Alain Devreker

Experimental Validation of a Robotic Comanipulation and Telemanipulation System for Retinal Surgery

Retinal Vein Occlusion is a common retinal vascular disorder which can cause severe loss of vision. Retinal vein cannulation is a promising treatment, but given the small diameter of retinal veins and the surgeons limited positioning precision, it is considered too risky to perform this procedure manually. The authors previously reported on the development of both a robotic comanipulation and telemanipulation system which have the potential to augment the surgeons positioning precision. This work investigates the potential benefit of these systems for retinal surgery. For this purpose, a targeting test setup was developed to quantify the attainable positioning precision one can expect when using the robotic systems during procedures like retinal vein cannulation. Ten subjects completed targeting tests in a free-hand, comanipulation and telemanipulation fashion. Results show that both the usage of the comanipulation and telemanipulation system significantly improve the positioning precision compared to a free-hand test. The telemanipulation system currently outperforms the comanipulation system with respect to precision, while subjects appreciate the remarkable ease of use of the comanipulation system.

Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking

Real-time tool segmentation is an essential component in computer-assisted surgical systems. We propose a novel real-time automatic method based on Fully Convolutional Networks (FCN) and optical flow tracking. Our method exploits the ability of deep neural networks to produce accurate segmentations of highly deformable parts along with the high speed of optical flow. Furthermore, the pre-trained FCN can be fine-tuned on a small amount of medical images without the need to hand-craft features. We validated our method using existing and new benchmark datasets, covering both ex vivo and in vivo real clinical cases where different surgical instruments are employed. Two versions of the method are presented, non-real-time and real-time. The former, using only deep learning, achieves a balanced accuracy of 89.6% on a real clinical dataset, outperforming the (non-real-time) state of the art by 3.8% points. The latter, a combination of deep learning with optical flow tracking, yields an average balanced accuracy of 78.2% across all the validated datasets.

Fluidic actuation for intra-operative in situ imaging

A novel fluidic actuation system has been developed for in situ imaging of anatomic tissues. The actuator consists of a micromachined superelastic tool guide driven by a pair of pneumatic artificial muscles. Two additional working channels allow easy interchange of instruments or sensing equipment. This paper describes the design and construction of the actuation system. Experimental results are also reported indicating a bending repeatability of 0.1 degrees and an operational bandwidth exceeding 8Hz. To show-case the performance of the device, the actuator was loaded with an all-optical ultrasound imaging probe. First scanned images of human placental tissue surface using an all-optical ultrasound probe are presented. While a model has been developed to estimate the probe position in space as function of the input pressure, in future work, this model will be complemented with additional sensor measurements of the bending probe taking into account the hysteretic behaviour of both muscles and nitinol structure.

Intuitive teleoperation of active catheters for endovascular surgery

Advances in miniature surgical instrumentation are key to less invasive and safer medical interventions. In cardiovascular procedures interventionalists turn towards catheter-based interventions, treating patients considered unfit for classical more invasive approaches. Improvements in design and steerability of catheters could further reduce the invasiveness of these interventions. For example, by improving controllability and interaction forces with the vessels, tissue damage could be limited. Through improved steerability and coordinated control, operation times and exposure to radiation might also be reduced. Latter argument formed the original motivation for the development of teleoperated robotic catheters. Despite the large kinematic dissimilarity and thus non-trivial mapping between joystick input and catheter output motion, few investigations have been conducted to find intuitive mappings that allow straightforward catheter steering. This paper presents some recent work in this direction. Three promising mappings are proposed. The mappings were implemented and validated upon a robotic catheter moving inside an artificial aorta model. Experimental results show good steerability of the robotic catheter for all the mappings. Although superiority of one mapping with respect to the others was observed, further investigation and validation is planned. In the future, additional visual cues that increase the situational awareness of the user are expected to further simplify the steering.

Intuitive Control Strategies for Teleoperation of Active Catheters in Endovascular Surgery

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.

Cognitive Autonomous Catheters Operating in Dynamic Environments

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.