脑微出血及其磁共振成像检查的研究进展
Research Progress on Cerebral Microbleeds and Its Magnetic Resonance Imaging Examination
DOI: 10.12677/acm.2024.1461859, PDF, HTML, XML, 下载: 24  浏览: 47 
作者: 柴圣杰*, 钱昕毓, 葛丽红#:内蒙古医科大学附属医院影像诊断科,内蒙古 呼和浩特
关键词: 磁共振成像脑出血脑微出血磁敏感加权成像Magnetic Resonance Imaging Intracerebral Hemorrhage Cerebral MicrobleedsSusceptibility-Weighted Imaging
摘要: 脑微出血(cerebral microbleeds, CMBs)是一种由于各种危险因素破坏血脑屏障或损伤血管内皮导致的微小出血灶。CMBs的危险因素包括年龄、高血压、脑淀粉样血管病、糖尿病、高同型半胱氨酸血症、炎症反应、药物及手术等。随着磁共振成像技术持续发展,不断提高了对微小出血灶的检测和定位准确性。总之,脑微出血是一个值得关注和研究的话题,需要进一步深入研究其发生机制和危险因素,同时也需要继续发展和优化磁共振成像技术,以提高对脑微出血的检测和定位准确性,为临床诊断和治疗提供更准确的依据。
Abstract: Cerebral microbleeds (CMBs) are tiny hemorrhagic foci resulting from various risk factors that disrupt the blood-brain barrier or damage vascular endothelium. These risk factors encompass age, hypertension, cerebral amyloid angiopathy, diabetes, hyperhomocysteinemia, inflammatory reactions, medications, and surgical procedures. The continuous advancement of magnetic resonance imaging (MRI) technology has progressively improved the accuracy of detecting and locating these minute hemorrhagic foci. In conclusion, CMBs is a noteworthy topic for research, requiring further investigation into its pathogenesis and risk factors. Additionally, there is a need to continue developing and optimizing MRI technology to enhance the detection and localization accuracy of CMBs, thereby providing a more precise basis for clinical diagnosis and treatment.
文章引用:柴圣杰, 钱昕毓, 葛丽红. 脑微出血及其磁共振成像检查的研究进展[J]. 临床医学进展, 2024, 14(6): 906-912. https://doi.org/10.12677/acm.2024.1461859

1. 引言

脑微出血(cerebral microbleeds, CMBs)这个概念最早在1996年由Offenbacher等学者在美国神经放射学杂志中提出[1],随着医疗技术的进步,CMBs这一过去被忽视的征象正受到越来越多的关注。磁共振成像(magnetic resonance imaging, MRI)作为一种非侵入性的影像学技术,已广泛用于诊断CMBs,它利用人体组织对磁场的反映来获取高分辨率的脑部图像,从而清晰地显示微小出血灶,相比于传统的计算机断层扫描(computed tomography, CT),MRI具有更高的灵敏度和空间分辨率,能更准确地检测和定位CMBs [2]。本文将在以下几个方面综述磁共振成像在脑微出血研究中的进展。

2. CMBs的概念及发生机制

CMBs指的是由于各种危险因素破坏血脑屏障或损伤血管内皮导致血液从微小血管中渗出或漏出,含铁血黄素沉积在脑组织中形成的微小病灶[3]。这些微小病灶在梯度回波T2*成像(T2*-gradient echo imaging, T2*-GRE)或磁敏感加权成像(susceptibility weighted imaging, SWI)中表现为边界清晰、形态均匀的圆形或椭圆形低信号或信号缺失灶,直径在2~5 mm,最大不超过10 mm;且周围不伴水肿信号,或者至少有一半被脑实质包围[4]-[6]

3. CMBs的危险因素

3.1. 年龄

在一项针对无卒中社区老年人的研究中共纳入199名受试者,其中CMBs的总体患病率为12.6% (25/199),并随着年龄增长而增加,从7.5% (55~64岁)增加到19.3% (75岁以上),且CMBs与年龄的关系不受性别影响,该研究分析指出随着年龄增加,血管壁硬化,血管内皮细胞受损严重,血液更容易从微小血管中渗出导致CMBs增加[7]。且年龄作为CMBs的独立危险因素已被许多研究证实[8]

