Model-updated image guidance: initial clinical experiences with gravity-induced brain deformation

IEEE Trans Med Imaging. 1999 Oct;18(10):866-74. doi: 10.1109/42.811265.

Abstract

Image-guided neurosurgery relies on accurate registration of the patient, the preoperative image series, and the surgical instruments in the same coordinate space. Recent clinical reports have documented the magnitude of gravity-induced brain deformation in the operating room and suggest these levels of tissue motion may compromise the integrity of such systems. We are investigating a model-based strategy which exploits the wealth of readily-available preoperative information in conjunction with intraoperatively acquired data to construct and drive a three dimensional (3-D) computational model which estimates volumetric displacements in order to update the neuronavigational image set. Using model calculations, the preoperative image database can be deformed to generate a more accurate representation of the surgical focus during an operation. In this paper, we present a preliminary study of four patients that experienced substantial brain deformation from gravity and correlate cortical shift measurements with model predictions. Additionally, we illustrate our image deforming algorithm and demonstrate that preoperative image resolution is maintained. Results over the four cases show that the brain shifted, on average, 5.7 mm in the direction of gravity and that model predictions could reduce this misregistration error to an average of 1.2 mm.

Publication types

  • Case Reports
  • Comparative Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Algorithms
  • Brain / pathology*
  • Brain / surgery
  • Cerebrospinal Fluid / physiology
  • Female
  • Gravitation*
  • Humans
  • Intraoperative Period
  • Magnetic Resonance Imaging / methods*
  • Magnetic Resonance Imaging / statistics & numerical data
  • Male
  • Middle Aged
  • Models, Neurological*
  • Neurosurgical Procedures / methods
  • Neurosurgical Procedures / statistics & numerical data
  • Retrospective Studies