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:
- 金额:$ 63.5万
- 依托单位:
- 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:
- 关键词:3-DimensionalAbdomenAblationBiopsyBreathingCancer EtiologyCancerousCessation of lifeComputer AssistedComputer softwareDataDevicesDiagnosisDiameterEarly DiagnosisEffectivenessEngineeringExcisionFaceFamily suidaeFeedbackFoundationsFreedomFrequenciesGenerationsHumanImageInterdisciplinary StudyInterventionIonizing radiationLength of StayLesionLiverLiver neoplasmsMagnetic Resonance ImagingMalignant NeoplasmsMalignant neoplasm of abdomenMechanicsMethodsModelingMorbidity - disease rateMorphologic artifactsMotionNeedlesNormal tissue morphologyOperative Surgical ProceduresOrganPatientsPenetrationPhysiciansPhysiologicalPre-Clinical ModelPrimary carcinoma of the liver cellsProceduresRadialRobotRoboticsSafetyScanningScientistSlaveSliceStructureSurvival RateSystemTechniquesTechnologyTestingTimeTissuesVisualizationWorkX-Ray Computed Tomographyaccurate diagnosisbulk motionclinically relevantcurative treatmentsdeep learningexperimental studyflyhuman subjectimage guidedimprovedin vivoinnovationinnovative technologiesminimally invasivemortalitynew technologynext generationporcine modelpredictive modelingpreservationradiologistreal-time imagesrobotic systemsimulationsoft tissuesuccesstissue phantomtransmission processtumorultrasound
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
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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:
- 影响因子:3
- 作者:Wenqi Zhou;Xinzhou Li;Fatemeh Zabihollahy;David S Lu;Holden H. Wu
- 通讯作者:Wenqi Zhou;Xinzhou Li;Fatemeh Zabihollahy;David S Lu;Holden H. Wu
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David S.K. Lu其他文献
Prediction of treatment response and outcome of transarterial chemoembolization in patients with hepatocellular carcinoma using artificial intelligence: A systematic review of efficacy
利用人工智能预测肝细胞癌患者经动脉化疗栓塞治疗反应和结果:疗效的系统评价
- DOI:
10.1016/j.ejrad.2025.111948 - 发表时间:
2025-03-01 - 期刊:
- 影响因子:3.300
- 作者:
Pedram Keshavarz;Nariman Nezami;Fereshteh Yazdanpanah;Maryam Khojaste-Sarakhsi;Zahra Mohammadigoldar;Mobin Azami;Azadeh Hajati;Faranak Ebrahimian Sadabad;Jason Chiang;Justin P. McWilliams;David S.K. Lu;Steven S. Raman - 通讯作者:
Steven S. Raman
Helical Computed Tomography for Abdominal Imaging
- DOI:
10.1007/s002689900040 - 发表时间:
1996-02-01 - 期刊:
- 影响因子:2.500
- 作者:
Robert M. Krasny;David S.K. Lu - 通讯作者:
David S.K. Lu
David S.K. Lu的其他文献
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{{ truncateString('David S.K. Lu', 18)}}的其他基金
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:
10530929 - 财政年份:2022
- 资助金额:
$ 63.5万 - 项目类别:
MULTICENTER FEASIBILITY STUDY OF PERCUTANEOUS RADIOFREQUENCY ABLATION OF HEPA
经皮射频消融HEPA的多中心可行性研究
- 批准号:
7951555 - 财政年份:2009
- 资助金额:
$ 63.5万 - 项目类别:
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