3.2. 高血压

CMBs是脑小血管疾病的主要影像标志物,常发生在高血压患者中,在一项探讨不同高血压分级和持续时间对CMBs影响的研究中,学者发现在1期和2期高血压患者中,CMBs患者比例均显著高于无CMBs患者(p < 0.05),在>20岁组中,1期和2期高血压患者中CMBs患者的比例均显著高于无CMBs的患者(p < 0.05),且高血压患者的CMBs好发于深部脑组织[9]。既往研究指出长期高血压可使脑细小动脉发生玻璃样变性、纤维素样坏死,还可能引起脑部小动脉痉挛和狭窄,使脑组织缺氧、缺血,导致脑组织坏死和软化,进一步增加脑微出血的风险,因此控制高血压对于预防CMBs尤为重要[10]

3.3. 脑淀粉样血管病

脑淀粉样血管病(cerebral amyloid angiopathy, CAA)是由于β-淀粉样物质在脑皮质和髓质的中小动脉中层和外膜的不断沉积。随着CAA的进展,淀粉样物质沉积的血管壁发生结构性改变,从而导致血管壁坏死、出血。Giulia等在对61例CAA患者的研究中发现,伴随着认知障碍的CAA患者表现出更高的患病率(p < 0.001),尤其在颞叶(p = 0.015)和岛叶中(p = 0.002)。因而许多研究者认为CAA是CMBs的危险因素,且二者在脑内分布一致,部分学者提出可以通过减少脑淀粉样物质沉积来预防和治疗CMBs的建议[11]

3.4. 糖尿病

糖尿病会使血糖升高,进而对内皮细胞功能及结构造成破坏,通过氧化应激、干扰一氧化氮代谢等途径影响血管舒张功能,导致血液渗出。Lena等人对191名1型糖尿病患者的研究指出相比于健康对照组,CMBs在患1型糖尿病的年轻人中更为常见(p = 0.008) [12]。糖尿病与脑微出血的相关性已被多位学者证实,控制血糖对于预防CMBs尤为重要。

3.5. 新型冠状病毒肺炎(Coronavirus Disease 2019, COVID-19)

尽管COVID-19呼吸系统症状表现明显,但也有研究证明它具有神经系统表现并伴有CMBs [13],Matthew等学者的研究表明COVID-19可能是通过血管紧张素转换酶进入宿主细胞,进而影响肾素–血管紧张素系统,产生高血压、炎症反应、纤维化、缺氧等表现,最后损伤血管内皮导致血液外渗。这些假设为我们研究CMBs的危险因素提供了新思路,同时也为CMBs与COVID-19的关系提供了证据支持[14]

3.6. 高同型半胱氨酸血症

同型半胱氨酸(Homocysteine, Hcy)作为动脉粥样硬化的传统危险因素,可能参与脑小血管疾病的发展并伴有CMBs [15],Wang的一项研究表明在大动脉粥样硬化引起的急性缺血性卒中患者中,血清Hcy水平与CMBs的存在密切相关,降低Hcy水平可能是缓解CMBs不良临床结局的潜在治疗靶点[16]

3.7. 炎症反应

Jiang等的研究发现中性粒细胞计数、中性粒细胞与淋巴细胞比值和全身免疫炎症指数与脑小血管疾病具有相关性,且随着上述炎症指标的升高会加重脑微出血的风险[17]。Rob发现C反应蛋白水平与脑微出血密切相关,认为活化的单核细胞/巨噬细胞通过增加血脑屏障的通透性从而导致脑小血管疾病[18]。关于炎症反应对脑微出血的影响有待更多的研究论证。

3.8. 药物及手术

许多研究显示,抗血小板药物与脑微出血具有相关性。Ge等回顾性研究了300例缺血性脑血管病门诊患者,分成两组各150例进行多因素评估阿司匹林对发生CMBs的影响。结果显示接受阿司匹林治疗≥1年的患者比未接受阿司匹林治疗患者的脑微出血患病率高(40%比12%) [19]。Ge的另一项研究表明在服用阿司匹林或氯吡格雷>1年的患者中,脑白质高信号与CMBs相关,长期使用会增加CMBs和出血的风险[20]

Eric等学者发现每4名接受导管主动脉瓣置换术的患者中就有1名在手术前患CMBs,且每4名患者中就有1名出现新的CMBs。手术或抗血栓治疗以及获得性血管性血友病因子缺陷与新发CMBs的发生有关[21]。Tipirneni等人的荟萃分析指出CMBs与接受溶栓治疗的急性缺血性脑卒中患者的不良预后结果之间有着显著关联,还强调CMBs加重了症状性脑出血及出血转化的风险,从而间接导致患者死亡率的增加[22]。由上可见脑出血目前多数是针对CMBs患者溶栓及手术预后的研究,还需要更多对于溶栓与手术后是否新发CMBs的研究。

