Novel Method to Improve the Uniformity of 7T Body MR Images

IF 0.9 4区 医学 Q4 CHEMISTRY, PHYSICAL
Bu S. Park, S. Rajan
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引用次数: 0

Abstract

When using ultrahigh-field MR systems (7T), the variations in the RF magnetic field can lead to significant loss in image uniformity. To optimize the overall MR image quality, the image region is divided into multiple smaller regions of interest (the ROIs), which can be independently optimized using transmit array optimization techniques including RF shimming, to improve RF magnetic fields and image intensity. Electromagnetic numerical simulations and corresponding transverse magnetization (|Mt|) acquired using the Bloch equation-based MRI simulator are used to evaluate the proposed method. Compared to the simulation results of quadrature driving method, mean and standard deviation (SD) of |Mt| in the full image (an inner diameter of 500 mm) were improved 47% (mean) and 48% (SD), whereas 94% (max) and 97% (mean) improved in the unaveraged SAR using the proposed method. The uniformity of |Mt| acquired using the method was especially improved in the peripheral region of the selected phantom image compared to that of other methods. The proposed method using multiple independently optimized ROIs and numerical simulations significantly improved the uniformity of |Mt| body images at 7T. This technique would be generally applicable to any high-field strength MR systems, which generate short RF wavelengths compared to the field of view.
一种提高7T体MR图像均匀性的新方法
当使用超高场MR系统(7T)时,射频磁场的变化会导致图像均匀性的显著损失。为了优化整体MR图像质量,将图像区域划分为多个较小的感兴趣区域(roi),这些区域可以使用发射阵列优化技术(包括射频调光)独立优化,以提高射频磁场和图像强度。利用基于Bloch方程的MRI模拟器获得的电磁数值模拟和相应的横向磁化强度(|Mt|)来评估所提出的方法。与正交驱动方法的模拟结果相比,在全图像(内径500 mm)中,Mt的均值和标准差(SD)分别提高了47%(均值)和48% (SD),而在非平均SAR中,采用该方法的Mt的均值和标准差(SD)分别提高了94%(最大值)和97%(均值)。与其他方法相比,该方法获得的Mt值的均匀性在选取的幻像外围区域得到了显著提高。该方法利用多个独立优化的roi和数值模拟,显著提高了7T时Mt体像的均匀性。这种技术通常适用于任何高场强度的MR系统,与视场相比,它产生的RF波长短。
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来源期刊
CiteScore
2.60
自引率
0.00%
发文量
3
审稿时长
>12 weeks
期刊介绍: Concepts in Magnetic Resonance Part B brings together engineers and physicists involved in the design and development of hardware and software employed in magnetic resonance techniques. The journal welcomes contributions predominantly from the fields of magnetic resonance imaging (MRI), nuclear magnetic resonance (NMR), and electron paramagnetic resonance (EPR), but also encourages submissions relating to less common magnetic resonance imaging and analytical methods. Contributors come from both academia and industry, to report the latest advancements in the development of instrumentation and computer programming to underpin medical, non-medical, and analytical magnetic resonance techniques.
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