Department of Industrial Engineering, University of Tor Vergata, Rome, Italy.
Department of Health Research, SINTEF Digital, Trondheim, Norway.
Int J Comput Assist Radiol Surg. 2024 Nov;19(11):2239-2247. doi: 10.1007/s11548-024-03187-y. Epub 2024 Jun 2.
Currently, the intra-operative visualization of vessels during endovascular aneurysm repair (EVAR) relies on contrast-based imaging modalities. Moreover, traditional image fusion techniques lack a continuous and automatic update of the vessel configuration, which changes due to the insertion of stiff guidewires. The purpose of this work is to develop and evaluate a novel approach to improve image fusion, that takes into account the deformations, combining electromagnetic (EM) tracking technology and finite element modeling (FEM).
To assess whether EM tracking can improve the prediction of the numerical simulations, a patient-specific model of abdominal aorta was segmented and manufactured. A database of simulations with different insertion angles was created. Then, an ad hoc sensorized tool with three embedded EM sensors was designed, enabling tracking of the sensors' positions during the insertion phase. Finally, the corresponding cone beam computed tomography (CBCT) images were acquired and processed to obtain the ground truth aortic deformations of the manufactured model.
Among the simulations in the database, the one minimizing the in silico versus in vitro discrepancy in terms of sensors' positions gave the most accurate aortic displacement results.
The proposed approach suggests that the EM tracking technology could be used not only to follow the tool, but also to minimize the error in the predicted aortic roadmap, thus paving the way for a safer EVAR navigation.
目前,血管内动脉瘤修复术 (EVAR) 中的术中血管可视化依赖于基于对比的成像方式。此外,传统的图像融合技术缺乏对由于插入刚性导丝而导致的血管结构变化的连续自动更新。本研究旨在开发和评估一种新方法,以改善图像融合,该方法考虑到了变形,结合了电磁 (EM) 跟踪技术和有限元建模 (FEM)。
为了评估 EM 跟踪是否可以提高数值模拟的预测,对患者特定的腹主动脉模型进行了分割和制造。创建了具有不同插入角度的模拟数据库。然后,设计了一个带有三个嵌入式 EM 传感器的专用传感器工具,能够在插入阶段跟踪传感器的位置。最后,采集并处理相应的锥形束计算机断层扫描 (CBCT) 图像,以获得制造模型的主动脉变形的真实情况。
在数据库中的模拟中,根据传感器位置使模拟与体外测量之间差异最小的模拟给出了最准确的主动脉位移结果。
所提出的方法表明,EM 跟踪技术不仅可以用于跟踪工具,还可以最小化预测的主动脉路径图中的误差,从而为更安全的 EVAR 导航铺平道路。