Anatomical Modeling to Improve the Precision of Image Guided Liver Ablation

解剖建模提高图像引导肝脏消融的精度

• 批准号: 9815803
• 负责人: Kristy Brock
• 金额: $ 36.24万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9815803
• 关键词: Ablation; Algorithms; Anatomic Models; Anatomy; Biomechanics; Cessation of life; Clinical; Computer software; Data; Diagnosis; Elements; Ensure; Excision; Goals; Image; Incidence; Inflammation; Intervention; Laboratories; Liver; Liver neoplasms; Local Therapy; Location; Magnetic Resonance; Malignant neoplasm of liver; Maps; Metastatic Neoplasm to the Liver; Methods; Modality; Modeling; Molecular Conformation; Monitor; Morphologic artifacts; Normal tissue morphology; Operative Surgical Procedures; Patients; Phase; Procedures; Progression-Free Survivals; Publishing; Randomized Clinical Trials; Recurrence; Residual Tumors; Second Primary Cancers; Series; Survival Rate; Technology; Testing; Thermal Ablation Therapy; Time; Tissue Model; Tissues; Treatment Efficacy; Tumor Tissue; Water; Work; X-Ray Computed Tomography; base; biomechanical model; curative treatments; image guided; image registration; imaging probe; improved; innovation; mathematical model; post intervention; response; standard of care; success; tool; tumor; tumor ablation; tumor progression

Primary and secondary liver cancers are increasing in incidence and are collectively responsible for over 1 million deaths per year worldwide. Among the curative treatments available for liver cancers, surgical resection is considered the standard of care. Unfortunately, less than 20% of patients are eligible for such resection at the time of the diagnosis. Image-guided percutaneous thermal ablation (PTA) has become a widely utilized option for patients not eligible for surgery with local control success rates ranging from 55% to 85% (4-6). In order to achieve optimal results following PTA, rates of residual tumor or recurrence should be minimized (6, 8), which can be achieved by providing adequate minimal ablation margins around the tumor. To meet this goal, it is critical to have high-quality intra-procedurally imaging that offers information in respect precise definition of extent of the target tumor, confirmation of ablation probe placement at the target tumor(s), and accurate ablation margins assessment. Currently, there are no commercially available tools that enable an accurate method for tumor mapping and ablation assessment while taking in consideration biomechanical conformational changes associated with the ablation therapy. Based in our preliminary work, we hypothesize that local tumor control following ablation of liver cancers will be improved with the application of a dedicated anatomical linear elastic biomechanical model for treatment guidance and efficacy assessment by enabling accurate identification and targeting of the tumor and providing intra-procedural assessment of the ablation, respectively. This hypothesis will be tested through three specific aims. Firstly, we will optimize the anatomical modeling liver ablation guidance in the RayStation Platform by validating the accuracy of the linear elastic biomechanical models of the liver for the application of mapping the tumor defined on the pre-interventional images onto the intra-procedural images obtained just prior to ablation; Secondly, we will evaluate the impact of this model on local tumor control following liver ablation by conducting a phase II randomized clinical trial; Finally, we will optimize the biomechanical model to enable modeling of the local changes in the tumor and surrounding normal tissue resulting from the ablation. We believe that the integration of accurate, precise, and efficient biomechanical modeling tools to determine the tumor location at the time of ablation and to monitor the ablation margin will improve local tumor control rates in patients with liver cancers, potentially improving overall survival rates. The ability to perform deformable image registration to map the tumor, identified on pre-intervention imaging, in the presence of artifacts from the ablation probe and with little to no contrast within the liver presents a significant challenge to most intensity-based algorithms. The use of a biomechanical-based model in this application is poised to make a significant impact, potentially enabling local control for the 20% of patients who fail this therapy. The integration of this technology into the RayStation platform ensures that this technology is widely available to patients.

原发性和继发性肝癌的发病率正在增加， 全球每年有100万人死亡在肝癌的治愈性治疗中，手术切除 被认为是护理标准。不幸的是，不到20%的患者有资格接受这种切除术， 诊断的时间。图像引导经皮热消融（PTA）已成为一种广泛使用的选择 对于不适合手术的患者，局部控制成功率范围为55%至85%（4-6）。 为了在PTA后获得最佳结果，应 最小化（6，8），这可以通过在肿瘤周围提供足够的最小消融边缘来实现。到 为了实现这一目标，至关重要的是要有高质量的术中成像，提供准确的信息， 确定靶肿瘤的范围，确认消融探针放置在靶肿瘤处，以及 准确的消融边缘评估。目前，还没有商业上可用的工具， 在考虑生物力学的同时，提供一种准确的肿瘤标测和消融评估方法 与消融治疗相关的构象变化。 基于我们的初步工作，我们假设肝癌消融后的局部肿瘤控制 将通过应用专用的解剖学线性弹性生物力学模型进行治疗来改善 通过实现肿瘤的准确识别和靶向， 消融术的术中评估。这一假设将通过三个具体的测试 目标。首先，我们将通过以下方式优化RayStation平台中的解剖建模肝脏消融引导： 验证肝脏的线性弹性生物力学模型用于映射肝脏的应用的准确性， 将介入前图像上定义的肿瘤转移到消融前获得的术中图像上; 其次，我们将评估该模型对肝脏消融后局部肿瘤控制的影响， II期随机临床试验;最后，我们将优化生物力学模型，以实现对 由消融引起的肿瘤和周围正常组织的局部变化。 我们相信，准确、精确和有效的生物力学建模工具的整合， 在消融时确定肿瘤位置并监测消融边缘将改善局部肿瘤 肝癌患者的控制率，可能提高总生存率。履行能力 - 可变形图像配准，以在存在以下情况下映射在介入前成像上识别的肿瘤： 来自消融探头的伪影以及肝脏内几乎没有造影剂， 大多数基于强度的算法。在这种应用中使用基于生物力学的模型， 一个显著的影响，可能使局部控制的20%的患者谁失败了这种治疗。整合 将该技术的最新版本整合到RayStation平台中，确保了该技术可广泛用于患者。