Vision-based guidance for robot assisted endovascular intervention

Finished: 2021-12-06

MSc assignment

Aims and objectives

To extract required interaction between catheter tip/body and tissue exclusively from concomitantly applied imaging (e.g., MRI or fluoroscopy) to avoid the use of additional tracking technologies.

Background

Vascular diseases are one of the major causes of death in the Western world. Common treatments are endovascular interventions which involve the manual introduction of catheters to a specific target in the aorta or auxiliary vessels. Intraprocedural risks are associated with mechanical interaction between the catheter and the vessel wall. The application of high forces can result in trauma or rupture of the vessel and can cause severe complications if biomechanical limits are exceeded. Currently, the manipulation of the catheter and/or guidewire in multiple DoF and simultaneous fluoroscopy-based perception of interaction with anatomy requires continuous training and generates cognitive load to the interventionist to estimate the advancement of the catheter within the vessel.  In this regard, we are developing new robotic technologies for endovascular treatments with standard catheters that aid to eliminate drawbacks, increase precision, and improve the level of patient safety.

Brief project plan

A common approach to evaluating the interaction between tissue and catheter is related to force sensing. Intracorporal sensing considers the instrumentation of catheter tips or sections of the catheter body. Exemplary, reports considered the development of tactile sensors [1], integration of strain sensors to standard catheters [2], or tri-axial PDMS sensors [3]. However, these approaches cannot be applied to intended scenarios that make use of standard catheters due to clearance, miniaturization, and costs. Alternatively, reports targeted extracorporeal instrumentation of the catheter, i.e., with customized handpieces or instrumented manipulation devices [4]. Further approaches made use of image-based shape detection and fusion with kinematic models to estimate the magnitude and direction of contact forces between tip and environment  [5]. However, methods are still dependent on 1) catheter imaging with cameras in laboratory environments, 2) the use of customized catheters with well-known mechanical parameters and tendon forces, and 3) additional tip pose information obtained from simultaneous EM tracking.

This project targets to extract required interaction between catheter tip/body and tissue exclusively from concomitantly applied imaging (e.g., MRI or fluoroscopy) to avoid the use of additional tracking technologies. Previous work generally addressed tip forces but the determination of contact and associated friction along the catheter body is mandatory for adaptation of haptic forces during insertion. In this regard, a framework for the analysis of fluoroscopy data will be implemented for the image-based generation of haptic forces. Early work has demonstrated feasibility with tip tracking in a phantom study [6].

[1]        J. Guo, S. Guo, P. Wang, W. Wei and Y. Wang, "A novel type of catheter sidewall tactile sensor array for vascular interventional surgery," in 2013 ICME International Conference on Complex Medical Engineering, 2013.

[2]        C. J. Payne, H. Rafii-Tari and G. Yang, "A force feedback system for endovascular catheterization," in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012.

[3]        H. J. Pandya, J. Sheng and J. P. Desai, "Towards a tri-axial flexible force sensor for catheter contact force measurement," in 2016 IEEE SENSORS, 2016.

[4]        H. Rafii-Tari, C. J. Payne, C. Bicknell, K. W. Kwok, N. J. W. Cheshire, C. Riga and G.-Z. Yang, "Objective Assessment of Endovascular Navigation Skills," Annals of Biomedical Engineering, vol. 45, p. 1315–1327, 2017.

[5]        J. Back, T. Manwell, R. Karim, K. Rhode, K. Althoefer and H. Liu, "Catheter contact force estimation from shape detection using a real-time Cosserat rod model," in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

[6]        G. Dagnino, J. Liu, M. E. M. K. Abdelaziz, W. Chi, C. Riga and G.-Z. Yang, "Haptic Feedback and Dynamic Active Constraints for Robot-Assisted Endovascular Catherization," in IEEE/RSJ International Conference on Intelligent Robots and Systems, Madrid, 2018.