不同加速因子的人工智能压缩感知在臂丛 MRI 成像中的比较：扫描时间和图像质量。
Comparison of different acceleration factors of artificial intelligence-compressed sensing for brachial plexus MRI imaging: scanning time and image quality.
机构信息
Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 Yongan Road, Beijing, 100050, China.
Department of Radiology, BaoShan Hospital of Traditional Chinese Medicine, Baoshan, Yunnan, China.
出版信息
BMC Med Imaging. 2024 Nov 14;24(1):309. doi: 10.1186/s12880-024-01493-0.
BACKGROUND
3D brachial plexus MRI scanning is prone to examination failure due to the lengthy scan times, which can lead to patient discomfort and motion artifacts. Our purpose is to investigate the efficacy of artificial intelligence-assisted compressed sensing (ACS) in improving the acceleration efficiency and maintaining or enhancing the image quality of brachial plexus MR imaging.
METHODS
A total of 30 volunteers underwent 3D sampling perfection with application-optimized contrast using different flip angle evolution short time inversion recovery using a 3.0T MR scanner. The imaging protocol included parallel imaging (PI) and ACS employing acceleration factors of 4.37, 6.22, and 9.03. Radiologists evaluated the neural detail display, fat suppression effectiveness, presence of image artifacts, and overall image quality. Signal intensity and standard deviation of specific anatomical sites within the brachial plexus and background tissues were measured, with signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) subsequently calculated. Cohen's weighted kappa (κ), One-way ANOVA, Kruskal-Wallis and pairwise comparisons with Bonferroni-adjusted significance level. P < 0.05 was considered statistically significant.
RESULTS
ACS significantly reduced scanning times compared to PI. Evaluations revealed differences in subjective scores and SNR across the sequences (P < 0.05), with no marked differences in CNR (P > 0.05). For subjective scores, ACS 9.03 were lower than the other three sequences in neural details display, image artifacts and overall image quality. There was no significant difference in fat suppression. For objective quantitative evaluation, SNR of right C6 root in ACS 6.22 and ACS 9.03 was higher than that in PI; SNR of left C6 root in ACS 4.37, ACS 6.22 and ACS 9.03 was higher than that in PI; SNR of medial cord in ACS 6.22, ACS 9.03 was higher than that in PI.
CONCLUSION
Compared with PI, ACS can shorten scanning time while ensuring good image quality.
背景
3D 臂丛 MRI 扫描由于扫描时间长，容易导致检查失败，从而导致患者不适和运动伪影。我们的目的是研究人工智能辅助压缩感知（ACS）在提高臂丛磁共振成像加速效率和保持或提高图像质量方面的效果。
方法
共 30 名志愿者在 3.0T 磁共振扫描仪上使用不同翻转角演化的应用优化对比的三维采样完美短反转时间恢复进行检查。成像方案包括并行成像（PI）和 ACS，加速因子分别为 4.37、6.22 和 9.03。放射科医生评估神经细节显示、脂肪抑制效果、图像伪影的存在和整体图像质量。测量臂丛内特定解剖部位和背景组织的信号强度和标准偏差，随后计算信噪比（SNR）和对比噪声比（CNR）。采用 Cohen's 加权 kappa（κ）、One-way ANOVA、Kruskal-Wallis 和配对比较，并用 Bonferroni 调整的显著性水平进行比较。P<0.05 为统计学差异显著。
结果
ACS 与 PI 相比，明显缩短了扫描时间。评估结果显示，主观评分和 SNR 在不同序列之间存在差异（P<0.05），但 CNR 没有明显差异（P>0.05）。对于主观评分，ACS 9.03 在神经细节显示、图像伪影和整体图像质量方面低于其他三个序列。脂肪抑制无显著差异。客观定量评价显示，ACS 6.22 和 ACS 9.03 右侧 C6 神经根 SNR 高于 PI；ACS 4.37、ACS 6.22 和 ACS 9.03 左侧 C6 神经根 SNR 高于 PI；ACS 6.22 和 ACS 9.03 内侧束 SNR 高于 PI。
结论
与 PI 相比，ACS 可以缩短扫描时间，同时保证良好的图像质量。
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