Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada.
Ultrasound Med Biol. 2010 Jan;36(1):95-110. doi: 10.1016/j.ultrasmedbio.2009.08.005.
Quantitative measurements of the progression (or regression) of carotid plaque burden are important in monitoring patients and evaluating new treatment options. We previously developed a quantitative metric to analyze changes in carotid plaque morphology from 3-D ultrasound (US) on a point-by-point basis. This method requires multiple segmentations of the arterial wall and lumen boundaries to obtain the local standard deviation (SD) of vessel-wall-plus-plaque thickness (VWT) so that t-tests could be used to determine whether a change in VWT is statistically significant. However, the requirement for multiple segmentations makes clinical trials laborious and time-consuming. Therefore, this study was designed to establish the relationship between local segmentation SD and local signal difference on the arterial wall and lumen boundaries. We propose metrics to quantify segmentation SD and signal difference on a point-by-point basis, and studied whether the signal difference at arterial wall or lumen boundaries could be used to predict local segmentation SD. The ability to predict the local segmentation SD could eliminate the need of repeated segmentations of a 2-D transverse image to obtain the local segmentation standard deviation, thereby making clinical trials less laborious and saving time. Six subjects involved in this study were associated with different degrees of atherosclerosis: three carotid stenosis subjects with mean plaque area >3 cm(2) and >60% carotid stenosis were involved in a clinical study evaluating the effect of atorvastatin, a cholesterol-lowering and plaque-stabilizing drug; and three subjects with carotid plaque area >0.5 cm(2) were subjects with moderate atherosclerosis. Our results suggest that when local signal difference is higher than 8 greyscale value (GSV), the local segmentation SD stabilizes at 0.05 mm and is thus predictable. This information provides a target value of local signal difference on the arterial boundaries that should be achieved to obtain an accurate prediction of local segmentation SD. (E-mail: bcychiu@alumni.uwo.ca).
定量测量颈动脉斑块负荷的进展（或消退）对于监测患者和评估新的治疗选择非常重要。我们之前开发了一种定量指标，用于从 3D 超声（US）上逐点分析颈动脉斑块形态的变化。该方法需要对动脉壁和管腔边界进行多次分割，以获得血管壁加斑块厚度（VWT）的局部标准差（SD），以便 t 检验可以用于确定 VWT 的变化是否具有统计学意义。然而，多次分割的要求使得临床试验既费力又耗时。因此，本研究旨在建立局部分割 SD 与动脉壁和管腔边界的局部信号差异之间的关系。我们提出了用于逐点量化分割 SD 和信号差异的指标，并研究了动脉壁或管腔边界的信号差异是否可用于预测局部分割 SD。能够预测局部分割 SD 可以消除对 2D 横断图像进行重复分割以获得局部分割标准差的需要，从而使临床试验不那么费力并节省时间。本研究涉及 6 名受试者，他们与不同程度的动脉粥样硬化有关：3 名颈动脉狭窄受试者，平均斑块面积>3cm2 和>60%颈动脉狭窄，参与了一项评估阿托伐他汀（一种降低胆固醇和稳定斑块的药物）效果的临床试验；3 名颈动脉斑块面积>0.5cm2 的受试者为中度动脉粥样硬化患者。我们的结果表明，当局部信号差异高于 8 个灰度值（GSV）时，局部分割 SD 稳定在 0.05mm，因此可以预测。该信息提供了动脉边界上的局部信号差异的目标值，应该达到该值以获得局部分割 SD 的准确预测。（电子邮件：bcychiu@alumni.uwo.ca）。
