FRE 3313 CNRS/University Victor Segalen Bordeaux, Bordeaux, France.
IEEE Trans Med Imaging. 2012 Mar;31(3):533-42. doi: 10.1109/TMI.2011.2171772. Epub 2011 Oct 13.
Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint. The requirement to resolve both physiological motion of mobile organs and the rapid temperature variations induced by state-of-the-art high-power HIFU systems require fast MRI-acquisition schemes, which are generally hampered by low signal-to-noise ratios (SNRs). This directly limits the precision of real time MR-thermometry and thus in many cases the feasibility of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data. Here, we propose a novel filter that aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy. For this, an adaptive extended Kalman filter using a model describing the heat transfer for acoustic heating in biological tissues was employed together with an additional outlier rejection to address the problem of sparse artifacted temperature points. The filter was compared to an efficient matched FIR filter and outperformed the latter in all tested cases. The filter was first evaluated on simulated data and provided in the worst case (with an approximate configuration of the model) a substantial improvement of the accuracy by a factor 3 and 15 during heat up and cool down periods, respectively. The robustness of the filter was then evaluated during HIFU experiments on a phantom and in vivo in porcine kidney. The presence of strong temperature artifacts did not affect the thermal dose measurement using our filter whereas a high measurement variation of 70% was observed with the FIR filter.
实时磁共振（MR）测温技术在监测和引导高强度聚焦超声（HIFU）消融肿瘤组织方面的临床应用越来越重要。温度信息可用于实时调整 HIFU 系统的位置和功率，并确定治疗终点。需要同时解决移动器官的生理运动和最先进的高功率 HIFU 系统引起的快速温度变化，这就需要快速的 MRI 采集方案，而这些方案通常受到低信噪比（SNR）的限制。这直接限制了实时 MR 测温的精度，从而在许多情况下限制了复杂控制算法的可行性。为了克服这些限制，过去曾提出对温度进行时间滤波，但这通常会对滤波后数据的准确性和延迟产生不利影响。在这里，我们提出了一种新的滤波器，旨在提高 MR 测温的精度，同时监测和适应其对准确性的影响。为此，使用了一种描述生物组织中声热传递的模型的自适应扩展卡尔曼滤波器，并结合额外的异常值拒绝来解决稀疏伪温度点的问题。该滤波器与高效匹配的 FIR 滤波器进行了比较，在所有测试案例中均优于后者。该滤波器首先在模拟数据上进行了评估，并在最坏情况下（模型的近似配置）提供了实质性的改进，在升温期和降温期分别提高了精度 3 倍和 15 倍。然后在体模和猪肾的体内 HIFU 实验中评估了滤波器的鲁棒性。尽管存在强烈的温度伪影，但我们的滤波器不会影响热剂量测量，而 FIR 滤波器则观察到高达 70%的高测量变化。
