Di Vito Luca, Agozzino Manuela, Marco Valeria, Ricciardi Andrea, Concardi Monica, Romagnoli Enrico, Gatto Laura, Calogero Giordano, Tavazzi Luigi, Arbustini Eloisa, Prati Francesco
Interventional Cardiology Unit, San Giovanni Addolorata Hospital, Via dell'Amba Aradam 8, 00184 Rome, Italy CLI Foundation, Rome, Italy.
Centre for Inherited Cardiovascular Diseases, Policlinico San Matteo, Pavia, Italy.
Eur Heart J Cardiovasc Imaging. 2015 Jul;16(7):807-13. doi: 10.1093/ehjci/jeu307. Epub 2015 Jan 14.
Vulnerable plaques are characterized by a high macrophage content. We investigated the optical coherence tomography (OCT) capability of identifying coronary plaque macrophage presence using tissue property indexes.
Fifteen epicardial coronary arteries were imaged by OCT and subsequently analysed by histology. Correlating OCT-histological sections were identified and regions of interest (ROIs) were selected on both atherosclerotic plaques and normal appearing vessel tracts. OCT-derived tissue property indexes named normalized standard deviation (NSD), signal attenuation, and granulometry index were applied on ROIs to identify inflamed ROIs defined as a macrophage percentage >10 by histology. Forty-three paired samples (OCT frame and histology section) were considered suitable as ROIs for analysis. Eleven out of 43 ROIs were considered inflamed and the remaining 32 ROIs were non-inflamed on the basis of histological count of macrophage percentage. All OCT-derived tissue property indexes were positively correlated with macrophage percentage (P = 0.0001 for all). Receiver operating characteristic curve analysis showed that NSD, granulometry index, and signal attenuation had a significant area under the curve (area = 0.906, 0.804, and 0.793, respectively). A two-step algorithm requiring to first apply NSD with a cut-off value of 0.0570 followed by granulometry index was able to identify an inflamed ROI with a sensitivity of 100% and a specificity of 96.8%.
OCT was able to identify and quantify macrophage presence in coronary artery specimens using tissue property indexes. NSD and granulometry index showed the highest accuracy in identifying a significant plaque inflammation, especially if used together in a two-step algorithm.
易损斑块的特征是巨噬细胞含量高。我们研究了利用组织特性指标通过光学相干断层扫描（OCT）识别冠状动脉斑块中巨噬细胞存在情况的能力。
对15条心外膜冠状动脉进行OCT成像，随后进行组织学分析。确定了OCT与组织学相关的切片，并在动脉粥样硬化斑块和外观正常的血管段上选择了感兴趣区域（ROI）。将OCT得出的名为归一化标准差（NSD）、信号衰减和粒度指数的组织特性指标应用于ROI，以识别经组织学定义为巨噬细胞百分比>10%的炎症性ROI。43对样本（OCT图像帧和组织学切片）被认为适合作为ROI进行分析。根据巨噬细胞百分比的组织学计数，43个ROI中有11个被认为是炎症性的，其余32个ROI是非炎症性的。所有OCT得出的组织特性指标均与巨噬细胞百分比呈正相关（所有P = 0.0001）。受试者工作特征曲线分析表明，NSD、粒度指数和信号衰减的曲线下面积显著（面积分别为0.906、0.804和0.793）。一种两步算法，首先应用截断值为0.0570的NSD，然后应用粒度指数，能够识别炎症性ROI，灵敏度为100%，特异性为96.8%。
OCT能够利用组织特性指标识别和量化冠状动脉标本中的巨噬细胞存在情况。NSD和粒度指数在识别显著的斑块炎症方面显示出最高的准确性，特别是在两步算法中一起使用时。
