AN INTEGRATED SYSTEM FOR IMAGE-GUIDED RADIOFREQUENCY ABLATION OF LIVER TUMORS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 这项提案的总体目标是开发和验证一个基于开源软件的集成系统，以改进射频消融(RFA)期间肝脏肿瘤的可视化和探针放置。尽管射频消融术正在成为不能切除的肝细胞癌和肝转移瘤的一种越来越重要的治疗选择，但该手术有几个技术限制。这些局限性主要与精确放置RFA针以消融整个肿瘤并获得足够的切缘有关。特别是，较大的肿瘤需要多个重叠的针头放置，这可能很难实现。该项目的具体目标是：1)在两个合作机构现有开源项目的基础上，为肝脏RFA计划/治疗工作站开发一个开源软件架构；2)开发和评估肝脏、肝脏血管和肝脏肿瘤的半自动分割技术。这些技术将与图形用户界面集成，分割结果将通过与专业放射科医生的比较进行评估。3)基于分割的肝脏数据集，开发路径规划模块，用于评估通往肝脏肿瘤的备选路径，并根据需要合并多个重叠放置。4)将上述两种能力与RFA探头的电磁跟踪相结合，为肝脏肿瘤的规划、可视化和执行提供完整的软件环境。这一软件环境将合并乔治敦和布里格姆妇女医院正在进行的为图像引导程序开发开源软件的工作。5)在猪动物模型上验证该系统的临床可行性。将在猪的肝脏中产生琼脂结节，并将评估该系统分割这些结节并提供路径规划的能力。还将对系统的准确性进行评估。这项研究对于推进目前现有治疗方法不能很好治疗的肝癌的治疗技术具有重要意义。这项技术还将使现代的个性化治疗成为可能，这依赖于大功率计算机的集成和医学科学的创新。它将通过开发肝癌治疗方法来为公共健康做出贡献，而不需要更多的侵入性手术。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The overall goal of this proposal is to develop and validate an integrated system based on open source software for improved visualization and probe placement during radiofrequency ablation (RFA) of liver tumors. While radiofrequency ablation is becoming an increasingly important treatment option for unresectable hepatocellular carcinoma (HCC) and liver metastases, the procedure has several technical limitations. These limitations are mostly related to the difficulty of precisely placing the RFA needle to ablate the entire tumor and achieve adequate margins. In particular, larger tumors require multiple overlapping needle placements, which can be difficult to achieve. The specific aims of the project are to: 1) Develop an open source software architecture for a liver RFA planning/treatment workstation that builds on existing open source projects at the two collaborating institutions 2) Develop and evaluate semi-automatic segmentation techniques for the liver, liver vasculature, and liver tumors. These techniques will be integrated with a graphical user interface and the segmentation results will be evaluated by comparison with expert radiologists. 3) Based on the segmented liver data set, develop a path planning module for evaluating alternative paths to the liver tumor and incorporating multiple overlapping placements as needed. 4) Integrate the two capabilities developed above along with electromagnetic tracking of the RFA probe to provide a complete software environment for liver tumor planning, visualization, and execution. This software environment will merge ongoing work at Georgetown and Brigham and Women's Hospital in developing open source software for image-guided procedures. 5) Validate the clinical feasibility of the system in a swine animal model. Agar nodules will be created in the swine liver and the ability of the system to segment and provide path planning for these nodules will be assessed. The accuracy of the system will also be evaluated. This research is important in advancing the technology for treatment of liver cancer that presently can not be treated well with current available therapies. This technology would also enable a modern, individualized therapy, which relies on integration of high power computers and innovations in medical science. It would have a contribution to public health by developing liver cancer treatments without the need for more invasive surgeries.