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综述
7 T磁共振成像的优势和挑战及在神经系统的典型临床运用
杨先菲 甄志铭 陈康 吴眉 欧沛灵 余红 刘晨

Cite this article as: YANG X F, ZHEN Z M, CHEN K, et al. Advantages and challenges of 7 T magnetic resonance imaging and typical clinical application for neurological disorders[J]. Chin J Magn Reson Imaging, 2024, 15(12): 187-193.本文引用格式:杨先菲, 甄志铭, 陈康, 等. 7 T磁共振成像的优势和挑战及在神经系统的典型临床运用[J]. 磁共振成像, 2024, 15(12): 187-193. DOI:10.12015/issn.1674-8034.2024.12.029.


[摘要] 超高场磁共振成像(ultra-high-field magnetic resonance imaging, UHF-MRI)作为一项前沿技术,凭借卓越的信噪比(signal-to-noise ratio, SNR)和分辨率广受关注。7 T磁共振成像(magnetic resonance imaging, MRI)作为其中的典型代表,已开始从科研走向临床,在包括高分辨率结构成像、磁敏感成像、多核成像、波谱和血氧水平依赖等磁共振技术方面取得诸多变革,极大提高了神经系统疾病的诊断能力。然而,磁场强度的增加也带来了射频场不均匀性增强、比吸收率增高等多方面的考验。这些考验可能会加剧图像伪影,限制特定成像序列的使用,影响UHF-MRI在临床的推广。本文根据陆军军医大学第一附属医院7 T MRI使用经验,结合相关文献,阐述了UHF-MRI的核心优势与面临的主要挑战,简要介绍了其在神经系统的优势和潜力,期望能为其他单位开展7 T MRI相关工作提供经验性探索。
[Abstract] Ultra-high-field magnetic resonance imaging (UHF-MRI), as a cutting-edge technology, has received widespread attention for its distinct advantages to both signal-to-noise ratio (SNR) and resolution. Recently, as the prototypical representative of UHF-MRI, 7 T magnetic resonance imaging (MRI) has begun to move from scientific research to clinical practice, and has made many changes in magnetic resonance techniques, including high-resolution structural imaging, susceptibility weighted imaging, X-nuclei MRI, magnetic resonance spectroscopy and blood oxygen level dependent magnetic resonance, which have greatly improved the diagnosis of neurological diseases. However, the increase in magnetic field strength also brings some challenges, such as enhanced radio frequency field inhomogeneity and specific absorption ratio limitation. These problems may exacerbate image artifacts, limit the utility of certain imaging sequences, and affect the promotion of UHF-MRI in clinical practice. Based on the experience of using 7 T MRI in the First Affiliated Hospital of the Army Medical University, this paper discusses the core advantages and main challenges of UHF-MRI, and briefly introduces its potentials in neurological system in the light of relevant literature, with the expectation of providing empirical insights for others to conduct 7 T MRI related research.
[关键词] 超高场强;磁共振成像;神经影像学;神经系统疾病;7 T磁共振成像
[Keywords] ultra-high-field;magnetic resonance imaging;neuroimaging;neurological disease;7 T magnetic resonance imaging

杨先菲 1, 2   甄志铭 1, 2   陈康 1, 2   吴眉 1, 2   欧沛灵 1, 2   余红 1, 2   刘晨 1, 2*  

1 陆军军医大学第一附属医院7 T磁共振转化医学研究中心,重庆 400038

2 陆军军医大学(第三军医大学)西南医院放射科,重庆 400038

通信作者:刘晨,E-mail: liuchen@tmmu.edu.cn

作者贡献声明:刘晨构思并设计了本综述的方向和框架,并对重要内容进行了修改,获得重庆市中青年医学高端人才工作室项目、重庆市中青年医学高端人才项目以及国家自然科学基金项目的资助;杨先菲、甄志铭查阅文献并初步构思本综述的内容,起草、撰写并修改本稿件;陈康、吴眉、欧沛灵、余红负责查找神经系统疾病经典案例影像资料,并对稿件重要内容做出修改;全体作者都同意最后的修改稿发表,同意对本综述的所有方面负责,确保本综述的准确性和诚信。


基金项目: 重庆市中青年医学高端人才工作室项目 524Z28921 重庆市中青年医学高端人才项目 514Z395 国家自然科学基金项目 82071910
收稿日期:2024-10-06
接受日期:2024-12-10
中图分类号:R445.2  R322.81 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2024.12.029
本文引用格式:杨先菲, 甄志铭, 陈康, 等. 7 T磁共振成像的优势和挑战及在神经系统的典型临床运用[J]. 磁共振成像, 2024, 15(12): 187-193. DOI:10.12015/issn.1674-8034.2024.12.029.

0 引言

       超高场磁共振成像(ultra-high-field magnetic resonance imaging, UHF-MRI)技术因其卓越的成像质量、丰富的生物标志物信息以及出色的组织对比度,正逐步渗透至各级医疗机构,成为从三甲教学医院到区县级医院在超微影像研究和临床诊断领域的重要新工具。然而,由于技术和成本等限制,作为UHF-MRI的代表性技术,7 T磁共振成像(magnetic resonance imaging, MRI)在临床中的普及率仍然较低,目前多局限于科研机构和教学医院进行临床科学研究。尽管如此,随着技术进步和设备成本的逐步降低,7 T MRI在临床诊断中的应用前景依然广阔。特别是,在一些高水平教学医院中,7 T MRI初步应用所积累的临床数据和技术经验,为其未来在临床实践中的普及奠定了坚实基础。值得注意的是,人工智能和深度学习技术正不断与UHF-MRI技术结合,以进行影像图像的自动分析和疾病预测。这不仅可以提高影像解读的准确性,还能显著缩短诊断周期,提高临床工作效率[1]

       7 T MRI的超高时空分辨率和信噪比(signal-to-noise ratio, SNR)使颅脑细微结构和超微结构的显示成为可能[2],为神经系统疾病的早期诊断和鉴别诊断提供了更好的工具。该技术在神经系统的结构、功能和代谢研究中的独特优势,使7 T MRI在神经系统的应用相较于其他人体系统更为广泛。但关于7 T MRI在神经系统应用的综述目前尚较为稀缺。因此,本文探讨了7 T MRI的临床应用潜力和挑战,特别是UHF-MRI在神经系统疾病中的价值,以期对未来临床医生更有效地选择和应用成像设备和序列、充分利用现有技术诊断和治疗疾病,具有重要指导意义。

