Robotics, imaging, and artificial intelligence in the catheterisation laboratory

Abstract

The catheterisation laboratory today combines diagnosis and therapeutics, through various imaging modalities and a prolific list of interventional tools, led by balloons and stents. In this review, we focus primarily on advances in image-based coronary interventions. The X-ray images that are the primary modality for diagnosis and interventions are combined with novel tools for visualisation and display, including multi-imaging co-registration modalities with three- and four-dimensional presentations. Interpretation of the physiologic significance of coronary stenosis based on prior angiographic images is being explored and implemented. Major efforts to reduce X-ray exposure to the staff and the patients, using computer-based algorithms for image processing, and novel methods to limit the radiation spread are being explored. The use of artificial intelligence (AI) and machine learning for better patient care requires attention to universal methods for sharing and combining large data sets and for allowing interpretation and analysis of large cohorts of patients. Barriers to data sharing using integrated and universal protocols should be overcome to allow these methods to become widely applicable. Robotic catheterisation takes the physician away from the ionising radiation spot, enables coronary angioplasty and stenting without compromising safety, and may allow increased precision. Remote coronary procedures over the internet, that have been explored in virtual and animal studies and already applied to patients in a small pilot study, open possibilities for sharing experience across the world without travelling. Application of those technologies to neurovascular, and particularly stroke interventions, may be very timely in view of the need for expert neuro-interventionalists located mostly in central areas.

Central illustration

Current imaging and physiology methods pre-, during, and post intervention. Pre-intervention multimodality 3D imaging may be obtained to allow better understanding and planning of the procedure. Fusion of the angiographic images with CT data enhances 3D understanding of procedures such as TAVR (A). During the procedure, fluoroscopy is the main tool for guidance, but various intravascular methods may be combined with angiographic procedures. Dynamic Coronary Roadmap is a novel tool to aid navigation during the procedure (B). Post-procedure imaging varies between different imaging modalities, with or without flow reserve challenges. An example of SPECT CT is shown in panel C. AI can access all these data in the background to aid the physician in planning and execution of an optimal patient intervention.

Figure 1

Schematic presentation of the use of artificial intelligence (AI) with data mining in the interventional laboratory. Integration of X-ray and intravascular imaging data, ECG, laboratory results, and the patient’s electronic health records are analysed by AI. Imaging interpretation will be supported by AI and enhanced by real-time clinical, laboratory and other important information to support the physician’s decision-making process.

Figure 2

The HoloLens mixed reality display (Microsoft, Redmond, WA, USA) is used to overlay 3D data on a hologram reality view during a balloon mitral valve intervention. Data obtained for ultrasound echocardiography are visible as a semi-transparent holographic cube positioned in front of the echocardiographist and shared by an interventional cardiologist. Reproduced with permission from Kasprazak et al, and from the European Society of Cardiology. All rights reserved.

Figure 3

The evolution of the robotic PCI system and concept. A) The original Remote Navigation System manipulating wire and device are controlled at the console by a joystick (B). Reprinted from Beyar et al, with permission from Elsevier. C) The current CorPath GRX control station is positioned within a shielded cockpit in the catheterisation laboratory with the operator console controlling the wire, the device, and the guide catheter (taken during robotic PCI at the Interventional Cardiology Center, Jagiellonian University Hospital, Poland). D) Set-up for the first remote catheterisation performed by Dr Tejas Patel in Ahmadabad, India. The control station is located 35 km away from the catheterisation laboratory, with the robotic arm at the patient side. The video of the patient room and the monitor screen are transmitted via the internet. From Patel et al [CC BY-NC-ND 4.0].

Figure 4

Local and remote schematics. The robotic arm, located in the catheterisation laboratory, is hard-wired to the control station, which can be placed either in the catheterisation laboratory or in the control room, according to the operator’s preference. A second remote control unit, which can also be installed on a mobile device, is connected through the internet or a 5G wireless connection and can be placed in any other location (i.e., either elsewhere in the same or a different hospital, or any location worldwide).

Figure 5

The future catheterisation laboratory with artificial intelligence-enabled technology, clinical decision support system, voice-powered virtual assistant, and augmented reality platforms. A semi-autonomous/autonomous robotic system can provide optimisation as well as the remote operations presented above. Reprinted from Figure 2 of Sardar et al, copyright (2019), with permission from Elsevier.