Sensor-controlled precision: the future of surgical tumor removal

The complete removal of malignant tumors is a decisive factor for the success of cancer treatment. Until now, the tissue examinations required for this have been time-consuming. In the future, sensor-based methods could come into play to help surgeons detect tumor boundaries more accurately and thus perform a more precise operation.

In this interview with MEDICA-tradefair.com, Prof. Orlando Guntinas-Lichius provides insight into the challenges in this field as well as current research projects in which he is involved.

Prof. Guntinas-Lichius, to jump right in: What exactly is sensor-based surgery and how does it work?

Prof. Orlando Guntinas-Lichius: Sensor-based surgery is based on the combination of biophotonic and biomechanical methods. Biophotonics is used to direct light of specific wavelengths into the tissue. This light interacts with the molecules in the tissue and produces effects such as scattering and reflection.

By analyzing these effects, surgeons can obtain important information about the tissue and distinguish between tumor and healthy tissue. It is like a "light scanner" for tissue. With biomechanics, we additionally measure the mechanical impedance, i.e. the elasticity of the tissue.

What are the advantages of sensor-based surgery for tumor removal?

Guntinas-Lichius: First and foremost, it is about improving the precision of tumor removal. When removing tumors in sensitive areas, such as the head and neck or neurosurgery, precision is crucial to spare healthy tissue and prevent potential recurrences.

Therefore, we are working on integrating robotics more into classical surgery. Here we work with so-called passive robotics. This means that my arm movements are translated to the robotic arms. In theory, this enables a cutting precision of about 0.1 millimeters. In other words, much more precise than is possible by hand.

But at the moment we cannot utilize this robotic precision at all, because the tumor boundaries cannot be indicated so clearly. We have a three-dimensional image because two endoscopes are used but we work exclusively with white light. That means we see a white image, and then use various parameters to decide where to cut or not.

Sensor-based methods enable surgeons to identify tumor boundaries more accurately and thus perform more effective and safer surgery. And with the help of this technology, the full potential of robotics could theoretically also be exploited.

What other data can be collected with sensor-based technology?

Guntinas-Lichius: A team of researchers, of which I am a member, is working on a technology that measures tissue elasticity and provides haptic feedback to the surgeons. This will allow for even more accurate differentiation between healthy tissue and tumor during surgery. This technology shows a lot of potential for head and neck surgery and neurosurgery. Haptization of information, i.e. making the tumor and its boundaries tangible, is an important innovation for improved and intuitive surgical guidance, especially when combined with robotics.

During surgery, decisions need to be made quickly. How quickly can the data be retrieved?

Guntinas-Lichius: Unfortunately, real-time data is not yet possible. Surgeons still have to send samples to pathology after removing the tumor in order to perform further examinations. But now researchers from medicine, computer science and physics are working together to perform the surgery in layers.

Unlike optical coherence tomography (OCT) and optoacoustic tomography, with which it is already theoretically possible today to penetrate several centimeters into the tissue, the multimodal imaging we use biophotonically has only a shallow penetration depth. Therefore, our concept is based on iteratively repeating these measurements until the tumor is completely removed – i.e., measure, slice, measure again, slice, and so on.

Another important point is the detailed visualization. A specialized research team is working on intuitive and user-friendly visualization systems that can be integrated into endoscopes, for example. This technology shows a lot of potential and could revolutionize surgical practice in the near future. But here, too, we are still at the beginning. In the end, it will depend on computer performance how quickly the data is available.

Are there already concrete applications or is the technology still in the research phase?

Guntinas-Lichius: The technology is still in the research phase. The first studies are being prepared. But as is so often the case in medical research, it takes a long time before all studies are completed and new technologies are approved. We expect it to take at least ten years.