1 UHF-MRI的主要优势

1.1 结构成像

       UHF-MRI的核心优势在于成像的高空间分辨率和高SNR。实验证明,SNR与静磁场B01.65近似成正比,从3 T到7 T MRI,SNR约提高了3.10倍[3]。7 T MRI的空间分辨率可达百微米级,使得基底核[4]等颅脑重要核团、微小病灶的观察在UHF-MRI中成为了可能。

       此外,随着磁场强度的增加,T1弛豫时间显著延长,这为多种磁共振血管成像技术带来了技术优势,其中就包括了磁共振时间飞跃血管成像(time of flight magnetic resonance angiography, TOF-MRA)。延长的T1弛豫时间可以更有效地抑制背景信号,同时获得更清晰的血管轮廓。利用7 T MRI显著提高的空间分辨率和SNR,TOF-MRA可检测到细小的外周血管、微小的颅内动脉瘤以及基底节区豆纹动脉等超微结构[5, 6]。在颅内血管病变的诊断和显示方面,7 T MRI的表现与数字减影血管造影(digital subtraction angiography, DSA)相当[7],甚至还能提供DSA无法显示的血管壁细节[8],这为脑血管疾病的非侵入性诊 断提供了更精确的手段。

       UHF-MRI在提高器官结构和功能变化的检测敏感度方面具有显著优势。这种技术在疾病早期诊断、鉴别诊断、神经外科手术路径的精确规划以及颅脑功能和连接组学的研究中,展现出不可估量的潜力。

1.2 功能成像

       从3 T到7 T,脱氧血红蛋白的T2*失相位加剧,组织的血氧水平依赖(blood oxygen level dependent, BOLD)对比度随之提高,特别是增加了小血管的BOLD信号,从而有助于更精确地识别和评估颅脑不同部位的代谢活性。在7 T场强下,这种BOLD功能磁共振成像(functional magnetic resonance imaging, fMRI)技术的灵敏度得到了显著提高,使得在低场强下难以察觉的微小病灶能够被精准地发现和定位。

       研究表明,7 T fMRI可以通过更高的空间分辨率更好地捕捉微小血管和神经活动的变化。例如,fMRI结合脑电图EEG可精确定位癫痫患者间歇性放电位置,以支持手术规划及术后语言功能受损风险的评估[9]。此外,在≥7 T磁场下的fMRI可以实现对视觉[10, 11]、嗅觉[12]、听觉[13]和运动皮层[14]等多个大脑初级皮层进行无创可靠的高精度灰质分层功能成像。近年来,研究人员还使用层特异性fMRI无创绘制高级脑区的人类认知加工过程[15],为理解复杂的神经活动提供了重要数据。

       7 T fMRI的优势与其他检测颅脑神经活动和网络连接的技术相结合,有望深化我们对脑功能网络和疾病病理机制的理解。这种多模态影像学方法能够提供更加全面的信息,有助于早期诊断神经系统疾病,从而为临床干预提供更多机会,改善患者的预后和生存质量。

1.3 代谢成像

       磁共振波谱(magnetic resonance spectroscopy, MRS)的光谱分辨率可以随场强的增加而显著提高。磁场强度越大,质子进动频率越高,使得相同的化学位移差异在频谱中表现得更为显著。因此,7 T MRS基于代谢物间的化学位移差异,得以更准确检测、量化和鉴别各种代谢物,甚至记录到常规场强下无法检测的潜在代谢性生物标志物,如2-羟基戊二酸、乳酸和葡萄糖等重要代谢物[16],为疾病的早期诊断和干预提供新的途径。如最近一项研究利用7 T下基于图谱的高分辨率1H-MRS成像,发现γ-氨基丁酸和谷氨酸可能是阿尔茨海默病潜在的生物标志物和早期干预的治疗靶点[17]

       化学交换饱和转移(chemical exchange saturation transfer, CEST)成像作为一种新兴成像技术,检测低浓度代谢物的敏感度和特异度均高于MRS,可为神经胶质瘤提供生物标志物[18],帮助预测患者的生存期以及评估放化疗后的早期反应[19]

       除了传统的1H-MRS,其他非质子核,如23Na和31P,也在研究中展现出应用潜力。由于非质子(如23Na、17O、31P)的磁旋比较小且体内浓度较低,其SNR比传统1H-MRS低了两个以上数量级,因而难以在低场强下实现多核成像。UHF-MRI的SNR的显著提升以及仪器设备进步带来的图像编码效率的提高,共同促进了多核成像在人体中的应用,如23Na在神经退行性疾病早期诊断中表现出了强大的应用潜能[20, 21]

       7 T磁共振代谢成像的优势能够揭示较低场强下难以探测的代谢变化,从而准确描绘出脑代谢的各项生物标志物,这有助于揭示潜在的免疫反应路径,为疾病的诊断和治疗提供新的科学依据。

2 UHF-MRI主要挑战

       随着磁场强度提升至7 T及以上,UHF-MRI在揭示颅脑微小结构和功能连接方面表现出更强的能力(表1)。然而,更高的磁场强度虽然能带来高空间分辨率和高SNR的优势,但也可能会导致图像伪影加重及组织对比度降低,并且增加射频能量沉积的安全风险。因此,如何平衡这些技术优势与潜在的安全隐患,成为了当前研究的重点之一。为了减轻超高场下更加显著的成像伪影和安全风险,需要积极开发出更先进的成像设备,优化脉冲序列,探索更有效的图像重建技术,旨在提高成像质量的同时,确保UHF-MRI的可行性与安全性。

2.1 硬件

       7 T MRI系统硬件设备成本高昂、构造复杂、体积庞大是推广UHF-MRI临床应用的阻碍之一。从第一代重数百吨的7 T被动屏蔽磁体到第三代自重小于25吨的主动屏蔽磁体,表明磁体技术朝着更轻、更便捷的方向发展,为临床应用的推广提供技术支撑[27]。目前,由于价格和安装条件的限制,7 T MRI在临床的推广较为受限,一般仅用于临床研究和疑难病例的诊断。相比之下,1.5 T、3 T MRI因其成本效益和更广泛的可用性,依然是临床工作中的主流选择。因此,未来研究应着重于降低磁体设备的体积和成本,以推动UHF-MRI在临床中广泛应用,充分发挥其优势。

