Pub Date : 2024-10-03DOI: 10.1109/TMRB.2024.3472833
Jixiu Li;Tao Zhang;Truman Cheng;Yehui Li;Calvin Sze Hang Ng;Philip Wai Yan Chiu;Zheng Li
Magnetic anchored and guided system(MAGS) is a promising solution for minimally invasive surgery, particularly in the realm of endoscope robotics. However, the inherent tight tissue contact in MAGS limits certain degrees of freedom, constraining the surgeon’s ability to adjust the field of view. To address this, we propose a novel solution by combining magnetic actuation with a cable-driven flexible link. Our study encompasses the design, analysis of magnetic force/torque, and kinematics of the flexible link. One prototype was fabricated, and experiments, including the evaluation of magnetic coupling performance and the motion of the flexible link, were conducted. These experiments validated both the theoretical modeling and the functionality of the magnetic endoscope system.
{"title":"Design, Analysis, and Preliminary Validation of Magnetic Anchored and Cable Driven Endoscope for Minimally Invasive Surgery","authors":"Jixiu Li;Tao Zhang;Truman Cheng;Yehui Li;Calvin Sze Hang Ng;Philip Wai Yan Chiu;Zheng Li","doi":"10.1109/TMRB.2024.3472833","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3472833","url":null,"abstract":"Magnetic anchored and guided system(MAGS) is a promising solution for minimally invasive surgery, particularly in the realm of endoscope robotics. However, the inherent tight tissue contact in MAGS limits certain degrees of freedom, constraining the surgeon’s ability to adjust the field of view. To address this, we propose a novel solution by combining magnetic actuation with a cable-driven flexible link. Our study encompasses the design, analysis of magnetic force/torque, and kinematics of the flexible link. One prototype was fabricated, and experiments, including the evaluation of magnetic coupling performance and the motion of the flexible link, were conducted. These experiments validated both the theoretical modeling and the functionality of the magnetic endoscope system.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1397-1400"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Robot-assisted surgery (RAS) requires effective control strategies to ensure safety and accuracy while respecting the physical limits of the robot during tasks such as suturing and tissue manipulation. Model Predictive Control (MPC), with its inherent capability to handle complex dynamic systems, predict the future response and enforce constraints, is well-suited for these tasks. In this paper, MPC is employed to automate the suturing stitch task by mapping the operational space trajectory to the joint space while ensuring compliance with system kinematics constraints and safety requirements. To address varying requirements during suturing sub-tasks, two different objective functions and their corresponding constraint sets are used. The proposed framework is implemented using the ACADO toolkit to solve the Optimal Control Problem (OCP) and ROS to connect ACADO to CoppeliaSim/DVRK. Validation through simulations in CoppeliaSim and real-time experiments on the DVRK demonstrated that our approach achieved a positional/orientational accuracy of less than $1mm/4 ^{circ }$ in simulations, and an error norm of approximately $1.9mm$ in real world implementations, confirming its effectiveness in automating suturing task.
