MIS AI - artificial intelligence application in minimally invasive surgery

Artificial inteligence

In my opinion, artificial intelligence is a part of robotics. The source of the word robot is associated with the figure of an artificial man introduced by the Czech Karel Čapek 100 years ago - R.U.R. Rossumovi Univerzální Roboti (Rossum’s Universal Robots). Robotics is a technical discipline, which deals with the synthesis of certain human functions through the use of mechanisms, sensors, executive assemblies and computers. Because humans have a brain, artificial intelligence is an integral part of robotics.

Generally, artificial intelligence was created for communication between machinery and human intelligence. The robot is an artificial man or part of a humanoid robot, artificial organs or artificial intelligence.

Kevin Warwick, known as the first human cyborg (after implanting an electronic interface) claims^[3] that “where a brain is involved it must be seen as part of an overall system - adapting to the system’s needs”. Warwick is a pioneer in studying the connection between the biological body and the robot.

Robots

The traditional definition of robot means artificial man. From this point of view, the robot should have the ability to move (to perform mechanical work) and make decisions based on information provided by its senses (intelligence). While many animals have these features as well, human beings also have, apart from intelligence (which determines the correct response to stimuli), a reasoning mind, i.e., the ability to use abstract objects (theory) for calculation, objectification, prevention, and planning. Man also has consciousness.

The number of people in the world is approaching 8 billion and 3 million robots help them in industries, factories and services. According to the IFR^[4] there are 85 and 114 robots per 10,000 employees in the world and Europe respectively. Websites providing various current data measurements for humanity (such as https://www.worldometers.info/pl/) may soon provide information about robots supporting people at work and at home too.

Robots were introduced to factories when there were not enough people to produce the right number of products. And how is it with the surgeons? Accordingly^[5], “an insufficient client surgical workforce is a major barrier to safe surgical care for billions of people worldwide”. Worldwide, there are an estimated 1,112,727 specialist surgeons and 550,134 anesthesiologists. Low- and lower-middle income countries, representing 48% of the global population, comprise about 20% of this workforce. In terms of density, low-income countries have 0.7 providers per 100,000 population, compared with 5.5 in lower-middle income countries and 56.9 in high-income countries^[6].

I believe that many individuals, like me, believe that it is our duty to reduce these differences in access to a good level of medical services. Of course, the biggest role here is in education and investment but perhaps progress in the use of artificial intelligence (AI) in medicine (that is the dissemination of the standard) will provide a real chance to reverse this catastrophic trend of ever-growing disparity in access.

How many operations are performed in the world? Depending on the definition used and access to data, at least 10 million different types of operations are performed each year^[7] and this number can even go up to 300 million^[8]. Based on available data, an estimation of the global volume of surgery using a modeling strategy suggests that “We have estimated that the global volume of major surgery in 2004 was between 187.2 and 281.2 million cases per year, which has substantial implications for public-health planning.”^[9]. The authors’ findings suggest that surgery now occurs at a tremendous volume worldwide, in both rich and poor settings. This unprecedented worldwide growth in surgery shows a great need for public-health efforts to improve the monitoring, safety, and availability of surgical services, especially in view of their high risk and expense^[9].

It is important yet difficult to estimate the real number of operations. There are certainly about 300 million if the authors calculate^[9] based on one operated person per 25 living people.

What about standards? How do you count and oversee it? From these examples, we can see that one of the needs that can be met by digital monitoring and AI methods is supervision and access to current data and to analyze them.

Let’s return to the robots. Just as robots solved the problem of mass production, perhaps they will allow the dissemination of uniform standards in surgery. They will facilitate access to good medical services. For now, however, while robots increase precision for some medical tasks, they are very expensive; surgeons are helped by about 5000 robots. Every year, almost 1 million minimally-invasive operations using da Vinci robots are performed^[10]. But these are telemanipulators and every movement of the tool and all decisions are still made by the operator. In addition, thousands of diagnostic robots perform tasks semi-automatically.

