Department of Radiology, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen, China.
Laboratory for Engineering and Scientific Computing, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Medicine (Baltimore). 2024 Nov 29;103(48):e40613. doi: 10.1097/MD.0000000000040613.
To compare the characteristics of stable and vulnerable carotid plaques, and investigate the diagnostic performance of wall shear stress (WSS) based on magnetic resonance plaque imaging in carotid plaques. Retrospectively analyzed and divided 64 atherosclerotic plaques into stable carotid plaque groups with mild-to-moderate stenosis and vulnerable carotid plaque groups with significant stenosis. Computational fluid dynamics simulations were performed to calculate WSS parameters by using three-dimensional wall geometry based on high-resolution magnetic resonance plaque imaging of carotid bifurcation and patient specific boundary conditions obtained through color Doppler ultrasound. WSS parameters including upstream (WSSup), downstream (WSSdown), and core (WSScore) of plaque. The WSS parameters values were compared between the stable and vulnerable carotid plaque groups. Receiver operating characteristic curves and area under the curve (ROC-AUC) and Python were used to evaluate discriminative efficacy of WSS. WSSdown exhibited significant decrease in the vulnerable carotid plaque group (2.88 ± 0.41 Pa) compared to the stable carotid plaque group (4.47 ± 0.84 Pa) (P = .003). The difference of WSSup (3.28 ± 0.85 Pa vs 4.02 ± 0.74 Pa) and WSScore (1.12 ± 0.18 Pa vs 1.38 ± 0.38 Pa) between the two groups were also pronounced (P = .02, 0.01, respectively). The ROC-AUC values for WSSup, WSSdown, WSScore were 0.75 (95% CI, 0.58-0.93), 0.96 (95% CI, 0.79-1.14), 0.69 (95% CI, 0.56-0.83) respectively. When the value of WSSdown was 3.5 Pa, the sensitivity was 93.7% (95% CI, 76.1-111), specificity and accuracy was 87.5% (95% CI, 70.0-105), 88.4% (95% CI, 70.6-105) respectively. Notably, among these parameters, WSSdown demonstrated the highest discriminative efficiency with a F1 Score of 0.90, Diagnostic Odds Ratio of 105.0 and Matthews Correlation Coefficient of 0.81. Vulnerable carotid plaques with significant stenosis have lower WSS compared to stable plaques with mild-to-moderate stenosis, and downstream WSS showing the highest diagnostic efficacy.
为了比较稳定和易损颈动脉斑块的特征，并探讨基于磁共振斑块成像的壁面切应力（WSS）在颈动脉斑块中的诊断性能，我们回顾性分析并将 64 个动脉粥样硬化斑块分为狭窄程度为轻-中度的稳定颈动脉斑块组和狭窄程度显著的易损颈动脉斑块组。通过颈动脉分叉的高分辨率磁共振斑块成像和通过彩色多普勒超声获得的患者特定边界条件，基于三维壁几何结构对计算流体动力学模拟进行了计算，以计算 WSS 参数。WSS 参数包括斑块的上游（WSSup）、下游（WSSdown）和核心（WSScore）。比较了稳定和易损颈动脉斑块组之间的 WSS 参数值。使用接收者操作特征曲线和曲线下面积（ROC-AUC）和 Python 评估 WSS 的判别效能。WSSdown 在易损颈动脉斑块组（2.88±0.41 Pa）中显著降低，而在稳定颈动脉斑块组（4.47±0.84 Pa）中显著降低（P=0.003）。两组之间 WSSup（3.28±0.85 Pa 与 4.02±0.74 Pa）和 WSScore（1.12±0.18 Pa 与 1.38±0.38 Pa）的差异也很明显（P=0.02，0.01）。WSSup、WSSdown 和 WSScore 的 ROC-AUC 值分别为 0.75（95%CI，0.58-0.93）、0.96（95%CI，0.79-1.14）和 0.69（95%CI，0.56-0.83）。当 WSSdown 值为 3.5 Pa 时，敏感性为 93.7%（95%CI，76.1-111），特异性和准确性分别为 87.5%（95%CI，70.0-105）和 88.4%（95%CI，70.6-105）。值得注意的是，在这些参数中，WSSdown 的判别效率最高，F1 评分为 0.90，诊断优势比为 105.0，马修斯相关系数为 0.81。与狭窄程度为轻-中度的稳定斑块相比，狭窄程度显著的易损颈动脉斑块的 WSS 较低，下游 WSS 显示出最高的诊断效能。
