Norwegian University of Science and Technology, Department of Electronics and Telecommunications, 7034 Trondheim, Norway.
J Biomed Opt. 2011 Feb;16(2):026011. doi: 10.1117/1.3540657.
Vulnerable plaques constitute a risk for serious heart problems, and are difficult to identify using existing methods. Hyperspectral imaging combines spectral- and spatial information, providing new possibilities for precise optical characterization of atherosclerotic lesions. Hyperspectral data were collected from excised aorta samples (n = 11) using both white-light and ultraviolet illumination. Single lesions (n = 42) were chosen for further investigation, and classified according to histological findings. The corresponding hyperspectral images were characterized using statistical image analysis tools (minimum noise fraction, K-means clustering, principal component analysis) and evaluation of reflectance/fluorescence spectra. Image analysis combined with histology revealed the complexity and heterogeneity of aortic plaques. Plaque features such as lipids and calcifications could be identified from the hyperspectral images. Most of the advanced lesions had a central region surrounded by an outer rim or shoulder-region of the plaque, which is considered a weak spot in vulnerable lesions. These features could be identified in both the white-light and fluorescence data. Hyperspectral imaging was shown to be a promising tool for detection and characterization of advanced atherosclerotic plaques in vitro. Hyperspectral imaging provides more diagnostic information about the heterogeneity of the lesions than conventional single point spectroscopic measurements.
易损斑块是严重心脏问题的一个风险因素,目前使用的方法很难识别。高光谱成像是一种结合光谱和空间信息的技术,为动脉粥样硬化病变的精确光学特性提供了新的可能性。使用白光和紫外线照明从离体主动脉样本中采集高光谱数据(n=11)。选择了 42 个单独的病变进行进一步研究,并根据组织学发现进行分类。使用统计图像分析工具(最小噪声分数、K-均值聚类、主成分分析)和反射/荧光光谱评估对相应的高光谱图像进行了特征描述。图像分析与组织学相结合揭示了主动脉斑块的复杂性和异质性。可以从高光谱图像中识别出斑块的特征,如脂质和钙化。大多数晚期病变的中心区域周围都有一个外边缘或斑块的肩部区域,这被认为是易损病变的一个弱点。这些特征可以在白光和荧光数据中识别出来。高光谱成像被证明是一种很有前途的体外检测和表征动脉粥样硬化斑块的工具。与传统的单点光谱测量相比,高光谱成像提供了更多关于病变异质性的诊断信息。