{"title":"MPC for Suturing Stitch Automation","authors":"Pasquale Marra;Sajjad Hussain;Marco Caianiello;Fanny Ficuciello","doi":"10.1109/TMRB.2024.3472796","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3472796","url":null,"abstract":"Robot-assisted surgery (RAS) requires effective control strategies to ensure safety and accuracy while respecting the physical limits of the robot during tasks such as suturing and tissue manipulation. Model Predictive Control (MPC), with its inherent capability to handle complex dynamic systems, predict the future response and enforce constraints, is well-suited for these tasks. In this paper, MPC is employed to automate the suturing stitch task by mapping the operational space trajectory to the joint space while ensuring compliance with system kinematics constraints and safety requirements. To address varying requirements during suturing sub-tasks, two different objective functions and their corresponding constraint sets are used. The proposed framework is implemented using the ACADO toolkit to solve the Optimal Control Problem (OCP) and ROS to connect ACADO to CoppeliaSim/DVRK. Validation through simulations in CoppeliaSim and real-time experiments on the DVRK demonstrated that our approach achieved a positional/orientational accuracy of less than \u0000<inline-formula> <tex-math>$1mm/4 ^{circ }$ </tex-math></inline-formula>\u0000 in simulations, and an error norm of approximately \u0000<inline-formula> <tex-math>$1.9mm$ </tex-math></inline-formula>\u0000 in real world implementations, confirming its effectiveness in automating suturing task.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1468-1477"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-03DOI: 10.1109/TMRB.2024.3472856
Diego Dall’Alba;Lorenzo Busellato;Thiusius Rajeeth Savarimuthu;Zhuoqi Cheng;Iñigo Iturrate
Vascular diseases are commonly diagnosed using Ultrasound (US) imaging, which can be inconsistent due to its high dependence on the operator’s skill. Among these, Deep Vein Thrombosis (DVT) is a common yet potentially fatal condition, often leading to critical complications like pulmonary embolism. Robotic US Systems (RUSs) aim to improve diagnostic test consistency but face challenges with the complex scanning pattern requiring precise control over US probe pressure, such as the one needed for indirectly detecting occlusions during DVT assessment. This work introduces an imitation learning method based on Kernelized Movement Primitives (KMP) to standardize the contact force profile during US exams by training a robotic controller using sonographer demonstrations. A new recording device design enhances demonstration acquisition, integrating with US probes and enabling seamless force and position data recording. KMPs are used to link scan trajectory and interaction force, enabling generalization beyond the demonstrations. Our approach, evaluated on synthetic models and volunteers, shows that the KMP-based RUS can replicate an expert’s force control and US image quality, even under conditions requiring compression during scanning. It outperforms previous methods using manually defined force profiles, improving exam standardization and reducing reliance on specialized sonographers.
血管疾病通常使用超声波（US）成像进行诊断，但由于高度依赖操作员的技术，这种诊断方法并不稳定。其中，深静脉血栓（DVT）是一种常见但可能致命的疾病，往往会导致肺栓塞等严重并发症。机器人 US 系统（RUS）旨在提高诊断测试的一致性，但面临着复杂扫描模式的挑战，需要精确控制 US 探头的压力，例如在 DVT 评估过程中间接检测闭塞情况所需的压力。这项研究引入了一种基于核化运动原型（KMP）的模仿学习方法，通过超声波技师的演示来训练机器人控制器，从而使超声波检查过程中的接触力曲线标准化。新的记录设备设计增强了演示采集功能，可与超声探头集成，实现无缝力和位置数据记录。KMP 用于连接扫描轨迹和相互作用力，从而实现演示之外的推广。我们的方法在合成模型和志愿者身上进行了评估，结果表明，基于 KMP 的 RUS 可以复制专家的力控制和 US 图像质量，即使在扫描过程中需要压缩的条件下也是如此。它优于以前使用手动定义力曲线的方法，提高了检查的标准化程度，减少了对专业超声技师的依赖。
{"title":"Imitation Learning of Compression Pattern in Robotic-Assisted Ultrasound Examination Using Kernelized Movement Primitives","authors":"Diego Dall’Alba;Lorenzo Busellato;Thiusius Rajeeth Savarimuthu;Zhuoqi Cheng;Iñigo Iturrate","doi":"10.1109/TMRB.2024.3472856","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3472856","url":null,"abstract":"Vascular diseases are commonly diagnosed using Ultrasound (US) imaging, which can be inconsistent due to its high dependence on the operator’s skill. Among these, Deep Vein Thrombosis (DVT) is a common yet potentially fatal condition, often leading to critical complications like pulmonary embolism. Robotic US Systems (RUSs) aim to improve diagnostic test consistency but face challenges with the complex scanning pattern requiring precise control over US probe pressure, such as the one needed for indirectly detecting occlusions during DVT assessment. This work introduces an imitation learning method based on Kernelized Movement Primitives (KMP) to standardize the contact force profile during US exams by training a robotic controller using sonographer demonstrations. A new recording device design enhances demonstration acquisition, integrating with US probes and enabling seamless force and position data recording. KMPs are used to link scan trajectory and interaction force, enabling generalization beyond the demonstrations. Our approach, evaluated on synthetic models and volunteers, shows that the KMP-based RUS can replicate an expert’s force control and US image quality, even under conditions requiring compression during scanning. It outperforms previous methods using manually defined force profiles, improving exam standardization and reducing reliance on specialized sonographers.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1567-1580"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10704653","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-03DOI: 10.1109/TMRB.2024.3473299
