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多模态磁共振成像评估未破脑动脉瘤不稳定状态风险的研究进展
付其昌 张勇 刘朝 管生 程敬亮

Cite this article as: FU Q C, ZHANG Y, LIU C, et al. Progress in assessment of unstable state risk of unruptured cerebral aneurysms by multimodal MRI[J]. Chin J Magn Reson Imaging, 2023, 14(2): 163-167.本文引用格式:付其昌, 张勇, 刘朝, 等. 多模态磁共振成像评估未破脑动脉瘤不稳定状态风险的研究进展[J]. 磁共振成像, 2023, 14(2): 163-167. DOI:10.12015/issn.1674-8034.2023.02.029.


[摘要] MRI在未破脑动脉瘤(unruptured intracranial aneurysms, UIAs)不稳定状态风险的个体化评价中占有重要地位。MRI在UIAs中的应用首先是能够显示其形态学特征,MR血管成像(MR angiography, MRA)技术的成熟有效解决了这一问题。随着科技的进步,MRI可以提供UIAs的功能信息,MRA可能显示UIAs的血流动力学特征,高分辨MRI可能显示UIAs的动脉瘤壁病理学特征。近年来,人工智能(artificial intelligence, AI)有望满足医师在UIAs不稳定状态风险个体化评价中对更高准确性的需求。笔者将从UIAs形态学、动脉瘤壁病理学、血流动力学及AI等多个维度对多模态MRI在评价IAs不稳定风险中的应用价值进行综述,旨在为UIAs精准风险分层的研究提供参考。
[Abstract] MRI plays a vital role in the individualized evaluation of unstable state risk of unruptured intracranial aneurysms (UIAs). The initial step in using MRI in UIAs is to show the morphological traits. The maturity of MR angiography (MRA) effectively fixed this issue. With the advancement of science and technology, MRI can now provide functional information on UIAs. MR blood flow imaging may now reveal UIAs hemodynamic characteristics, and high-resolution MRI may show pathological features of the aneurysm wall. In recent years, artificial intelligence (AI) has had the potential to satisfy physicians' demands for greater precision in the tailored assessment of unstable state risk in UIAs. The author will go over the importance of multi-mode MRI in assessing the risk of aneurysm instability from UIAs morphology, aneurysm wall pathology, hemodynamics and AI to serve as a reference for the research on precise risk stratification of UIAs.
[关键词] 未破脑动脉瘤;磁共振成像;磁共振血管成像;人工智能;风险评价
[Keywords] unruptured intracranial aneurysms;magnetic resonance imaging;magnetic resonance angiography;artificial intelligence;risk evaluation

付其昌 1   张勇 1   刘朝 2   管生 2   程敬亮 1*  

1 郑州大学第一附属医院MRI科,郑州 450052

2 郑州大学第一附属医院神经介入科,郑州 450052

*通信作者:程敬亮,E-mail:fccchengjl@zzu.edu.cn

作者贡献声明::程敬亮设计本研究的方案,对稿件重要的智力内容进行了修改;付其昌起草和撰写稿件,获取、分析或解释本研究的数据/文献,并获得了国家自然科学基金青年项目资助;张勇、刘朝、管生获取、分析或解释本研究的数据,对稿件重要的智力内容进行了修改;全体作者都同意发表最后的修改稿,同意对本研究的所有方面负责,确保本研究的准确性和诚信。


基金项目: 国家自然科学基金 82202105
收稿日期:2022-10-17
接受日期:2023-02-13
中图分类号:R445.2  R739.41 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2023.02.029
本文引用格式:付其昌, 张勇, 刘朝, 等. 多模态磁共振成像评估未破脑动脉瘤不稳定状态风险的研究进展[J]. 磁共振成像, 2023, 14(2): 163-167. DOI:10.12015/issn.1674-8034.2023.02.029.

