Journal of Medical Robotics Research

Advances in miniaturized surgical instrumentation are key to less demanding and safer medical interventions. In cardiovascular procedures interventionalists turn towards catheter-based interventions, treating patients considered unfit for more invasive approaches. A positive outcome is not guaranteed. The risk for calcium dislodgement, tissue damage or even vessel rupture cannot be eliminated when instruments are maneuvered through fragile and diseased vessels. This paper reports on the progress made in terms of catheter design, vessel reconstruction, catheter shape modeling, surgical skill analysis, decision making and control. These efforts are geared towards the development of the necessary technology to autonomously steer catheters through the vasculature, a target of the EU-funded project Cognitive AutonomouS CAtheters operating in Dynamic Environments (CASCADE). Whereas autonomous placement of an aortic valve implant forms the ultimate and concrete goal, the technology of individual building blocks to reach such ambitious goal is expected to be much sooner impacting and assisting interventionalists in their daily clinical practice.

Using realistic benchtop models in early stages of device development can reduce time and efforts necessary to move the device to further testing. In this study, we propose several patient specific vascular benchtop models for the development and validation of a robotic catheter for transcatheter aortic valve implantation. The design and manufacturing of these models, and their properties are presented. Additionally, it is demonstrated that the described design process provides virtual models that are accurately linked to the physical models.

Catheter navigation is typically based on fluoroscopy. This implies exposure to harmful radiation, lack of depth perception and limited soft-tissue contrast. Catheter navigation would benefit from guidance that makes better use of detailed pre-operatively acquired MR/CT images, while reducing radiation exposure and improving spatial awareness of the catheter pose and shape. A prerequisite for such guidance is an accurate registration between the catheter tracking system and the MR/CT scans. Existing registration methods are lengthy and cumbersome as they require a lot of user interaction. This forms a major obstacle for their adoption into clinical practice. This paper proposes a radiation-free registration method that minimizes the impact on the surgical workflow and avoids most user interaction. The method relies on catheters with embedded sensors that provide intra-operative data that can either belong to the vessel wall or to the lumen of the vessel. Based on the acquired surface and lumen points an accurate registration is computed automatically, with minimal user interaction. Validation of the proposed method is performed on a synthetic yet realistic aorta phantom. Input from electromagnetic tracking, force sensing, and intra-vascular ultrasound are used as intra-operative sensory data.

Minimally invasive endovascular interventions have evolved rapidly over the past decade, facilitated by breakthroughs in medical imaging and sensing, instrumentation and most recently robotics. Catheter-based operations are potentially safer and applicable to a wider patient population due to the reduced comorbidity. As a result endovascular surgery has become the preferred treatment option for conditions previously treated with open surgery and as such the number of patients undergoing endovascular interventions is increasing every year. This fact coupled with a proclivity for reduced working hours results in a requirement for efficient training and assessment of new surgeons, that deviates from the “see one, do one, teach one” model introduced by William Halsted, so that trainees obtain operational expertise in a shorter period. Developing more objective assessment tools based on quantitative metrics is now a recognized need in interventional training and this manuscript reports the current literature for endovascular skills assessment and the associated emerging technologies. A systematic search was performed on PubMed (MEDLINE), Google Scholar, IEEXplore and known journals using the keywords, “endovascular surgery”, “surgical skills”, “endovascular skills”, “surgical training endovascular” and “catheter skills”. Focusing explicitly on endovascular surgical skills, we group related works into three categories based on the metrics used; structured scales and checklists, simulation-based and motion-based metrics. This review highlights the key findings in each category and also provides suggestions for new research opportunities towards fully objective and automated surgical assessment solutions.

Cardiovascular surgeons increasingly resort to catheter-based diagnostic and therapeutic interventions because of their limited invasiveness. Although, these approaches allow treatment of patients considered unfit for conventional open surgery, exposure to radiation and high procedural complexity could lead to complications. These factors motivated the introduction of robotic technology offering more dexterous catheters, enhanced visualization and opening new possibilities in terms of guidance and coordinated control. In addition to improvements of patient outcome, through teleoperated catheter control radiation exposure of surgeons can be reduced. In order to limit surgical workload, intuitive mappings between joystick input and resulting catheter motion are essential. This paper presents and compares two proposed mappings and investigates the benefits of additional visual guidance. The comparison is based on data gathered during an experimental campaign involving 14 novices and three surgeons. The participants were asked to perform an endovascular task in a virtual reality simulator presented in the first part of this paper. Statistical results show significant superiority of one mapping with respect to the other and a significant improvement of performance thanks to additional visual guidance. Future work will focus on translating the results to a physical setup for surgical validation, also the learning effect will be analyzed more in-depth.