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

• 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
• 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

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 腹部癌症是全世界发病率和死亡率的毁灭性原因。例如，肝细胞 肝癌（HCC）的五年生存率低于20%，是癌症发病率上升最快的原因。 早期和准确的诊断是至关重要的，因为手术治疗是可行的。 切除和/或局部消融。与外科手术相比，局灶性消融减少了住院时间， 保护周围正常组织，并降低治疗相关的发病率。然而，焦点 由于不充分的图像引导，消融术在适用性和有效性方面仍然面临严重的限制， 当前方法提供的程序准确性。因此，迫切需要建立新的 微创干预，以改善腹部癌症的诊断和治疗。 传统的腹部介入依赖于超声和/或计算机断层扫描（CT）的图像引导， 这可能不能提供癌性病变的充分可视化。此外，CT利用电离辐射 并且不能在整个介入过程中用于实时成像。磁共振成像（MRI） 使其成为腹部介入实时指导的理想选择的关键优势：它是最佳和/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，并具有真实的- 对不断运动的腹部器官进行实时成像。然而，当前的实时MRI遭受以下问题： 图像质量、时间延迟以及在跟踪过程中的设备和组织目标的困难的折衷 议案此外，MRI扫描仪的狭窄物理空间严重阻碍了医生接近MRI扫描仪。 在成像过程中，患者在扫描仪内。因此，目前MRI引导的干预需要繁琐的 妨碍准确性和效率的工作流程。 该提案的目的是克服这些挑战，并实现实时MRI引导的腹部 干预措施。跨学科研究团队将利用协同创新（1）实时MRI， 计算机辅助引导方法，（2）MRI兼容机器人，（3）计算机辅助反馈控制 方法和交互式用户界面，以创建一个新的实时MRI引导的机器人系统。系统将 在可编程动态组织模型和体内猪肝模型中进行评估，以实现安全，准确， 以及移动目标中的有效针头放置-所有腹部干预的基础。这个新 机器人系统将使下一代实时MRI引导的干预措施，可以积极影响 肝肿瘤和腹部肿瘤患者的诊断和治疗。

项目成果

Deep learning-based automatic pipeline for 3D needle localization on intra-procedural 3D MRI.

• DOI: 10.1007/s11548-024-03077-3
• 发表时间: 2024-03
• 期刊: International journal of computer assisted radiology and surgery
• 影响因子: 3
• 作者: Wenqi Zhou;Xinzhou Li;Fatemeh Zabihollahy;David S Lu;Holden H. Wu