Siyi Wei;Zhiwei Wu;Jinhui Zhang;Shaomeng Gu;Zhanxin Geng;Jiahao Luo;Yueyang Gao;Zheng Li
Minimally invasive surgery, as a promising treatment method for coronary heart disease and intracranial aneurysm, has received extensive research interest due to its appealing characteristics, e.g., the little surgical trauma, short rehabilitation time, determined curative effect, and less pain. However, the accumulated X-ray radiation during the percutaneous coronary intervention (PCI) and neurovascular intervention (NVI) greatly increases the probability of medical staff suffering from cataracts and brain tumors. In this article, the telemanipulated vascular intervention (TVI) system is presented, a compact and versatile vascular interventional system. The TVI system comprised of a leader joystick, a follower delivery device, and a graphical user interface is designed for intravascular delivery during the robot-assisted PCI and robot-assisted NVI. The performance of the TVI system is evaluated by demonstrating its ability to achieve telemanipulated navigation in the real-sized 3D cardio-cerebrovascular model with coronary stenosis and intracranial aneurysms. The experimental results demonstrate that the TVI system can navigate to 3 types of coronary stenosis, 6 types of cerebral artery, and an intracranial aneurysm with a diameter of 8 mm. To further demonstrate the performance of the TVI system, the robot-assisted renal artery angioplasty is conducted in a rabbit model for preclinical evaluation. These promising results indicate that the TVI system is capable of precisely manipulating the guidewire remotely, mitigating the health risks associated with prolonged exposure to X-ray radiation for interventionists.
{"title":"Telemanipulated Vascular Intervention System for Minimally Invasive Surgery","authors":"Siyi Wei;Zhiwei Wu;Jinhui Zhang;Shaomeng Gu;Zhanxin Geng;Jiahao Luo;Yueyang Gao;Zheng Li","doi":"10.1109/TMRB.2024.3473299","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3473299","url":null,"abstract":"Minimally invasive surgery, as a promising treatment method for coronary heart disease and intracranial aneurysm, has received extensive research interest due to its appealing characteristics, e.g., the little surgical trauma, short rehabilitation time, determined curative effect, and less pain. However, the accumulated X-ray radiation during the percutaneous coronary intervention (PCI) and neurovascular intervention (NVI) greatly increases the probability of medical staff suffering from cataracts and brain tumors. In this article, the telemanipulated vascular intervention (TVI) system is presented, a compact and versatile vascular interventional system. The TVI system comprised of a leader joystick, a follower delivery device, and a graphical user interface is designed for intravascular delivery during the robot-assisted PCI and robot-assisted NVI. The performance of the TVI system is evaluated by demonstrating its ability to achieve telemanipulated navigation in the real-sized 3D cardio-cerebrovascular model with coronary stenosis and intracranial aneurysms. The experimental results demonstrate that the TVI system can navigate to 3 types of coronary stenosis, 6 types of cerebral artery, and an intracranial aneurysm with a diameter of 8 mm. To further demonstrate the performance of the TVI system, the robot-assisted renal artery angioplasty is conducted in a rabbit model for preclinical evaluation. These promising results indicate that the TVI system is capable of precisely manipulating the guidewire remotely, mitigating the health risks associated with prolonged exposure to X-ray radiation for interventionists.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1512-1525"},"PeriodicalIF":3.4,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-30DOI: 10.1109/TMRB.2024.3468381
Giacomo Zuccon;Alberto Doria;Giulio Rosati;Christopher A. Johnson;Lee McEligot;Kohl Hertz;Kyle Fernan;Ishaq Khan;V. Reggie Edgerton;David J. Reinkensmeyer
Practicing walking motions while supine might help accelerate recovery after neurologic injury. This paper presents the design, modeling, and initial testing of a novel cable-driven device called AirStep that compensates for the weight of the legs, facilitating air-stepping practice while supine. AirStep integrates multiple mass-spring counterbalancing mechanisms to minimize the effect of gravity throughout the entire gait cycle such that patients can perform active or passive stepping motions in a near-zero gravity environment. Handles allow a rehabilitation therapist to manually assist leg motion through the cables as needed. Data acquired from an optical motion capture system validated the mathematical model of the AirStep, showing that the leg trajectories in air-stepping resembled those from running. In pilot testing, two individuals with spinal cord injury (SCI) required manual assistance at the hips from a physical therapist to achieve step-like motions through the AirStep interface. AirStep can apply low-forces, allow stepping in the supine position, and can quantify changes in patient-generated force production. Compared to other rehabilitation robots, AirStep offers the advantages of a low-cost mechanical structure, high acceptability by the patient and easy transportability aside a hospital bed, making the AirStep a good candidate for adoption in the early-stage gait rehabilitation.
