Ex vivo characterization of human atherosclerotic iliac plaque components using cryo-imaging.
Ex vivo characterization of human atherosclerotic iliac plaque components using cryo-imaging.
复制标题
使用冷冻成像的人动脉粥样硬化小斑块成分的体内表征。
DOI：
10.1111/j.1365-2818.2008.02138.x
复制
发表时间：
2008-12
影响因子：
2
通讯作者：
Wilson DL
中科院分区：
文献类型：
--
作者：
Nguyen MS;Salvado O;Roy D;Steyer G;Stone ME;Hoffman RD;Wilson DL
我们用一种新的冷冻成像系统代替通常用于成像验证和研究终点的标准组织学方法来表征动脉粥样硬化斑块成分。我们的目标是从新鲜身体标本中快速准确地识别斑块组织类型，对于大标本(长达4厘米的血管节段)，三维快速(小于5小时)。设计了一项以组织学为金标准的单盲验证性研究，以确定冷冻成像组织类型的敏感性、特异性和评价者间一致性(Fleiss‘Kappa)。六名天真的人类评分员在接受培训后，在36组冷冻图像中识别出344个组织类型样本。组织类型敏感性如下：外膜、基质相关、平滑肌细胞内长、外弹力板、内弹力板、纤维化、致密钙化和出血的敏感性大于90%；脂类和轻度钙化的敏感性大于80%；胆固醇裂隙的敏感性大于50%。所有组织类型的特异性均大于95%。结果令人信服地表明，冷冻成像可以用来准确地识别大多数组织类型。如果将冷冻成像数据输入可视化软件，就可以生成斑块的三维效果图，以可视化和量化斑块成分。
We characterized atherosclerotic plaque components with a novel cryo-imaging system in lieu of standard histological methods commonly used for imaging validation and research endpoints. We aim to accurately identify plaque tissue types from fresh cadaver specimens rapidly (less than 5 h) in three dimensions for large specimens (up to 4 cm vessel segments). A single-blind validation study was designed to determine sensitivity, specificity and inter-rater agreement (Fleiss’ Kappa) of cryo-imaging tissue types with histology as the gold standard. Six naïve human raters identified 344 tissue type samples in 36 cryo-image sets after being trained. Tissue type sensitivities are as follows: greater than 90% for adventitia, media-related, smooth muscle cell ingrowth, external elastic lamina, internal elastic lamina, fibrosis, dense calcification and haemorrhage; greater than 80% for lipid and light calcification; and greater than 50% for cholesterol clefts. Specificities were greater than 95% for all tissue types. The results demonstrate convincingly that cryo-imaging can be used to accurately identify most tissue types. If the cryo-imaging data are entered into visualization software, three-dimensional renderings of the plaque can be generated to visualize and quantify plaque components.
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影响因子：
3.4
作者：
PRENTICE, AI
通讯作者：
PRENTICE, AI
影响因子：
37.8
作者：
Fleiner, M;Kummer, M;Biedermann, BC
通讯作者：
Biedermann, BC
DOI：
10.1161/01.atv.0000253907.51681.0e
发表时间：
2007-02-01
影响因子：
8.7
作者：
Granada, Juan F.;Wallace-Bradley, David;Kaluza, Greg L.
通讯作者：
Kaluza, Greg L.
DOI：
10.1161/01.atv.0000240518.90124.57
发表时间：
2006-10-01
影响因子：
8.7
作者：
de Weert, Thomas T.;Ouhlous, Mohamed;van der Lugt, Aad
通讯作者：
van der Lugt, Aad
影响因子：
37.8
作者：
Larose, E;Yeghiazarians, Y;Ganz, P
通讯作者：
Ganz, P