当前位置: X-MOL 学术Skelet. Radiol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Ultrafast lumbar spine MRI protocol using deep learning–based reconstruction: diagnostic equivalence to a conventional protocol
Skeletal Radiology ( IF 2.1 ) Pub Date : 2022-10-01 , DOI: 10.1007/s00256-022-04192-5
Masahiro Fujiwara 1 , Nobuo Kashiwagi 2 , Chisato Matsuo 3 , Hitoshi Watanabe 4 , Yoshimori Kassai 5 , Atsushi Nakamoto 6 , Noriyuki Tomiyama 3
Affiliation  

Objective

To evaluate the diagnostic equivalency between an ultrafast (1 min 53 s) lumbar MRI protocol using deep learning–based reconstruction and a conventional lumbar MRI protocol (12 min 31 s).

Materials and methods

This study included 58 patients who underwent lumbar MRI using both conventional and ultrafast protocols, including sagittal T1-weighted, T2-weighted, short-TI inversion recovery, and axial T2-weighted sequences. Compared with the conventional protocol, the ultrafast protocol shortened the acquisition time to approximately one-sixth. To compensate for the decreased signal-to-noise ratio caused by the acceleration, deep learning–based reconstruction was applied. Three neuroradiologists graded degenerative changes and analyzed for presence of other pathologies. For the grading of degenerative changes, interprotocol intrareader agreement was assessed using kappa statics. Interchangeability between the two protocols was also tested by calculating the individual equivalence index between the intraprotocol interreader agreement and interprotocol interreader agreement. For the detection of other pathologies, interprotocol intrareader agreement was assessed.

Results

For the grading of degenerative changes, the kappa values for interprotocol intrareader agreement of all three readers ranged from 0.707 to 0.804, indicating substantial to almost perfect agreement. Except for foraminal stenosis and disc contour on axial images, the 95% confidence interval of the individual equivalence index was < 5%, indicating the two protocols were interchangeable. For the detection of other pathologies, the interprotocol intrareader agreement rates were > 98% for each individual pathology.

Conclusions

Our proposed ultrafast lumbar spine MRI protocol provided almost equivalent diagnostic results to that of the conventional protocol, except for some degenerative changes.



中文翻译:

使用基于深度学习的重建的超快腰椎 MRI 协议:与传统协议的诊断等效性

客观的

评估使用基于深度学习的重建的超快(1 分 53 秒)腰椎 MRI 协议与传统腰椎 MRI 协议(12 分 31 秒)之间的诊断等效性。

材料和方法

这项研究包括 58 名使用常规和超快方案进行腰椎 MRI 的患者,包括矢状 T1 加权、T2 加权、短 TI 反转恢复和轴向 T2 加权序列。与传统协议相比,超快协议将采集时间缩短到大约六分之一。为了补偿由加速引起的信噪比降低,应用了基于深度学习的重建。三位神经放射学家对退行性变化进行分级,并分析是否存在其他病症。对于退行性变化的分级,使用 kappa statics 评估协议间阅读器协议。还通过计算协议内阅读器协议和协议间阅读器协议之间的个体等效指数来测试两个协议之间的互换性。为了检测其他病理,评估了协议间阅读器协议。

结果

对于退行性变化的分级,所有三个阅读器的协议间阅读器一致性的 kappa 值范围为 0.707 到 0.804,表明基本一致到几乎完美一致。除了轴向图像上的椎间孔狭窄和椎间盘轮廓外,个体等效指数的 95% 置信区间 < 5%,表明两种方案可以互换。对于其他病理的检测,每个单独病理的协议间阅读器一致性率 > 98%。

结论

我们提出的超快腰椎 MRI 协议提供了与传统协议几乎相同的诊断结果,除了一些退行性变化。

更新日期:2022-10-01
down
wechat
bug