New Technologies for Real-Time MRI-Guided Robotic-Assisted Abdominal Interventions

实时 MRI 引导机器人辅助腹部干预新技术

基本信息

批准号：
10697329
负责人：
David S.K. Lu
金额：
$ 63.5万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-06 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10697329
关键词：
3-Dimensional Abdomen Ablation Biopsy Breathing Cancer Etiology Cancerous Cessation of life Computer Assisted Computer software Data Devices Diagnosis Diameter Early Diagnosis Effectiveness Engineering Excision Face Family suidae Feedback Foundations Freedom Frequencies Generations Human Image Interdisciplinary Study Intervention Ionizing radiation Length of Stay Lesion Liver Liver neoplasms Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of abdomen Mechanics Methods Modeling Morbidity - disease rate Morphologic artifacts Motion Needles Normal tissue morphology Operative Surgical Procedures Organ Patients Penetration Physicians Physiological Pre-Clinical Model Primary carcinoma of the liver cells Procedures Radial Robot Robotics Safety Scanning Scientist Slave Slice Structure Survival Rate System Techniques Technology Testing Time Tissues Visualization Work X-Ray Computed Tomography accurate diagnosis bulk motion clinically relevant curative treatments deep learning experimental study fly human subject image guided improved in vivo innovation innovative technologies minimally invasive mortality new technology next generation porcine model predictive modeling preservation radiologist real-time images robotic system simulation soft tissue success tissue phantom transmission process tumor ultrasound

项目摘要

PROJECT SUMMARY Abdominal cancers are a devastating cause of morbidity and mortality worldwide. For example, hepatocellular carcinoma (HCC) has a grim five-year survival rate of less than 20% and is the fastest rising cause of cancer- related deaths in the U.S. Early and accurate diagnosis is crucial, as curative treatment is feasible by surgical resection and/or focal ablation. Compared to surgery, focal ablation reduces hospital stay, increases preservation of surrounding normal tissues, and decreases treatment-related morbidities. However, focal ablation still faces critical limitations in applicability and effectiveness due to inadequate image guidance and procedural accuracy provided by current approaches. Consequently, there is a pressing need to establish new minimally invasive interventions to improve the diagnosis and treatment of abdominal cancers. Conventional abdominal interventions rely on image guidance by ultrasound and/or computed tomography (CT), which can fail to provide sufficient visualization of the cancerous lesions. In addition, CT utilizes ionizing radiation and cannot be used for real-time imaging throughout an intervention. Magnetic resonance imaging (MRI) has crucial advantages that make it ideal for real-time guidance of abdominal interventions: it is the best and/or only way to visualize HCC and several types of abdominal cancers, has no ionizing radiation, and has the potential for real- time imaging of abdominal organs that are constantly in motion. However, current real-time MRI suffers from compromises in image quality, time latency, and difficulties in tracking the devices and tissue targets during motion. Furthermore, the narrow physical space of MRI scanners severely impedes the physician’s access to the patient inside the scanner during imaging. As a result, current MRI-guided interventions require cumbersome workflows that hamper the accuracy and efficiency. The objective of this proposal is to overcome these challenges and enable real-time MRI-guided abdominal interventions. The interdisciplinary research team will leverage synergistic innovations in (1) real-time MRI and computer-aided guidance methods, (2) MRI-compatible robotics, and (3) computer-aided feedback control methods and interactive user interfaces to create a new real-time MRI-guided robotic system. The system will be evaluated in programmable dynamic tissue phantoms and in vivo pig liver models to achieve safe, accurate, and efficient needle placement in moving targets – the foundation for all abdominal interventions. This new robotic system will enable next-generation real-time MRI-guided interventions that can positively impact the diagnosis and treatment of patients with liver tumors and abdominal cancers.

项目摘要腹部癌症是全球发病率和死亡率的毁灭性原因。例如，肝细胞癌（HCC）的五年生存率小于20％，是癌症的最快崛起原因 - 美国相关死亡的早期和准确的诊断至关重要，因为治疗是可行的切除和/或焦点消融。与手术相比，局灶性消融可减少住院时间，增加保存周围正常组织，并降低与治疗相关的病因。但是，焦点消融仍然面临着由于图像指导不足和当前方法提供的程序准确性。因此，有迫切需要建立新的最小的侵入性干预措施，以改善腹部癌症的诊断和治疗。常规的腹部干预依赖于超声和/或计算机断层扫描（CT）的图像指导，可能无法提供取消病变的足够可视化。另外，CT利用电离辐射并且不能在整个干预措施中用于实时成像。磁共振成像（MRI）具有至关重要的优势，是实时指导腹部干预措施的理想优势：这是最好和/或唯一的方法可视化HCC和几种类型的腹部癌症，没有电离辐射，并且有可能实现的不断运动的腹部器官的时间成像。但是，当前的实时MRI遭受图像质量，时间延迟以及在跟踪设备和组织目标的困难妥协运动。此外，MRI扫描仪的狭窄物理空间严重阻碍了物理的访问成像过程中扫描仪内部的患者。结果，当前的MRI引导干预措施需要麻烦工作流可以阻碍准确性和效率。该提案的目的是克服这些挑战并实现实时MRI引导腹部干预措施。跨学科研究团队将利用（1）实时MRI和计算机辅助指导方法，（2）MRI兼容机器人技术和（3）计算机辅助反馈控制方法和交互式用户界面来创建新的实时MRI引导机器人系统。系统将在可编程的动态组织幻像和体内猪肝模型中进行评估，以实现安全，准确，在移动目标中有效的针头放置 - 所有腹部干预的基础。这个新机器人系统将实现下一代实时MRI引导的干预措施，以积极影响肝肿瘤和腹部癌症患者的诊断和治疗。