基于深度学习技术的TSE-T2WI在纵隔MRI中的应用价值

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

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(T2WIDLR)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:T2WIDLR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。

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:T2WIDLR 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.