Department of Public Health and Clinical Medicine, Umeå University, 901 87, Umeå, Sweden.
Umeå University, Umeå, Sweden.
Int J Cardiovasc Imaging. 2020 Jun;36(6):1061-1068. doi: 10.1007/s10554-020-01801-z. Epub 2020 Mar 6.
Ultrasound examinations of atherosclerotic carotid plaques can be used to calculate risk markers associated with plaque vulnerability. Recent studies demonstrate significant inter-frame variability in risk markers. Here, we investigate risk marker variability in symptomatic plaques and its impact on reclassification of plaque vulnerability, as well as its association with the shape of the temporal variation over the cardiac cycle.
56 patients with symptomatic carotid stenosis were included in this study. 88 plaques were identified and the plaque risk markers size (area), echogenicity (gray scale median, GSM) and heterogeneity (coarseness) were measured in all frames of ultrasound B-mode image sequences. Inter-frame variability was quantified using the coefficient of variation (CV).
Inter-frame variabilities of the risk markers were area CV 5-8%; GSM CV 4-7%; coarseness CV 8-15% and was in general significantly lower in large as compared to smaller plaques. The variability in GSM risk marker caused a reclassification of vulnerability in 30 to 38% of the plaques. Temporal variations in GSM with a heart rate periodic or drift/trending pattern were found in smaller plaques (< 26 mm), whereas random pattern was found in larger plaques. In addition, hypoechoic plaques (GSM < 25) were associated with cyclic variation pattern, independent of their size.
Risk marker variability causes substantial reclassification of plaque vulnerability in symptomatic patients. Inter-frame variation and its temporal pattern should be considered in the design of future studies related to risk markers.
动脉粥样硬化颈动脉斑块的超声检查可用于计算与斑块易损性相关的风险标志物。最近的研究表明,风险标志物存在显著的帧间变异性。在此,我们研究了有症状斑块中风险标志物的变异性及其对斑块易损性再分类的影响,并探讨了其与斑块在心动周期内时间变化形态的相关性。
本研究纳入了 56 例有症状颈动脉狭窄患者。共识别出 88 个斑块,并在所有超声 B 模式图像序列帧中测量了斑块风险标志物的大小(面积)、回声(灰度中位数,GSM)和异质性(粗糙度)。使用变异系数(CV)来量化帧间变异性。
风险标志物的帧间变异性为面积 CV 5-8%、GSM CV 4-7%、粗糙度 CV 8-15%,一般来说,较大斑块的变异性明显低于较小斑块。GSM 风险标志物的变异性导致 30%至 38%的斑块易损性重新分类。在较小的斑块(<26mm)中发现了 GSM 的时间变化具有心率周期性或漂移/趋势模式,而在较大的斑块中则发现了随机模式。此外,低回声斑块(GSM<25)与周期性变化模式相关,而与斑块大小无关。
风险标志物的变异性导致有症状患者的斑块易损性发生显著的再分类。在未来与风险标志物相关的研究设计中,应考虑帧间变异性及其时间模式。