血管周围脂肪组织在动脉粥样硬化中的研究进展
Research Progress of Perivascular Adipose Tissue in Atherosclerosis
DOI: 10.12677/ACM.2024.141247, PDF, HTML, XML, 下载: 84  浏览: 149 
作者: 吴 月, 邢 艳*:新疆医科大学第一附属医院影像中心,新疆 乌鲁木齐
关键词: 脂肪组织动脉粥样硬化血管周围脂肪衰减指数影像组学Adipose Tissue Atherosclerosis Perivascular Fat Attenuation Index Imagomics
摘要: 血管周围脂肪组织(PVAT)包围大部分脉管系统,可以调节血管稳态并且影响动脉粥样硬化的过程。最近的研究表明,在血管壁及其PVAT之间存在双向信号通路,这在心血管诊断和治疗中具有深远的意义。血管炎症在动脉粥样硬化进展和斑块破裂中其主要作用,冠状动脉CT血管造影(CCTA)通过分析冠脉周围脂肪组织(PCAT)密度的变化随之提出一种可以检测冠状动脉炎症的生物标记物——血管周围脂肪衰减指数(FAI),由于冠状动脉硬化还与不良纤维化和血管重构有关,通过分析PCAT细微的组织结构变化提出了放射组学特征,其有望最大化CCTA的诊断和预后效果。在本综述中,我们首先阐述了脂肪组织、炎症及动脉粥样硬化之间的关系,随后我们描述了血管周围脂肪组织和心血管系统之间相互作用的双向作用,介绍了基于CCTA的影像学成像用于心血管风险分层的进展。
Abstract: Perivascular adipose tissue (PVAT) surrounds most of the vasculature and can regulate vascular homeostasis and influence the process of atherosclerosis. Recent studies have shown that there is a bidirectional signaling pathway between blood vessel walls and their PVAT, which has profound implications in cardiovascular diagnosis and therapy. Vascular inflammation plays a major role in the progression of atherosclerosis and plaque rupture. Coronary CT angiography (CCTA) proposes a biomarker that can detect coronary inflammation, the perivascular fat attenuation index (FAI), by analyzing the changes in the density of pericoronary adipose tissue (PCAT). Since coronary arterio-sclerosis is also associated with adverse fibrosis and vascular remodeling, radiomic features are proposed by analyzing subtle structural changes in PCAT, which are expected to maximize the di-agnostic and prognostic effects of CCTA. In this review, we first describe the relationship between adipose tissue, inflammation, and atherosclerosis, then we describe the bidirectional interaction between perivascular adipose tissue and the cardiovascular system, and we present advances in CCTA-based imaging for cardiovascular risk stratification.
文章引用:吴月, 邢艳. 血管周围脂肪组织在动脉粥样硬化中的研究进展[J]. 临床医学进展, 2024, 14(1): 1729-1735. https://doi.org/10.12677/ACM.2024.141247

1. 引言

冠状动脉疾病(Coronary artery disease, CAD)是老年人群中的常见疾病,目前仍是世界上发病率和死亡率的第一大原因 [1] ,所以迫切需要新的工具来预测冠心病的不良后果和风险分层。已有研究证明血管炎症在冠状动脉粥样硬化中起着重要作用 [2] ,冠状动脉炎症的检测及研究对于心血管风险分层及治疗具有重要意义。在目前的临床实践中,炎症既可以用血液生物标志物来表示,也可以应用影像学成像来描述,但前者往往缺乏特异性。正电子发射计算机断层扫描(PET/CT)是评估动脉粥样硬化炎症的金标准,可无创、定量测量动脉粥样硬化靶组织中的炎症水平 [3] 。