Robot control consists of perception, data processing and action. For robots to make a decision, it will need to have access to information and the ability to analyze it. Having information reduces the uncertainty (indeterminacy) of objects or relationships between objects, and allows recognition of the state of the system. Sensors are responsible for obtaining information about the environment and the current state (position) of the robot’s components and its system. An important element of service robot control systems is the ability to process video information received from the robot’s environment.

Like humans, the knowledge and skills of robots result from education, experience and usable memory. As with human verification, optimization must be associated with the elimination of wrong decisions and deeds. AI robots can get knowledge from people - this is the first level of learning in robots. If we pass on a collection of information about how it is or how we think it is, then the robot will make decisions that are perhaps burdened with our mistakes. If we teach the robot to read information (measurable data) from sensors and provide algorithms for the formation of correct decisions based on this information, we will achieve an automated device. If we allow it to modify decisions and actions and assess their effects, we will have a self-learning system that can make decisions different from those that we consider as appropriate. Many of us have already been refused a loan in a bank on a similar basis. But, if we give the robot design features based on human, but with additional motion capabilities, we can achieve much better “manual” function than humans. If we give the robot tools and greater efficiency and accessibility to the areas of the human body that we operate on, tissues, cells or genes - then we get a surgical robot with practical skills that are not accessible by humans.

Robots (Cobots) interacting with people change the way many professions perform. Robots create the possibility of standardization and constant improvement of quality through learning (AI) and communication with a professional information network (professional databases and management systems) as well as with other medical devices (diagnostic, therapeutic, rehabilitation), and also elements of hospital infrastructure.

Why do we need artificial intelligence in mini-invasive surgery?

Man is only as good and useful as his senses allow. Similarly, a robot that is created in the image of a human being, by definition, cannot do more advanced work if it has a limited number of sensors, or lacks the processing of sufficient information to make the right decisions. After all, robots are all about doing work and in surgery, it is all about decision-making and mechanical work.

Suppose, in favor of these considerations, that (1) intelligence is a certain ability to make decisions independently, based on the analysis of signals (senses) that determine the state of the environment and the possibility of the subject’s impact (the surgeon using his tools) based on basic knowledge of the entire system (memory) that was developed during the learning process (system evolution by verification and optimization of goal achievement); (2) surgery is an action of removing the effects of a disease, birth defects or injury (bodily injury due to various reasons), the action of mechanically modifying the structure of tissues and organs (surgery) and/or the introduction of natural or artificial elements to replace parts of the body or supporting proper bodily functions (passive or active, artificial and biotechnological implants - e.g., stem cells and devices for physical, and mechanical, electrical or chemical stimulation of tissues).

We treat the human body as a biological, physical, chemical and biocybernetic (IT) system. Why is artificial intelligence important in medicine? First of all, decision-making plays a key role in every medical process. Based on the analysis of diagnostic data and medical history, the treatment process begins and its effectiveness is verified in the next step. The basis of evolutionary progress is the process of learning, remembering and disseminating standards. In medicine, the possibility of direct proof is very rare. Usually, the number of unknowns does not allow building full cause-and-effect knowledge to define the possibilities of our therapeutic effects. We do not have the theory of the whole organism, nor do we have the theory of one or another disease, similar to the theories of physics. That is why the doctor makes decisions based on random diagnostic data (and not a full description of the whole organism) and in the treatment specialties such as surgery, the role of sensory assessment (sight, touch, smell, hearing) and manual skills increases (due to the speed of action and real risk).

If, however, we assume that we would like to operate in a place where our intervention is necessary by methods that reduce the risk of damage to healthy tissues as much as possible, it means the loss of the ability to freely view and touch the tissue, the inability to directly insert our hands in the place of surgery. This is the current MIS dilemma. Is this beneficial for the patient? Can a surgeon possibly do this?

This is a challenge for creating new tools and both artificial intelligence and robots are one of them.

