Deep learning reconstruction for 1.5 T cervical spine MRI: effect on interobserver agreement in the evaluation of degenerative changes
Deep learning reconstruction for 1.5 T cervical spine MRI: effect on interobserver agreement in the evaluation of degenerative changes
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DOI：
10.1007/s00330-022-08729-z
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发表时间：
2022-03-29
影响因子：
5.9
通讯作者：
Kiryu, Shigeru
中科院分区：
文献类型：
--
作者：
Yasaka, Koichiro;Tanishima, Tomoya;Kiryu, Shigeru
目的研究深度学习重建（DLR）是否使用1.5 T装置在不增加成像时间的情况下改善颈椎退行性变化的评价。方法21名志愿者（年龄42.4 ± 11.9岁;男性17名）接受了1.5T颈椎矢状位T2加权MRI检查。根据采集次数（NAQ）为1或2的成像数据，分别使用DLR（NAQ 1-DLR）和无DLR（NAQ 1）或无DLR（NAQ 2）重建图像。两名阅片者评价了图像的结构描述、伪影、噪声、整体图像质量、椎管狭窄和神经孔狭窄。两位读片员随机盲读研究。使用Wilcoxon符号秩检验比较NAQ 1-DLR和NAQ 1之间以及NAQ 1-DLR和NAQ 2之间的值。结果分析显示，NAQ 1-DLR的结果明显优于NAQ 1和NAQ 2（p < 0.023），但NAQ 1-DLR和NAQ 2之间的比较中，一名阅片师对椎间盘和椎间孔的描述以及两名阅片师对伪影的描述除外。观察员间协议NAQ 1-DLR/NAQ 1/NAQ 2的椎管狭窄评估中的Cohen加权Kappa值[97.5%置信区间]为0.874（0.866-0.883）/0.778（0.767-0.789）/0.818评价神经孔狭窄的平均值为0.878（0.872-0.883）/0.855（0.849-0.860）/0.852（0.845-0.860）。结论DLR改善了1.5T颈椎MR图像对颈椎退变性改变的评价。
Objectives To investigate whether deep learning reconstruction (DLR) provides improved cervical spine MR images using a 1.5 T unit in the evaluation of degenerative changes without increasing imaging time. Methods This study included 21 volunteers (age 42.4 +/- 11.9 years; 17 males) who underwent 1.5 T cervical spine sagittal T2-weighted MRI. From the imaging data with number of acquisitions (NAQ) of 1 or 2, images were reconstructed with DLR (NAQ1-DLR) and without DLR (NAQ1) or without DLR (NAQ2), respectively. Two readers evaluated the images for depiction of structures, artifacts, noise, overall image quality, spinal canal stenosis, and neuroforaminal stenosis. The two readers read studies blinded and randomly. Values were compared between NAQ1-DLR and NAQ1 and between NAQ1-DLR and NAQ2 using the Wilcoxon signed-rank test. Results The analyses showed significantly better results for NAQ1-DLR compared with NAQ1 and NAQ2 (p < 0.023), except for depiction of disc and foramina by one reader and artifacts by both readers in the comparison between NAQ1-DLR and NAQ2. Interobserver agreements (Cohen's weighted kappa [97.5% confidence interval]) in the evaluation of spinal canal stenosis for NAQ1-DLR/NAQ1/NAQ2 were 0.874 (0.866-0.883)/0.778 (0.767-0.789)/0.818 (0.809-0.827), respectively, and those in the evaluation of neuroforaminal stenosis were 0.878 (0.872-0.883)/0.855 (0.849-0.860)/0.852 (0.845-0.860), respectively. Conclusions DLR improved the 1.5 T cervical spine MR images in the evaluation of degenerative spine changes.