2.2 受检者

       头晕是受检者在进行7 T MRI扫描时最常见的不适症状[28]。进出磁场必然经历的场强变化会使受试者和操作人员的前庭迷路淋巴内的离子电流相互作用产生洛伦兹力,从而导致眩晕和持续性眼球震颤[29]。51%的受检者在7 T中有一定感觉,通常描述为“旋转与空间感受错配”[30]。为最大限度减少这种不适,应嘱咐患者在靠近或处于磁体中时不要快速移动头部。另外,为了产生较均匀的B1场,发射和接收线圈紧挨着受检者,可能增加幽闭恐惧症的诱发风险。因此,在进行7 T MRI扫描前,应对患者进行充分的知情教育,让患者对扫描过程中可能产生的不适症状有足够的心理预期,尽可能地保证7 T MRI扫描的安全运行以及患者的舒适度。

2.3 成像和图像后处理

       安全性是临床工作的首要考虑因素,其中射频能量沉积是一个关键问题。由于射频场的致热效应,扫描过程中使用的大角度射频脉冲电磁能量会在受检者体内转化为热能。研究人员引入了比吸收率(specific absorption rate, SAR)来定量描述这种致热效应。场强越高,射频场致热效应越明显。由于7 T MRI的射频脉冲能量高于3 T,局部和全身组织的SAR值更易超出安全限制[31]。这一特点限制了某些需要高射频功率的成像序列的应用,其中主要包括了快速成像、动态增强成像和高分辨率成像等序列。优化射频脉冲设计、调整脉冲序列,如减小脉冲序列的翻转角度、增加脉冲间隔、减少回波数量,有助于将SAR值控制在合理范围内,但这通常伴随着扫描时间延长,从而造成了扫描效率的降低。因此,在实际应用中需要综合考虑,确保图像质量的同时,平衡SAR和扫描效率。另外,在相同扫描条件下,低体重患者的单位体积吸收的射频能量较多,导致组织过热的风险增加,因此SAR值的增高还影响着7 T MRI在低体重人群中的应用。因此,在进行7 T MRI扫描前,测量患者的身高和体重,对于保证低体重患者安全至关重要。

       人体内的电磁波因存在复杂的相消相长干涉机制,难以形成分布均匀的B1场。在7 T及更高场强下,这一问题更加突出。射频波长与场强成反比关系,UHF-MRI中射频脉冲的波长缩短至约11 cm,这加剧了B1场的不均匀性,易在颞叶和小脑产生较明显的信号丢失[32, 33]。使用高介电常数介质垫和并行传输技术可以提高射频场的均匀性[34, 35],从而减少相关伪影的发生。

       UHF-MRI的高SNR和高空间分辨率虽然提高了成像质量,但也使其对患者运动更为敏感,即使是微小的运动也可能产生显著的运动伪影。即便患者配合良好,无意识地运动,如呼吸和心脏跳动,仍可能降低有效分辨率。快速成像序列和运动校正后处理技术可以在一定程度上减少运动伪影对图像质量的影响[36]。此外,高空间分辨率和高SNR也意味着数据采集量的大幅增加,计算需求也随之加大。近年来,深度学习等人工智能技术逐步运用于图像数据的处理和分析,提高了图像分割的准确性和效率[37]。随着数据量的不断增加,未来仍需要继续开发高效的算法和工具,以满足数据储存、检索和分析的需求。

表1  与3 T MRI相比,7 T MRI的主要优势
Tab. 1  With the comparison of 3 T MRI, the principal advantages of 7 T MRI

3 UHF-MRI在神经系统的典型临床应用

       相比于3 T,7 T能更灵敏地检测出神经退行性疾病患者大脑细微损伤[38, 39, 40]、识别出脑卒中患者的小血管病变[41]和微梗死病灶[42]、发现脑肿瘤的多种代谢生物标志物。这些优势使得7 T MRI能够在疾病的早期诊断和鉴别诊断中发挥重要作用,从而实现及时干预,帮助预防严重残疾和认知障碍的发生。通过检测和分析特定的生物标志物,7 T MRI还能够推测相关功能和代谢变化,精确地进行疾病分型[43],为个性治疗方案的制订提供支持,从而延缓疾病进展。尽管仍面临一些技术挑战,但其优势已在临床应用中得到显现,未来有望为更多神经系统疾病的精确诊断和治疗提供新的可能性。

3.1 神经退行性疾病

       海马(图1A)是与学习、记忆、空间等认知功能密切相关的脑区,也是阿尔茨海默病(Alzheimer's disease, AD)患者最早出现萎缩的部位之一(图1B),其萎缩与记忆力下降等早期临床表现关系紧密。7 T高分辨率T2加权成像可以描绘出海马显微结构,定位出具体海马亚区神经元的丢失[44]。β-淀粉样蛋白沉积与铁代谢改变有关,是AD发病机制的关键之一,该病变常小于150 μm,难以在低场强下发现。7 T MRI凭借其优越的空间分辨率,有助于这些微小病灶的检出,并通过MRS为AD提供丰富的非侵入性生物标志物[40, 45]。一项研究显示,灰质中较高的GABA 和谷氨酸水平以APOE4依赖性方式与大脑β-淀粉样蛋白负荷呈正性相关,且这些变化可在无明显认知障碍的老年人中观察到[17]。这表明,灰质中的GABA和谷氨酸可能是早期AD的潜在生物标志物,反映了AD早期阶段突触代谢或神经元活动的变化,有助于进行风险分层,识别出未来可能患AD的高危人群。