In the mathematical context, artificial intelligence is not an ordinary algorithm, which is a mathematical record of a cause and effect relationship, but a system based on say, neural networks that map the way of building memory pathways in the human brain - i.e., a decision system based on knowledge and experience, similar to the learning process. We do not quite know why such a decision is made but we are sure that the process of system optimization achieved the appropriate level of excellence. This is interesting from the point of view of applying AI successfully in medicine, as it proves the existence of an art factor in the craft of the doctor. You cannot replace a doctor with an automatic machine, i.e., a simple machine. Algorithms alone are likely not enough. There must be artificial intelligence in the decision making process and the robot in execution.

In medicine, artificial intelligence can definitely play a positive role in developing strategies and solutions for operations.

The word “strategy” comes from the Greek words stratós - army, army, and ágein - to command. Carl von Clausewitz defined that strategy is the science of using battles for war purposes. Strategy is not theoretical planning, but it is very close to action, modified by a steady flow of information.

The word “tactics” comes from the Greek words tássein, meaning táttein stack, organize, arrange. The commander creates and effectively uses the elemental system to combat factors such as destruction, movement and information. Isn’t it also the essence of surgical intervention?

Surgery is a special human activity related to complex actions for achieving specific purposes. The complexity of an action is the need to assess the condition of the starting issue and making decisions about the distributed action in time divided into roles of the members of a special team.

Operation is a part of the patient’s treatment. The doctor develops a treatment strategy and tactics to define the next elements of the procedure. Operation planning includes defining the space and subject of the operation, choosing methods, materials and devices, program of using the operating and accompanying team, and finally, the choice of the sequence of treatments, activities, movements and the impact of tools in the space of operations. The way of conducting surgery significantly depends on the equipment available.

Planning and advisory systems - extended surgeon information space

The surgeon who operates in a less invasive way has impaired access to information from the patient’s body, the surgical field. In the classic version of video-surgery, a very good quality image is obtained - enlarged with clear outlines of contours and colors. We can support this set of visual information by adding information obtained in the diagnostic and analytical process. The ways to visualize this additional information is a separate field of ergonomics, including virtual and augmented reality technology.

In my team, we have been developing the use of computer simulation of surgical operations and the use of physical modeling to improve the patient-specific decision making process for many years [Figure 1]. The skillful use of physicists’ knowledge allows us to obtain information, e.g., what will be the flow in a given branch of the coronary vessels after performing a sequential or single bypass, what will be the flow, pressure, regurgitation after implantation of a given type of prosthesis, etc.

Figure 1. Virtual operating room made in FRK (in a team led by the author). It is used for planning operations using Robin Heart robots (examples are for heart surgery) and for testing robots (in the conceptual phase) and training surgeons. The developed program in virtual space technology was tested for use: (1) on a computer stand; (2) in the Robin Heart Shell 2 robot control console; (3) VR goggles (Oculus). The images below are examples of how to visualize simulated operations. The last image outlines the green work space available for the tool chosen by the surgeon

This means that we can enrich the image with prognostic information. Moreover, if we introduce an image analysis system of the operations performed by a surgeon, we can modify it to keep up with the effects of surgery. This is one of the aims of my research work in my Fundacja Rozwoju Kardiochirurgii (FRK) team.

However, this is still not putting AI into surgery. We have known for many years that we can use telemedicine systems for consulting and verification of the correctness of actions taken by a teacher surgeon who is located away from the operating room. The endoscopic track can be connected to a conference room where all participants can comment live on the operation which is performed in the hospital.

Telemedicine systems are successfully used when, for example, the surgeon has to undertake very little surgery, which is unusual for the practice, but in this way can use the advice directly from a more experienced specialist. In the information exchange system, we thus turn on the brain of another person who does not physically participate directly in the operation. However, if we imagine that we can model on-line surgery in a digital, computer (simulation) or physical (modeling) system and thus create possibilities for the history of operations by forecasting the results of subsequent steps taken by the doctor, we are then building a very advanced advisory system based on experimental facts (model). If the model is perfect (which is extremely difficult for physiological models) then we will get excellent advice. We can also base our advice for the surgeon on the analysis of real data, from real operations, i.e., Big Data analysis. In this way, we can build a very advanced advisory system based on medical facts. Clearly, this reasoning seeks to demonstrate that the combination of these approaches can be a breakthrough in the quality of advisory systems. The systems supporting the real surgeon while making decisions should graphically indicate the location, place of intervention and provide biological-chemical-physical data that is both current and forecasted based on a specific selection of tactics.

