System Design of an Automated Drilling Device for Neurosurgical Applications

Abstract

Mechanical drilling and perforation of bone is one of the most standard practices followed in neurosurgery, but is a highly specialised task performed by trained neurosurgeons. Craniotomy refers to removing part of the skull bone to access the underlying tissues, which is currently performed manually involving a series of precautionary procedures. The non-planar surface of the brain makes the manual drilling process over a series of marked points less accurate. Guided robotic drilling is one such alternative towards the contemporary craniotomy method that leads to increased accuracy, thereby minimizing permanent secondary damages to the patient under treatment. The paper proposes a design towards achieving the first step in building an autonomous neurosurgical tool for craniotomy practices over a non-planar surface. The proposed device caters towards reaching to a specified target location in the surgical space, and orient the drilling head system perpendicular to the specified point on the non-planar surface to perform needle insertion, or deep drilling. In addition, the proposed tool follows the guided path in a perpendicular orientation along the series of drilling points on a non-planar skull surface, where the skull surface is derived from IR imaging of the patient in the operative field. The real-time 3D model of the patient’s head is reconstructed post multiple scanning from the handheld portable IR camera. The developed autonomous drilling system is driven by the path planned and annotated by the neurosurgeon on the 3D model generated from the handheld IR camera in the intraoperative space. The autonomous drill positioning system is validated experimentally on a 3D printed human head, and the system placement, along with the orientation errors and accuracy in guided path showed promising results.