This paper reviews the critical capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments in the field of Neuro Surgery.
AI's roots are found across multiple fields, including robotics, philosophy, psychology, linguistics, and statistics. Significant advances in computer science, such as improvements in processing speed and power, have functioned as a catalyst to allow for the base technologies required for the advent of AI. The growing popularity of AI across many different industries has attracted venture capital investment up to $5 billion in 2016 alone. Much of the current attention on AI has focused on the four core subfields introduced below.
AI for surgical robots
Brain tumor ablation has been identified as an ideal procedure for autonomous robotic surgery. “It involves the perception of the environment by the robotic system and a corresponding adaption of its behavior to the changing environmental parameters. Knot tying in suturing is also a challenge for the deployment of AI. The shape and exact location of cortical motor areas vary among individuals. The exact knowledge of these locations is crucial for the planning of neurosurgical procedures. Robot-assisted image-guided transcranial magnetic stimulation (Ri-TMS) to elicit motor evoked potential responses recorded for individual muscles have been used to reconstruct functional motor maps of the primary motor cortex (Little, S.,2016). It is becoming increasingly difficult for a neurosurgical resident to “learn” on a patient in the OT. Realistic neurosurgical simulations are the need of the hour. A computer-based, virtual reality platform offers simulated resistance and relaxation, with passage of a virtual three-dimensional (3D) ventriculostomy catheter through the brain parenchyma into the ventricle. Advances in AI and science and technology of haptics (recognizing objects through touch) is improving the learning of clinical skills and procedures” (Beudel, M., 2016).