Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK.
Magn Reson Med. 2024 Jan;91(1):388-397. doi: 10.1002/mrm.29822. Epub 2023 Sep 7.
MR-guided cardiac catheterization procedures currently use passive tracking approaches to follow a gadolinium-filled catheter balloon during catheter navigation. This requires frequent manual tracking and repositioning of the imaging slice during navigation. In this study, a novel framework for automatic real-time catheter tracking during MR-guided cardiac catheterization is presented.
The proposed framework includes two imaging modes (Calibration and Runtime). The sequence starts in Calibration mode, in which the 3D catheter coordinates are determined using a stack of 10-20 contiguous saturated slices combined with real-time image processing. The sequence then automatically switches to Runtime mode, where three contiguous slices (acquired with partial saturation), initially centered on the catheter balloon using the Calibration feedback, are acquired continuously. The 3D catheter balloon coordinates are estimated in real time from each Runtime slice stack using image processing. Each Runtime stack is repositioned to maintain the catheter balloon in the central slice based on the prior Runtime feedback. The sequence switches back to Calibration mode if the catheter is not detected. This framework was evaluated in a heart phantom and 3 patients undergoing MR-guided cardiac catheterization. Catheter detection accuracy and rate of catheter visibility were evaluated.
The automatic detection accuracy for the catheter balloon during the Calibration/Runtime mode was 100%/95% in phantom and 100%/97 ± 3% in patients. During Runtime, the catheter was visible in 82% and 98 ± 2% of the real-time measurements in the phantom and patients, respectively.
The proposed framework enabled real-time continuous automatic tracking of a gadolinium-filled catheter balloon during MR-guided cardiac catheterization.
目前,磁共振引导下心导管检查程序采用被动跟踪方法在导管导航过程中跟踪充满钆的导管球囊。这需要在导航过程中频繁地手动跟踪和重新定位成像片。在这项研究中,提出了一种用于磁共振引导下心导管检查中自动实时导管跟踪的新框架。
所提出的框架包括两种成像模式(校准和运行时)。序列从校准模式开始,其中使用 10-20 个连续的饱和片堆栈结合实时图像处理来确定 3D 导管坐标。然后,序列自动切换到运行时模式,其中连续获取三个连续的切片(使用部分饱和采集),初始时使用校准反馈中心位于导管球囊上。使用图像处理从每个运行时切片堆栈实时估计 3D 导管球囊坐标。根据之前的运行时反馈,重新定位每个运行时堆栈以保持导管球囊在中心切片中。如果未检测到导管,则序列切换回校准模式。该框架在心脏模型和 3 名接受磁共振引导下心导管检查的患者中进行了评估。评估了导管检测的准确性和导管可见性的速率。
在心脏模型和患者中,校准/运行时模式下导管球囊的自动检测准确性分别为 100%/95%和 100%/97±3%。在运行时,导管在心脏模型和患者中的实时测量中分别有 82%和 98±2%是可见的。
所提出的框架实现了磁共振引导下心导管检查中充满钆的导管球囊的实时连续自动跟踪。