Development of real-time color intravascular ultrasound using Wavelet Analysis

背景与对象：小波分析是一种新的数学模型，用于评估时间序列信号几何剖面的局部变化。我们之前报道了血管内超声（IVUS）视频图像的小波分析可能有助于检测体内富含脂质的动脉粥样硬化斑块区域。本研究的目的是利用小波分析开发实时彩色血管内超声。方法：采用40MHz IVUS导管对32例人尸检中经福尔马林固定的非钙化动脉粥样硬化斑块进行IVUS信号采集。利用Daubechies-2小波对图像进行小波分析，得到小波尺度x-y平面重构的小波与IVUS导管距离的相关系数。结果：组织学检查发现26个斑块有脂质堆积段。当进行小波分析时，鸟瞰图显示，与其他类型的斑块相比，含脂斑块的模式明显不同。使用小波分析，检测脂质斑块的灵敏度为81%(26/32)，特异性为80%。

Background and Objects : Wavelet analysis is a new mathematical model for assessing local changes in geometrical profile of time-series signals. We previously reported that Wavelet analysis of video-images of intravascular ultrasound (IVUS) might be useful for detecting lipid-rich area with atherosclerotic plaque in vivo. The purpose of this study is the development of real-time color intravascular ultrasound using Wavelet Analysis. Methods : IVUS signals were acquired from 32 formalin-fixed noncalcifled atherosclerotic plaques from human necropsy by a 40MHz IVUS catheter. Wavelet analysis of these images was performed with Daubechies-2 wavelet to obtain the correlation coefficient with the wavelet reconstructed over the x-y plane of the wavelet scale and the distance from IVUS catheter. Results : Histological examination revealed lipid-laden segment in 26 plaques. When performing a wavelet analysis, the bird eye view revealed an apparently different pattern in lipid-laden plaque compared to other types of plaque. Using this wavelet analysis, the lipid-laden plaque could be detected with sensitivity of 81% (26/32) and specificity of 80%.