       帕金森病(Parkinson's disease, PD)的病理特征之一是黑质致密部多巴胺能神经元的变性。7 T的高分辨率和高SNR可以清晰显示出黑质致密部中黑质小体-1解剖结构。健康人群中,黑质小体-1在磁敏感加权成像上表现为高信号,其两侧为低信号,构成了典型的“燕尾征”图像(图1C)。研究表明,多巴胺能纹状体功能障碍与黑质致密部神经元丢失及铁沉积密切相关[46],黑质铁沉积的增加导致燕尾征的消失(图1D),这一变化可能是PD的早期影像标志物[47]。尽管在3 T和7 T都能发现PD患者的燕尾征消失,但7 T对PD诊断的敏感度、特异性和准确率都高于3 T[48]。另外,黑质致密部内常有神经黑色素(neuromelanin, NM)的积聚,这是PD的另一个关键特征。黑质致密部NM信号的不对称丢失已被证明是区分PD与非PD患者的特异性生物标志物,且在运动性强直亚型中,NM信号的损失程度明显大于震颤为主亚型[49]。7 T MRI的NM成像技术有望为PD的临床诊断提供更早期的诊断信息,帮助区分PD亚型,并根据具体情况针对性地制订治疗方案,评估患者预后。

       在多发性硬化症(multiple sclerosis, MS)(图1E)中,病灶中央常有小静脉穿过,这些静脉的管径可能只有250 μm或更小。7 T MRI在提高磁化率效应和SNR方面具有明显优势,从而增加了这些小静脉的检出。一项研究显示,7 T下使用磁敏感加权成像和T2加权成像对MS病灶中心静脉(图1F)的检出率分别为73%和87%,显著高于3 T的31%[50]。有证据表明,中心静脉的存在有助于准确区分出MS和其他相似白质疾病[51, 52]。另外,灰质病变与运动和认知功能障碍的发展息息相关[53]。然而,多数灰质病变在低场强下难以检出。与3 T相比,7 T对灰质病变的检出率提高了一倍多[54]。基于7 T在中心静脉和皮质病变的检出优势,7 T磁共振在提高MS诊断的准确性,帮助早期诊断和分类方面发挥着关键作用[55]

       上述研究成果表明,得益于超高的空间分辨率和SNR,UHF-MRI在早期诊断神经退行性疾病、揭示其病理机制、寻找新的治疗靶点及评估疾病进展方面具有显著优势。此外,随着人工智能的迅猛发展,采用深度学习算法来提升从磁共振信号中提取高精度脑结构影像的能力[56],已成为当前研究的热点。未来,UHF-MRI技术与人工智能的深度融合,将成为该技术进一步发展和临床应用的关键方向。

图1  7 T在神经退行性疾病的应用。1A:23岁健康女性的海马磁共振图像;1B:82岁男性阿尔茨海默病患者海马萎缩的磁共振图像;1C:29岁健康男性黑质明显的“燕尾征”;1D:53岁女性帕金森病患者的磁共振图像,磁敏感加权成像上显示燕尾征消失;1E:42岁男性多发性硬化症患者的磁共振图像,弥散加权成像上显示多发性硬化症缓解期(蓝箭)和复发期(黄箭);1F:42岁男性多发性硬化患者的磁共振图像,磁敏感加权成像上显示“中心静脉征”(红箭)。
Fig. 1  The applications of seven tesla MRI in neurodegenerative diseases. 1A: Magnetic resonance image of hippocampus in a healthy female aged 23; 1B: Magnetic resonance image of a patient, an 82-year-old male, with Alzheimer's disease with hippocampal atrophy; 1C: Typical swallow tail sign in a healthy male aged 29; 1D: Magnetic resonance image of a patient, a 53-year-old female, with Parkinson's disease with swallow tail sign in susceptibility weighted imaging; 1E: Magnetic resonance image of a patient, a 42-year-old male, with multiple sclerosis, with the remission stage of multiple sclerosis (blue arrow) and the relapse stage of multiple sclerosis (yellow arrow) in diffusion weighted imaging; 1F: Magnetic resonance image of a patient, a 42-year-old male, with multiple sclerosis, with central vein sign shown in susceptibility weighted imaging (red arrow).

3.2 脑肿瘤

       UHF-MRI显示微小血管的优势可能有助于肿瘤的分级。与低级别病变相比,高级别胶质瘤,通常具有丰富的肿瘤微血管(图2A2B),多形性胶质母细胞瘤就是其中一个典型。因此,7 T MRI量化肿瘤微血管和坏死区域的特征有助于胶质瘤的早期分级[57]。此外,7 T MRI更高的空间分辨率不仅可以细致显示肿瘤内部结构和供血动脉,还能提供肿瘤的精准定位,明确肿瘤边界,这有利于肿瘤的定向活检和手术放疗规划[58, 59]。另外,肿瘤微环境(tumor microenvironment, TME)是肿瘤存活和转移的关键。7 T MRI光谱分离度的提高,使得2-羟基戊二酸和其他肿瘤相关代谢物的定量检测成为了可能[60]。2-羟基戊二酸是异柠檬酸脱氢酶(isocitrate dehydrogenase, IDH)突变的代谢标志物,而携带IDH突变的胶质瘤患者对化疗和放疗的反应较好[61],这进一步强调了通过检测突变代谢物以指导临床治疗的重要性。因此,7 T下MRS和CEST技术对TME的精确显示具有重要临床价值,有助于更深入地揭示TME中的代谢反应,完善免疫反应路径,进而帮助识别相关基因突变位点,推动新型化疗药物的开发,成为肿瘤预防和治疗的潜在突破口[62, 63]。在新型药物研发的过程中,疗效监测是至关重要的一环。已有研究表明,胆碱类化合物释放减少可能与肿瘤死亡密切相关,有望成为评估肿瘤治疗效果的潜在标志物[64]。然而,是否能将胆碱类化合物作为肿瘤疗效的可靠标志物,目前尚未达成明确的共识,仍需更多实验证据予以验证。结合UHF-MRI技术,有望为这一观点提供有力支持,进而拓展UHF-MRI在疗效监测中的潜力和实际应用价值。

图2  7 T对微小血管的清晰显示。2A、2B:53岁女性神经胶质瘤患者的磁共振图像,T1加权成像示肿瘤新生血管;2C:68岁健康女性,7 T高分辨率时间飞跃法磁共振血管成像清晰显示其双侧豆纹动脉及其分支;2D:68岁健康女性豆纹动脉的7 T血管壁成像(白箭)。
Fig. 2  Seven tesla magnetic resonance imaging provides clear visualization of small vessel. 2A, 2B: T1 weighted imaging shows the tumor neovascularization in the magnetic resonance image of a patient, a 53-year-old female, with high-grade glioma. 2C: High resolution time-of-flight magnetic resonance angiography clearly shows the lenticulostriate arteries and their branches in a healthy female aged 68. 2D: Intracranial vessel wall magnetic resonance imaging of the lenticulostriate arteries in 7 T in a healthy female aged 68 (white arrow).