{"title":"Design of a Cable-Suspended Robot for Early Stage Gait Rehabilitation","authors":"Giacomo Zuccon;Alberto Doria;Giulio Rosati;Christopher A. Johnson;Lee McEligot;Kohl Hertz;Kyle Fernan;Ishaq Khan;V. Reggie Edgerton;David J. Reinkensmeyer","doi":"10.1109/TMRB.2024.3468381","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3468381","url":null,"abstract":"Practicing walking motions while supine might help accelerate recovery after neurologic injury. This paper presents the design, modeling, and initial testing of a novel cable-driven device called AirStep that compensates for the weight of the legs, facilitating air-stepping practice while supine. AirStep integrates multiple mass-spring counterbalancing mechanisms to minimize the effect of gravity throughout the entire gait cycle such that patients can perform active or passive stepping motions in a near-zero gravity environment. Handles allow a rehabilitation therapist to manually assist leg motion through the cables as needed. Data acquired from an optical motion capture system validated the mathematical model of the AirStep, showing that the leg trajectories in air-stepping resembled those from running. In pilot testing, two individuals with spinal cord injury (SCI) required manual assistance at the hips from a physical therapist to achieve step-like motions through the AirStep interface. AirStep can apply low-forces, allow stepping in the supine position, and can quantify changes in patient-generated force production. Compared to other rehabilitation robots, AirStep offers the advantages of a low-cost mechanical structure, high acceptability by the patient and easy transportability aside a hospital bed, making the AirStep a good candidate for adoption in the early-stage gait rehabilitation.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1616-1626"},"PeriodicalIF":3.4,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-30DOI: 10.1109/TMRB.2024.3468385
Shunlei Li;Ajay Gunalan;Muhammad Adeel Azam;Veronica Penza;Darwin G. Caldwell;Leonardo S. Mattos
This paper introduces a new controller for real-time dynamic laser ablation: the autonomous computer-assisted laser microsurgery system (Auto-CALM). Auto-CALM allows the surgeon to define the ablation area, which is then precisely ablated by the system while compensating for tissue motions and deformations. This is achieved based on three control blocks: target tracking, laser tracking, and ablation control algorithm. The ablation area, i.e., the target, is defined by the surgeon using a graphics tablet and graphics overlay on the surgical video. This target is then tracked in real-time using improved optical flow and a novel scaling strategy that makes the system robust against tissue deformations. Laser tracking is based on a pretrained Segment Anything Model that localizes the position of the laser in the surgical video. The ablation algorithm generates a trajectory to ablate the target given the dynamically updated laser position and target position. This enables motion compensation, which increases the accuracy of the system. Auto-CALM was validated through laser ablation experiments based on a porcine larynx fixed to a breathing motion simulation stage. The obtained results were also compared with those achieved under manual operation of CALM, and under autonomous ablation using the Track Anything Model as the target tracking algorithm. Furthermore, four different parts of the ex-vivo porcine larynx were tested to investigate different tracking features and the robustness of the system. Auto-CALM achieved a Dice Similarity Coefficient of 95.49% under the most challenging conditions (including tissue motion and no feature), reaching an ablation speed of $1.43~mm^{2}/s$ . The accuracy and usability of the integrated platform bear potential for the accurate ablation of tissue volumes in clinical settings. Further ex-vivo and in-vivo animal studies shall help translate these findings to clinical use.
