标题： 通过使用深度卷积神经网络自适应调整绝热脉冲功率以提高7T下的FLAIR SAR效率 显示英文标题

标题： Improving FLAIR SAR efficiency at 7T by adaptive tailoring of adiabatic pulse power using deep convolutional neural networks

摘要： 目的：本研究的目的是展示一种方法，用于在7T下针对T2-FLAIR MRI序列减少特定吸收率（SAR），通过预测所需的绝热脉冲功率并以切片方式缩放幅度。 方法：我们在T2-FLAIR序列中使用TR-FOCI绝热脉冲进行自旋反转，以提高B1+均匀性，并逐切片计算实现绝热性的脉冲功率以最小化SAR。 利用标准定位扫描中存在的隐含B1+不均匀性，获得了8名志愿者的3D AutoAlign定位器和SA2RAGE B1+图。 然后训练了一个卷积神经网络（CNN）从定位器预测B1+轮廓，并计算每个切片的脉冲功率缩放因子。 评估了预测B1+轮廓的能力以及推导出的脉冲缩放因子对FLAIR反转效率的影响，分别在横断面、矢状面和冠状面方向上进行。 结果：预测的B1+图与测量的B1+图在所有切片上的平均差异为4.45%。 结果显示，在横断面方向上该方法最为有效，实现了SAR降低40%，同时扫描时间减少了1分钟30秒（28%），而图像质量没有下降。 结论：我们提出了一种基于使用CNN从标准定位扫描预测B1+轮廓的SAR降低技术，并表明在7T下对FLAIR序列逐切片缩放反转脉冲功率可以降低SAR和扫描时间，而不会影响图像质量。 显示英文摘要

摘要： Purpose: The purpose of this study is to demonstrate a method for Specific Absorption Rate (SAR) reduction for T2-FLAIR MRI sequences at 7T by predicting the required adiabatic pulse power and scaling the amplitude in a slice-wise fashion. Methods: We used a TR-FOCI adiabatic pulse for spin inversion in a T2-FLAIR sequence to improve B1+ homogeneity and calculate the pulse power required for adiabaticity slice-by-slice to minimize the SAR. Drawing on the implicit B1+ inhomogeneity present in a standard localizer scan, 3D AutoAlign localizers and SA2RAGE B1+ maps were acquired in eight volunteers. A convolutional neural network (CNN) was then trained to predict the B1+ profile from the localizers and scale factors for the pulse power for each slice were calculated. The ability to predict the B1+ profile as well as how the derived pulse scale factors affected the FLAIR inversion efficiency were assessed in transverse, sagittal, and coronal orientations. Results: The predicted B1+ maps matched the measured B1+ maps with a mean difference of 4.45% across all slices. The acquisition in the transverse orientation was shown to be most effective for this method and delivered a 40% reduction in SAR along with 1min and 30-sec reduction in scan time (28%) without degradation of image quality. Conclusion: We propose a SAR reduction technique based on the prediction of B1+ profiles from standard localizer scans using a CNN and show that scaling the inversion pulse power slice-by-slice for FLAIR sequences at 7T reduces SAR and scan time without compromising image quality.