A novel free-breathing abdominal RAVE T2/T1 hybrid MRI sequence in patients with cystic fibrosis: Preliminary results

European Journal of Radiology(2022)

引用 0|浏览0
暂无评分
摘要
Objectives Patients with cystic fibrosis (CF) increasingly require imaging for the diagnosis of abdominal complications. We prospectively evaluated the image quality and signal-to-noise ratio (SNR) of a modern radial volumetric encoding (RAVE) T2/T1 hybrid sequence for abdominal magnetic resonance imaging (MRI). RAVET2/T1 is a three-dimensional radial sequence with fat saturation and blood flow suppression that acquires T2- and T1-weighted contrasts in one scan in an identical slice position during free-breathing. Methods Sixteen CF patients underwent axial T2 HASTE (1000 ms/93 ms TR/TE), T1 DIXON (6.8 ms/2.4 ms/4.8 ms TR/TE1/TE2), and RAVE T2/T1 hybrid sequence (1200 ms/1.7 ms/3.3 ms/4.9 ms/102 ms TR/TE1/TE2/TE3/TE4) of the upper abdomen at 1.5 Tesla. The SNR values in six different regions were assessed and compared using the Wilcoxon signed-rank test. The image quality criteria were rated on a 5-point Likert scale. Results In all regions, the SNR was significantly higher in the T2 weighted aspect of the RAVE T2/T1 hybrid sequence compared to T2 HASTE (p < 0.05) and significantly lower in the T1 weighted in-phase aspect of the RAVE T2/T1 hybrid sequence compared to the T1 DIXON sequence (p < 0.05).Qualitatively the T2 weighted aspect of the RAVE T2/T1 hybrid sequence was rated significantly higher than the T2 HASTE in 6 of 7 categories (p < 0.05) and the T1 weighted in-phase aspect of the RAVE T2/T1 hybrid sequence was rated significantly higher than the T1 DIXON in 2 of 6 categories (p < 0.05). Conclusions The abdominal radial RAVE T2/T1 hybrid sequence provided higher image quality and SNR than the T2HASTEsequence. Together with increased robustness against motion artifacts, the RAVE T2/T1 hybrid sequence appears to be a good tool for abdominal imaging in CF patients.
更多
查看译文
关键词
Magnetic resonance imaging,Motion,Gallbladder,Cystic fibrosis related liver disease
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要