{"title":"基于磁共振的机器人辅助血管内手术导航","authors":"Jelle Bijlsma, Dennis Kundrat, Giulio Dagnino","doi":"10.1007/s41315-024-00340-3","DOIUrl":null,"url":null,"abstract":"<p>There is increasing interests in robotic and computer technologies to accurately perform endovascular intervention. One major limitation of current endovascular intervention—either manual or robot-assisted is the surgical navigation which still relies on 2D fluoroscopy. Recent research efforts are towards MRI-guided interventions to reduce ionizing radiation exposure, and to improve diagnosis, planning, navigation, and execution of endovascular interventions. We propose an MR-based navigation framework for robot-assisted endovascular procedures. The framework allows the acquisition of real-time MR images; segmentation of the vasculature and tracking of vascular instruments; and generation of MR-based guidance, both visual and haptic. The instrument tracking accuracy—a key aspect of the navigation framework—was assessed via 4 dedicated experiments with different acquisition settings, framerate, and time. The experiments showed clinically acceptable tracking accuracy in the range of 1.30–3.80 mm RMSE. We believe that this work represents a valuable first step towards MR-guided robot-assisted intervention.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MR-based navigation for robot-assisted endovascular procedures\",\"authors\":\"Jelle Bijlsma, Dennis Kundrat, Giulio Dagnino\",\"doi\":\"10.1007/s41315-024-00340-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>There is increasing interests in robotic and computer technologies to accurately perform endovascular intervention. One major limitation of current endovascular intervention—either manual or robot-assisted is the surgical navigation which still relies on 2D fluoroscopy. Recent research efforts are towards MRI-guided interventions to reduce ionizing radiation exposure, and to improve diagnosis, planning, navigation, and execution of endovascular interventions. We propose an MR-based navigation framework for robot-assisted endovascular procedures. The framework allows the acquisition of real-time MR images; segmentation of the vasculature and tracking of vascular instruments; and generation of MR-based guidance, both visual and haptic. The instrument tracking accuracy—a key aspect of the navigation framework—was assessed via 4 dedicated experiments with different acquisition settings, framerate, and time. The experiments showed clinically acceptable tracking accuracy in the range of 1.30–3.80 mm RMSE. We believe that this work represents a valuable first step towards MR-guided robot-assisted intervention.</p>\",\"PeriodicalId\":44563,\"journal\":{\"name\":\"International Journal of Intelligent Robotics and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-04-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Intelligent Robotics and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41315-024-00340-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Robotics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41315-024-00340-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ROBOTICS","Score":null,"Total":0}
MR-based navigation for robot-assisted endovascular procedures
There is increasing interests in robotic and computer technologies to accurately perform endovascular intervention. One major limitation of current endovascular intervention—either manual or robot-assisted is the surgical navigation which still relies on 2D fluoroscopy. Recent research efforts are towards MRI-guided interventions to reduce ionizing radiation exposure, and to improve diagnosis, planning, navigation, and execution of endovascular interventions. We propose an MR-based navigation framework for robot-assisted endovascular procedures. The framework allows the acquisition of real-time MR images; segmentation of the vasculature and tracking of vascular instruments; and generation of MR-based guidance, both visual and haptic. The instrument tracking accuracy—a key aspect of the navigation framework—was assessed via 4 dedicated experiments with different acquisition settings, framerate, and time. The experiments showed clinically acceptable tracking accuracy in the range of 1.30–3.80 mm RMSE. We believe that this work represents a valuable first step towards MR-guided robot-assisted intervention.
期刊介绍:
The International Journal of Intelligent Robotics and Applications (IJIRA) fosters the dissemination of new discoveries and novel technologies that advance developments in robotics and their broad applications. This journal provides a publication and communication platform for all robotics topics, from the theoretical fundamentals and technological advances to various applications including manufacturing, space vehicles, biomedical systems and automobiles, data-storage devices, healthcare systems, home appliances, and intelligent highways. IJIRA welcomes contributions from researchers, professionals and industrial practitioners. It publishes original, high-quality and previously unpublished research papers, brief reports, and critical reviews. Specific areas of interest include, but are not limited to:Advanced actuators and sensorsCollective and social robots Computing, communication and controlDesign, modeling and prototypingHuman and robot interactionMachine learning and intelligenceMobile robots and intelligent autonomous systemsMulti-sensor fusion and perceptionPlanning, navigation and localizationRobot intelligence, learning and linguisticsRobotic vision, recognition and reconstructionBio-mechatronics and roboticsCloud and Swarm roboticsCognitive and neuro roboticsExploration and security roboticsHealthcare, medical and assistive roboticsRobotics for intelligent manufacturingService, social and entertainment roboticsSpace and underwater robotsNovel and emerging applications