0 前言

       脑动脉瘤(intracranial aneurysms, IAs)是颅内主干分支动脉壁的浆果样病理性扩张,在成年人群中患病率为3.2%[1]。随着MR血管成像(MR angiography, MRA)等在临床实践中的广泛应用,IAs的检出率呈逐年增加的趋势[2]。因此对未破脑动脉瘤(unruptured intracranial aneurysms, UIAs)的研究有重要意义[3]。血流动力学异常与瘤壁病理学损伤之间的动态平衡导致了动脉瘤的发生、发展和破裂,即IAs的不稳定状态[4]。UIAs不稳定状态风险的个体化评价是临床工作中亟须解决的一项现实问题[5]。UIAs的不稳定状态风险因素包括患者相关的风险因素和动脉瘤相关的风险因素[6]。医学影像是评价IAs相关风险因素的基石,MRI在UIAs不稳定状态风险的个体化评价中占有重要地位。

       既往研究已经充分论证了MRA在UIAs诊断和随访中的价值(诊断UIAs的敏感度和特异度均在90%以上)[7]。除了结构信息外,最近的研究表明MRI还可以提供与UIAs不稳定状态风险密切相关的功能信息,如血流动力学及动脉瘤壁病理学信息。MRA可以反映IAs的血流动力学信息,高分辨MRI能够对IAs进行瘤壁病理学评价。基于数据科学的人工智能(artificial intelligence, AI)模型也有助于UIAs不稳定状态风险的个体化评价[8]。我们将从UIAs瘤腔形态学、动脉瘤壁病理学、血流动力学及AI等多个维度对多模态MRI在评价IAs不稳定风险中的应用价值作进一步综述,旨在为UIAs精准风险分层的研究提供参考。

1 IAs不稳定状态的瘤腔形态学风险因素

       MRA是显示IAs瘤腔形态学特征的主要成像方式,包括时间飞越MRA(time of flight magnetic resonance angiography, TOF-MRA)、相位对比MRA(phase contrast MRA, PC-MRA)、对比增强MRA(contrast-enhanced MRA, CE-MRA)和零回波时间MRA(zero echo time MRA, ZTE-MRA)等。

       TOF-MRA基于流体饱和效应的流入增强效应,通过脉冲激发静止组织的射频饱和抑制背景实现血管显影。TOF-MRA成像速度快,对小IAs的敏感度和特异度均在90%以上,巨大IAs由于血液流空效应则显影欠佳[9]。3D-TOF-MRA较2D-TOF-MRA成像效果好。PC-MRA基于梯度场中流动血液的相位变化原理,通过流速编码及相位变化抑制背景实现血管显影。PC-MRA成像速度慢并且分辨率较低,对小IAs的敏感度和特异度不高[10]。CE-MRA通过外源性对比剂缩短血液的T1值,利用快速T1加权成像(T1 weighted imaging, T1WI)序列显示血液内的T1弛豫变化实现血管显影。CE-MRA成像速度快,对小IAs和大IAs均能较好显影,但是外源性对比剂的应用可能导致过敏或肾毒性等不良反应[10]。ZTE-MRA通过结合连续动脉自旋标记技术和ZTE径向采集技术将标记的血液作为内源性对比剂,通过标记组和非标记组剪影抑制背景实现血管显影。ZTE-MRA对IAs能较好显影,但是成像速度较慢[11]。综上所述,MRA技术能够获得IAs的瘤腔形态学特征。

       IAs不稳定状态的形态学危险因素主要通过对特定人群(如欧洲人或日本人等)或病例对照研究获得,因此可能不适用于普通人群的动脉瘤患者。IAs不稳定状态的形态学危险因素主要包括位置、直径、不规则性、尺寸比(size ratio, SR)、纵横比(aspect ratio, AR)及数量等(图1)。

       IAs的位置与动脉瘤不稳定状态有关。PHASES评分研究提示,颈内动脉IAs出现不稳定状态的可能性最低,大脑前动脉、后交通动脉、后循环IAs出现不稳定状态的可能性最高,大脑中动脉IAs出现不稳定状态的可能性则位于二者之间[12]。IAs的直径与动脉瘤不稳定状态有关。IAs直径一般指动脉瘤瘤底部到动脉瘤瘤颈部的最大距离。既往研究均提示,IAs的直径越大,出现不稳定状态的可能性越高[13]。IAs的不规则性与动脉瘤不稳定状态有关。IAs的不规则性指动脉瘤呈分叶状或伴有子囊。ELAPSS评分等研究提示,形态不规则IAs出现不稳定状态的可能性较高[13]。IAs的SR指动脉瘤瘤体最大高度与载瘤动脉平均直径之比,其与动脉瘤不稳定状态有关。既往研究提示SR>3的IAs出现不稳定状态的可能性较高[14]。IAs的AR指动脉瘤高度与瘤颈宽度之比,其与动脉瘤不稳定状态有关。既往研究提示AR>1.06的IAs出现不稳定状态的可能性较高[15]。IAs的数量与动脉瘤不稳定状态有关。既往研究提示,多发动脉瘤出现不稳定状态的可能性较高[16]。因此,MRA能够有效评价IAs不稳定状态的瘤腔形态学风险因素。