The decision-making system based on learning from patient databases, controlled and verified in every degree and iteration of its development, was developed by a group of outstanding professionals such as the well-known IBM Watson computer. Unfortunately, its skills, despite the enormous computing power, are still no better than a good doctor. Watson has now obtained approval for decisions regarding selected oncological diseases (by analyzing data from 200,000 correctly identified patients, he can make decisions with an accuracy of up to 97%, but only for a few diseases for now). However, Watson’s difficulties indicate that entering into a live partnership during operations is still a long way off. Artificial intelligence can contribute to reducing errors, improving standards and the quality of performed operations, and increasing patient safety.

• Indirectly, passively as the basis for the work of the advisory system when planning and performing operations.

• Indirectly - as an element of surgical telemanipulator or mechatronic tools.

• Directly - as the basis for the operation of an autonomous surgical robot.

Improving the decision making process is always associated with access to good, reliable and timely information. The surgeon manually performing a classic operation uses information from all his senses. The surgeon loses access to all this information by moving away from the patient during surgery. For instance, in endoscopic instruments with a distance of about half a meter and with telemanipulators over a distance of several meters or many kilometers.

Medical robots

The segment of medical robot systems (in market analyses) is divided into surgical robot systems, rehabilitation robots, non-invasive radio surgical robots, hospital and pharmacy robots and other medical robot systems. The following companies are present on the market: Intuitive Surgical, Inc. (USA), Stryker Corporation (USA), Mazor Robotics Ltd. (Israel), Hocoma AG (Switzerland), Hansen Medical Inc. (USA), Accuray Incorporated (USA), Omnicell, Inc. (USA), Ekso Bionics Holdings, Inc. (USA), ARxIUM (USA), Kirby Lester LLC (USA), Houston Medical Robotics (USA), Otto Bock Healthcare, Kinova robotics, Varian Medical Systems, Hocoma AG, Vecna Robotics, Globus Medical, IRobot Corporation, Titan Medical, Inc., and KB Medical SA.

Medical robotics has been the most successful so far in the field of surgical and rehabilitation robots (including exoskeletons). The robot leader on the soft tissue telemanipulator market is the da Vinci robot (Intuitive Surgical). Five thousand robots are currently used in approximately 1 million operations per year, mainly urological and gynecological. New surgical robots appear, e.g., ALF-X (USA), Titan (Canada), and in other areas such as Virtual Incision, TransEnterix (SurgiBot, Senhence robot-assisted surgical system), Coridus Vascular Robotics (cardiological robot, CorPath GRX) or Artas (robot platform for hair implantation) and endoscopic Monarch (Auris Health) and orthopedic Renaissance (Mazor Robotics). Medtronic introduced surgical HUGO (Einstein), and Medrobotics - FLEX - flexible endoscopic robotic tools.

Corindus, producer of CorPath GRX platform, received permission from the United States Food and Drug Administration (FDA) for the first automated robot movement called “Rotate on Retract (RoR)” in 2018^[11]. This is the first step towards introducing autonomous robot operations.

Telemaniplators allow remote-controlled operations from different distances. However, there is a distance-dependent delay in transmission of operation images to the surgeon that can be dangerous. Most researchers consider 300 ms as the limit in delay time^[12]. The implementation of 5G technology will overcome barriers and reduce the delay of 0.27 s to 0.01 s and also improve image quality^[13]. Worldwide, about 143 million surgical procedures are not performed due to the lack of knowledge of specific procedures^[5]. Creating a network in which surgical operations are possible at a distance is a technological and political challenge. But only in this way we will then be able to solve the problem of “equal opportunities” for access to appropriate quality medical services.