{"title":"Auto-CALM: Autonomous Computer-Assisted Laser Microsurgery","authors":"Shunlei Li;Ajay Gunalan;Muhammad Adeel Azam;Veronica Penza;Darwin G. Caldwell;Leonardo S. Mattos","doi":"10.1109/TMRB.2024.3468385","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3468385","url":null,"abstract":"This paper introduces a new controller for real-time dynamic laser ablation: the autonomous computer-assisted laser microsurgery system (Auto-CALM). Auto-CALM allows the surgeon to define the ablation area, which is then precisely ablated by the system while compensating for tissue motions and deformations. This is achieved based on three control blocks: target tracking, laser tracking, and ablation control algorithm. The ablation area, i.e., the target, is defined by the surgeon using a graphics tablet and graphics overlay on the surgical video. This target is then tracked in real-time using improved optical flow and a novel scaling strategy that makes the system robust against tissue deformations. Laser tracking is based on a pretrained Segment Anything Model that localizes the position of the laser in the surgical video. The ablation algorithm generates a trajectory to ablate the target given the dynamically updated laser position and target position. This enables motion compensation, which increases the accuracy of the system. Auto-CALM was validated through laser ablation experiments based on a porcine larynx fixed to a breathing motion simulation stage. The obtained results were also compared with those achieved under manual operation of CALM, and under autonomous ablation using the Track Anything Model as the target tracking algorithm. Furthermore, four different parts of the ex-vivo porcine larynx were tested to investigate different tracking features and the robustness of the system. Auto-CALM achieved a Dice Similarity Coefficient of 95.49% under the most challenging conditions (including tissue motion and no feature), reaching an ablation speed of \u0000<inline-formula> <tex-math>$1.43~mm^{2}/s$ </tex-math></inline-formula>\u0000. The accuracy and usability of the integrated platform bear potential for the accurate ablation of tissue volumes in clinical settings. Further ex-vivo and in-vivo animal studies shall help translate these findings to clinical use.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1423-1435"},"PeriodicalIF":3.4,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1109/TMRB.2024.3468397
Nils Marahrens;Dominic Jones;Nikita Murasovs;Chandra Shekhar Biyani;Pietro Valdastri
While only a limited number of procedures have image guidance available during robotically guided surgery, they still require the surgeon to manually reference the obtained scans to their projected location on the tissue surface. While the surgeon may mark the boundaries on the organ surface via electrosurgery, the precise margin around the tumor is likely to remain variable and not guaranteed before a pathological analysis. This paper presents a first attempt to autonomously extract and mark tumor boundaries with a specified margin on the tissue surface. It presents a first concept for tool-tissue interaction control via Inertial Measurement Unit (IMU) sensor fusion and contact detection from the electrical signals of the Electrosurgical Unit (ESU), requiring no force sensing. We develop and assess our approach on Ultrasound (US) phantoms with anatomical surface geometries, comparing different strategies for projecting the tumor onto the surface and assessing its accuracy in repeated trials. Finally, we demonstrate the feasibility of translating the approach to an ex-vivo porcine liver. We achieve mean true positive rates above $mathbf {0.84}$ and false detection rates below $mathbf {0.12}$ compared to a tracked reference for each calculation and execution of the marking trajectory for dummy and ex-vivo experiments.
