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3特斯拉(3T)下运动校正肝脏扩散加权成像的优化:结合复数平均和重新参数化的 sinc 脂肪抑制脉冲与优化的水激励脉冲。

Optimization of motion-corrected liver diffusion-weighted imaging at 3 Tesla (3T): incorporating complex averaging and reparametrized sinc fatsat pulse with optimized water excitation pulse.

作者信息

Chen Zhiyong, Xing Zhangli, Zheng Enshuang, Luo Mingcong, Fu Caixia, Li Guijin, Benkert Thomas, Xue Yunjing, Sun Bin

机构信息

Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China.

MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China.

出版信息

Quant Imaging Med Surg. 2024 Sep 1;14(9):6579-6589. doi: 10.21037/qims-24-340. Epub 2024 Aug 28.

Abstract

BACKGROUND

In liver diffusion-weighted imaging (DWI), single-shot echo-planar imaging (SS-EPI) sequences are susceptible to motion artifacts, resulting in image blurring and decreased lesion detection rates. This study aimed to develop and optimize a motion-corrected (MOCO) technique for liver DWI at 3 Tesla (3T). The technique incorporates motion correction, complex averaging, and a combination of a reparametrized sinc fatsat pulse with an optimized water excitation pulse.

METHODS

This prospective cross-sectional study performed at Fujian Medical University Union Hospital included 42 healthy volunteers who underwent four SS-EPI DWI sequences on a 3T magnetic resonance imaging (MRI) system between January 2023 and March 2023. The sequences included a navigator-triggered (NT) MOCO-DWI, two free-breathing (FB) MOCO-DWI, and an FB conventional DWI (FB cDWI) sequence. Motion correction and complex averaging were performed for both MOCO-DWI sequences, and fat suppression was achieved using either a sinc fatsat pulse with optimized water excitation or a conventional spectral attenuated inversion recovery (SPAIR) pulse. Liver signal-to-noise ratio (SNR) was measured at b=1,000 s/mm. Qualitative parameters were independently evaluated by three radiologists using 5-point Likert scales. Quantitative parameters were assessed using the Kolmogorov-Smirnov test, and variance homogeneity was assessed using Levene's test. Regarding the qualitative analysis, the Friedman test was used to compare subjective scores among the four techniques.

RESULTS

The SNRs of the liver were significantly higher with FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm (P<0.05). In the superior-inferior direction, the SNRs of the inferior level of the liver were higher than those of the superior level in NT MOCO-DWI. The qualitative results showed significantly higher ratings for NT MOCO-DWI and FB MOCO-DWI compared to the other EPI DWI sequences at b=1,000 s/mm (P<0.05). Regarding the apparent diffusion coefficient (ADC) quantification, the ADC values of the left lobe were higher than those of the right lobe in all four techniques.

CONCLUSIONS

The proposed EPI DWI technique, incorporating motion correction, complex averaging, and a modified fat suppression scheme using spectral fat saturation and binomial water excitation, was found to be clinically feasible for liver MRI. The FB MOCO-DWI sequence, with its superior SNR and excellent image quality, is recommended for liver DW imaging at 3T in clinical routine.

摘要

背景

在肝脏扩散加权成像(DWI)中,单次激发回波平面成像(SS-EPI)序列易受运动伪影影响,导致图像模糊和病变检出率降低。本研究旨在开发并优化一种用于3特斯拉(3T)肝脏DWI的运动校正(MOCO)技术。该技术结合了运动校正、复数平均,以及重新参数化的 sinc 脂肪抑制脉冲与优化的水激励脉冲的组合。

方法

这项前瞻性横断面研究在福建医科大学附属协和医院进行,纳入了42名健康志愿者,他们于2023年1月至2023年3月在3T磁共振成像(MRI)系统上接受了四个SS-EPI DWI序列检查。这些序列包括一个导航触发(NT)的MOCO-DWI、两个自由呼吸(FB)的MOCO-DWI,以及一个FB常规DWI(FB cDWI)序列。对两个MOCO-DWI序列都进行了运动校正和复数平均,并且使用具有优化水激励的 sinc 脂肪抑制脉冲或传统的频谱衰减反转恢复(SPAIR)脉冲来实现脂肪抑制。在b = 1000 s/mm²时测量肝脏的信噪比(SNR)。由三名放射科医生使用5级李克特量表独立评估定性参数。使用柯尔莫哥洛夫-斯米尔诺夫检验评估定量参数,使用莱文检验评估方差齐性。关于定性分析,使用弗里德曼检验比较四种技术之间的主观评分。

结果

在b = 1000 s/mm²时,与其他EPI DWI序列相比,FB MOCO-DWI的肝脏SNR显著更高(P < 0.05)。在上下方向上,NT MOCO-DWI中肝脏下级的SNR高于上级。定性结果显示,在b = 1000 s/mm²时,与其他EPI DWI序列相比,NT MOCO-DWI和FB MOCO-DWI的评分显著更高(P < 0.05)。关于表观扩散系数(ADC)定量,在所有四种技术中,左叶的ADC值均高于右叶。

结论

所提出的EPI DWI技术,结合了运动校正、复数平均,以及使用频谱脂肪饱和和二项式水激励的改良脂肪抑制方案,被发现对于肝脏MRI在临床上是可行的。具有更高SNR和优异图像质量的FB MOCO-DWI序列,推荐用于3T临床常规肝脏DW成像。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7cd7/11400668/909cc2d46cc0/qims-14-09-6579-f1.jpg

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