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一种用于研究动脉粥样硬化斑块纤维帽中胶原蛋白与脂质比例的荧光寿命成像分类方法。

A fluorescence lifetime imaging classification method to investigate the collagen to lipid ratio in fibrous caps of atherosclerotic plaque.

作者信息

Phipps Jennifer E, Sun Yinghua, Fishbein Michael C, Marcu Laura

机构信息

Department of Biomedical Engineering, University of California Davis, Davis, California 95616, USA.

出版信息

Lasers Surg Med. 2012 Sep;44(7):564-71. doi: 10.1002/lsm.22059. Epub 2012 Aug 6.

Abstract

BACKGROUND AND OBJECTIVE

This study describes a novel fluorescence lifetime imaging (FLIM) classification method to determine the ratio of collagen to lipid content in the fibrous cap of atherosclerotic plaques. Additionally, an analytical process to assess risk of plaque rupture based on this ratio is proposed. Collagen to lipid ratio has been shown to be an important parameter to evaluate structural integrity of the fibrous cap. FLIM and other time-resolved fluorescence techniques have recently been applied to the study of atherosclerosis based on the ability to assess biochemical composition.

STUDY DESIGN/MATERIALS AND METHODS: Autofluorescence of specimens retrieved during carotid endarterectomy procedures was measured through three optical filters, F377: 377/50 nm, F460: 460/66 nm, and F510: 510/84 nm (center wavelength/bandwidth). A Laguerre deconvolution technique was used for the evaluation of fluorescence decay dynamics. The resulting decay parameters (average fluorescence lifetime and 4 Laguerre coefficients at each of the recorded bandwidths) were used for sample characterization. Linear discriminant analysis (LDA) was used to classify each image into collagen or lipid-rich regions based on these parameters. Ultimately, a risk-level was assigned based on the ratio of collagen to lipid on the surface of the fibrous cap.

RESULTS

FLIM images were acquired in 18 carotid plaque specimens at 43 locations. Classification of collagen and lipid-rich regions within the fibrous cap was performed with sensitivity and specificity of 80% and 82%, respectively.

CONCLUSIONS

Results from this study show that an LDA method of classifying regions of FLIM images of carotid plaque into collagen and lipid-rich regions is capable of being automated and used to rate the risk of plaque rupture based on autofluorescence decay dynamics and without the need for fluorescence intensity or contrast agents.

摘要

背景与目的

本研究描述了一种新型荧光寿命成像(FLIM)分类方法,用于确定动脉粥样硬化斑块纤维帽中胶原蛋白与脂质含量的比例。此外,还提出了一种基于该比例评估斑块破裂风险的分析流程。胶原蛋白与脂质的比例已被证明是评估纤维帽结构完整性的重要参数。基于评估生化成分的能力,FLIM和其他时间分辨荧光技术最近已应用于动脉粥样硬化的研究。

研究设计/材料与方法:通过三个光学滤光片测量颈动脉内膜切除术过程中获取的标本的自发荧光,滤光片分别为F377:377/50nm、F460:460/66nm和F510:510/84nm(中心波长/带宽)。采用拉盖尔反卷积技术评估荧光衰减动力学。所得衰减参数(平均荧光寿命以及每个记录带宽处的4个拉盖尔系数)用于样本表征。基于这些参数,使用线性判别分析(LDA)将每个图像分类为富含胶原蛋白或脂质的区域。最终,根据纤维帽表面胶原蛋白与脂质的比例确定风险等级。

结果

在18个颈动脉斑块标本的43个位置采集了FLIM图像。对纤维帽内富含胶原蛋白和脂质的区域进行分类,灵敏度和特异性分别为80%和82%。

结论

本研究结果表明,一种将颈动脉斑块FLIM图像区域分类为富含胶原蛋白和脂质区域的LDA方法能够实现自动化,并用于基于自发荧光衰减动力学对斑块破裂风险进行评级,且无需荧光强度或造影剂。

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