MRI深度学习重建对乳腺脂肪抑制序列扫描时间和图像质量的影响

Impact of deep learning reconstruction in MRI on scan time and image quality of breast fat suppression sequence

目的探讨磁共振成像(MRI)深度学习重建(DLR)对乳腺T_(2)加权(T_(2)WI)脂肪抑制序列扫描时间及图像质量的影响。方法招募30名女性志愿者为研究对象,采用平均采集次数(NAQ)为1和2的T_(2)WI脂肪抑制序列行乳腺MRI扫描,扫描时间分别为217 s和421 s,扫描完成获得Routine NAQ1和Routine NAQ2图像,Routine NAQ1组图像行DLR重建获DLR NAQ1图像,分析比较3组图像的信噪比(SNR)、对比噪声比(CNR)及临床医生主观定性评价资料。结果女性志愿者DLR NAQ1图像的SNR及CNR优于Routine NAQ1和Routine NAQ2图像(P<0.001),图像整体质量评分均优于Routine NAQ1和Routine NAQ2图像(P<0.001)。结论MRI DLR可缩短乳腺T2WI脂肪抑制序列的扫描时间,提高图像质量。

Objective To investigate the impact of deep learning reconstruction(DLR)in magnetic resonance imaging(MRI)on scan time and image quality of breast T_(2)-weighted(T_(2)WI)fat suppression sequence.Methods Thirty female volunteers were recruited as research subjects.Breast MRI scan was performed using T_(2)WI fat suppression sequence with an average number of acquisition(NAQ)of 1 and 2 as well as scan time of 217 s and 421 s,respectively.After scanning,Routine NAQ1 and Routine NAQ2 images were obtained.DLR was run on Routine NAQ1 image group to obtain DLR NAQ1 images.Signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the images as well as the subjective and qualitative evaluation data from clinicians were analyzed and compared among three groups.Results SNR and CNR of DLR NAQ1 images of female volunteers were better than those of Routine NAQ1 and Routine NAQ2 images(P<0.001),and the overall quality score of the images is better than that of both Route NAQ1 and Route NAQ2 images(P<0.001).Conclusion DLR in MRI can shorten scan time of breast T 2WI fat suppression sequence and improve image quality.