{"title":"An Ultrasound-Guided System for Autonomous Marking of Tumor Boundaries During Robot-Assisted Surgery","authors":"Nils Marahrens;Dominic Jones;Nikita Murasovs;Chandra Shekhar Biyani;Pietro Valdastri","doi":"10.1109/TMRB.2024.3468397","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3468397","url":null,"abstract":"While only a limited number of procedures have image guidance available during robotically guided surgery, they still require the surgeon to manually reference the obtained scans to their projected location on the tissue surface. While the surgeon may mark the boundaries on the organ surface via electrosurgery, the precise margin around the tumor is likely to remain variable and not guaranteed before a pathological analysis. This paper presents a first attempt to autonomously extract and mark tumor boundaries with a specified margin on the tissue surface. It presents a first concept for tool-tissue interaction control via Inertial Measurement Unit (IMU) sensor fusion and contact detection from the electrical signals of the Electrosurgical Unit (ESU), requiring no force sensing. We develop and assess our approach on Ultrasound (US) phantoms with anatomical surface geometries, comparing different strategies for projecting the tumor onto the surface and assessing its accuracy in repeated trials. Finally, we demonstrate the feasibility of translating the approach to an ex-vivo porcine liver. We achieve mean true positive rates above \u0000<inline-formula> <tex-math>$mathbf {0.84}$ </tex-math></inline-formula>\u0000 and false detection rates below \u0000<inline-formula> <tex-math>$mathbf {0.12}$ </tex-math></inline-formula>\u0000 compared to a tracked reference for each calculation and execution of the marking trajectory for dummy and ex-vivo experiments.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1699-1712"},"PeriodicalIF":3.4,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1109/TMRB.2024.3465828
Giovanni Pittiglio;Fabio Leuenberger;Margherita Mencattelli;Max McCandless;Edward O’Leary;Pierre E. Dupont
This paper introduces a novel magnetic navigation system for cardiac ablation. The system is formed from two key elements: a magnetic ablation catheter consisting of a chain of spherical permanent magnets; and an actuation system comprised of two cart-mounted permanent magnets undergoing pure rotation. The catheter design enables a large magnetic content with the goal of minimizing the footprint of the actuation system for easier integration with the clinical workflow. We present a quasi-static model of the catheter, the design of the actuation units, and their control modalities. Experimental validation shows that we can use small rotating magnets (119mm diameter) to reach cardiac ablation targets while generating clinically-relevant forces. Catheter control using a joystick is compared with manual catheter control. While total task completion time is similar, smoother navigation is observed using the proposed robotic system. We also demonstrate that the ball chain can ablate heart tissue and generate lesions comparable to the current clinical ablation catheters.
{"title":"Magnetic Ball Chain Robots for Cardiac Arrhythmia Treatment","authors":"Giovanni Pittiglio;Fabio Leuenberger;Margherita Mencattelli;Max McCandless;Edward O’Leary;Pierre E. Dupont","doi":"10.1109/TMRB.2024.3465828","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3465828","url":null,"abstract":"This paper introduces a novel magnetic navigation system for cardiac ablation. The system is formed from two key elements: a magnetic ablation catheter consisting of a chain of spherical permanent magnets; and an actuation system comprised of two cart-mounted permanent magnets undergoing pure rotation. The catheter design enables a large magnetic content with the goal of minimizing the footprint of the actuation system for easier integration with the clinical workflow. We present a quasi-static model of the catheter, the design of the actuation units, and their control modalities. Experimental validation shows that we can use small rotating magnets (119mm diameter) to reach cardiac ablation targets while generating clinically-relevant forces. Catheter control using a joystick is compared with manual catheter control. While total task completion time is similar, smoother navigation is observed using the proposed robotic system. We also demonstrate that the ball chain can ablate heart tissue and generate lesions comparable to the current clinical ablation catheters.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1322-1333"},"PeriodicalIF":3.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1109/TMRB.2024.3464670
Nicholas E. Pacheco;Chaitanya S. Gaddipati;Siavash Farzan;Loris Fichera
This paper reports on a study whose goal is to control the tissue temperature at a specific spot during laser surgery, for the purpose of, inducing coagulation or sealing blood vessels. We propose a solution that relies on the automatic adjustment of the laser focus (and thus how concentrated the laser beam is), combined with the use of an infrared thermal camera for non-contact temperature monitoring. One of the main challenges in the control of thermal laser-tissue interactions is that these interactions can be hard to predict due to the inherent variability in the molecular composition of biological tissue. To tackle this challenge, we explore two different control approaches: (1) a model-less controller using a Proportional-Integral (PI) formulation, whose gains are set via a tuning procedure performed on laboratory-made tissue phantoms; and (2) a model-based controller using an adaptive formulation that makes it robust to tissue variability. We report on experiments, performed on four types of tissue specimens, showing that both controllers can consistently achieve temperature tracking with a Root-Mean-Square Error (RMSE) $approx$ 1 °C.
