Endovascular guidewire manipulation is essential for minimally-invasive clinical applications (Percutaneous Coronary Intervention (PCI), Mechanical thrombectomy techniques for acute ischemic stroke (AIS), or Transjugular intrahepatic portosystemic shunt (TIPS)). All procedures commonly require 3D vessel geometries from 3D CTA (Computed Tomography Angiography) images. During these procedures, the clinician generally places a guiding catheter in the ostium of the relevant vessel and then manipulates a wire through the catheter and across the blockage. The clinician only uses X-ray fluoroscopy intermittently to visualize and guide the catheter, guidewire, and other devices. However, clinicians still passively control guidewires/catheters by relying on limited indirect observation (i.e., 2D partial view of devices, and intermittent updates due to radiation limit) from X-ray fluoroscopy. Modeling and controlling the guidewire manipulation in coronary vessels remains challenging because of the complicated interaction between guidewire motions with different physical properties (i.e., loads, coating) and vessel geometries with lumen conditions resulting in a highly non-linear system. This paper introduces a scalable learning pipeline to train AI-based agent models toward automated endovascular predictive device controls. First, we create a scalable environment by pre-processing 3D CTA images, providing patient-specific 3D vessel geometry and the centerline of the coronary. Next, we apply a large quantity of randomly generated motion sequences from the proximal end to generate wire states associated with each environment using a physics-based device simulator. Then, we reformulate the control problem to a sequence-to-sequence learning problem, in which we use a Transformer-based model, trained to handle non-linear sequential forward/inverse transition functions.
Autonomous Guidewire Navigation for Robot-assisted Endovascular Interventions: A Knowledge-Driven Visual Guidance Approach
Wandong Medical Technology Co., Ltd（万东医疗科技有限公司）；Beijing Police College（北京警察学院）；School of Intelligent Engineering and Automation, Beijing University of Posts and Telecommunications（北京邮电大学智能工程与自动化学院）；Department of Vascular Surgery, Shanghai Changhai Hospital, Naval Medical University（海军军医大学上海长海医院血管外科）；Beijing Institute of Satellite Information Engineering（北京卫星信息工程研究所）
Vision-Language Procedural Reasoning for Context-Aware Reward Modeling of Robotic Endovascular Guidewire Navigation
Department of Control Science and Engineering, College of Electronic and Information Engineering, and Shanghai Institute of Intelligent Science and Technology, Tongji University（同济大学电子与信息工程学院控制科学与工程系，以及上海智能科学与技术研究院）；Department of Electronic Engineering, Faculty of Engineering, The Chinese University of Hong Kong（香港中文大学工程学院电子工程系）；Shanghai Operation Robot Co., Ltd.（上海微创医疗机器人（集团）股份有限公司）
Real-Time 3D Guidewire Reconstruction from Intraoperative DSA Images for Robot-Assisted Endovascular Interventions
Department of Control Science and Engineering, College of Electronic and Information Engineering, and Shanghai Institute of Intelligent Science and Technology, Tongji University（控制科学与工程系，电子与信息工程学院，智能科学与技术上海研究院，同济大学）；Department of Electronic Engineering, Faculty of Engineering, The Chinese University of Hong Kong（电子工程系，工程学院，香港中文大学）；Department of Artificial Intelligence and Computer Science, School of Computer Science, University of Birmingham（人工智能与计算机科学系，计算机科学学院，伯明翰大学）；Robotics and Microsystems Center, School of Mechanical and Electric Engineering, Soochow University（机器人与微系统中心，机械与电子工程学院，苏州大学）；School of Oriental Pan-Vascular Devices Innovation College, University of Shanghai for Science and Technology（东方血管器件创新学院，上海科学技术大学）；State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University（心血管疾病国家重点实验室，医疗创新中心，上海东方医院，同济大学医学院）
Autonomous navigation of catheters and guidewires in mechanical thrombectomy using inverse reinforcement learning
School of Biomedical Engineering & Imaging Sciences（生物医学工程与影像科学学院）；Kings College London（伦敦国王学院）；AIBE；Friedrich-Alexander University Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）
