A marker-based contactless catheter-sensing method to detect surgeons’ operations for catheterization training systems

It is challenging to position a catheter or a guidewire within a patient’s complicated and delicate vascular structure due to the lack of intuitive visual feedback by only manipulating the proximal part of the surgical instruments. Training is therefore critical before an actual surgery because any mistake due to the surgeon’s inexperience can be fatal for the patient. The catheter manipulation skills of experienced surgeons can be useful as input for training novice surgeons. However, few research groups focused on designs with consideration of the contactless catheter motion measurement, which allows obtaining expert surgeons’ catheter manipulation trajectories whilst still allowing them to employ an actual catheter and apply conventional pull, push and twist of the catheter as used in bedside intravascular interventional surgeries. In this paper, a novel contactless catheter-sensing method is proposed to measure the catheter motions by detecting and tracking a passive marker with four feature-point groups. The passive marker is designed to allow simultaneously sensing the translational and rotational motions of the input catheter. Finally, the effectiveness of the proposed contactless catheter-sensing method is validated by conducting a series of comparison experiments. The accuracy and error analysis are quantified based on the absolute error, relative error, mean absolute error, and the success rate of the detection.

[1]  Hannes Bleuler,et al.  Design and Evaluation of a Novel Haptic Interface for Endoscopic Simulation , 2012, IEEE Transactions on Haptics.

[2]  Pierre E. Dupont,et al.  Passive Markers for Ultrasound Tracking of Surgical Instruments , 2005, MICCAI.

[3]  J. Brachmann,et al.  Atrial fibrillation ablation using a robotic catheter remote control system: initial human experience and long-term follow-up results. , 2008, Journal of the American College of Cardiology.

[4]  Kunio Takahashi,et al.  A Virtual Reality for Catheter-based EPS based on Whole-heart Model , 2009 .

[5]  Conor J. Walsh,et al.  Simple and effective ultrasound needle guidance system , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  Pheng-Ann Heng,et al.  A Catheterization-Training Simulator Based on a Fast Multigrid Solver , 2012, IEEE Computer Graphics and Applications.

[7]  F Arai,et al.  An Intelligent Catheter System Robotic Controlled Catheter System , 2001, Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences.

[8]  Maria Drangova,et al.  A device for real-time measurement of catheter-motion and input to a catheter navigation system , 2007, SPIE Medical Imaging.

[9]  Nan Xiao,et al.  A novel robotic catheter system with force and visual feedback for vascular interventional surgery , 2012, Int. J. Mechatronics Autom..

[10]  Tom Drummond,et al.  Faster and Better: A Machine Learning Approach to Corner Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Thenkurussi Kesavadas,et al.  Design and fabrication of a robotic mechanism for remote steering and positioning of interventional devices , 2010, The international journal of medical robotics + computer assisted surgery : MRCAS.

[12]  Yanjun Zeng,et al.  Application study of medical robots in vascular intervention , 2011, The international journal of medical robotics + computer assisted surgery : MRCAS.

[13]  F Arai,et al.  Autonomous catheter insertion system using magnetic motion capture sensor for endovascular surgery , 2007, The international journal of medical robotics + computer assisted surgery : MRCAS.

[14]  Yuru Zhang,et al.  Toward In-Vivo Force and Motion Measurement for Vascular Surgery , 2014, IEEE Transactions on Instrumentation and Measurement.

[15]  Zeng-Guang Hou,et al.  Design and evaluation of a bio-inspired robotic hand for percutaneous coronary intervention , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[16]  Fumihito Arai,et al.  Patient-specific neurovascular simulator for evaluating the performance of medical robots and instrumens , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[17]  Hang Yin,et al.  Optics Based Motion Measurement for a Catheter Navigation System: A Novel and Low Cost Approach , 2010, ICIRA.

[18]  Chien-Ming Li,et al.  Virtual-reality simulator system for double interventional cardiac catheterization using haptic force producer with visual feedback , 2016, Comput. Electr. Eng..

[19]  Hedyeh Rafii-Tari,et al.  Current and Emerging Robot-Assisted Endovascular Catheterization Technologies: A Review , 2013, Annals of Biomedical Engineering.

[20]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  N. Cheshire,et al.  Robot-assisted fenestrated endovascular aneurysm repair (FEVAR) using the Magellan system. , 2013, Journal of vascular and interventional radiology : JVIR.

[22]  Shuxiang Guo,et al.  A VR-based training system for vascular interventional surgery , 2013, 2013 ICME International Conference on Complex Medical Engineering.

[23]  Fumihito Arai,et al.  Catheter manipulation training system based on quantitative measurement of catheter insertion and rotation , 2014, Adv. Robotics.

[24]  Fumihito Arai,et al.  Numerical comparison of catheter insertion trajectory within blood vessel model using image processing , 2010, 2010 International Symposium on Micro-NanoMechatronics and Human Science.

[25]  Fumihito Arai,et al.  2-D optical encoding of catheter motion and cyber-physical system for technical skills measurement and quantitative evaluation in endovascular surgery , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[26]  Toshio Fukuda,et al.  In vitro three‐dimensional aortic vasculature modeling based on sensor fusion between intravascular ultrasound and magnetic tracker , 2012, The international journal of medical robotics + computer assisted surgery : MRCAS.

[27]  Tom Drummond,et al.  Fusing points and lines for high performance tracking , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[28]  Fumihito Arai,et al.  Micro force sensor for intravascular neurosurgery , 1997, Proceedings of International Conference on Robotics and Automation.

[29]  Ara Darzi,et al.  Virtual reality simulation training can improve inexperienced surgeons' endovascular skills. , 2006 .

[30]  Fumihito Arai,et al.  Technical skills measurement based on a cyber‐physical system for endovascular surgery simulation , 2013, The international journal of medical robotics + computer assisted surgery : MRCAS.

[31]  I. Sakuma,et al.  Intravascular catheter navigation using path planning and virtual visual feedback for oral cancer treatment , 2011, The international journal of medical robotics + computer assisted surgery : MRCAS.

[32]  Shuxiang Guo,et al.  Evaluating performance of a novel developed robotic catheter manipulating system , 2013 .

[33]  Maria Drangova,et al.  Design and Performance Evaluation of a Remote Catheter Navigation System , 2009, IEEE Transactions on Biomedical Engineering.

[34]  Shuxiang Guo,et al.  Design and performance evaluation of a master controller for endovascular catheterization , 2015, International Journal of Computer Assisted Radiology and Surgery.