3.3 脑血管疾病

       脑血管管径通常较小,且穿支动脉数量较多,常规场强在显示其解剖细节方面存在一定局限性。7 T MRI可以在百微米尺度上观察脑实质变化,从而改善皮质微梗死灶[65]和穿支小动脉[66]的显示效果。由于场强增强,SNR和组织T1值提高,7 T MRI可以在不使用对比剂的情况下,利用TOF-MRA获得更好的脑脊液背景抑制,提升脑血管壁和腔体的对比度,以清楚观察包括豆纹动脉(图2C)在内的更多远端血管的解剖细节,并详细描述颅脑主要供血动脉的狭窄或闭塞[67, 68]。7 T高分辨率磁共振血管壁成像(图2D)还可以测量管壁厚度[69],判断颅内动脉粥样硬化斑块的形态和成分[70],早期评估斑块的稳定性,有助于隐源性脑卒中患者病因分析和最佳治疗方案的确定[71]

       尽管7 T MRI在颅内血管病变筛查和量化评估方面展现了巨大潜力,但超高SNR不可避免会导致一定的假阳性问题。尤其是在微小病变的评估中,过度敏感的成像可能会带来误诊风险[72]。因此,如何在7 T MRI的临床应用中,合理进行影像判读并有效避免假阳性结果,仍然是一个亟待解决的重要课题。未来的研究需要进一步探讨,仅在超高场下检测到的微小病变是否真正具有临床相关性,以确保诊断的准确性和可靠性。

4 总结

       7 T MRI在空间分辨率和SNR方面具有显著优势,能够更清晰地呈现微小结构并识别潜在的生物标志物,为早期诊断和鉴别诊断神经系统疾病、完善疾病病理生理学研究、区分疾病亚型提供了新的途径和手段。然而,要充分释放这一技术的潜力,仍需要克服多方面的挑战,包括射频能量沉积导致的安全性问题、运动伪影的控制以及数据处理的复杂性等。随着技术的不断创新和产学研医的充分交叉合作,未来UHF-MRI的全面优化和广泛应用值得期待。相信通过技术的不断进步和临床研究的逐渐增多,UHF-MRI将为精准医疗带来更多突破。UHF-MRI在临床诊断、手术规划和治疗监测中的显著潜力也将为患者预后的改善提供宝贵机会,最终进一步提高患者的治疗效果和生活质量。

