By Vinod K. Goel

In 1806, Philipp Bozzini unveiled to the world his Lichtleiter, a contraption that used mirrors to shine candlelight into a tube inserted in the body and to reflect an image back out. We now consider the Lichtleiter to be the first endoscope. And in 1895, Wilhelm Roentgen discovered that he could create energy rays capable of shining through a human body and creating on film an image of the inside of the body – rays he dubbed “X-rays.” Their work laid the foundation for minimally-invasive surgery.

Today, minimally-invasive surgery (MIS) is of course commonplace. Using high-tech digital imaging and precision tools, a wide variety of surgeries are performed through small incisions, promising reduced pain (and accompanying need for painkillers), quicker recovery, improved access to care, better results, and reduced costs.

In some cases this has manifested as true; however, in many cases MIS still falls short of achieving these benefits. With today’s rapid pace of innovation, we as a society stand positioned to bridge this gap and truly revolutionize healthcare through MIS.

What is holding MIS back? In short, the skill set required for effective MIS places a significant cognitive burden on interventionalists. This is true on the “input” side – the imaging which is used to navigate and make decisions, as well as the “output” side – the tools and instruments which are used to perform the surgery.

Whereas traditionally, a surgeon can easily examine the structures being treated – using both sight and touch – in MIS the images can be quite limiting. A scope provides an image from an unnatural and limited viewpoint, with a limited field of view. And imaging modalities based on X-ray, ultrasound, or similar technology generate noisy two-dimensional grayscale projections, to make any sense of which requires significant training and concentration.

Similarly, in conventional open surgery the anatomy is much more readily manipulated and repaired. With minimally-invasive techniques, on the other hand, there is a limited range of movement permitted, as tools with specific limited functionality are deployed from a distance. This presents a significant challenge with respect to both precision and control.

Additionally, certain types of MIS create new risks which are absent in open surgery. X-ray fluoroscopy, used to guide many interventional procedures, subjects patients as well as caregivers to ionizing radiation. And contrast agents can prove damaging to the kidneys. There is an element of chasing one’s tail in using MIS to avoid damaging healthy tissue while simultaneously irradiating a roomful of people and risking kidney failure.

How are innovators addressing these challenges? None of these are new, and the drive to provide better care to more patients at lower costs has spurred innovations that are making a big difference. But today, the state of the art has matured to the point where we can expect these forward steps to become leaps. In particular, I believe that the three technologies to keep watching are: big data and machine learning, advanced imaging modalities, and autonomous surgery. There are overlapping reasons why these three are positioned to bring about this revolution.

Big data is the missing link between today’s MIS practice and the ability to truly democratize it and bring about the ability to provide care to as many patients as possible. Because of the high levels of skills, training, and experience required, there has long existed a chasm of ability between high-volume practitioners and centers and their lower-volume counterparts. As a result, depending on geography, socioeconomic status, and type of health insurance, many patients today effectively lack access to the best form of surgical therapy – often MIS.

Convergence of the maturity of machine learning algorithms, widespread ability to store and efficiently access huge amounts of data and processing power, and growing high-bandwidth low-latency data networks will allow computers to bolster human skill and intuition like never before. A highly skilled high-volume clinician today achieves excellent results in large part thanks to having thousands of cases of experience to draw upon. When an AI-based assistant is able to provide decision support based on tens of thousands, or millions, of cases, the chasm will narrow and the quality of MIS will improve across the board.

Advanced imaging is an area of highly active research. We are starting to see not only the growth of alternate modalities themselves, such as optical coherence tomography and ultra wideband radar, but also the advent of sophisticated image processing capable of generating images that are much more readily interpreted than before. As imaging innovation continues, we will see a continued reduction in unintended damage and an increased ability for clinicians to intuitively appreciate the structures being navigated and treated.

In autonomous surgery, or semi-autonomous surgery, robots provide assistance to surgeons. Existing surgical robots already give surgeons more control and higher precision than they might be able to achieve using their hands and passive tools. New innovations combining robotics with machine learning and advanced imaging will bring this to the next level, allowing robots to handle many parts of surgical procedures. In essence, there will be a division of labor in which the surgeon gives the robot high-level instructions about how to obtain access and positioning for the procedure at hand. Once the appropriate instruments are positioned in precisely the correct way autonomously, the surgeon will be able to take over knowing that they are poised for optimal performance.

Each of these key technologies are represented in today’s medical device, imaging, and digital health markets. But today we stand at the doorstep of a future in which they can leverage the most advanced technological capabilities to truly bring about a revolution in healthcare. And as the three themselves converge, we will see that we will reach more patients than ever and cause far less harm in the process of healing. We will realize better outcomes than could be achieved before and do so with less time and money cost. This is an exciting time.

About the author: Vinod K. Goel, Ph.D. is president of Centerline Biomedical Inc. Centerline is developing next-generation imaging and precise real-time 3D navigation to empower physicians with solutions designed to improve outcomes, lower costs, simplify complex procedures, and reduce radiation exposure to patients, clinicians and caregivers in minimally-invasive endovascular procedures. Founded in 2014 as a spinoff of Cleveland Clinic, Centerline is changing the way healthcare is delivered.