图1  未破脑动脉瘤(UIAs)不稳定状态相关的风险因素(部分)。A1:UIAs的位置(依据PHASES评分)。UIAs不稳定状态风险与位置有关:颈内动脉的风险最低(绿色),后交通动脉的风险最高(红色)。动脉瘤的位置:1为脉络膜前动脉;2为眼动脉;3为前交通动脉;4为垂体上动脉;5为颈内动脉末端;6为大脑中动脉;7为后交通动脉;8为基底动脉;9为椎动脉与基底动脉结合处;10为小脑上动脉;11为椎动脉与基底动脉结合处;12为小脑前下动脉。A2:UIAs直径(依据PHASES评分)。UIAs不稳定状态风险与最大直径(Dmax)有关,直径分类:a为<5 mm;b为5.0~6.9 mm;c为7.0~9.9 mm;d为10.0~19.9 mm;e为≥20 mm。A3:UIAs 生长(在任何直径上生长>1 mm),生长的UIAs 不稳定状态风险增加。A4:UIAs 形态不规则(呈分叶状或伴有子囊),形态不规则的UIAs 不稳定状态风险增加1.5 倍。B:UIAs形态。尺寸比(SR)>3或纵横比(AR)>1.06的UIAs不稳定状态风险较高。SR=Hmax/[(PD1+PD2+PD3)/3],AR=H/ND。式中H为垂直于动脉瘤颈直径的高度;Hmax为动脉瘤最大高度;ND为动脉瘤颈直径;PD为载瘤动脉直径。C:钆剂增强VWI中动脉瘤壁强化。动脉瘤壁强化反映动脉瘤壁炎症,从而导致动脉瘤不稳定(生长或破裂)。

2 IAs不稳定状态的瘤壁病理学风险因素

       高分辨MRI是显示IAs瘤壁病理学特征的主要成像方式,包括血管壁成像(vascular wall imaging, VWI)、动态对比增强MRI(dynamic contrast-enhanced MRI, DCE-MRI)、磁敏感加权成像(susceptibility weighted imaging, SWI)、定量磁化率成像(quantitative susceptibility mapping, QSM)及7.0 T MRI等。

       VWI基于超高的空间分辨率,通过抑制血管内血流信号凸显组织信号,实现动脉瘤壁成像[17]。3D-VWI较2D-VWI对动脉瘤壁成像有各向同性及大观察视野等优势[18]。VWI多用来对动脉瘤壁厚度(aneurysm wall thickness, AWT)变化及炎症反应进行观察[19]。DCE-MRI基于超高的时间分辨率,利用顺磁性对比剂缩短组织的T1值观察不同时间点的信号变化,实现动脉瘤壁的功能成像[20]。DCE-MRI多用来对动脉瘤壁的渗透性进行观察。SWI基于高空间分辨率,通过相位成像增强组织间固有的磁敏感差异,实现动脉瘤壁成像[21]。SWI多用来对动脉瘤壁的微出血进行定性观察。QSM基于SWI技术,通过相位信息获得组织的磁敏感分布,实现动脉瘤壁的功能成像[22]。QSM多用来对动脉瘤壁的微出血进行定性或定量观察。7.0 T MRI基于超高的时间和空间分辨率,通过VWI等技术实现动脉瘤壁成像[23]。7.0 T MRI尚未在临床实践中常规应用。综上所述,高分辨MRI能够获得IAs的瘤壁病理学特征。

       IAs不稳定状态的动脉瘤壁病理学危险因素与动脉瘤壁的病理学变化对应,成为近年来的研究热点。IAs不稳定状态的动脉瘤壁病理学危险因素主要包括:厚度、炎症(图1)、渗透性及微出血等。