[1]
WENDEROTT K, KRUPS J, ZARUCHAS F, et al. Effects of artificial intelligence implementation on efficiency in medical imaging-a systematic literature review and meta-analysis[J/OL]. NPJ Digit Med, 2024, 7(1): 265 [2024-10-01]. https://pubmed.ncbi.nlm.nih.gov/39349815/. DOI: 10.1038/s41746-024-01248-9.
[2]
TRATTNIG S, SPRINGER E, BOGNER W, et al. Key clinical benefits of neuroimaging at 7T[J/OL]. NeuroImage, 2018, 168: 477-489 [2024-10-01]. https://pubmed.ncbi.nlm.nih.gov/27851995/. DOI: 10.1016/j.neuroimage.2016.11.031.
[3]
POHMANN R, SPECK O, SCHEFFLER K. Signal-to-noise ratio and MR tissue parameters in human brain imaging at 3, 7, and 9.4 tesla using current receive coil arrays[J]. Magn Reson Med, 2016, 75(2): 801-809. DOI: 10.1002/mrm.25677.
[4]
KUMAR V J, SCHEFFLER K, HAGBERG G E, et al. Quantitative susceptibility mapping of the basal Ganglia and thalamus at 9.4 tesla[J/OL]. Front Neuroanat, 2021, 15: 725731 [2024-10-01]. https://pubmed.ncbi.nlm.nih.gov/34602986/. DOI: 10.3389/fnana.2021.725731.
[5]
RADOJEWSKI P, DOBROCKY T, BRANCA M, et al. Diagnosis of small unruptured intracranial aneurysms[J]. Clin Neuroradiol, 2024, 34(1): 45-49. DOI: 10.1007/s00062-023-01282-2.
[6]
SUI B B, SANNANANJA B, ZHU C C, et al. Report from the society of magnetic resonance angiography: clinical applications of 7T neurovascular MR in the assessment of intracranial vascular disease[J]. J Neurointerv Surg, 2024, 16(8): 846-851. DOI: 10.1136/jnis-2023-020668.
[7]
COSOTTINI M, CALZONI T, LAZZAROTTI G A, et al. Time-of-flight MRA of intracranial vessels at 7 T[J/OL]. Eur Radiol Exp, 2024, 8(1): 68 [2024-10-01]. https://pubmed.ncbi.nlm.nih.gov/38844683/. DOI: 10.1186/s41747-024-00463-z.
[8]
FENG J Q, LIU X K, ZHANG Z H, et al. Comparison of 7T and 3T vessel wall MRI for the evaluation of intracranial aneurysm wall[J]. Eur Radiol, 2022, 32(4): 2384-2392. DOI: 10.1007/s00330-021-08331-9.
[9]
KOUPPARIS A, VON ELLENRIEDER N, KHOO H M, et al. Association of EEG-fMRI responses and outcome after epilepsy surgery[J/OL]. Neurology, 2021, 97(15): e1523-e1536 [2024-10-01]. https://pubmed.ncbi.nlm.nih.gov/34400584/. DOI: 10.1212/WNL.0000000000012660.
[10]
CHO S, ROY A, LIU C J, et al. Cortical layer-specific differences in stimulus selectivity revealed with high-field fMRI and single-vessel resolution optical imaging of the primary visual cortex[J/OL]. Neuroimage, 2022, 251: 118978 [2024-10-01]. https://pubmed.ncbi.nlm.nih.gov/35143974/. DOI: 10.1016/j.neuroimage.2022.118978.
[11]
JIA K, GOEBEL R, KOURTZI Z. Ultra-high field imaging of human visual cognition[J/OL]. Annu. Rev. Vis. Sci., 2023, 9: 479-500 [2024-09-30]. https://pubmed.ncbi.nlm.nih.gov/37137282/. DOI: 10.1146/annurev-vision-111022-123830.
[12]
POPLAWSKY A J, COVER C, REDDY S, et al. Odor-evoked layer-specific fMRI activities in the awake mouse olfactory bulb[J/OL]. Neuroimage, 2023, 274: 120121 [2024-09-30]. https://pubmed.ncbi.nlm.nih.gov/37080347/. DOI: 10.1016/j.neuroimage.2023.120121.
[13]
MOEREL M, YACOUB E, GULBAN O F, et al. Using high spatial resolution fMRI to understand representation in the auditory network[J/OL]. Prog Neurobiol, 2021, 207: 101887 [2024-09-30]. https://pubmed.ncbi.nlm.nih.gov/32745500/. DOI: 10.1016/j.pneurobio.2020.101887.
[14]
CHAN R W, CRON G O, ASAAD M, et al. Distinct local and brain-wide networks are activated by optogenetic stimulation of neurons specific to each layer of motor cortex[J/OL]. Neuroimage, 2022, 263: 119640 [2024-09-30]. https://pubmed.ncbi.nlm.nih.gov/36176220/. DOI: 10.1016/j.neuroimage.2022.119640.
[15]
FINN E S, HUBER L, BANDETTINI P A. Higher and deeper: bringing layer fMRI to association cortex[J/OL]. Prog Neurobiol, 2021, 207: 101930 [2024-09-30]. https://pubmed.ncbi.nlm.nih.gov/33091541/. DOI: 10.1016/j.pneurobio.2020.101930.
[16]
KOUSH Y, ROTHMAN D L, BEHAR K L, et al. Human brain functional MRS reveals interplay of metabolites implicated in neurotransmission and neuroenergetics[J]. J Cereb Blood Flow Metab, 2022, 42(6): 911-934. DOI: 10.1177/0271678x221076570.
[17]
SCHREINER S J, VAN BERGEN J M G, GIETL A F, et al. Gray matter gamma-hydroxy-butyric acid and glutamate reflect beta-amyloid burden at old age[J/OL]. Alzheimers Dement, 2024, 16(2): e12587 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/38690510/. DOI: 10.1002/dad2.12587.
[18]
MANCINI L, CASAGRANDA S, GAUTIER G, et al. CEST MRI provides amide/amine surrogate biomarkers for treatment-naïve glioma sub-typing[J]. Eur J Nucl Med Mol Imaging, 2022, 49(7): 2377-2391. DOI: 10.1007/s00259-022-05676-1.
[19]
MEISSNER J E, KORZOWSKI A, REGNERY S, et al. Early response assessment of glioma patients to definitive chemoradiotherapy using chemical exchange saturation transfer imaging at 7 T[J]. J Magn Reson Imaging, 2019, 50(4): 1268-1277. DOI: 10.1002/jmri.26702.
[20]
GRIMALDI S, MENDILI M M EL, ZAARAOUI W, et al. Increased sodium concentration in substantia nigra in early Parkinson's disease: a preliminary study with ultra-high field (7T) MRI[J/OL]. Front Neurol, 2021, 12: 715618 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/34566858/. DOI: 10.3389/fneur.2021.715618.
[21]
HAEGER A, BOTTLAENDER M, LAGARDE J, et al. What can 7T sodium MRI tell us about cellular energy depletion and neurotransmission in Alzheimer's disease?[J]. Alzheimers Dement, 2021, 17(11): 1843-1854. DOI: 10.1002/alz.12501.
[22]
MCCARTHY L, VERMA G, HANGEL G, et al. Application of 7T MRS to high-grade gliomas[J]. AJNR Am J Neuroradiol, 2022, 43(10): 1378-1395. DOI: 10.3174/ajnr.A7502.
[23]
REGNERY S, BEHL N G R, PLATT T, et al. Ultra-high-field sodium MRI as biomarker for tumor extent, grade and IDH mutation status in glioma patients[J/OL]. Neuroimage Clin, 2020, 28: 102427 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/33002860/. DOI: 10.1016/j.nicl.2020.102427.
[24]