血管周围脂肪组织(Perivascular Adipose Tissue, PVAT)在心血管疾病发生机制中扮演着不可或缺的角色,具有重要的代谢和血管保护功能 [4] 。根据血管炎症影响PVAT的信号改变,从而影响PVAT形态的改变,基于冠状动脉CT血管造影(Coronary computed tomography angiography, CCTA)的血管周围脂肪衰减指数(Fat attenuation index, FAI)及PVAT影像组学随之被提出,这是一种能够无创、便捷及高效率诊断高危心血管疾病的生物标志物,对预测不稳定斑块及高危CAD患者提供了巨大价值 [5] [6] [7] [8] 。在本综述中,我们首先阐述脂肪组织的作用机制、炎症与冠脉粥样硬化之间的关系,随后关注PCAT对冠脉粥样硬化的促成机制,并总结基于CCTA的影像学标记物对于冠脉粥样硬化的检测。

2. 脂肪组织的病理生理功能

脂肪组织(Adipose Tissue, AT)被认为是邻近器官的脂肪保护垫,或是被动的能量储存库,脂肪组织堆积引起的过度肥胖是心血管疾病和代谢综合征的独立危险因素 [9] [10] 。体重指数(BMI)是衡量肥胖的传统指标,尽管BMI这一因素被广泛使用,但它未能考虑到AT质量和分布的差异,而这些差异现在被确定为其心脏代谢作用的关键决定因素 [11] 。

脂肪组织根据颜色分类主要由白色脂肪组织和棕色脂肪组织所组成 [12] [13] 。近年来,脂肪组织作为一种重要的内分泌器官,产生并储存大量的生物活性分子,包括脂肪因子、炎性细胞因子和无机分子 [14] [15] [16] [17] 。白色脂肪由于过量的脂质累积,有害脂肪因子和炎性细胞因子分泌增加,从而进入血液循环损害血管内皮的功能 [18] [19] ,而棕色脂肪可以通过解偶联氧化,吸收脂质产生热量,防止脂质在白色脂肪和其他器官中储存 [20] 。由此可见,功能失调的白色脂肪组织可能促进动脉粥样硬化的发展,而棕色脂肪组织的激活可能保护动脉粥样硬化的发展。

除了根据脂肪组织的颜色分类,脂肪组织还可以根据解剖位置分类。血管周围脂肪组织围绕在血管周围,由于其在解剖学上接近血管壁,已被确定为心血管稳态和疾病的关键参与者 [21] ,在心血管疾病中具有独特的生物学意义。冠脉周围脂肪组织与冠状动脉血管直接接触,并且靠近动脉平滑肌细胞,同样可能影响血管稳态和冠状动脉粥样硬化,所以为了降低心血管疾病的患病率和致死率,对PCAT研究显得尤为重要 [22] 。

3. 炎症与动脉粥样硬化的关系

功能失调的PVAT可能会导动脉粥样硬化的发生和发展,而炎症会导致PVAT的功能失调,从而产生脂肪因子、细胞因子等生物活性因子。大量的研究已经阐明了动脉粥样硬化中炎症的分子机制,血管炎症几乎在动脉粥样硬化过程的每个阶段都起着关键作用,从疾病早期发展到斑块破裂和临床事件的发展 [23] [24] 。血管炎症是由内皮细胞的机械应力引起的,并且血液中ILD含量越高,炎症发生的概率就越高。为了应对这些压力,血管内皮表达产生免疫细胞,并释放出促炎细胞因子,如INF-α、IL-1、IL-6和干扰素-γ,随后单核细胞分化为巨噬细胞,巨噬细胞吸收氧化的ILD形成泡沫细胞,最终与平滑肌细胞增生一同促进动脉粥样硬化斑块的形成 [23] 。最近,Canakinumab抗炎血栓结局研究试验的结果显示,使用靶向IL-1b的治疗性单克隆抗体Canakinumab可显著降低高炎症风险,并且稳定冠状动脉疾病患者的心血管事件的发生 [2] 。另外,病理学研究表明,易损的冠状动脉斑块具有破裂的危险,Lin A等人的研究中已经证明了炎症参与斑块破裂的发生 [24] 。炎症是动脉粥样硬化形成的关键特征,能够准确检测血管炎症的方法将有助于更好地进行心血管风险分层,并实施适当的预防策略。