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This paper presents a novel simultaneous localization and mapping (SLAM) technique, termed SLAM-TKA, for assisting total knee arthroplasty (TKA), a highly effective orthopaedic surgery that replaces arthritic or dysfunctional joint surfaces with knee prostheses. Our proposed SLAM algorithm uses information from a pre-operative tibia CT scan, intra-operative 2D X-ray images, and a trocar pin 3D mesh model to simultaneously localise the X-ray device and map the two trocar pins. Then, the estimated pins are used to evaluate the accuracy of the bone resection plane before the actual bone cutting, which plays a crucial role in precisely implanting the knee prostheses. To ensure high accuracy and robustness of the proposed SLAM algorithm, three energy terms are proposed and used together to align the edge observations of the tibia, fibula and pins on the intra-operative X-ray images and their corresponding pre-operative 3D mesh models in both 2D and 3D space. To enable the proposed iteration-based SLAM algorithm to be implemented in real-time such that the evaluation processing does not interrupt much on the workflow of TKA, the data association of edge correspondences matching and exhausted points-to-mesh distance calculation are pre-computed using the signed distance field method. Simulations are used to evaluate the accuracy and robustness of the proposed algorithm, and the experiments using in-vivo datasets from five patients demonstrate the high accuracy and efficiency in practice. The code and datasets are released at https://github.com/zsustc/SLAM-TKA .
本文介绍了一种新型同步定位和绘图（SLAM）技术，称为 SLAM-TKA，用于辅助全膝关节置换术（TKA），这是一种高效的矫形外科手术，用膝关节假体取代关节炎或功能障碍的关节面。我们提出的 SLAM 算法利用术前胫骨 CT 扫描、术中二维 X 射线图像和套管针三维网格模型中的信息，同时定位 X 射线装置并绘制两个套管针。然后，在实际切骨之前，利用估算出的套管针来评估骨切除平面的准确性，这对精确植入膝关节假体起着至关重要的作用。为了确保所提出的 SLAM 算法的高精确度和鲁棒性，我们提出了三个能量项，并将其共同用于对齐术中 X 射线图像上的胫骨、腓骨和栓骨的边缘观测值，以及它们在二维和三维空间中对应的术前三维网格模型。为了使所提出的基于迭代的 SLAM 算法能够实时实施，从而使评估处理不会对 TKA 的工作流程造成太大干扰，边缘对应匹配的数据关联和耗尽的点到网格距离计算都是使用带符号的距离场方法预先计算的。模拟评估了所提算法的准确性和鲁棒性，使用五名患者的体内数据集进行的实验证明了该算法在实践中的高准确性和高效性。代码和数据集发布于 https://github.com/zsustc/SLAM-TKA。
{"title":"SLAM-TKA: Simultaneously Localizing X-Ray Device and Mapping Pins in Conventional Total Knee Arthroplasty","authors":"Shuai Zhang;Liang Zhao;Shoudong Huang;Hua Wang;Qi Luo;Qi Hao;Danail Stoyanov","doi":"10.1109/TMRB.2024.3465565","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3465565","url":null,"abstract":"This paper presents a novel simultaneous localization and mapping (SLAM) technique, termed SLAM-TKA, for assisting total knee arthroplasty (TKA), a highly effective orthopaedic surgery that replaces arthritic or dysfunctional joint surfaces with knee prostheses. Our proposed SLAM algorithm uses information from a pre-operative tibia CT scan, intra-operative 2D X-ray images, and a trocar pin 3D mesh model to simultaneously localise the X-ray device and map the two trocar pins. Then, the estimated pins are used to evaluate the accuracy of the bone resection plane before the actual bone cutting, which plays a crucial role in precisely implanting the knee prostheses. To ensure high accuracy and robustness of the proposed SLAM algorithm, three energy terms are proposed and used together to align the edge observations of the tibia, fibula and pins on the intra-operative X-ray images and their corresponding pre-operative 3D mesh models in both 2D and 3D space. To enable the proposed iteration-based SLAM algorithm to be implemented in real-time such that the evaluation processing does not interrupt much on the workflow of TKA, the data association of edge correspondences matching and exhausted points-to-mesh distance calculation are pre-computed using the signed distance field method. Simulations are used to evaluate the accuracy and robustness of the proposed algorithm, and the experiments using in-vivo datasets from five patients demonstrate the high accuracy and efficiency in practice. The code and datasets are released at \u0000<uri>https://github.com/zsustc/SLAM-TKA</uri>\u0000.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1526-1541"},"PeriodicalIF":3.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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