PAECH D, NAGEL A M, SCHULTHEISS M N, et al. Quantitative dynamic oxygen 17 MRI at 7.0 T for the cerebral oxygen metabolism in glioma[J]. Radiology, 2020, 295(1): 181-189. DOI: 10.1148/radiol.2020191711.
[25]
PAECH D, WECKESSER N, FRANKE V L, et al. Whole-brain intracellular pH mapping of gliomas using high-resolution 31P MR spectroscopic imaging at 7.0 T[J/OL]. Radiol Imaging Cancer, 2024, 6(1): e220127 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/38133553/. DOI: 10.1148/rycan.220127.
[26]
PAYNE T, BURGESS T, BRADLEY S, et al. Multimodal assessment of mitochondrial function in Parkinson's disease[J]. Brain, 2024, 147(1): 267-280. DOI: 10.1093/brain/awad364.
[27]
KRAFF O, FISCHER A, NAGEL A M, et al. MRI at 7 Tesla and above: demonstrated and potential capabilities[J]. J Magn Reson Imaging, 2015, 41(1): 13-33. DOI: 10.1002/jmri.24573.
[28]
HANSSON B, MARKENROTH BLOCH K, OWMAN T, et al. Subjectively reported effects experienced in an actively shielded 7T MRI: a large-scale study[J]. J Magn Reson Imaging, 2020, 52(4): 1265-1276. DOI: 10.1002/jmri.27139.
[29]
MIAN O S, LI Y, ANTUNES A, et al. On the vertigo due to static magnetic fields[J/OL]. PLoS One, 2013, 8(10): e78748 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/24205304/. DOI: 10.1371/journal.pone.0078748.
[30]
COSOTTINI M, FROSINI D, BIAGI L, et al. Short-term side-effects of brain MR examination at 7 T: a single-centre experience[J]. Eur Radiol, 2014, 24(8): 1923-1928. DOI: 10.1007/s00330-014-3177-y.
[31]
WINTER L, SEIFERT F, ZILBERTI L, et al. MRI-related heating of implants and devices: a review[J]. J Magn Reson Imaging, 2021, 53(6): 1646-1665. DOI: 10.1002/jmri.27194.
[32]
VU A T, AUERBACH E, LENGLET C, et al. High resolution whole brain diffusion imaging at 7T for the Human Connectome Project[J/OL]. Neuroimage, 2015, 122: 318-331 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/26260428/. DOI: 10.1016/j.neuroimage.2015.08.004.
[33]
OLIVEIRA Í A F, ROOS T, DUMOULIN S O, et al. Can 7T MPRAGE match MP2RAGE for gray-white matter contrast?[J/OL]. Neuroimage, 2021, 240: 118384 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/34265419/. DOI: 10.1016/j.neuroimage.2021.118384.
[34]
JACOBS P S, BENYARD B, CAO Q, et al. B1+ inhomogeneity correction of volumetric brain NOEMTR via high permittivity dielectric padding at 7 T[J]. Magn Reson Med, 2023, 90(4): 1537-1546. DOI: 10.1002/mrm.29739.
[35]
YETISIR F, POSER B A, GRANT P E, et al. Parallel transmission 2D RARE imaging at 7T with transmit field inhomogeneity mitigation and local SAR control[J/OL]. Magn Reson Imaging, 2022, 93: 87-96 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/35940379/. DOI: 10.1016/j.mri.2022.08.006.
[36]
SOLOMON O, PATRIAT R, BRAUN H, et al. Motion robust magnetic resonance imaging via efficient Fourier aggregation[J/OL]. Med Image Anal, 2023, 83: 102638 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/36257133/. DOI: 10.1016/j.media.2022.102638.
[37]
HEPHZIBAH R, ANANDHARAJ H C, KOWSALYA G, et al. Review on deep learning methodologies in medical image restoration and segmentation[J]. Curr Med Imaging, 2023, 19(8): 844-854. DOI: 10.2174/1573405618666220407112825.
[38]
KLINKMUELLER P, KRONENBUERGER M, MIAO X Y, et al. Impaired response of cerebral oxygen metabolism to visual stimulation in Huntington's disease[J]. J Cereb Blood Flow Metab, 2021, 41(5): 1119-1130. DOI: 10.1177/0271678X20949286.
[39]
MARXREITER F, LAMBRECHT V, MENNECKE A, et al. Parkinson's disease or multiple system atrophy: potential separation by quantitative susceptibility mapping[J/OL]. Ther Adv Neurol Disord, 2023, 16: 17562864221143834 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/36846471/. DOI: 10.1177/17562864221143834.
[40]
VAN EGROO M, RIPHAGEN J M, ASHTON N J, et al. Ultra-high field imaging, plasma markers and autopsy data uncover a specific rostral locus coeruleus vulnerability to hyperphosphorylated tau[J]. Mol Psychiatry, 2023, 28(6): 2412-2422. DOI: 10.1038/s41380-023-02041-y.
[41]
VAN DEN BRINK H, DOUBAL F N, DUERING M. Advanced MRI in cerebral small vessel disease[J]. Int J Stroke, 2023, 18(1): 28-35. DOI: 10.1177/17474930221091879.
[42]
HUANG J N, BIESSELS G J, DE LEEUW F E, et al. Cerebral microinfarcts revisited: detection, causes, and clinical relevance[J]. Int J Stroke, 2024, 19(1): 7-15. DOI: 10.1177/17474930231187979.
[43]
DUSEK P, HOFER T, ALEXANDER J, et al. Cerebral iron deposition in neurodegeneration[J/OL]. Biomolecules, 2022, 12(5): 714 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/35625641/. DOI: 10.3390/biom12050714.
[44]
PERERA MOLLIGODA ARACHCHIGE A S, GARNER A K. Seven Tesla MRI in Alzheimer's disease research: state of the art and future directions: a narrative review[J]. AIMS Neurosci, 2023, 10(4): 401-422. DOI: 10.3934/Neuroscience.2023030.
[45]
DAS N, REN J M, SPENCE J, et al. Phosphate brain energy metabolism and cognition in Alzheimer's disease: a spectroscopy study using whole-brain volume-coil 31Phosphorus magnetic resonance spectroscopy at 7Tesla[J/OL]. Front Neurosci, 2021, 15: 641739 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/33889067/. DOI: 10.3389/fnins.2021.641739.
[46]
BIONDETTI E, SANTIN M D, VALABRÈGUE R, et al. The spatiotemporal changes in dopamine, neuromelanin and iron characterizing Parkinson's disease[J]. Brain, 2021, 144(10): 3114-3125. DOI: 10.1093/brain/awab191.
[47]
CHAU M T, TODD G, WILCOX R, et al. Diagnostic accuracy of the appearance of Nigrosome-1 on magnetic resonance imaging in Parkinson's disease: a systematic review and meta-analysis[J/OL]. Parkinsonism Relat Disord, 2020, 78: 12-20 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/32668370/. DOI: 10.1016/j.parkreldis.2020.07.002.
[48]
BAE Y J, KIM J M, SOHN C H, et al. Imaging the substantia nigra in parkinson disease and other parkinsonian syndromes[J]. Radiology, 2021, 300(2): 260-278. DOI: 10.1148/radiol.2021203341.
