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5.0特斯拉下豆纹动脉成像的3D时间飞跃磁共振血管造影:一种分层分析方法及临床应用

3D time-of-flight magnetic resonance angiography of lenticulostriate artery imaging at 5.0 Tesla: a hierarchic analysis method and clinical applications.

作者信息

Mei Hao, Lv Jinfeng, Xu Dan, Gao Lei, Sun Wenbo, Zhong Xiaoli, Fan Chenhong, Tao Ran, Song Xiaopeng, Xiao Feng, Xu Haibo

机构信息

Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China.

Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

Quant Imaging Med Surg. 2025 Mar 3;15(3):1768-1783. doi: 10.21037/qims-24-1554. Epub 2025 Feb 26.

DOI:10.21037/qims-24-1554
PMID:40160666
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11948410/
Abstract

BACKGROUND

Lenticulostriate artery (LSA) arteriosclerosis is a key pathological basis for cerebrovascular diseases including stroke and cerebral small vessel disease. However, the comprehensive visualization and the meticulous quantitative analysis of the entire spectrum of LSA branches remain an ongoing clinical challenge. This study aimed to explore the efficacy of LSA branch detection using ultra-high field clinical 5.0 Tesla (T) magnetic resonance imaging (MRI) with 3D time-of-flight (TOF) magnetic resonance angiography (MRA) and to introduce a hierarchic categorization method for better LSA branching pattern analysis.

METHODS

A total of 12 participants were included and scanned using 5.0T and 3.0T TOF-MRA. First, an LSA hierarchic analysis method that categorized the LSA into three levels was proposed. Morphological parameters and signal-to-noise ratio/contrast-to-noise ratio (SNR/CNR) were calculated separately at each level. Then, the LSA imaging quality was compared between 5.0T and 3.0T TOF-MRA, utilizing the hierarchic analysis method. Next, the resolution setting in 5.0T TOF-MRA was optimized for better LSA imaging. Finally, the patient with left cerebral infarction underwent a 4-month follow-up examination using 5.0T TOF-MRA to validate the clinical utility of the 5.0T TOF-MRA and the proposed hierarchic analysis method.

RESULTS

The LSA imaging quality on 5.0T is significantly better than that of 3.0T in different levels of the LSA branches both in the numbers and lengths (P<0.05). Critically, LSA tertiary branches which were commonly delineated in the 5.0T TOF-MRA images were barely visible in the 3.0T images; furthermore, at the origin of LSA branches, 5.0T TOF-MRA showed notably superior visualization in comparison to the 3.0T (P<0.001). The clinical application studies showed the advantageous prospects of the proposed quantitative analysis method for LSA-related research at 5.0T.

CONCLUSIONS

The visibility in the branching of LSA with 5.0T TOF-MRA is superior to that of 3.0T, especially at the origination from the middle cerebral artery (MCA) and the periphery of its branches. With the implementation of the proposed hierarchic analysis method for LSA, 5.0T TOF-MRA could be a valuable instrument for identifying subtle changes in LSA associated with various cerebrovascular-related diseases.

摘要

背景

豆纹动脉(LSA)动脉硬化是包括中风和脑小血管疾病在内的脑血管疾病的关键病理基础。然而,对LSA分支全谱进行全面可视化和细致定量分析仍是一项持续存在的临床挑战。本研究旨在探讨使用超高场临床5.0特斯拉(T)磁共振成像(MRI)结合三维时间飞跃(TOF)磁共振血管造影(MRA)检测LSA分支的有效性,并引入一种分层分类方法以更好地分析LSA分支模式。

方法

共纳入12名参与者,使用5.0T和3.0T TOF-MRA进行扫描。首先,提出一种将LSA分为三个级别的LSA分层分析方法。分别计算每个级别上的形态学参数和信噪比/对比噪声比(SNR/CNR)。然后,利用分层分析方法比较5.0T和3.0T TOF-MRA之间的LSA成像质量。接下来,对5.0T TOF-MRA中的分辨率设置进行优化以获得更好的LSA成像。最后,对左侧脑梗死患者使用5.0T TOF-MRA进行为期4个月的随访检查,以验证5.0T TOF-MRA及所提出的分层分析方法的临床实用性。

结果

在LSA分支的不同级别上,5.0T的LSA成像质量在数量和长度方面均明显优于3.0T(P<0.05)。关键的是,在5.0T TOF-MRA图像中通常能清晰显示的LSA三级分支在3.0T图像中几乎不可见;此外,在LSA分支的起源处,5.0T TOF-MRA的可视化效果明显优于3.0T(P<0.001)。临床应用研究显示了所提出的5.0T下LSA定量分析方法在相关研究中的有利前景。

结论

5.0T TOF-MRA对LSA分支的显示优于3.0T,尤其是在大脑中动脉(MCA)起始处及其分支周边。随着所提出的LSA分层分析方法的实施,5.0T TOF-MRA可能成为识别与各种脑血管相关疾病相关的LSA细微变化的有价值工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/8b30a5e84a77/qims-15-03-1768-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/72dd599f54a2/qims-15-03-1768-f1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/227fe841b05a/qims-15-03-1768-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/c48a9fd183c9/qims-15-03-1768-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/8b30a5e84a77/qims-15-03-1768-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/72dd599f54a2/qims-15-03-1768-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/4a207767fc8b/qims-15-03-1768-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/d80439afd0f5/qims-15-03-1768-f3.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/227fe841b05a/qims-15-03-1768-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/c48a9fd183c9/qims-15-03-1768-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/707d/11948410/8b30a5e84a77/qims-15-03-1768-f7.jpg

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