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交互式确定肿瘤肝切除术的稳健安全边界。

Interactive determination of robust safety margins for oncologic liver surgery.

机构信息

Fraunhofer MEVIS, Institute for Medical Image Computing, Bremen, Germany.

出版信息

Int J Comput Assist Radiol Surg. 2009 Sep;4(5):469-74. doi: 10.1007/s11548-009-0359-1. Epub 2009 Jun 4.

Abstract

OBJECTIVE

Complex oncologic interventions in the liver require an extensive and careful preoperative analysis. Particularly the achievement of an optimal safety margin around tumors remains a difficult task for surgeons.

METHODS

We present new methods for evaluating different safety margins and their effect on the associated interruption of vascular supply or drainage. The characteristic of vascular risk distributions can be evaluated in real-time by exploiting precomputed safety maps that provide a volume curve for each vascular system. By applying fast visualization methods in 3D it is possible to assist the surgeon in the determination of a tumor-free safety margin while preserving sufficient vital hepatic parenchyma. The combination of risk analysis from different vascular systems and their sensitivity is considered.

RESULTS

We provide physicians with a novel computer-aided planning tool that allows for interactive determination of safety margins in real-time. The planning tool integrates smoothly into the preoperative workflow. Preliminary evaluations confirm that the width of safety margins can be determined more precisely, which may affect the proposed resection strategy.

CONCLUSION

Our new methods provide interactive feedback and support for decision making during the preoperative planning stage and thus might potentially improve the outcome of surgical interventions.

摘要

目的

肝脏的复杂肿瘤介入需要广泛而仔细的术前分析。特别是在肿瘤周围获得最佳安全边界仍然是外科医生的一项艰巨任务。

方法

我们提出了新的方法来评估不同的安全边界及其对相关血管供应或引流中断的影响。通过利用提供每个血管系统体积曲线的预计算安全图,可以实时评估血管风险分布的特征。通过在 3D 中应用快速可视化方法,可以在保留足够的重要肝实质的同时,帮助外科医生确定无肿瘤安全边界。考虑了来自不同血管系统的风险分析及其敏感性的组合。

结果

我们为医生提供了一种新的计算机辅助规划工具,允许实时交互式确定安全边界。该规划工具可无缝集成到术前工作流程中。初步评估证实,可以更精确地确定安全边界的宽度,这可能会影响拟议的切除策略。

结论

我们的新方法在术前规划阶段提供了交互式反馈和决策支持,因此可能潜在地改善手术干预的结果。

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