Stereovision to MR image registration for cortical surface displacement mapping to enhance image-guided neurosurgery.

PURPOSE

A surface registration method is presented to align intraoperative stereovision (iSV) with preoperative magnetic resonance (pMR) images, which utilizes both geometry and texture information to extract tissue displacements as part of the overall process of compensating for intraoperative brain deformation in order to maintain accurate neuronavigational image guidance during surgery.

METHODS

A sum-of-squared-difference rigid image registration was first executed to detect lateral shift of the cortical surface and was followed by a mutual-information-based block matching method to detect local nonrigid deformation caused by distention or collapse of the cortical surface. Ten (N = 10) surgical cases were evaluated in which an independent point measurement of a dominant cortical surface feature location was recorded with a tracked stylus in each case and compared to its surface-registered counterpart. The full three-dimensional (3D) displacement field was also extracted to drive a biomechanical brain deformation model, the results of which were reconciled with the reconstructed iSV surface as another form of evaluation.

RESULTS

Differences between the tracked stylus coordinates of cortical surface features and their surface-registered locations were 1.94 ± 0.59 mm on average across the ten cases. When the complete displacement map derived from surface registration was utilized, the resulting images generated from mechanical model updates were consistent in terms of both geometry (1-2 mm of model misfit) and texture, and were generated with less than 10 min of computational time. Analysis of the surface-registered 3D displacements indicate that the magnitude of motion ranged from 4.03 to 9.79 mm in the ten patient cases, and the amount of lateral shift was not related statistically to the direction of gravity (p = 0.73 ≫ 0.05) or the craniotomy size (p = 0.48 ≫ 0.05) at the beginning of surgery.

CONCLUSIONS

The iSV-pMR surface registration method utilizes texture and geometry information to extract both global lateral shift and local nonrigid movement of the cortical surface in 3D. The results suggest small differences exist in surface-registered locations when compared to positions measured independently with a coregistered stylus and when the full iSV surface was aligned with model-updated MR. The effectiveness and efficiency of the registration method is also minimally disruptive to surgical workflow.