Autonomy - independence of medical robots

For medical robots to play their role fully in the face of challenges from the growing needs of services, and the need to increase their quality, they must soon become independent. Stand-alone robots should operate in an information network, which allows access to all information needed to optimize operations in every situation. In history, medical robotics has already received support, several times, from technologies that were perfected for performing industrial tasks, aerospace or military projects. This time, the growing interest of the industry in co-robots - robots cooperating with employees on production lines - and strategies for the development of automation in the field of autonomous vehicles will give appropriate acceleration for the new projects of medical robots. Autonomous vehicles are currently being developed by technology giants such as Google, Apple, Tesla and Uber, a number of automotive companies including Mercedes, Volkswagen/Audi, BMW, General Motors, Volvo, Ford, a consortium of Renault-Nissan-Mitsubishi and Toyota, and companies producing computer components like Nvidia and Intel.

We probably will not make the mistake of systematizing the autonomous capabilities of medical robots based on the five-level classification of autonomous vehicles introduced by the SAE International (Society of Automotive Engineers) standardization organization. The autonomy of medical robots on a five-point scale (modeled on the SAE J3016 standard) though, with the lowest level, 0, is a lack of autonomy:

• Level 1 is telemanipulation (remote control) with support. In this type of robots, some elements have been introduced to support operations automatically. It can be, for example, an emergency stop system for a robot in a hazardous situation. Surgical robots such as da Vinci and Robin Heart are currently in this group.

• Level 2 represents robots with the option of partly automated work. A robot that can perform one of the tasks in an automated manner, e.g., tying a node or orientation of the cam-vision track to a tool.

• Level 3 is highly automated work. The system moves independently in the work space and scope of tasks but is still able to assess the limits of its freedom. If it judges that the working conditions are outside the defined area, the operator must immediately take control of the robot. In the absence of such a reaction, the robot stops. Such robots are self-propelled robots for tele-presentation and so-called robotic nurses for communication and transport of various products and materials in hospitals.

• Level 4 is fully automated work. The robot works independently but should still be supervised, e.g., by a doctor, rescuer or physiotherapist. An example of a vehicle - a robot - included in this level is the autonomous Volvo XC90 used in Uber tests (in the vehicle there is a driver - a human verification element that can take over steering, after warnings from the control system). Such machines are currently computer tomography or robotic radio-surgical knives that move and operate in accordance with the planned trajectory and tasks specified before the surgery.

• Level 5 means a robot working fully autonomously. The medical robot works independently, sharing space with the patient and medical staff, makes independent decisions and performs tasks provided for in its specialization. The robot has no tele-manipulation system. An example is the city car prototype developed by Google, Waymo Firefly i.e., a car without a manual control system, including the steering wheel, gear lever or pedals. There are currently no such medical robots.

AI and ethics

Text based on^[20] The Ethics of Artificial Organs in Implant Expert by Zbigniew Nawrat, with permission.

I believe ethics to be the art of making the right choices. And modern medicine, with its new medical techniques, healthcare systems and financing schemes, creates a completely new area of insecurity in this regard. For ages, philosophers have been analyzing issues connected with man-vs.-man and man-vs.-the world relations in order to help us comprehend the reality and find the correct conduct.

The term “ethics” comes from the Greek word ethicos, meaning a way of conduct accepted in society, a conduct according to the legal character (ethoscharacter). Today, “ethics” is colloquially understood as “morality”, although the Latin word moralis denotes judgement of the appropriateness of a given action, more so than a person’s character.

The use of AI and robotics in the treatment process facilitates remote medical care, consultations and the monitoring of a patient’s condition. It is therefore a chance for greater availability and the quality of medical services. AI and robots are a breakthrough in infrastructure, organization of the operating theatre, and in the specialist training of surgeons. But how do we evaluate a wrong decision or action of a doctor from a distance? How do we divide the responsibility for mistakes of remote robotic devices? The access to information depends on technical resources such as software, etc. Therefore, the final effect is influenced by a number of people - engineers, administrators and economists, etc. as well as fortuitous events. Ethics and morality assume human-to-human contact. Our conscience and empathy work differently in the absence of a direct connection between our actions and their effect on others.