4. 针对脑微出血磁共振成像技术的发展

4.1. 磁共振成像的基本原理

磁共振成像的原理主要包括以下几个步骤:首先患者需要躺在磁共振成像设备里,身体被强大的磁场包围,然后磁场会定向并激发患者身体内的氢原子核,使其产生一个特定的共振信号,进而通过向氢原子核施加无线电脉冲,激发患者体内的氢原子核,释放出能量。不同的脉冲序列可以产生不同类型的图像,如T1加权图像(T1-weighted imaging, T1WI)、T2加权图像(T2-weighted imaging, T2WI)、定量磁敏感图谱(Quantitative Susceptibility Mapping, QSM)等。磁共振成像设备会接收这部分能量并转变成信号,这些信号会经过处理和分析,最终转换成图像。总的来说,磁共振成像通过利用磁场和无线电波的相互作用,生成高分辨率的图像,用于检测和定位CMBs。正是因为这种成像技术的非侵入性和无放射性,所以它被广泛应用于临床诊断和研究中[23]

4.2. 脑微出血扫描序列的发展:从T2*GRE到SWI再到QSM

目前,临床上针对CMBs的诊断主要以T2*GRE、SWI、QSM为主其中以前两者最为常见,而T2*GRE序列又是最早用于检测CMBs的序列[24] [25]。当出血代谢产物随着时间改变时,磁场局部均匀性就会发生变化——早期是从氧合血红蛋白变成脱氧血红蛋白,脱氧血红蛋白具有顺磁效应,较强的磁敏感效应会导致信号丢失或减低,因此在SWI和QSM成像技术未出现前,T2*GRE能够精确显示脑内血肿体积,其CMBs检出率高于常规MRI序列和CT检查[26]。随着对影像技术研究的深入,SWI序列被发现并投入日常MRI检查使用。

SWI是一种长回波时间、三个方向均有流动补偿的全新序列,它的原始图像是以T2*GRE序列为基础,利用不同组织磁化率的差异获得幅值图和相位图,然后将显示精细解剖结构的幅值图和反映磁化率差异性的相位图结合起来[27],它的优势在于具有高分辨率,高信噪比以及显示组织磁化率差异等特点并已广泛应用于临床[28]-[30]。Cheng等人的对照研究分析了两组患者,涉及31个研究对象,结果表明在9例脑淀粉样血管病病例中,评分者在T2*GRE上发现了1146个CMBs,在SWI上发现了1432个CMBs;在22名健康对照受试者中,评分者在T2*GRE检测的6/22 (共9个CMBs)和SWI检测的5/22 (共19个CMBs)中发现了≥1个CMBs。在脑淀粉样血管病病例中,SWI的CMBs计数评分者之间的可靠性良好(组内相关系数,0.87),但GRE的可靠性中等(组内相关性系数,0.52) [31]。国内学者严小兰,选取94例高血压脑出血患者接受T1加权成像、T2加权成像和SWI三种序的磁共振成像检查,结果显示,SWI序列早期诊断率明显高于T1WI、T2WI序列(p < 0.05) [32]。上述结果提示与常规T1、T2、T2*GRE相比,SWI具有更高的CMBs检测可靠性和灵敏度,应该是目前计量CMBs的首选序列。尽管SWI已经可以对CMBs定性诊断,但还是无法做到精确的量化磁敏感物质,所以QSM应运而生。

QSM首先通过处理相位图信息然后去除背景场,再通过特有的算法重建出磁敏感图像,之后采用偶极子场反演算法降低图像噪声及伪影干扰得到最终QSM图像,它的优势在于能够精确显示大脑解剖结构、静脉血管、并可以区分出血和钙化,还可以监测血氧及铁沉积水平[33]-[35]。QSM的定量特性使得来自不同设备或不同研究中心的检查结果可比性更高[36],且可比较同一患者在不同时期的磁化率变化而观察其疾病进展[37]。在一项对QSM可改善CMBs检测的研究中,Kyuwon Lee等学者纳入了48例急性颅内出血患者,他们接受了用于生成SWI和形态学偶极子反转QSM图像的多回波梯度回波MRI,然后对这些图像进行对比分析,结果表明QSM显示CMBs信号强度是SWI的三倍、描述均匀病变强度的概率是SWI的三倍(p < 0.01) [38]。由此可以得出与SWIP相比,QSM可以更精确地显示出CMBs的信号,提高了临床医生发现CMBs的能力。

