力学参数(A 或 Δ 压力)和血流模式的组合在总体人群(c 指数=0.862)和 AAA<55mm 的亚组患者中均具有最高的判别能力(c 指数=0.972)。与 AAA 直径相比,添加血流模式可显著提高总体人群(净重新分类指数[NRI]=0.321;p<0.001)和 AAA<55mm 的亚组(NRI=0.732;p<0.001)的重新分类能力。
III 型血流模式与 AAA 破裂的风险显著增加相关。血流模式的整合可以提高总体人群和 AAA<55mm 的人群中高危动脉瘤的识别能力。