The technological progress in biomedical engineering and regenerative medicine constitute the basis for innovative artificial organs which are adequately small, efficient, durable and energetically and mechanically functional.

A new generation of Micro-Electro-Mechanical Systems is entering medicine. The fast development of bioelectromechanical microsystems (bioMEMS), micropumps and bioinformatics has created new possibilities such as the “lab on a chip” micro-laboratory, which are revolutionizing diagnostics and therapy.

In the near future, technical devices, entirely artificial organs and robots will be used to secure tissue therapy and genetic therapy. The integration of engineering and biology is a fact.

Thanks to bioengineering and medicine, today we can influence the survival of certain individuals and entire groups of patients.

With the harmonious development of technical and biological sciences and their reasonable implementation, and the quality of life on Earth.

Artificial intelligence is part of this evolution. Since it is an element of management at the level of organs and organisms, such medical procedures on the body will require hospital or state management and we must introduce ethical criteria agreed by all people.

AI - towards greater efficiency, permanent improvement and credibility

The popularization of telecommunications and the Internet is a good example of democratization and equal access to human achievements. We all can, rich or poor, in America and Africa, in the city or in the countryside, have access to Google search engines and data collected in public libraries around the world. Just as we can check the weather, because we supervise data from various places around the world, we will be able to supervise our body condition - as long as we are able to collect relevant data from all organs of our body. This is the future of “lab on chip”. But today, by collecting data from our health records, we can make better decisions about caring for our health. By analyzing diagnostic data, we can make better decisions about invasive medical intervention, but for now the mediator is a person - the doctor. Soon, however, we will be giving the next decision to robots (communication of devices without the mediation of a human as a decision maker) and no one is surprised today when the door in front of us opens automatically. I am convinced that it will be a good time for humans, their health and safety, and we will be able to develop our skills and activities in completely new directions.

In the case of legal responsibility, it is worth looking for an analogy to obtain adequate social support. Computer advisory programs, decision systems and autonomous robots operate either on 1) the basis of transparent algorithms linking the cause and observation with effect and decision, or 2) on the basis of machine and deep learning - AI. In the former, we can conclude that the rules of operation are legible to the professional user (e.g., doctor) and the beneficiary, the client (e.g., patient) and the right of informed consent can be introduced. If the system of performing tasks, producing a council or a specific medical act does not take into account the absolute safety of the patient but other factors like economics (e.g., whether the client has paid for the service or is insured) then it is a matter of rules that we know perfectly well from the operation of health services. If someone introduces a virus and changes the system in a way that poses a danger, we already have (?) ways that are working such as criminal law. However, if the system works on the basis of machine learning, it is a completely new type of relationship where the client is the robot. First, we have an analogy: generally, neither the teacher nor the professor or the father is responsible for the student’s deeds although in each case they are in a teacher-student relationship. Similar to the teaching process of students by introducing a different learning system, we can obtain a good or bad AI program/robot. It can make right or wrong decisions based on the data and save or kill a patient. No one is able to check how it works without starting the system because there are no readable rules inside. Just like looking into the human brain, by itself it is difficult (?) to assess whether it belongs to a surgeon or a shopkeeper. Our only option, as well as the system of training doctors and their acquisition of specialties entitling practice of the profession, will be to test and assess the effectiveness of autonomous robots, and to make sure that no computer virus destroys learning outcomes! Then we free robots from responsibility, just as we free specialists from responsibility, believing that he does the best, in a world where the end result is never obvious and certain. Just like man, AI does not have all the data to “solve the equation of life” for the patient.