5. 小结与展望

CMBs是一种在多种模式MRI序列上得以描述的病症,与年龄、高血压、糖尿病和COVID-19等血管疾病有着密切的关系。目前,对于CMBs的治疗主要集中在控制血压和预防卒中方面。但随着对CMBs认知的深入,未来可能会探索出更多新的治疗方法,如可以通过研究同型半胱氨酸、淀粉样蛋白β和血浆脂蛋白相关磷脂酶A2等与CMBs相关的危险因素,为预防和治疗CMBs提供更多的依据。或者利用影像组学先进的图像处理分析技术结合机器学习算法,实现对CMBs的自动识别和分类,从而提高检测效率和准确性。总之,随着对CMBs研究的不断深入,我们对这一病症的认识将越来越全面。我们期待在未来的研究中能够取得更多的突破,为预防和治疗CMBs提供更好的方法和手段。

NOTES

*第一作者。

#通讯作者。

参考文献

[1] Offenbacher, H., Fazekas, F., Schmidt, R., et al. (1996) MR of Cerebral Abnormalities Concomitant with Primary Intracerebral Hematomas. American Journal of Neuroradiology, 17, 573-578.
[2] Schwarz, G., Banerjee, G., Hostettler, I.C., Ambler, G., Seiffge, D.J., Ozkan, H., et al. (2022) MRI and CT Imaging Biomarkers of Cerebral Amyloid Angiopathy in Lobar Intracerebral Hemorrhage. International Journal of Stroke, 18, 85-94.
https://doi.org/10.1177/17474930211062478
[3] Wach-Klink, A., Iżycka-Świeszewska, E., Kozera, G. and Sobolewski, P. (2021) Cerebral Microbleeds in Neurological Practice: Concepts, Diagnostics and Clinical Aspects. Neurologia i Neurochirurgia Polska, 55, 450-461.
https://doi.org/10.5603/pjnns.a2021.0058
[4] Haller, S., Scheffler, M., Salomir, R., Herrmann, F.R., Gold, G., Montandon, M., et al. (2019) MRI Detection of Cerebral Microbleeds: Size Matters. Neuroradiology, 61, 1209-1213.
https://doi.org/10.1007/s00234-019-02267-0
[5] Weerink, L.B., Appelman, A.P., Kloet, R.W. and Van der Hoorn, A. (2023) Susceptibility-weighted Imaging in Intracranial Hemorrhage: Not All Bleeds Are Black. The British Journal of Radiology, 96, Article ID: 20220304.
https://doi.org/10.1259/bjr.20220304
[6] Puy, L., Pasi, M., Rodrigues, M., van Veluw, S.J., Tsivgoulis, G., Shoamanesh, A., et al. (2021) Cerebral Microbleeds: From Depiction to Interpretation. Journal of Neurology, Neurosurgery & Psychiatry, 92, 598-607.
https://doi.org/10.1136/jnnp-2020-323951
[7] Luo, Q., Tang, H., Xu, X., Huang, J., Wang, P., He, G., et al. (2021) The Prevalence and Risk Factors of Cerebral Microbleeds: A Community-Based Study in China. Therapeutics and Clinical Risk Management, 17, 165-171.
https://doi.org/10.2147/tcrm.s297708
[8] Lu, D., Liu, J., MacKinnon, A.D., Tozer, D.J. and Markus, H.S. (2021) Prevalence and Risk Factors of Cerebral Microbleeds. Neurology, 97, e1493-e1502.
https://doi.org/10.1212/wnl.0000000000012673
[9] Liang, C., Wang, J., Feng, M., Zhang, N. and Guo, L. (2022) White Matter Changes, Duration of Hypertension, and Age Are Associated with Cerebral Microbleeds in Patients with Different Stages of Hypertension. Quantitative Imaging in Medicine and Surgery, 12, 119-130.
https://doi.org/10.21037/qims-21-28
[10] An, S.J., Kim, T.J. and Yoon, B. (2017) Epidemiology, Risk Factors, and Clinical Features of Intracerebral Hemorrhage: An Update. Journal of Stroke, 19, 3-10.
https://doi.org/10.5853/jos.2016.00864
[11] Perini, G., Ramusino, M.C., Farina, L.M., Fabbro, B.D., Canavero, I., Picascia, M., et al. (2023) Cognitive versus Hemorrhagic Onset in Cerebral Amyloid Angiopathy: Neuroimaging Features. Current Alzheimer Research, 20, 267-276.
https://doi.org/10.2174/1567205020666230713151211
[12] Thorn, L.M., Shams, S., Gordin, D., Liebkind, R., Forsblom, C., Summanen, P., et al. (2018) Clinical and MRI Features of Cerebral Small-Vessel Disease in Type 1 Diabetes. Diabetes Care, 42, 327-330.
