Compensation for intraoperative tissue motion in the registration of preoperative image volumes with the OR is important for improving the utility of image guidance in the neurosurgery setting. Model-based strategies for neuroimage compensation are appealing because they offer the prospect of retaining the high-resolution preoperative information without the expense and complexity associated with full volume intraoperative scanning. Further, they present opportunities to integrate incomplete or sparse, partial volume sampling of the surgical field as a guide for full volume estimation and subsequent compensation of the preoperative images. While potentially promising, there are a number of unresolved difficulties associated with deploying computational models for this purpose. For example, to date they have only been successful in representing the tissue motion that occurs during the earliest stages of neurosurgical intervention and have not addressed the later more complex events of tissue retraction and resection. IN this paper, we develop a mathematical framework for implementing retraction and resection within the context of finite element modeling of brain deformation using the equations of linear consolidation. Specifically, we discuss the critical boundary conditions applied at the new tissue surfaces created by these respective interventions and demonstrate the ability to model compound events where updated image volumes are generated in succession to represent the significant occurrences of tissue deformation which take place during the course of surgery. In this regard, we show image compensation for an actual OR case involving the implantation of a subdural electrode array for recording neural activity.

Date Published: 28 May 2001
PDF: 9 pages
Proc. SPIE 4319, Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures, (28 May 2001); doi: 10.1117/12.428039

Published in SPIE Proceedings Vol. 4319:
Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures
Seong Ki Mun, Editor(s)