The robot has the right to break. It is not allowed to make a move without the consent of the operator. During power outages and other problems, it must be possible to remove the tools from the patient by means of a medical team. I myself was a witness to this in the early phase of implementation of the da Vinci robot: during an on-line operation for its participants at a conference in Leipzig, one of the arms of the da Vinci robot stopped listening to the surgeon’s hand. Our excellent colleague continued his classic surgery without squinting. Experience and skills, reason and knowledge always promote happiness.

Excessive optimism related to the shorter path of gaining experience in robotic operations was the reason for many crisis situations and simple mistakes. The patient’s death during the first mitral valve surgery with a robot in the UK was resounding. The surgeon lost visibility after damage to the aorta which flooded the camera. The patient died. “An inquest has heard how Sukumaran Nair lobbied to be allowed to perform a mitral valve repair using a state-of-the art Da Vinci robot, despite performing slowly during non-robotic operations and passing up opportunities to practice on the machine”^[21].

The da Vinci robot is a telemanipulator. The control system allows you to direct the movement of the tools using the movement of the hand of the surgeon sitting at the console. Sometimes the control signal transmission system (e.g., cable damage) or movement mechanism (e.g., mechanical damage) fails. Here is an example of the description of such an event noted by the FDA: “System error codes #20009 and #21009 appear when the da Vinci safety system determines a differential change in the angular position of one or more robotic joints on the specified manipulator, as measured by that joint’s primary control sensor encoder and the secondary sensor potentiometer. The system alarm system generated fault code- functioned as designed and there was no injury to the pt. Upon determining this condition, the safety system put da vinci in a “recoverable safe state”^[22].

The FDA has an online database MAUDE (Manufacturer and User Device Experience) filed by manufacturers, health care facilities, patients and lawyer, and includes thousands of incidents (ranging from error code bugs to patient deaths) related to the use of various da Vinci robotic systems. In Homa Alemzadeh and colleagues “A Retrospective Study of 14 Years of FDA Data” summarized that between 2000 and 2013, a total of 144 deaths, 1391 patient injuries and 8061 device malfunctions were reported with robotic surgery (10,624 reports at a time when 1.75 million robotic procedures were performed). Device and instrument malfunctions, such as falling of burnt/broken pieces of instruments into the patient (14.7%), electrical arcing of instruments (10.5%), unintended operation of instruments (8.6%), system errors (5%), and video/imaging problems (2.6%), constituted a major part of the reports. Device malfunctions impacted patients in terms of injuries or procedure interruptions. In 1104 (10.4%) of all the events, the procedure was interrupted to restart the system (3.1%), convert the procedure to non-robotic techniques (7.3%), or to reschedule it (2.5%)^[23].

According to the FDA database, in the 5-year period ending on Aug 31, 2017, the agency received 30 reports of incidents in which the patient died in connection with surgery using the da Vinci system. The system did not necessarily cause those deaths, but they occurred after or during surgery in which surgeons used the system. During the same time period, the FDA received 282 reports involving patient injury.

Experts say that the main contributing factors to robotic surgery adverse-event reports are: device failure (30%), device operational/setup (25%), user error (20%), inadequate training (7%), maintenance issue (7%) and others (11%)^[24].

That’s all for the manipulator. The equipment or person may fail. But if we were to have an autonomous robot, who or what will be considered guilty? Who will be responsible for the wrong diagnosis or bad result from surgery? Engineer, constructor, director (owner) of the hospital, the supervising doctor or even, the economist? Or maybe a lawyer? Or perhaps the family/patient agreeing to use it? Again, looking at the successes and progress (including failures) of the development of autonomous vehicles, we see that the solution will not be easy. It will probably be different for different treatments and activities, depending on the patient’s balance of risk and chance. Just as we agree, as road users, that the fire brigade should not follow common traffic rules (as a delaying factor) in order to rescue people. But before we worry about how to solve this problem for interventional medicine, we need to solve this problem for better-developed artificial intelligence applications in diagnostics. Already today, there are companies, for example, which diagnose on the basis of an image analysis of the cornea of the eye and bravely take full responsibility for the opinions issued. Of course, none of these areas of diagnostic imaging (using humans or robots) is 100% correct.