基于深度学习技术的TSE⁃T2WI在纵隔MRI中的应用价值

目的：探讨基于深度学习重建（deep learning reconstruction，DLR）技术的快速自旋回波（turbo spin echo，TSE）T2加权成像（T2 weighted imaging，T2WI）序列提高纵隔T2WI图像质量和减少扫描时间的应用价值。方法：前瞻性收集35例纵隔病变的患者进行纵隔常规T2WI序列和基于DLR的T2WI（T2WI_DLR）序列扫描。由2位放射科医师各自独立对两组图像的伪影、图像清晰度、病灶的细节显示和整体图像质量进行定性评分，并测量和比较两组图像的病灶信噪比（SNR _病灶）和病灶与竖直肌的对比噪声比（CNR _{病灶/肌肉}）。结果：T2WI_DLR在伪影、图像清晰度、病灶细节显示和整体图像质量的评分均优于常规T2WI（P均 ＜ 0.001）。 T2WIDLR序列图像的SNR和CNR均优于常规T2WI序列（P均 ＜ 0.001）。结论：与常规T2WI序列相比，T2WI_DLR序列的运动伪影更少，图像清晰度、病灶细节显示和整体图像质量更优，图像SNR和CNR更高，在纵隔疾病的临床应用中有较大潜力。

Application value of TSE ⁃ T2WI based on deep learning technique in mediastinum MRI scanning

Objective：To explore the application value of the turbo spin echo（TSE）T2-weighted imaging based on deep learning reconstruction（DLR）technology in improving mediastinum image quality and reducing scanning time. Methods：35 patients with mediastinal lesions were prospectively collected for mediastinal conventional T2WI and DLR - based T2WI scanning. The artifacts， image clarity，display of the detail of the lesion and overall image quality of the two groups were qualitatively scored by two radiologists independently. The signal -to - noise ratio of the lesion（SNR_lesion）and the contrast to noise ratio of the lesion to vertical muscle（CNR_{lesion/muscle}）of the two groups of images were measured and compared. Results：Qualitative analysis：T2WI_DLR was superior to conventional T2WI in the scores of artifact，image sharpness，display of the detail of the lesion，and overall image quality（P ＜ 0.001）. Quantitative analysis：The SNR and CNR of the image of T2WI_DLR sequence were better than those of conventional T2WI（P ＜ 0.001）. Conclusion：Compared with conventional T2WI sequences，T2WI_DLR sequence has fewer motion artifacts，better image clarity，lesion detail display and overall image quality，and higher SNR and CNR，which has great potential in clinical application of mediastinal diseases.