Correcting for Soft Tissue Deformation in Image-Guided Liver Surgery

图像引导肝脏手术中软组织变形的校正

• 批准号: 7459606
• 负责人: Michael Ian Miga
• 金额: $ 29.73万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7459606
• 关键词: Abdomen; Accounting; Algorithms; Atlases; Clinical Data; Clinical Trials; Communities; Compatible; Computer Simulation; Condition; Consultations; Coupled; Custom; Data; Development; Disadvantaged; Disease; Disseminated Malignant Neoplasm; Environment; Evaluation; Excision; Financial compensation; Frustration; General Population; Generations; Generic Drugs; Goals; Image; Image-Guided Surgery; Imagery; Intra-abdominal; Invasive; Investigation; Lasers; Lead; Letters; Literature; Liver; Liver neoplasms; Magnetic Resonance; Mainstreaming; Measures; Mechanics; Medical center; Methodology; Methods; Modeling; Nature; Neuronavigation; Non-linear Models; Numbers; Operating Rooms; Operative Surgical Procedures; Optics; Organ; Outcome; Patient Care; Patients; Phase; Play; Population; Postoperative Period; Procedures; Process; Property; Range; Research; Research Ethics Committees; Role; Scanning; Secure; Series; Shapes; Site; Solutions; Specimen; Structure; Surgeon; Surgical margins; System; Techniques; Technology; Testing; Therapeutic; Time; Tissue Model; Tissues; Translating; United States Food and Drug Administration; Update; Validation; Weight; Work; X-Ray Computed Tomography; base; cost; design; experience; image guided intervention; improved; intraoperative imaging; neurosurgery; novel; prototype; reconstruction; soft tissue; tumor

DESCRIPTION (provided by applicant): To a degree, the use of soft-tissue modeling for updating image-guided navigational systems has not been embraced by the mainstream scientific community. It has only just recently found application within the neuronavigation community (although no commercial systems are available yet) and is still under investigation. Much of this frustration is not due to the growing number of methodologies but rather to a misunderstanding of the goals of model-updating, and an inability to test and validate. With respect to the former, it is na¿ve to believe that modeling can account for all fine-scale deformations. However, the question to be answered is, within the confines of surgical margin, can model-updating significantly impact surgical resection? This is a central research hypothesis to be investigated within this application. What sets this application apart is that if the milestones are achieved, the outcome could result in a soft-tissue deformation correction system for image- guided liver surgery systems that could be immediately commercially available for patient care. More specifically, at the conclusion of this work, an image-guided liver surgical system capable of deformation correction will be generated, a preliminary experience with the fidelity of those corrections will be established, and the technology will be commercially available to early adopters that secure approval from their Institutional Review Board (IRB). This is possible because this application will leverage an ongoing clinical trial being performed by Pathfinder Therapeutics Incorporated (PTI) that is in the process of testing their image-guided liver surgery (IGLS) system to start in the latter half of 2007. PTI has agreed to share their clinical data to support the novel tissue deformation correction strategy proposed herein. The hypothesis that models can be used to correct for deformation within IGLS will be supported by three specific aims which involve: (1) the development of deformation compensation strategy that involves a combined registration and shape correction technique that will reside on an adaptable deformation correction compute node, (2) the retrospective testing of this approach on data from three separate clinical trials, and (3) an investigation to improve the computer model for the updating process. Phase II for this application would involve upgrading the systems of the early adopters to include our deformation correction compute node and then prospectively test its fidelity clinically. Primary and metastatic cancer within the liver is becoming increasingly common. There is significant evidence that intra-abdominal liver surgery improves survival times for patients afflicted with metastatic disease. Currently the patient population is limited largely due to the complexity of this procedure. Better visualization and guidance would provide surgeons more confidence and would increase the number of surgical candidates and outcome for these patients. If this application is successful, it would lead to the first commercially available image-guided liver surgery system capable of soft-tissue deformation correction. The proposed "deformation correction compute node" would have more widespread impact by being readily adaptable to other surgical systems with similar data. In addition, the strategy would also be compatible with minimally invasive surgeries provided that information regarding organ shape can be acquired. Currently, the only commercial means to correct for soft-tissue deformation is to use intraoperative magnetic resonance (iMR) and computed tomography (iCT). These systems are of considerable expense, require staff, and can be costly to maintain. Due to their cumbersome nature, the patient through-put is also considerably less than a conventional operating room. iCT has been available since the mid-1980's and iMR has been available since the mid- 1990's, yet there are still only a handful of systems being used throughout the world. While these are disadvantages, it should be noted that these systems will not be dispensed with and will continue to be developed. However, it is highly probable that these facilities will become referral centers for the most critical cases rather than available as a mainstream technology. The strategy of augmenting an existing image- guidance system with a "deformation correction compute node" is very low cost, may be as effective as the iMR/iCT solution, and is translatable to any medical center with an image-guided surgery system. This application will play an important role in remedying a disconnection between these sparse referral centers and the vast assortment of local medical centers available to the general population.

