Experimental O-space turbo spin echo imaging.
Experimental O-space turbo spin echo imaging.
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DOI：
10.1002/mrm.25741
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发表时间：
2016-04
影响因子：
3.3
通讯作者：
Galiana G
中科院分区：
文献类型：
--
作者：
Wang H;Tam L;Kopanoglu E;Peters DC;Constable RT;Galiana G
涡轮旋转回波（TSE）成像通过每次重复（TR）采集多个回波来缩短成像时间，从而需要更少的TR。O-Space还可以通过使用非线性磁梯度场和表面线圈阵列的组合来减少TR。尽管到目前为止，O-Space仅被证明用于梯度回波成像，但将这两种技术联合收割机结合起来是有价值的。然而，由于不同的局部k空间轨迹和可变的T2加权，每个TR收集多个O空间回波是困难的。一个实用的方案证明了联合收割机的TSE和O空间的高度加速的T2加权图像的好处。该方案使用修改后的采集顺序和滤波投影重建来减少T2衰减引起的伪影，同时保留与特定回声时间对应的T2对比度。实验结果表明，该方法可以产生高加速T2加权图像。此外，所提出的方法可以从单个数据集生成具有不同T2对比度的多个图像。所提出的O-Space TSE成像方法需要比常规TSE更少的回波和比常规O-Space成像更少的重复。它保留了对欠采样的弹性，在高水平的欠采样下明显优于Cartesian SENSE，并且可以从单个采集数据集生成具有T2对比度范围的无失真图像。
Turbo Spin Echo (TSE) imaging reduces imaging time by acquiring multiple echoes per repetition (TR), requiring fewer TRs. O-Space also can require fewer TRs by using a combination of nonlinear magnetic gradient fields and surface coil arrays. Although to date, O-Space has only been demonstrated for gradient echo imaging, it’s valuable to combine these two techniques. However, collecting multiple O-Space echoes per TR is difficult because of the different local k-space trajectories and variable T2-weighting. A practical scheme is demonstrated to combine the benefits of TSE and O-Space for highly accelerated T2-weighted images. The scheme uses a modified acquisition order and filtered projection reconstruction to reduce artifacts caused by T2-decay, while retaining T2 contrast that corresponds to a specific echo time. The experiments illustrate the proposed method can produce highly accelerated T2-weighted images. Moreover, the proposed method can generate multiple images with different T2 contrasts from a single dataset. The proposed O-Space TSE imaging method requires fewer echoes than conventional TSE and fewer repetitions than conventional O-Space imaging. It retains resilience to undersampling, clearly outperforming Cartesian SENSE at high levels of undersampling, and can generate undistorted images with a range of T2 contrast from a single acquired dataset.