Department of Neurology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Department of Neurosurgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Ann Clin Transl Neurol. 2023 Dec;10(12):2334-2346. doi: 10.1002/acn3.51923. Epub 2023 Oct 12.
Risk stratification plays a critical role in patients with asymptomatic carotid atherosclerotic stenosis. Heavy macrophage infiltration (HMC) is an important factor of plaque destabilization. However, in vivo imaging technologies and screening criteria for HMC remain limited. We aimed to (i) introduce algorithms for in vivo detection of macrophage infiltrations using optical coherence tomography (OCT) and (ii) to investigate the threshold of HMC and its association with plaque vulnerability.
Ex vivo OCT images were co-registered with histopathology in 282 cross-sectional pairs from 19 carotid endarterectomy specimens. Of these, 197 randomly selected pairs were employed to define the parameters, and the remaining 85 pairs were used to evaluate the accuracy of the OCT-based algorithm in detecting macrophage infiltrations. Clinical analysis included 93 patients receiving carotid OCT evaluation. The prevalence and burden of macrophage infiltration were analyzed. Multivariable and subgroup analysis were performed to investigate the association between HMC and plaque rupture.
The sensitivity and specificity of algorithm for detecting macrophage infiltration were 88.0% and 74.9%, respectively. Of 93 clinical patients, ruptured plaques exhibited higher prevalence of macrophage infiltration than nonruptured plaques (83.7% [36/43] vs 32.0% [16/50], p < 0.001). HMC was identified when the macrophage index was greater than 60.2 (sensitivity = 74.4%, specificity = 84.0%). Multivariable analysis showed that HMC and multiple calcification were independent risk factors for non-lipid-rich plaque rupture.
This study provides a novel approach and screening criteria for HMC, which might be valuable for atherosclerotic risk stratification.
风险分层在无症状颈动脉粥样硬化性狭窄患者中起着至关重要的作用。巨噬细胞浸润（HMC）是斑块不稳定的一个重要因素。然而，体内成像技术和 HMC 的筛选标准仍然有限。我们的目的是：（i）介绍使用光学相干断层扫描（OCT）检测巨噬细胞浸润的体内算法；（ii）研究 HMC 的阈值及其与斑块脆弱性的关系。
在 19 个颈动脉内膜切除术标本的 282 个横截面对中，将离体 OCT 图像与组织病理学进行配准。其中，197 对随机选择的对用于定义参数，其余 85 对用于评估基于 OCT 的算法检测巨噬细胞浸润的准确性。临床分析包括 93 名接受颈动脉 OCT 评估的患者。分析巨噬细胞浸润的患病率和负担。进行多变量和亚组分析，以研究 HMC 与斑块破裂之间的关系。
用于检测巨噬细胞浸润的算法的灵敏度和特异性分别为 88.0%和 74.9%。在 93 例临床患者中，破裂斑块的巨噬细胞浸润患病率高于非破裂斑块（83.7%[36/43] vs 32.0%[16/50]，p<0.001）。当巨噬细胞指数大于 60.2 时，可识别 HMC（灵敏度为 74.4%，特异性为 84.0%）。多变量分析显示，HMC 和多发性钙化是非富含脂质斑块破裂的独立危险因素。
本研究为 HMC 提供了一种新的方法和筛选标准，可能对动脉粥样硬化风险分层有价值。