描述（由申请人提供）：在某种程度上，主流科学界尚未接受使用软组织建模来更新图像引导导航系统。它只是最近才在神经导航社区中找到应用（尽管还没有商业系统可用），并且仍在调查中。这种挫折感在很大程度上不是由于方法数量的增加，而是由于对模型更新目标的误解，以及无法进行测试和验证。关于前者，认为建模可以解释所有精细尺度的变形是天真的。然而，需要回答的问题是，在手术切缘的范围内，模型更新是否会显著影响手术切除？这是本申请中要研究的中心研究假设。使该应用与众不同的是，如果实现了里程碑，结果可能导致用于图像引导肝脏手术系统的软组织变形校正系统，其可以立即商业化用于患者护理。更具体地说，在这项工作结束时，将生成能够进行变形校正的图像引导肝脏手术系统，将建立这些校正保真度的初步经验，并且该技术将商业化提供给早期采用者，并获得其机构审查委员会（IRB）的批准。这是可能的，因为该应用程序将利用正在进行的临床试验正在进行的探路者治疗公司（PTI），这是在测试过程中的图像引导肝脏手术（IGLS）系统开始在2007年下半年。PTI已同意分享其临床数据，以支持本文提出的新型组织变形矫正策略。模型可用于校正IGLS内的变形的假设将得到三个具体目标的支持，包括：（1）变形补偿策略的开发，其涉及将驻留在自适应变形校正计算节点上的组合配准和形状校正技术，（2）对来自三个单独临床试验的数据的该方法的回顾性测试，（3）对更新过程的计算机模型进行了改进。该应用的第二阶段将涉及升级早期采用者的系统，以包括我们的变形校正计算节点，然后前瞻性地在临床上测试其保真度。肝脏内的原发性和转移性癌症变得越来越常见。有显著的证据表明，腹腔内肝脏手术可以改善患有转移性疾病的患者的生存时间。目前，由于该手术的复杂性，患者人群有限。更好的可视化和引导将为外科医生提供更多的信心，并将增加这些患者的手术候选人数量和结果。如果这一应用是成功的，它将导致第一个商业化的图像引导肝脏手术系统能够软组织变形校正。所提出的“变形校正计算节点”将通过容易地适应于具有类似数据的其他手术系统而具有更广泛的影响。此外，该策略也将与微创手术兼容，前提是可以获得有关器官形状的信息。目前，纠正软组织变形的唯一商业手段是使用术中磁共振（iMR）和计算机断层扫描（iCT）。这些系统的费用相当高，需要人员，并且维护成本也很高。由于其笨重的性质，患者吞吐量也大大低于传统的手术室。自20世纪80年代中期以来，iCT已经可用，自20世纪90年代中期以来，iMR已经可用，但全世界仍然只有少数系统在使用。虽然这些都是缺点，但应该指出，这些系统不会被放弃，并将继续发展。然而，这些设施极有可能成为最关键病例的转诊中心，而不是作为主流技术提供。用“变形校正计算节点”增强现有图像引导系统的策略成本非常低，可以与iMR/iCT解决方案一样有效，并且可转换到具有图像引导手术系统的任何医疗中心。这一应用程序将在弥补这些稀疏的转诊中心和广大的当地医疗中心提供给普通人群之间的脱节发挥重要作用。