https://doi.org/10.2337/dc18-1302
[13] Napolitano, A., Arrigoni, A., Caroli, A., Cava, M., Remuzzi, A., Longhi, L.G., et al. (2022) Cerebral Microbleeds Assessment and Quantification in COVID-19 Patients with Neurological Manifestations. Frontiers in Neurology, 13, Article 884449.
https://doi.org/10.3389/fneur.2022.884449
[14] Sparks, M.A., South, A.M., Badley, A.D., Baker-Smith, C.M., Batlle, D., Bozkurt, B., et al. (2020) Severe Acute Respiratory Syndrome Coronavirus 2, COVID-19, and the Renin-Angiotensin System. Hypertension, 76, 1350-1367.
https://doi.org/10.1161/hypertensionaha.120.15948
[15] Ji, Y., Li, X., Teng, Z., Li, X., Jin, W. and Lv, P.Y. (2020) Homocysteine Is Associated with the Development of Cerebral Small Vessel Disease: Retrospective Analyses from Neuroimaging and Cognitive Outcomes. Journal of Stroke and Cerebrovascular Diseases, 29, Article ID: 105393.
https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.105393
[16] Wang, B., Ou, Z., Jiang, T., Zhang, Y., Zhao, H., Tian, Y., et al. (2016) Independent Correlation of Serum Homocysteine with Cerebral Microbleeds in Patients with Acute Ischemic Stroke Due to Large-Artery Atherosclerosis. Journal of Stroke and Cerebrovascular Diseases, 25, 2746-2751.
https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.07.028
[17] Jiang, L., Cai, X., Yao, D., Jing, J., Mei, L., Yang, Y., et al. (2022) Association of Inflammatory Markers with Cerebral Small Vessel Disease in Community-Based Population. Journal of Neuroinflammation, 19, Article No. 106.
https://doi.org/10.1186/s12974-022-02468-0
[18] Rouhl, R.P.W., Damoiseaux, J.G.M.C., Lodder, J., Theunissen, R.O.M.F.I.H., Knottnerus, I.L.H., Staals, J., et al. (2012) Vascular inflammation in cerebral small vessel disease. Neurobiology of Aging, 33, 1800-1806.
https://doi.org/10.1016/j.neurobiolaging.2011.04.008
[19] Ge, L., Niu, G., Han, X., Gao, Y., Wu, Q., Wu, H., et al. (2011) Aspirin Treatment Increases the Risk of Cerebral Microbleeds. Canadian Journal of Neurological Sciences, 38, 863-868.
https://doi.org/10.1017/s0317167100012440
[20] Ge, L., Ouyang, X., Ban, C., Yu, H., Wu, Q., Wu, H., et al. (2019) Cerebral Microbleeds in Patients with Ischemic Cerebrovascular Disease Taking Aspirin or Clopidogrel. Medicine, 98, e14685.
https://doi.org/10.1097/md.0000000000014685
[21] Van Belle, E., Debry, N., Vincent, F., Kuchcinski, G., Cordonnier, C., Rauch, A., et al. (2022) Cerebral Microbleeds during Transcatheter Aortic Valve Replacement: A Prospective Magnetic Resonance Imaging Cohort. Circulation, 146, 383-397.
https://doi.org/10.1161/circulationaha.121.057145
[22] Tipirneni, S., Stanwell, P., Weissert, R. and Bhaskar, S.M.M. (2023) Prevalence and Impact of Cerebral Microbleeds on Clinical and Safety Outcomes in Acute Ischaemic Stroke Patients Receiving Reperfusion Therapy: A Systematic Review and Meta-Analysis. Biomedicines, 11, Article 2865.
https://doi.org/10.3390/biomedicines11102865
[23] Minhas, A.S. and Oliver, R. (2022) Magnetic Resonance Imaging Basics. Advances in Experimental Medicine and Biology, 1380, 47-82.
https://doi.org/10.1007/978-3-031-03873-0_3
[24] Raposo, N. and Viswanathan, A. (2020) MRI-Visible Enlarged Perivascular Spaces. Neurology, 95, 709-710.
https://doi.org/10.1212/wnl.0000000000010790
