Tsou Jean K, Liu Jie, Barakat Abdul I, Insana Michael F
Department of Biomedical Engineering, University of California, Davis, CA, USA.
Ultrasound Med Biol. 2008 Jun;34(6):963-72. doi: 10.1016/j.ultrasmedbio.2007.11.010. Epub 2008 Jan 22.
Atherosclerotic lesions preferentially originate in arterial regions that experience low wall shear stress (WSS) and reversing flow patterns. Therefore, routinely monitoring arterial WSS may help to identify the potential sites of early atherosclerosis. A new noninvasive ultrasonic method implemented with coded excitation techniques was utilized to improve WSS estimation accuracy and precision by providing high spatial and temporal resolution. WSS measurement errors were quantified in a model system by scanning a linearly varying WSS field (0.3 to 1.9 Pa) within a flow chamber. A 13-bit optimal code (Opt) was found to be most effective in reducing bias and standard deviation in WSS estimates down to approximately 10% and approximately 8%. The measurement errors slowly increased with input WSS for all imaging pulses. The expression of endothelial cellular adhesion molecules vascular cell adhesion molecule-1 (VCAM-1) and endothelial-leukocyte adhesion molecule-1 (E-selectin) was investigated over a similar shear range (0 to 1.6 Pa) to study the impact of relating shear-mediated cellular adhesion molecule (CAM) expression to inaccuracies in WSS measurements. We quantified this influence as the prediction error, which accounts for the ultrasonic measurement errors and the sensitivity of CAM expression within certain shear ranges. The highest prediction errors were observed at WSS <0.8 Pa, where CAM expression is most responsive to WSS. The results emphasize the importance of minimizing estimation errors, especially within low shear regions. Preliminary two-dimensional in vivo shear imaging is also presented to provide information about the spatial heterogeneity in arterial WSS distribution.
动脉粥样硬化病变优先起源于承受低壁面切应力(WSS)和反向血流模式的动脉区域。因此,常规监测动脉WSS可能有助于识别早期动脉粥样硬化的潜在部位。一种采用编码激励技术的新型非侵入性超声方法,通过提供高空间和时间分辨率,用于提高WSS估计的准确性和精度。通过在流动腔内扫描线性变化的WSS场(0.3至1.9 Pa),在模型系统中对WSS测量误差进行了量化。发现一个13位的最佳编码(Opt)在将WSS估计中的偏差和标准差降低到约10%和约8%方面最为有效。对于所有成像脉冲,测量误差随着输入WSS的增加而缓慢增加。在类似的切应力范围(0至1.6 Pa)内研究了内皮细胞粘附分子血管细胞粘附分子-1(VCAM-1)和内皮-白细胞粘附分子-1(E-选择素)的表达,以研究切应力介导的细胞粘附分子(CAM)表达与WSS测量不准确之间的关系。我们将这种影响量化为预测误差,它考虑了超声测量误差以及在特定切应力范围内CAM表达的敏感性。在WSS <0.8 Pa时观察到最高的预测误差,此时CAM表达对WSS最敏感。结果强调了将估计误差最小化的重要性,特别是在低切应力区域内。还展示了初步的二维体内切应力成像,以提供有关动脉WSS分布空间异质性的信息。