This work proposes the Temporal Differences (TED) Compressed Sensing (CS) method for accelerating thermal monitoring in MR‐guided High‐Intensity Focused Ultrasound (MRgHIFU) treatments. TED combines k‐space subsampling, parallel imaging, and a unique CS recovery of the temporal differences between pre‐heating and post‐heating multi‐coil data. TED was validated through retrospective experiments with (i) two phantom datasets acquired with 1.5 T and 3 T MRgHIFU systems from different vendors, (ii) data from an in vivo animal model experiment, and (iii) four datasets from clinical in vivo MRgHIFU treatments of prostate cancer in humans. TED produced highly accurate temperature change maps from subsampled k‐space data for all datasets. For the clinical in vivo data, an analysis of 105 time frames showed that the average TED reconstruction error is 1.06‐1.67 °C. Furthermore, TED consistently outperforms two state‐of‐the‐art methods, l₁‐SPIRiT and the K‐space Hybrid Method, and offers errors that are significantly lower, by 29% or more. Moreover, TED offers robust performance over a range of its tunable parameters, stability across MRgHIFU systems from different vendors, and a short runtime of 1.7 s. In summary, TED enables k‐space subsampling while retaining high‐temperature mapping accuracy.

中文翻译：

---

时差（TED）压缩感测：一种快速MRgHIFU温度成像的方法

这项工作提出了时差（TED）压缩传感（CS）方法，用于在MR引导的高强度聚焦超声（MRgHIFU）治疗中加速热监测。TED结合了k空间二次采样，并行成像以及独特的CS复原功能，可以对多线圈数据进行预热和加热后的时间差异。通过回顾性实验对TED进行了验证，其中包括：（i）使用不同供应商的1.5 T和3 T MRgHIFU系统采集的两个幻像数据集，（ii）体内动物模型实验的数据以及（iii）临床体内MRgHIFU治疗的四个数据集在人类中的前列腺癌。TED从所有数据集的子采样k空间数据中生成了高精度的温度变化图。对于临床体内数据，对105个时间范围的分析表明，平均TED重建误差为1。06-1.67°C。此外，TED始终优于两种最新方法，l ₁ ‐SPIRiT和K空间混合方法，其错误显着降低了29％或更多。此外，TED在其一系列可调参数上提供了强大的性能，跨不同供应商的MRgHIFU系统提供了稳定性，并且运行时间仅为1.7 s。综上所述，TED可以在保持高温映射精度的同时实现k空间二次采样。