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，主流科学社区尚未使用Tissue建模来更新图像引导的导航系统。 ）这种挫败感是对越来越多的方法，即误解了对模型升级的目标的理解，并且无法对前者进行测试和验证。认为可以回答的所有精细变形。那就是里程碑是疼痛的，结果可能会导致图像引导的肝脏系统的软组织变形系统，该系统可以立即可用于这项工作。将生成，TOR校正将为遇到stituti的早期采用者（IRB）。在2007年后半段开始测试图像引导的肝脏手术（IGL）系统。目的是：（1）DEF成为补偿策略的发展，涉及合并的注册和形状校正技术，该技术将存在于一个且适应性的变形校正PUTE节点，（2）从三个独立的临床试验中对数据进行回顾性测试，以及（3）和更新过程的模型。 。可以获取有关器官形状的策略，可以纠正软组织变形的唯一商业手段是使用术中磁共振（IMR）和计算机上的Tomagraphy（ICT）。自1980年中期以来，PUT也比传统的手术室少了。作为一种主流技术。 ATION将在纠正脱节的稀疏转介中心以及可供普通人群可用的当地医疗中心各种各样的地方发挥重要作用。