Accelerated MRI thermometry by direct estimation of temperature from undersampled k-space data.
Accelerated MRI thermometry by direct estimation of temperature from undersampled k-space data.
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DOI：
10.1002/mrm.25327
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发表时间：
2015-05
影响因子：
3.3
通讯作者：
Grissom, William A.
中科院分区：
文献类型：
--
作者：
Gaur, Pooja;Grissom, William A.
关键词：
MR温度测量的加速对于MR引导的聚焦超声的若干应用是期望的，诸如那些需要更大体积覆盖、更高空间分辨率或更高帧速率的应用。我们提出并验证了一个约束重建方法，估计焦点温度的变化直接从k空间没有空间或时间正则化。将包括完全采样的基线图像的模型拟合到欠采样的k空间数据，这从解空间中去除了混叠的温度图。重建的温度图进行比较，使用并行成像（SPIRiT）和传统的混合测温，和时间约束重建（TCR）测温重建的地图。时间阶跃响应模拟表明，与TCR相比，4×欠采样径向k空间重建具有更好的时间分辨率和更低的误差。仿真结果表明，k空间方法可以实现更高的加速度与多个接收线圈。体模加热实验进一步证明了该算法的优势，重建依赖于单独的并行成像，以克服欠采样伪影。体内模型误差比较表明，该算法在更高的加速因子（径向轨迹高达32倍）下实现了较低的温度误差。使用所提出的温度重建算法可以实现高加速因子，而不牺牲时间分辨率或精度。
Acceleration of MR thermometry is desirable for several applications of MR-guided focused ultrasound, such as those requiring greater volume coverage, higher spatial resolution, or higher frame rates. We propose and validate a constrained reconstruction method that estimates focal temperature changes directly from k-space without spatial or temporal regularization. A model comprising fully-sampled baseline images is fit to undersampled k-space data, which removes aliased temperature maps from the solution space. Reconstructed temperature maps are compared to maps reconstructed using parallel imaging (SPIRiT) and conventional hybrid thermometry, and temporally-constrained reconstruction (TCR) thermometry. Temporal step response simulations demonstrate finer temporal resolution and lower error in 4×-undersampled radial k-space reconstructions compared to TCR. Simulations show that the k-space method can achieve higher accelerations with multiple receive coils. Phantom heating experiments further demonstrate the algorithm’s advantage over reconstructions relying on parallel imaging alone to overcome undersampling artifacts. In vivo model error comparisons show the algorithm achieves low temperature error at higher acceleration factors (up to 32× with a radial trajectory) than compared reconstructions. High acceleration factors can be achieved using the proposed temperature reconstruction algorithm, without sacrificing temporal resolution or accuracy.
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