4. 炎症的无创检测

炎症参与动脉粥样硬化的发病机制,血管炎症的无创检测在心血管医学中具有无可替代的地位 [25] ,许多研究报道炎症的各种生物标志物不仅可以识别出未来心血管事件的高风险患者,并启动适当的风险降低策略,还可以预测表面健康的个体。高灵敏度试验(hsCRP)测量C-反应蛋白(CRP)可以独立于传统危险因素预测未来心血管事件,并且hsCRP的心血管危险程度与高脂血症或高血压等传统危险因素一样大 [26] 。在心血管风险评估中,加入hsCRP会对提高未来整体风险的预测 [27] 。除了hsCRP外,IL-6也与心血管风险相关,许多前瞻性队列研究表明,IL-6独立于传统心血管危险因素 [28] 。IL-1可以诱导包括IL-6在内的多种继发性炎症细胞因子的合成和表达,虽然没有流行病学研究证明IL-1b是心血管风险的生物标志物,但大量研究表明,IL-1b在动脉粥样硬化的发病过程中起着至关重要的作用 [29] 。

然而,这些炎症因子指标对CAD缺乏特异性 [30] ,冠状动脉炎症的具体评估可以通过影像成像的方式来实现。PET/CT可以检测冠心病潜在的冠状动脉炎症,如18F-氟脱氧葡萄糖PET/CT,通过摄取高代谢活性细胞中的放射性示踪剂来测量炎症活动 [31] ,但这也不是冠状动脉炎症所特有的,不能提供关于人类冠状动脉血管炎症的可靠信息,并且其具有昂贵的费用、高辐射以及采集时间长等缺陷,这些局限性使得PET/CT在实际生活中不作为常规扫描方式去筛查具有冠脉炎症的冠心病患者,所以研究学者迫切的想通过一种无创且快速的方式去提高冠状动脉的检测效率。

5. 血管周围脂肪衰减指数作为血管炎症的指标

脂肪细胞大小和细胞内脂质含量在组织水平上驱动水和脂质含量之间的平衡。由于血管壁与PVAT之间存在双向信号通路,当炎症释放因子扩散到PVAT时,使得邻近PVAT表型发生切换,从而脂肪细胞由脂相向水相转化,PVAT微环境中的“恶病质”,导致了血管周围脂质积累形成梯度改变,在靠近发炎的血管壁的地方有更高的水/脂比 [32] 。血管周围脂肪衰减被定义为位于与冠状动脉周围相关血管直径相等的血管外壁径向距离内的所有含脂肪组织体素的加权平均衰减。FAI作为是一种CT衍生的度量,可以通过检测PVAT衰减的梯度来追踪PVAT的表型变化,并作为血管炎症的传感器 [32] [33] 。冠状动脉周围FAI是一种通过分析常规CCTA图像来评估冠状动脉炎症的一种无创新方法。

基于CCTA的FAI目前在心血管疾病的诊断中发挥了很大的作用,并且已有大量研究表明其在检测炎症、评估冠脉斑块符合、预测不良心血管事件的发生等方面都具有出色的表现。Oikonomou EK在血管周围FAI预测临床结果的能力研究中,通过提供冠状动脉炎症的定量测量,确定了高血管周围FAI值(≥−70.1 HU)是心脏死亡率增加的一个指标,并且证明了在右冠状动脉周围测量血管周围FAI时,可以预测全因心脏死亡率且高于目前的风险分层方法 [33] 。Marwan等人在利用血管内超声筛选含有纤维斑块、富含脂质斑块以及无斑块的冠状动脉节段中发现,含有斑块的PCAT的平均CT衰减为−34 ± 14 (HU),而无斑块段的平均CT衰减为−56 ± 16 HU,这表明含有不同斑块类型的PCAT,其代谢活性更高的脂肪组织可能对冠状动脉血管产生局部影响,从而促进动脉粥样硬化 [34] 。