[25] Zivadinov, R., Ramasamy, D.P., Benedict, R.R.H., Polak, P., Hagemeier, J., Magnano, C., et al. (2016) Cerebral Microbleeds in Multiple Sclerosis Evaluated on Susceptibility-Weighted Images and Quantitative Susceptibility Maps: A Case-Control Study. Radiology, 281, 884-895.
https://doi.org/10.1148/radiol.2016160060
[26] Luijten, S.P.R., van der Ende, N.A.M., Cornelissen, S.A.P., Kluijtmans, L., van Hattem, A., Lycklama a Nijeholt, G., et al. (2023) Comparison of Diffusion Weighted Imaging B0 with T2-Weighted Gradient Echo or Susceptibility Weighted Imaging for Intracranial Hemorrhage Detection after Reperfusion Therapy for Ischemic Stroke. Neuroradiology, 65, 1649-1655.
https://doi.org/10.1007/s00234-023-03180-3
[27] Martínez Camblor, L., Peña Suárez, J.M., Martínez-Cachero García, M., Santamarta Liébana, E., Rodríguez Castro, J. and Saiz Ayala, A. (2023) Cerebral Microbleeds. Utility of SWI Sequences. Radiología (English Edition), 65, 362-375.
https://doi.org/10.1016/j.rxeng.2022.12.006
[28] 于海霞, 葛丽红, 牛广明. SWI、3D-ASL在急性缺血性脑卒中诊疗中的研究进展[J]. 内蒙古医科大学学报, 2019, 41(2): 199-202, 206.
https://doi.org/10.16343/j.cnki.issn.2095-512x.2019.02.027
[29] Martín-Noguerol, T., Montesinos, P., Casado-Verdugo, O.L., Beltrán, L.S. and Luna, A. (2021) Susceptibility Weighted Imaging for Evaluation of Musculoskeletal Lesions. European Journal of Radiology, 138, Article ID: 109611.
https://doi.org/10.1016/j.ejrad.2021.109611
[30] Haller, S., Haacke, E.M., Thurnher, M.M. and Barkhof, F. (2021) Susceptibility-Weighted Imaging: Technical Essentials and Clinical Neurologic Applications. Radiology, 299, 3-26.
https://doi.org/10.1148/radiol.2021203071
[31] Cheng, A., Batool, S., McCreary, C.R., Lauzon, M.L., Frayne, R., Goyal, M., et al. (2013) Susceptibility-weighted Imaging Is More Reliable than T2*-Weighted Gradient-Recalled Echo MRI for Detecting Microbleeds. Stroke, 44, 2782-2786.
https://doi.org/10.1161/strokeaha.113.002267
[32] 严小兰, 刘红翠. 不同序列磁共振加权成像对高血压脑出血患者的早期诊断价值比较[J]. 影像科学与光化学, 2020, 38(6): 1014-1017.
[33] Ruetten, P.P.R., Gillard, J.H. and Graves, M.J. (2019) Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging. The British Journal of Radiology, 92, Article ID: 20181016.
https://doi.org/10.1259/bjr.20181016
[34] Dimov, A.V., Li, J., Nguyen, T.D., Roberts, A.G., Spincemaille, P., Straub, S., et al. (2023) QSM throughout the Body. Journal of Magnetic Resonance Imaging, 57, 1621-1640.
https://doi.org/10.1002/jmri.28624
[35] Biondetti, E., Cho, J. and Lee, H. (2023) Cerebral Oxygen Metabolism from MRI Susceptibility. NeuroImage, 276, Article ID: 120189.
https://doi.org/10.1016/j.neuroimage.2023.120189
[36] 倪民桦, 颜林枫, 崔光彬. 定量磁化率图在脑微出血中的研究进展[J]. 国际医学放射学杂志, 2022, 45(3): 303-306.
https://doi.org/10.19300/j.2022.Z19401
[37] Li, K.R., Avecillas‐Chasin, J., Nguyen, T.D., Gillen, K.M., Dimov, A., Chang, E., et al. (2021) Quantitative Evaluation of Brain Iron Accumulation in Different Stages of Parkinson’s Disease. Journal of Neuroimaging, 32, 363-371.
https://doi.org/10.1111/jon.12957
[38] Lee, K., Ellison, B., Selim, M., Long, N.H., Filippidis, A., Thomas, A.J., et al. (2022) Quantitative Susceptibility Mapping Improves Cerebral Microbleed Detection Relative to Susceptibility‐Weighted Images. Journal of Neuroimaging, 33, 138-146.
https://doi.org/10.1111/jon.13054