Suppr超能文献

在商用0.55 T系统上构建全面的心血管磁共振检查:关于潜在应用的图文综述

Building a comprehensive cardiovascular magnetic resonance exam on a commercial 0.55 T system: A pictorial essay on potential applications.

作者信息

Varghese Juliet, Jin Ning, Giese Daniel, Chen Chong, Liu Yingmin, Pan Yue, Nair Nikita, Shalaan Mahmoud T, Khan Mahmood, Tong Matthew S, Ahmad Rizwan, Han Yuchi, Simonetti Orlando P

机构信息

Department of Biomedical Engineering, The Ohio State University, Columbus, OH, United States.

Cardiovascular MR R&D, Siemens Medical Solutions USA, Malvern, PA, United States.

出版信息

Front Cardiovasc Med. 2023 Mar 1;10:1120982. doi: 10.3389/fcvm.2023.1120982. eCollection 2023.

Abstract

BACKGROUND

Contemporary advances in low-field magnetic resonance imaging systems can potentially widen access to cardiovascular magnetic resonance (CMR) imaging. We present our initial experience in building a comprehensive CMR protocol on a commercial 0.55 T system with a gradient performance of 26 mT/m amplitude and 45 T/m/s slew rate. To achieve sufficient image quality, we adapted standard imaging techniques when possible, and implemented compressed-sensing (CS) based techniques when needed in an effort to compensate for the inherently low signal-to-noise ratio at lower field strength.

METHODS

A prototype CMR exam was built on an 80 cm, ultra-wide bore commercial 0.55 T MR system. Implementation of all components aimed to overcome the inherently lower signal of low-field and the relatively longer echo and repetition times owing to the slower gradients. CS-based breath-held and real-time cine imaging was built utilizing high acceleration rates to meet nominal spatial and temporal resolution recommendations. Similarly, CS 2D phase-contrast cine was implemented for flow. Dark-blood turbo spin echo sequences with deep learning based denoising were implemented for morphology assessment. Magnetization-prepared single-shot myocardial mapping techniques incorporated additional source images. CS-based dynamic contrast-enhanced imaging was implemented for myocardial perfusion and 3D MR angiography. Non-contrast 3D MR angiography was built with electrocardiogram-triggered, navigator-gated magnetization-prepared methods. Late gadolinium enhanced (LGE) tissue characterization methods included breath-held segmented and free-breathing single-shot imaging with motion correction and averaging using an increased number of source images. Proof-of-concept was demonstrated through porcine infarct model, healthy volunteer, and patient scans.

RESULTS

Reasonable image quality was demonstrated for cardiovascular structure, function, flow, and LGE assessment. Low-field afforded utilization of higher flip angles for cine and MR angiography. CS-based techniques were able to overcome gradient speed limitations and meet spatial and temporal resolution recommendations with imaging times comparable to higher performance scanners. Tissue mapping and perfusion imaging require further development.

CONCLUSION

We implemented cardiac applications demonstrating the potential for comprehensive CMR on a novel commercial 0.55 T system. Further development and validation studies are needed before this technology can be applied clinically.

摘要

背景

低场磁共振成像系统的当代进展可能会扩大心血管磁共振(CMR)成像的可及性。我们展示了在一台梯度性能为振幅26 mT/m和 slew率45 T/m/s的商用0.55 T系统上构建全面CMR方案的初步经验。为了获得足够的图像质量,我们尽可能采用标准成像技术,并在需要时实施基于压缩感知(CS)的技术,以弥补低场强下固有的低信噪比。

方法

在一台80 cm、超宽孔径商用0.55 T MR系统上构建了一个CMR检查原型。所有组件的实施旨在克服低场固有的较低信号以及由于梯度较慢导致的相对较长的回波和重复时间。利用高加速率构建基于CS的屏气和实时电影成像,以满足标称的空间和时间分辨率建议。同样,基于CS的二维相位对比电影成像用于血流成像。采用基于深度学习去噪的黑血涡轮自旋回波序列进行形态学评估。磁化准备单次心肌成像技术纳入了额外的源图像。基于CS的动态对比增强成像用于心肌灌注和三维磁共振血管造影。非对比三维磁共振血管造影采用心电图触发、导航门控磁化准备方法构建。延迟钆增强(LGE)组织表征方法包括屏气分段和自由呼吸单次成像,采用运动校正并增加源图像数量进行平均。通过猪梗死模型、健康志愿者和患者扫描证明了概念验证。

结果

在心血管结构、功能、血流和LGE评估方面展示了合理的图像质量。低场允许在电影成像和磁共振血管造影中使用更高的翻转角。基于CS的技术能够克服梯度速度限制,并在与高性能扫描仪相当的成像时间内满足空间和时间分辨率建议。组织成像和灌注成像需要进一步发展。

结论

我们实施了心脏应用,展示了在新型商用0.55 T系统上进行全面CMR的潜力。在该技术能够临床应用之前,需要进一步的开发和验证研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f5c5/10014600/f01d063b29ad/fcvm-10-1120982-g0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验