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在微创干预中选择呼吸相位以最小化目标配准误差

Selection of the respiratory phase in minimally invasive interventions for target registration error minimization.

作者信息

Spinczyk Dominik, Fabian Sylwester, Król Krzysztof

机构信息

Silesian University of Technology, Faculty of Biomedical Engineering, 40 Roosevelta, 41-800 Zabrze, Poland.

Silesian University of Technology, Faculty of Biomedical Engineering, 40 Roosevelta, 41-800 Zabrze, Poland.

出版信息

Surg Oncol. 2019 Mar;28:31-35. doi: 10.1016/j.suronc.2018.11.003. Epub 2018 Nov 8.

Abstract

BACKGROUND

In minimally invasive surgery, the main challenge is precisely locating the target during the intervention. For abdominal intervention, one of most important factors causing target motion is breathing. The aim of the study is to efficiently predict target localization during the respiratory in breathing cycle.

METHOD

Analysis of target registration error (TRE) for the registration circuits method was used to find the breathing phase corresponding to the preoperative Computed Tomography spatial configuration. Then, Elastic Body Spline (EBS) for modeling deformation field and Particle Swarm Optimization method were used to find the desired values of EBS parameters: ∝ and stiffness were used.

RESULTS

The proposed methodology was verified during experiments conducted on 21 patients diagnosed with liver tumors. This ability of TRE reduction has been achieved for the respiratory phases founded in registration chain analysis.

CONCLUSIONS

The proposed method presents the usability of spatio-temporal analysis of collected real breathing data in order to estimate the position of a target during the respiratory cycle. This method has been developed to perform operations in real-time on a standard workstation.

摘要

背景

在微创手术中,主要挑战是在干预过程中精确地定位目标。对于腹部干预,导致目标移动的最重要因素之一是呼吸。本研究的目的是在呼吸周期的呼吸过程中有效地预测目标定位。

方法

使用针对配准电路方法的目标配准误差(TRE)分析来找到与术前计算机断层扫描空间配置相对应的呼吸阶段。然后,使用用于建模变形场的弹性体样条(EBS)和粒子群优化方法来找到EBS参数的期望值:使用了∝和刚度。

结果

在对21名被诊断患有肝肿瘤的患者进行的实验中验证了所提出的方法。对于在配准链分析中找到的呼吸阶段,已经实现了这种降低TRE的能力。

结论

所提出的方法展示了对收集的真实呼吸数据进行时空分析以估计呼吸周期中目标位置的实用性。该方法已被开发用于在标准工作站上实时执行操作。

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