Robotics in Radiosurgery

Abstract

The practice of neurosurgery is being transformed by the increasing adaptation of robotics. The use of advanced robotics with image-guided computer software allows for the precise delivery of radiation to intracranial tumors while sparing the adjacent healthy brain tissue. This, combined with machine learning, is likely to reduce errors and reduce operative time and thus provide better patient outcomes.

Technological development has played a major role in recent advances in neurosurgery, although the adoption of robotics in this field has been slower than in other surgical specialties. However, there has been a significant uptake of robotics in radiosurgery, with advances in treatment modalities for malignant cerebral neoplasms, benign cerebral tumors, functional disorders, and vascular lesions. Leksell and Larsson pioneered Gamma Knife frame-based radiosurgery, the first patient being treated in 1967, followed by the linear accelerator (Linac) system in the 1980s and the robotic CyberKnife system in the 1990s (Adler et al. Stereotact Funct. 69:124–8, 1997, Leksell Acta Chir Scand. 102:316–9, 1951; Jayarao and Chin Neurosurg Focus. 23:E6, 2007; Colombo et al. Neurosurgery. 16:154–60, 1985) Robotics in radiosurgery has advanced in tandem with the significant improvement in the accuracy of imaging modalities.