[49]
LAKHANI D A, ZHOU X Z, TAO S Z, et al. Diagnostic utility of 7T neuromelanin imaging of the substantia nigra in Parkinson's disease[J/OL]. NPJ Parkinsons Dis, 2024, 10(1): 13 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/38191546/. DOI: 10.1038/s41531-024-00631-3.
[50]
OKROMELIDZE L, PATEL V, SINGH R B, et al. Central vein sign in multiple sclerosis: a comparison study of the diagnostic performance of 3T versus 7T MRI[J]. AJNR Am J Neuroradiol, 2023, 45(1): 76-81. DOI: 10.3174/ajnr.A8083.
[51]
SATI P, OH J, CONSTABLE R T, et al. The central vein sign and its clinical evaluation for the diagnosis of multiple sclerosis: a consensus statement from the North American Imaging in Multiple Sclerosis Cooperative[J]. Nat Rev Neurol, 2016, 12(12): 714-722. DOI: 10.1038/nrneurol.2016.166.
[52]
CHAABAN L, SAFWAN N, MOUSSA H, et al. Central vein sign: a putative diagnostic marker for multiple sclerosis[J]. Acta Neurol Scand, 2022, 145(3): 279-287. DOI: 10.1111/ane.13553.
[53]
HARRISON D M, ROY S, OH J, et al. Association of cortical lesion burden on 7-T magnetic resonance imaging with cognition and disability in multiple sclerosis[J]. JAMA Neurol, 2015, 72(9): 1004-1012. DOI: 10.1001/jamaneurol.2015.1241.
[54]
KILSDONK I D, JONKMAN L E, KLAVER R, et al. Increased cortical grey matter lesion detection in multiple sclerosis with 7 T MRI: a post-mortem verification study[J]. Brain, 2016, 139(Pt 5): 1472-1481. DOI: 10.1093/brain/aww037.
[55]
CAGOL A, CORTESE R, BARAKOVIC M, et al. Diagnostic performance of cortical lesions and the central vein sign in multiple sclerosis[J]. JAMA Neurol, 2024, 81(2): 143-153. DOI: 10.1001/jamaneurol.2023.4737.
[56]
PEROSA V, SCHERLEK A A, KOZBERG M G, et al. Deep learning assisted quantitative assessment of histopathological markers of Alzheimer's disease and cerebral amyloid angiopathy[J/OL]. Acta Neuropathol Commun, 2021, 9(1): 141 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/34419154/. DOI: 10.1186/s40478-021-01235-1.
[57]
NATSUMEDA M, MATSUZAWA H, WATANABE M, et al. SWI by 7T MR imaging for the microscopic imaging diagnosis of astrocytic and oligodendroglial tumors[J]. AJNR Am J Neuroradiol, 2022, 43(11): 1575-1581. DOI: 10.3174/ajnr.A7666.
[58]
CHENG K, DUAN Q, HU J X, et al. Evaluation of postcontrast images of intracranial tumors at 7T and 3T MRI: an intra-individual comparison study[J]. CNS Neurosci Ther, 2023, 29(2): 559-565. DOI: 10.1111/cns.14036.
[59]
REGNERY S, KNOWLES B R, PAECH D, et al. High-resolution FLAIR MRI at 7 Tesla for treatment planning in glioblastoma patients[J/OL]. Radiother Oncol, 2019, 130: 180-184 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/30177373/. DOI: 10.1016/j.radonc.2018.08.002.
[60]
EMIR U E, LARKIN S J, DE PENNINGTON N, et al. Noninvasive quantification of 2-hydroxyglutarate in human gliomas with IDH1 and IDH2 mutations[J]. Cancer Res, 2016, 76(1): 43-49. DOI: 10.1158/0008-5472.CAN-15-0934.
[61]
HAN X T, ZHOU H D, SUN W, et al. IDH1R132H mutation increases radiotherapy efficacy and a 4-gene radiotherapy-related signature of WHO grade 4 gliomas[J/OL]. Sci Rep, 2023, 13(1): 19659 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/37952042/. DOI: 10.1038/s41598-023-46335-1.
[62]
PARMIGIANI E, SCALERA M, MORI E, et al. Old stars and new players in the brain tumor microenvironment[J/OL]. Front Cell Neurosci, 2021, 15: 709917 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/34690699/. DOI: 10.3389/fncel.2021.709917.
[63]
GIRIDHARAN N, GLITZA OLIVA I C, O'BRIEN B J, et al. Targeting the tumor microenvironment in brain metastasis[J]. Neurosurg Clin N Am, 2020, 31(4): 641-649. DOI: 10.1016/j.nec.2020.06.011.
[64]
GLUNDE K, BHUJWALLA Z M, RONEN S M. Choline metabolism in malignant transformation[J]. Nat Rev Cancer, 2011, 11(12): 835-848. DOI: 10.1038/nrc3162.
[65]
VAN VELUW S J, SHIH A Y, SMITH E E, et al. Detection, risk factors, and functional consequences of cerebral microinfarcts[J]. Lancet Neurol, 2017, 16(9): 730-740. DOI: 10.1016/S1474-4422(17)30196-5.
[66]
VAN DEN BRINK H, DOUBAL F N, DUERING M. Advanced MRI in cerebral small vessel disease[J]. Int J Stroke, 2023, 18(1): 28-35. DOI: 10.1177/17474930221091879.
[67]
DE COCKER L J, LINDENHOLZ A, ZWANENBURG J J, et al. Clinical vascular imaging in the brain at 7T[J]. NeuroImage, 2018, 168: 452-458. DOI: 10.1016/j.neuroimage.2016.11.044.
[68]
BAI X Y, FAN P P, LI Z Y, et al. Evaluating middle cerebral artery plaque characteristics and lenticulostriate artery morphology associated with subcortical infarctions at 7T MRI[J]. J Magn Reson Imaging, 2024, 59(3): 1045-1055. DOI: 10.1002/jmri.28839.
[69]
VAN HESPEN K M, ZWANENBURG J J M, HENDRIKSE J, et al. Subvoxel vessel wall thickness measurements of the intracranial arteries using a convolutional neural network[J/OL]. Med Image Anal, 2021, 67: 101818 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/33049576/. DOI: 10.1016/j.media.2020.101818.
[70]
WU F, YU H, YANG Q. Imaging of intracranial atherosclerotic plaques using 3.0 T and 7.0 T magnetic resonance imaging-current trends and future perspectives[J]. Cardiovasc Diagn Ther, 2020, 10(4): 994-1004. DOI: 10.21037/cdt.2020.02.03.
[71]
FAKIH R, ROA J A, BATHLA G, et al. Detection and quantification of symptomatic atherosclerotic plaques with high-resolution imaging in cryptogenic stroke[J]. Stroke, 2020, 51(12): 3623-3631. DOI: 10.1161/STROKEAHA.120.031167.
[72]
ONDER O, YARASIR Y, AZIZOVA A, et al. Errors, discrepancies and underlying bias in radiology with case examples: a pictorial review[J/OL]. Insights Imaging, 2021, 12(1): 51 [2024-09-14]. https://pubmed.ncbi.nlm.nih.gov/33877458/. DOI: 10.1186/s13244-021-00986-8.

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