Robotic systems in interventional oncology: a narrative review of the current status

Interventional oncology offers minimally invasive treatments for malignant tumors for curative and palliative purposes based on the percutaneous insertion of needles or catheters into the target location under image guidance. Robotic systems have been gaining increasing attention as tools that provide potential advantages for image-guided interventions. Among the robotic systems developed for intervention, those relevant to the oncology field are mainly those for guiding or driving the needles in non-vascular interventional procedures such as biopsy and tumor ablation. Needle-guiding robots support planning the needle path and align the needle robotically according to the planned trajectory, which is combined with subsequent manual needle insertion by the physician through the needle guide. Needle-driving robots can advance the needle robotically after determining its orientation. Although a wide variety of robotic systems have been developed, only a limited number of these systems have reached the clinical phase or commercialization thus far. The results of previous studies suggest that such interventional robots have the potential to increase the accuracy of needle placement, facilitate out-of-plane needle insertion, decrease the learning curve, and reduce radiation exposure. On the other hand, increased complexity and costs may be a concern when using robotic systems compared with conventional manual procedures. Further data should be collected to comprehensively assess the value of robotic systems in interventional oncology.

Automated summary

Interventional oncology provides minimally invasive treatments for malignant tumors by inserting needles or catheters into the target location under image guidance. Robotic systems have gained attention for guiding and driving needles in non-vascular interventional procedures. These systems have the potential to increase accuracy, facilitate needle insertion, reduce learning curve, and minimize radiation exposure. However, concerns regarding complexity and costs remain.