血管炎症驱动冠状动脉粥样硬化的发展和易损斑块的破裂,导致急性冠状动脉综合征的发生。目前,有许多研究表明,FAI可能是识别高风险斑块的指标。Goeller等人发现与ACS患者罪犯斑块周围的冠状动脉CT衰减增加,结合定量高风险斑块特征和PCAT衰减可以更可靠地识别易损斑块 [35] 。Zhang等人在进行相似的实验中发现,FAI被认为是冠状动脉炎症的一种新的成像生物标志物,与易损斑块特征和狭窄严重程度相关 [36] 。Gaibazzi等人利用PCAT的FAI区分炎症性和非炎症性冠状动脉状态时,纳入了106例MINOCA/TTS患者,结果显示平均FAI平均衰减为−68.37 ± 8.29 HU,而对照组为−78.03 ± 6.2HU (P < 0.0001),这表明在MINOCA和TTS患者中,CCTA不仅能够检测血管造影不可见的动脉粥样硬化斑块,而且可以通过PCAT的FAI平均衰减测量来扩大其诊断率,以表征冠状动脉周围脂肪组织 [37] 。将血管周围FAI整合到标准的临床CCTA报告中,有可能将该成像技术从一种用于排除解剖性冠状动脉疾病的方法推进为一种动态心脏风险分层工具。

6. 影像组学在心血管疾病中的应用

影像组学的概念最早是在2012年Lambin和他的同事首次提出,从图像中提取了人类肉眼无法观察到的定量特征,并将有预测价值的特征引入机器学习模型,以提供准确的风险分层 [38] ,这不仅可用于指导临床决策,还可帮助鉴别诊断和预测治疗结果。最开始,影像组学是用于肿瘤的诊断及预测,但随着人工智能的提升,影像组学还可以用于预测心血管疾病中的高危患者或发现早期冠心病患者,现在已有多项研究证实。

除了前文所述FAI可以识别冠脉易损斑块,PCAT的影像组学同样可以识别易损斑块,并且具有比FAI更高的识别能力。Lin A等人在确定PCAT的影像组学能否区分稳定性心绞痛和急性心肌梗死患者的研究中发现,急性心肌梗死患者具有明显的PCAT放射组学表型,并且基于放射组学的模型在准确识别心肌梗死患者方面优于基于PCAT衰减的模型 [24] 。另外,还发现在心肌梗死后6个月,近端RCA周围或非罪魁祸首病变的PCAT放射谱无明显变化,这与FAI在使用治疗药物后随着疗效而变化不同 [5] 。Shang等人设计了一项回顾性研究,提取了107个放射组学特征,结果显示基于CCTA的冠状动脉周围脂肪组织放射组学特征可能具有预测3年内发生急性冠状动脉综合征的潜力,并且基于放射组学的综合评分在3年内识别未来急性冠脉综合征方面明显优于斑块评分 [39] 。PCAT影像组学作为一种新开发的影像标记物,还可以结合CT-FFR对病变血管的血流受限进行分析,结果显示PCAT影像组学比单纯解剖结构预测功能缺血的性能还要好,这避免了额外的辐射暴露和有创操作 [40] 。影像组学的应用前景广泛,虽然目前许多研究都证实了影像组学在疾病诊疗过程中的价值,但在应用于临床时还需要大量的实验。

7. 总结与展望

血管周围脂肪组织与血管壁之间存在复杂的双向相互作用,血管炎症可导致动脉粥样硬化的发生和斑块的破裂,所以对血管炎症的检测至关重要。循环免疫标记物或PET/CT对血管炎症的检测固然有效,但需要考虑其局限性等因素。目前根据血管炎症反应导致PVAT发生表型变化这一特性,找到了现阶段最新的影像标记物——基于CCTA的FAI和影像组学,将及时对高危患者进行有效的干预措施并制定个体化诊疗方案。影像组学在心脏疾病的诊疗方面也已经有很多研究,不仅可以通过影像组学识别高危、易破裂的冠脉斑块,而且可以通过对心肌组织的检测筛选出病变心肌,还可以通过纹理分析对左心耳血栓进行识别。利用基于人工智能的影像组学对心脏疾病进行筛查,将会给医生和患者都带来巨大的益处。

NOTES

*通讯作者。

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