Toward Autonomous Soft Robotic Endovascular Navigation via Imitation Learning
Johns Hopkins University（约翰霍普金斯大学）；Stanford University（斯坦福大学）；McGill University（麦吉尔大学）；University of Maryland（马里兰大学）；Swiss Federal Institute of Technology in Lausanne (EPFL)（日内瓦联邦理工学院（EPFL））；ETH Zurich（苏黎世联邦理工学院）
Remote Teleoperation of Endovascular Intervention Robots: A Systematic Review
School of Biomedical Engineering & Imaging Sciences, King’s College London（生物医学工程与成像科学学院，伦敦国王学院）；Department of Engineering, King’s College London（工程系，伦敦国王学院）；Department of Neuroradiology, King’s College Hospital（神经放射学系，伦敦国王医院）
Modular Robotic Catheters for Endovascular Aneurysm Repair
Hamlyn Centre for Robotic Surgery, Department of Mechanical Engineering, Imperial College London（伦敦帝国理工学院机械工程系机器人手术哈姆林中心）；Department of Metabolism, Digestion and Reproduction, Imperial College London（伦敦帝国理工学院代谢、消化与生殖系）；Department of Mechanical Engineering, Bursa Uludag University（布尔萨乌鲁达大学机械工程系）；Chair for Computer Aided Medical Procedures and Augmented Reality (CAMP), Technical University of Munich（慕尼黑工业大学计算机辅助医疗程序与增强现实主席）
A 2D Image Feedback-Based Autonomous Endovascular Navigation Method: A Perception and Control Framework
Beijing Institute of Technology（北京理工大学）；Advanced Institute for Ocean Research, Southern University of Science and Technology（南方科技大学海洋科学与工程研究院）；Shenzhen Institute of Advanced Biomedical Robot Company Limited（深圳先进生物医学机器人有限公司）；Southern University of Science and Technology（南方科技大学）；School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University（北京交通大学机械与电子控制工程学院）；Aerospace Center Hospital（航天中心医院）
Deep reinforcement learning for guidewire navigation in coronary artery phantom
Asan Medical Center, University of Ulsan College of Medicine（蔚山大学医学院峨山医学中心）；Medipixel, Inc.（Medipixel 公司）；Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine（蔚山大学医学院峨山医学中心峨山融合科学技术研究所）；Chungnam National University Sejong Hospital, Chungnam National University School of Medicine（忠南大学医学院世宗医院）
Artificial Intelligence in the Autonomous Navigation of Endovascular Interventions: A Systematic Review
School of Biomedical Engineering & Imaging Sciences（生物医学工程与影像科学学院）；Kings College London（伦敦国王学院）；AIBE；Friedrich-Alexander University Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）
A Position Statement on Endovascular Models and Effectiveness Metrics for Mechanical Thrombectomy Navigation, on behalf of the Stakeholder Taskforce for AI-assisted Robotic Thrombectomy (START)
on behalf of the Stakeholder Taskforce for AI-assisted Robotic Thrombectomy (START)（人工智能辅助机器人取栓任务组成员）
Sample-Efficient Learning with Online Expert Correction for Autonomous Catheter Steering in Endovascular Bifurcation Navigation
Tongji University（同济大学）；College of Electronics and Information Engineering（电子信息工程学院）；Shanghai Institute of Intelligent Science and Technology（上海智能科学与技术研究院）；The Chinese University of Hong Kong（香港中文大学）；School of Mechanical and Electric Engineering（机械电子工程学院）；Soochow University（苏州大学）；Shanghai Operation Robot Co., Ltd.（上海操作机器人有限公司）；State Key Laboratory of Cardiovascular Diseases（心血管疾病国家重点实验室）
Vision-Based Reasoning with Topology-Encoded Graphs for Anatomical Path Disambiguation in Robot-Assisted Endovascular Navigation
Department of Control Science and Engineering, College of Electronics and Information Engineering, and Shanghai Institute of Intelligent Science and Technology, Tongji University（控制科学与工程系，电子与信息工程学院和智能科学与技术上海研究院，同济大学）；Department of Electronic Engineering, Faculty of Engineering, The Chinese University of Hong Kong（电子工程系，工程学院，香港中文大学）；Shanghai Operation Robot Co., Ltd.（上海操作机器人有限公司）；Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Cardiovascular Diseases, National Clinical Research Center for Interventional Medicine（心内科，复旦大学中山医院，上海心血管疾病研究所，介入医学临床研究中心）；State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University（心血管疾病国家重点实验室和医学创新中心，上海东医院，同济大学医学院）
Anatomy-Informed Neural Networks: Encoding Anatomic Priors in Loss and Architecture, with an SE(3) Formulation of Guidewire-Induced Aortoiliac Deformation