       AWT与动脉瘤不稳定状态有关。IAs的尸检和术中研究表明,AWT的范围在0.02~0.50 mm之间,并且随载瘤动脉厚度的变化而变化[24]。既往研究提示,AWT变薄的IAs出现不稳定状态的可能性较高,在钆剂增强后VWI中AWT变厚的IAs出现不稳定状态的可能性较高[25]。MRI场强越高,对AWT的观察越可靠。动脉瘤壁炎症反应与动脉瘤不稳定状态有关[26]。既往研究提示,钆对比剂、髓过氧化物酶对比剂及超小型超顺磁性氧化铁颗粒对比剂增强的VWI中,动脉瘤壁强化均能提示动脉瘤壁炎症反应[27]。出现动脉瘤壁炎症反应的IAs出现不稳定状态的可能性较高[28]。在临床实践中,钆对比剂增强VWI的应用更广泛[29]。动脉瘤壁渗透性与动脉瘤不稳定状态有关。既往研究提示,动脉瘤壁渗透性较高的IAs出现不稳定状态的可能性较高[30]。DCE-MRI的药代动力学参数——容量转移常数(Ktrans)能够对动脉瘤壁的渗透率变化等进行量化评估[31]。动脉瘤壁微出血与动脉瘤不稳定状态有关[32]。既往研究提示,动脉瘤壁存在微出血的IAs出现不稳定状态的可能性较高[33]。动脉瘤壁在SWI中的低信号提示铁沉积(由微出血引起)[34]。动脉瘤壁在QSM中的高信号提示铁沉积(由微出血引起)[35]。综上所述,高分辨MRI能够从多个维度对IAs不稳定状态的瘤壁病理学风险因素进行评价。

3 IAs不稳定状态的血流动力学风险因素

       MRA能够显示IAs血流动力学变化,主要包括磁共振四维流动成像(four spatial dimensions flow MRI, 4D-Flow-MRI)。4D-Flow-MRI是目前用于活体3D定量血流评估的安全有效的方法。

       4D-Flow-MRI基于相位对比技术使用流动质子的相位移动变化来创建图像,沿磁场梯度方向移动的自旋质子会获得与其速度成比例的相位移动,相位对比采集包括具有和不具有流动编码的序列,这些序列会产生幅值图(流动信号的“解剖”信息)和相位图(流动信号的“功能”信息:流向和速度),从而实现动脉瘤的血流动力学成像[36]。综上所述,基于高时间和空间分辨率的4D-Flow-MRI能够获得IAs的血流动力学特征。

       MRA能够真实反映IAs不稳定状态的血流动力学危险因素,成为近年来的研究热点。IAs不稳定状态的血流动力学危险因素主要包括:流入射流模式、不规则的血流模式(涡流)及壁面切应力(wall shear stress, WSS)等。

       IAs的流入射流模式与动脉瘤不稳定状态有关。IAs的SR影响流入射流模式,IAs的流入射流模式结合SR有助于识别动脉瘤的不稳定状态[37]。IAs不规则的血流模式(涡流)与动脉瘤不稳定状态有关。存在涡流核心的IAs出现不稳定状态的可能性较高[38]。IAs的WSS与动脉瘤不稳定状态有关[39]。IAs的WSS与动脉瘤的大小、形状及动脉瘤壁功能异常等相关[40]。WSS较低的IAs出现不稳定状态的可能性较高[41]。综上所述,虽然MRA在IAs中的研究较少,但是现有研究已经证明该技术能够评价IAs不稳定状态的血流动力学风险因素。

4 AI辅助评估IAs不稳定状态的风险因素

       AI能够基于MRA自动识别IAs[42]。AI算法主要包括传统算法和深度学习算法。

       AI传统算法基于三维选择性增强滤波器的点或形状差异图像等技术提取MRA中的突起特征,从而实现IAs的自动识别[43]。AI深度学习算法基于深层卷积神经网络和最大强度投影算法等技术提取MRA中的突起特征,从而实现IAs的自动识别[44]。因此,AI能够自动识别IAs。

       AI评估IAs不稳定状态风险是IAs影像研究的热点[45]。AI模型评估IAs不稳定状态的风险因素主要包括瘤腔形态学特征[46]和血流动力学特征[47]等。

       IAs不稳定状态风险的传统AI预测模型多是基于瘤腔形态学特征构建[48]。最近有学者指出,在IAs不稳定状态的AI预测模型中血流动力学特征也是重要的预测指标[49]。目前的研究证明AI模型优于常规统计模型和PHASES评分方法[50],但是为了进一步改善预测性能,可能需要动脉瘤壁病理学的影像学特征等。

5 总结

       MRI由于无创无辐射等优势已经成为了UIAs患者诊断和随访的首选检查方式。多模态MRI能够提供UIAs“瘤腔形态学-瘤壁病理学-血流动力学”多维度影像特征,有助于动脉瘤不稳定状态的精准评估。MRA中的AI组件能够自动诊断IAs并评估其不稳定状态风险。未来,多模态MRI与AI组件的结合有望将IAs不稳定状态的精准预测提升到新的高度。

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